ALBERT

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Valentin Haselbeck, Jannes Kordilla, Florian Krause, Martin Sauter〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Growing inorganic and expansive hydrochemical datasets and large differences in the measured concentrations require methods that are capable of compressing data without the loss of critical information and subsequently displaying it in a condensed and comprehensive way. Here we train an artificial neural network, Kohonen’s self-organizing map (SOM), to model inorganic hydrochemical clusters and associate the salinity source with the distribution of the ionic concentration spatial variation at a former potash mining site. Kohonen’s self-organizing maps are applied to project the data onto a two-dimensional grid and the geometric relationship of the projected vectors is subsequently used to perform a hierarchical cluster analysis. The SOM clustering approach succeeded in assigning the groundwater samples automatically according to their inorganic chemical composition. Five different clusters, three geogenic and two anthropogenic, were identified. The final outcome is displayed and compared with the classification from Piper plotting of the same dataset. In order to see the SOM clustering results in the large scale hydrogeological context, the distribution of the clusters is displayed spatially. This approach is a tool for the hydrogeologist to quickly analyze large datasets and present them in a clear and concise format.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Andrew C. Knight, Adrian D. Werner, Dylan J. Irvine〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Offshore fresh groundwater is increasingly suggested as a potential water resource for onshore human demands. In many cases, onshore pumping already draws significant fresh groundwater from offshore. However, offshore aquifers and the extent of offshore freshwater are usually poorly characterised due to data scarcity. This study combines geophysical data, hydraulic information and a first-order mathematical analysis to investigate offshore freshwater extent in the Gambier Embayment (Australia). A large seismic data set, combined with onshore and offshore bore-log geological profiles, are used to explore the regional offshore hydro-stratigraphy. Aquifer hydraulic parameters and onshore heads are obtained from onshore investigations. A novel application of Archie’s law, geophysical data and onshore hydrochemical data provide useful insights into the salinity profiles within four offshore wells. These are compared to steady-state, sharp-interface estimates of the freshwater extent obtained from a recently developed analytical solution, albeit using simplified conceptual models. Salinities derived from resistivity measurements indicate that in the south of the study area, pore water with total dissolved solids (TDS) of 2.2 g L〈sup〉−1〈/sup〉 is found up to 13.2 km offshore. Offshore pore-water salinities are more saline in the northern areas, most likely due to thinning of the offshore confining unit. The analytical solution produced freshwater-saltwater interface locations that were approximately consistent with the freshwater-saltwater stratification in two of the offshore wells, although analytical uncertainty is high. This investigation provides a leading example of offshore freshwater evaluation applying multiple techniques, demonstrating both the benefit and uncertainty of geophysical interpretation and analytical solutions of freshwater extent.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Jagoda Crawford, Cecilia S. Azcurra, Catherine E. Hughes, John J. Gibson, Stephen D. Parkes〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉For a period of 16 months in Sydney, Australia, the variations of 〈sup〉2〈/sup〉H/〈sup〉1〈/sup〉H and 〈sup〉18〈/sup〉O/〈sup〉16〈/sup〉O in atmospheric vapour (〈em〉δ〈/em〉〈sup〉2〈/sup〉H〈sub〉A〈/sub〉 and 〈em〉δ〈/em〉〈sup〉18〈/sup〉O〈sub〉A〈/sub〉) were estimated using an evaporation pan method as well as using the isotopic precipitation-equilibrium approach. These calculations were then compared with δ〈sup〉2〈/sup〉H〈sub〉A〈/sub〉 values measured at 10 m above ground surface using a Fourier Transform Infrared Spectrometer (FTIR). As pan isotopic composition was available on a weekly time scale, the evaporation rates were measured daily, and the atmospheric variables were available hourly, the weekly time scale was used to calculate the arithmetic averages of the atmospheric variables that were used in the estimation of the pan-derived 〈em〉δ〈/em〉〈sup〉2〈/sup〉H〈sub〉A〈/sub〉.〈/p〉 〈p〉Good agreement (r = 0.7, P-value = 0.00) was found between the pan-derived and the FTIR measured 〈em〉δ〈/em〉〈sup〉2〈/sup〉H〈sub〉A〈/sub〉 for weekly intervals, although individual differences ranged from −25.0 to 20.4‰, with the absolute difference averaging 8.0‰. A sensitivity analysis showed that the determination of 〈em〉δ〈/em〉〈sup〉2〈/sup〉H〈sub〉A〈/sub〉 is most sensitive to air temperature, relative humidity and the isotopic composition of the pan water〈sub〉.〈/sub〉〈/p〉 〈p〉While the precipitation-equilibrium approach only appears to be representative of atmospheric conditions close to times of precipitation events, the pan-derived isotopic composition of atmospheric vapour was found to be closer to the FTIR averages over longer periods including intervals with no precipitation. Overall, this means that the pan method is far more effective for uninterrupted estimation of 〈em〉δ〈/em〉〈sup〉2〈/sup〉H〈sub〉A〈/sub〉 and 〈em〉δ〈/em〉〈sup〉18〈/sup〉O〈sub〉A〈/sub〉 of atmospheric water vapour, as required for water budget studies, than the precipitation-equilibrium method, and it is more cost effective and robust than continuous measurement.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Ping Wang, L. Zeng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Contaminant transport in the wetland flow is subject to various reactions. Most researches on this topic have limited to the single component contaminant, relatively little has concerned the effect of competitive reaction on the transport of coupled bicomponent contaminant. This work analytically studies the bicomponent contaminant transport in the free surface wetland flow under the combined conditions of reversible competitive transfer, irreversible degradation and bed absorption, by solving the constant-coefficient second-order linear system of parabolic type and the method of concentration moments. Up to the fourth order concentration moment in the previous work (Wang and Chen, 2017a) is applied to support the fourth order expansion of Hermite polynomials to rigorously derive the solutions with high accuracy. The results demonstrate that the masses of binary components decay at different rate, and the vertical concentration distributions of binary components are tremendously non-uniform in the asymptotic dispersion stage. Three types of reactions in addition to the hydraulic dispersion exert separate control on the concentration distributions. It suggests that the peak concentration rather than the mean should be based for strict environmental implements.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Chao Liu, Yuqi Shan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes an analytical model for predicting the longitudinal profile of depth-averaged streamwise velocities in a channel with an emergent array of rigid cylinders. The governing equation of the analytical model was derived from the momentum equation and flow continuity equation. The longitudinal transect through a flume with a vegetation patch was divided into four regions based on two length scales of flow adjustment upstream of and inside the array, and analytical solutions were proposed for the four regions. Laboratory experiments demonstrated that the array length does not influence flow adjustments near the upstream edge of the array, so the model can predict the longitudinal profile of streamwise velocity for either short or long arrays. Twenty groups of velocity data from different sources were used to verify the proposed model. The predicted velocities agreed well with the measured velocities, indicating that the model is capable of predicting the longitudinal profiles of the velocity upstream of and inside a model patch. The predicted velocity profile can be further employed to estimate regions of enhanced or diminished deposition of fine sediment or organic matter inside model patches.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Guowangchen Liu, Lei Chen, Zhenyao Shen, Yuechen Xiao, Guoyuan Wei〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The simulation and optimization of low impact development (LID) practices has been a key research topic in stormwater management. In this study, a fast and robust framework was proposed for providing the optimal design of LID practices by coupling a physically based model, the Markov chain, with the multi-objective shuffled frog leaping algorithm (MOSFLA). The proposed framework was then tested for chemical oxygen demand (COD) reduction in a typical urban catchment in China. The storm water management model (SWMM) was used to provide the flow/COD data during the baseline scenario, and the Markov chain method was then incorporated as a subset of the physically based model. Based on the results, the computational efficiency was improved by 500 times when the new framework was used, and the robustness of the optimal results increased over 50% compared to commonly used algorithms. The relative error between the SWMM and the Markov chain method was less than 5%, indicating that a satisfactory performance could be obtained using the proposed framework. This new method provides a useful tool for optimizing LID practices and green infrastructure, especially for complex urban catchments.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Xianzhe Tang, Haoyuan Hong, Yuqin Shu, Huijun Tang, Jiufeng Li, Wei Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urban waterlogging occurs frequently and often causes considerable damage that seriously affects human activities and the economy. Effectively assessing waterlogging susceptibility can reduce or even avoid the damage caused by such disasters. Here, a Support Vector Machine (SVM) was chosen for waterlogging susceptibility assessment due to its simplicity, objectivity, and understandability. The Particle Swarm Optimization method was used to compute parameters of the SVM. When selecting negative samples for machine learning methods, the methods of subjective selection and single random selection used in previous studies made it easy to select improper negative samples, and thus affected the classification accuracy and generalization capacity of the trained classifiers. To overcome these shortcomings, we proposed a repeatedly random sampling and verifying model to select negative samples for an SVM. As such, this study adopted the spatial framework of integrating GIS and an SVM to assess waterlogging susceptibility using the primary urban area of Guangzhou as an example. The results demonstrate that the waterlogging susceptibility map derived from the most accurate classifier (MAC) can reflect the real occurrence and spatial distribution of waterlogging. Moreover, we randomly generated 100,000 groups of samples to test the classification accuracy and generalization capacity of the MAC; the results show that in 82% of the samples, the area under the curve value of the MAC was higher than that of the randomly generated classifier. This demonstrated that the sampling and verifying model can allow the selection of an MAC with a relatively high and stable classification accuracy. The proposed sampling method can overcome the shortcomings of negative sample selection method employed in previous studies, which makes the machine learning results more accurate and reliable. Furthermore, the method requires less data, which can be helpful in developing countries where the availability of long-term intensive hydrologic monitoring data is limited.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Changkun Ma, Xiangdong Li, Yi Luo, Mingan Shao, Xiaoxu Jia〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Interception loss can remove a significant portion of rainwater from forested ecosystems. Therefore, the quantification and modelling of interception loss are of significant importance if human and ecosystem water demands are to be balanced under a future changing climate. This is particularly true for semi-arid/arid regions, where afforestation has become an important ecological restoration measure to tackle desertification, poverty and climate change. However, quantification and modelling of interception loss of plantations in these regions have rarely been reported. In the present study, rainfall interception loss was quantified and modelled over a one-year period (January-December 2016) for a deciduous broad-leafed 〈em〉R. pseudoacacia〈/em〉 plantation and an evergreen needle-leaf 〈em〉P. tabuliformis〈/em〉 plantation (common afforestation tree species) situated in the semi-arid Loess Plateau of China. The stand age, density, canopy cover and leaf area index of 〈em〉R. pseudoacacia〈/em〉 during the study period were 15 years, 2000 tree ha〈sup〉−1〈/sup〉, 0.48 and 1.41 m〈sup〉2〈/sup〉 m〈sup〉−2〈/sup〉, respectively. The corresponding values for 〈em〉Pinus tabuliformis〈/em〉 were 17 years, 1200 tree ha〈sup〉−1〈/sup〉, 0.62 and 2.53 m〈sup〉2〈/sup〉 m〈sup〉−2〈/sup〉. The measured throughfall, stemflow and derived estimates of interception loss for 〈em〉R. pseudoacacia〈/em〉 were 81.1%, 1.3% and 17.6%, respectively. The corresponding values for 〈em〉P. tabuliformis〈/em〉 were 75.4%, 0.7% and 23.9%. Given that the weather conditions experienced by the two forest stands were similar, the observed higher interception loss for 〈em〉P. tabuliformis〈/em〉 can be explained by the higher canopy storage capacity and wet canopy evaporation rate of this species. The revised Gash analytical model of rainfall interception was well calibrated and validated against field measurements and was able to simulate the cumulative interception loss at two forest stands accurately, and it also effectively captured the seasonal variation (leafed growing and leafless dormant seasons), provided that the optimized wet-canopy evaporation rates were used. The revised model was highly sensitive to the canopy storage capacity and changes in the ratio of mean wet canopy evaporation to mean rainfall intensity and less sensitive to canopy cover, but it was found to be fairly insensitive to the trunk storage capacity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Yonghuai Yang, Biyang Wen, Caijun Wang, Yidong Hou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Non-contact flow measurement method plays an increasingly important role in river discharge measurement. However, most channel cross-section velocity distribution models proposed by researchers have certain limitations in application, underwater velocities are always necessary when applied in narrow channels, which makes it challenging to calculate natural river discharge using water-surface velocities measured by remote sensing instruments. This letter takes water-surface velocities detected by UHF radar as boundary conditions and a new velocity distribution model is derived based on the Reynolds-Averaged Navier-Stokes (RANS) equations. UHF radar measures surface velocities of the cross-section, and velocities on the river bed of the cross-section are considered to be 0. The RANS equations are simplified to be a two-dimensional Poisson equation and the cross-section velocity distribution is solved by using the closed boundary conditions. Some field experiments were conducted in the Hanjiang River at Xiantao, Hubei, China in September 2017 and April–July 2018, the processing results of which show that the proposed model is superior to the power law and the log law models, especially near the side wall (narrow channel region). River discharges calculated by this method are highly consistent with those provided by Hubei Xiantao hydrologic station, which verifies the reliability of the model and the feasibility of using UHF radar to measure natural river discharge continuously and automatically.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Yunliang Li, Qi Zhang, Xinggen Liu, Zhiqiang Tan, Jing Yao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Seasonal lakes that exist in floodplain settings have significant effects on hydrological and ecological processes and are highly susceptible to various changes; however, they are rarely investigated, mainly because of the large extent and remoteness of floodplains. This study uses physically based hydrodynamic modeling in combination with a bathymetry adjustment approach to investigate the coupling effects of 77 seasonal lakes (defined as the seasonal lake group) on hydrological behaviors within the Poyang Lake-floodplain system (China) from a systemic perspective. Elucidation of the role of seasonal lake groups could benefit from hydrodynamic modeling, which enables complex lake-floodplain simulations and comparison analyses of natural (original bathymetry) and hypothetical conditions (adjusted bathymetry). In the present study, the simulation results showed that the temporal influences of the seasonal lake group on water levels, lake outflows, and inundation dynamics were greater during dry seasons than wet seasons for both the dry (2006) and wet years (2010). The spatial effects of the seasonal lake group on the hydrology of the lake’s floodplains were stronger than those of the main lake for both hydrological years. The findings demonstrate that the seasonal lakes are likely to have very limited effects on the main lake and the associated flood levels. On average, the role of the seasonal lake group during the dry seasons was around several times stronger than that during flood seasons in terms of the magnitudes of hydrological responses. Additionally, it is expected that the seasonal lake group may exert an important role in influencing the surface hydrological connectivity and associated dry-wet hydrological shift across lake-floodplains, indicating a dominant role of the floodplain bathymetry changes. Overall, the results of this study will support management and planning of Poyang Lake and other similar floodplain regions with numerous small, shallow, and seasonal lakes by providing more reliable information regarding bathymetry changes, water management and lake-floodplain interactions to decision-makers for improved floodplain protection strategy.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307826-ga1.jpg" width="285" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Kim Vercruysse, David A. Dawson, Vassilis Glenis, Robert Bertsch, Nigel Wright, Chris Kilsby〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Integrated flood management is essential in urban planning to align flood protection and mitigation with the complex social and physical infrastructure in cities, and involves managing surface water by retaining and transferring it along its pathway across multiple infrastructure systems. However, despite many potential flood management solutions (natural and engineered), spatial prioritization to implement these solutions from a catchment perspective remains difficult. A transferable, source-to-impact flood analysis is developed to identify locations with high surface flooding (impact) and locations contributing to this flooding (source), to define spatial prioritization criteria for flood management intervention. The analysis was applied to Newcastle-upon-Tyne (UK) and combined a spatial rainfall cell dependency analysis with the hydrodynamic flood model CityCAT. Locations within the study area were then classified based on four priority criteria: contribution to (i) total flood extent; (ii) maximum flood depths; (iii) flooded green spaces and roads; and (iv) likelihood of flood exposure. The results illustrate the importance of considering the catchment holistically and identify hydrological linkages between flood source and impact areas, and the corresponding impact on (and interaction with) different infrastructure systems. Different criteria lead to different spatial prioritization information, which stresses the importance of combining criteria that address the specific needs and targets of the desired flood management strategy (e.g. Blue-Green infrastructure). The concept offers a basis for developing a systematic, high-level approach to inform catchment-scale prioritization for flood management intervention, which can be applied prior to developing flood alleviation schemes. In doing so, the approach will help identify opportunities to combine multiple water management solutions and allocate resources more efficiently.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Ping-Cheng Hsieh, Ding-You Wang, Ming-Chang Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Urban areas are often covered by materials with smooth ground surface and poor water permeability, which may cause problems such as increasing flow velocity and discharge.〈/p〉 〈p〉This study employed the diffusion wave equation to investigate the variation of overland flow, and analytical solutions were obtained by the generalized integral transformation technique. Examining previous research, we found when the coefficients in the diffusion wave equation were treated as constants, the simulated results would be mass non-conservative. This study corrected the coefficients which makes the flow meet the mass conservation law to improve the simulation results. An alternative solution to the overland flow considering time-varying rainfall and infiltration were proposed and the results were well compared with previous numerical solutions and experimental data.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Bahram Choubin, Moslem Borji, Amir Mosavi, Farzaneh Sajedi-Hosseini, Vijay P. Singh, Shahaboddin Shamshirband〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Snow avalanches are among the most destructive natural hazards threatening human life, ecosystems, built structures, and landscapes in mountainous regions. The complexity of snow avalanche modelling has been discussed in many studies, but its modelling is not well-documented. Snow avalanche modeling in this study was done using three main categories of data, including avalanche occurrence locations, meteorological factors, and terrain characteristics. Two machine learning models, namely support vector machine (SVM) and multivariate discriminant analysis (MDA), were employed. A ratio of 70 to 30 of data was considered for calibrating and validating the models. Results indicated that both models had an excellent performance in snow avalanche modeling (area under curve, AUC 〉 90), although hits and misses analysis demonstrated the superior performance of MDA. Sensitivity analysis indicated that the topographic position index, slope, precipitation, and topographic wetness index were the most effective variables for modeling. A snow avalanche map indicated that the high snow avalanche hazard zone was mostly near the streams and was matched with hillsides around the water pathways. Findings of study can be helpful for land use planning, to control snow avalanche paths, and to prevent the probable hazards induced by it, and it can be a good reference for future studies on modeling snow avalanche hazards.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Xu Li, Zhang Wen, Hongbin Zhan, Qi Zhu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Single-well push-pull (SWPP) test is one of the most important ways to estimate flow and transport parameters, e.g. porosity, dispersivity, regional groundwater flow velocity. Usually the wellbore is surrounded by a finite-thickness skin, such as a gravel pack. The positive skin has a smaller hydraulic conductivity than the aquifer formation zone, and the negative skin has a greater one. In this study, a numerical model of a SWPP test considering skin effects was established using the finite-element COMSOL Multiphysics program to estimate aquifer parameters. Several important results were obtained. Firstly, regional groundwater velocity affects the types of breakthrough curves (BTCs) through changing the flow pattern. Secondly, a positive (or negative) skin leads to a slower (or faster) tracer transport process, and a smaller ratio between the hydraulic conductivity of the skin and that of the aquifer formation zone results in greater solute plume retardation in the skin zone. Thirdly, a larger thickness of the positive skin leads to a higher tracer concentration around the well, and the opposite is true if the skin is negative. Besides, the model of Leap and Kaplan (1988) underestimates the regional groundwater velocity for the second type of BTCs, and a larger longitudinal dispersivity can lead to a greater error, where the second type of BTCs has a rising limb at early stage followed by a falling limb at late stage. The general conclusion is that the estimations of groundwater velocity from SWPP tests are also affected by skin effects.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 6 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Pengcheng Qin, Hongmei Xu, Min Liu, Liangmin Du, Chan Xiao, Lüliu Liu, Brian Tarroja〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Climate change is expected to alter regional hydrological regimes, affecting the operation and performance of reservoirs and hydropower facilities. This study examines the impacts of climate change on the performance of the Three Gorges Reservoir (TGR) by means of a detailed daily reservoir regulation and hydropower model, linked to a physically-based hydrological model, and driven by an ensemble of five General Circulation Models (GCMs) under three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). As precipitation in the basin is expected to increase, the projected mean annual inflow and hydropower generation of the TGR will increase by 3.3-5.6% and 0.9-2.3% in 2040-2065, 7.9%-15.2% and 5.2-8.1% in 2080-2099 respectively. These increases are only statistically significant for 2080-2099 and are seasonally concentrated in the spring before the flood season and the early autumn during the end of the flood season. However, the inter-annual variation of power generation will increase strongly in the dry season. The reservoir performance is highly sensitive to the changes in the seasonal distribution and extremes of streamflow. Increases in streamflow that occur in the flood season cause significant increases in the amount of spilled water and advance the time when the reservoir reaches the normal storage level. Additionally, increases in both the inter-annual variation of inflow and the intensity of inflow shortages during extreme drought years in the impounding stage drive decreases in the fully filled rate and average water storage level in the dry season. The utilization rate of water resources under projected extreme streamflow is expected to decrease, reshaping the response of power generation to climate change into a non-linear pattern where increases in streamflow do not proportionally translate to increases in power generation. These findings highlight the complexity of hydropower management and production under future climate change scenarios, motivating the need for introducing detailed regulating models for impact assessment studies and adaptive adjustment of the reservoir management to combat climate change.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Mohamed Sultan, Neil C. Sturchio, Saleh Alsefry, Mustafa K. Emil, Mohamed Ahmed, Karem Abdelmohsen, Mazen M. AbuAbdullah, Eugene Yan, Himanshu Save, Talal Alharbi, Abdullah Othman, Kyle Chouinard〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉An integrated approach was developed to assess the sustainability, origin, age, evolution, and groundwater potential of large fossil aquifers using the Mega Aquifer System (MAS) (area: 2 × 10〈sup〉6〈/sup〉 km〈sup〉2〈/sup〉) in the Arabian Peninsula as a test site. A two-step exercise was adopted, the sustainability of the MAS was first investigated through the analysis of GRACE data and land surface model (LSM) outputs. Then, integrated geochemical, remote sensing, and field studies were conducted to address the age, origin, hydrogeological setting, and evolution of the southern sections of the MAS (Rub Al Khali Aquifer System (RAKAS)), the area identified from the analysis of GRACE and LSMs as being the most suited for sustainable development. Analysis of GRACE and LSMs revealed: (1) the MAS central and northern sections are experiencing high groundwater extraction (6.6 km〈sup〉3〈/sup〉/yr) and depletion rates (−2.8 ± 0.8 km〈sup〉3〈/sup〉/yr) with minimum balancing potential through aquifer capture processes, yet sustainability could be achieved by reducing annual extraction by 2.8 km〈sup〉3〈/sup〉, and (2) the MAS southern sections (Rub Al Khali Aquifer System (RAKAS)) are experiencing low groundwater depletion rates (eastern RAKAS: −1.8 ± 1.4 mm/yr) to steady-state conditions (western RAKAS: −0.73 ± 1.4 mm/yr). Geochemical, remote sensing, and field investigations over the RAKAS revealed: (1) the presence of west to east trending drainage networks and large-scale groundwater flow systems consistent with a meteoric source (precipitation over Red Sea Hills); (2) increasing 〈sup〉36〈/sup〉Cl model ages along groundwater flow directions (up to 970,000 years), indicating aquifer recharge in wet Pleistocene periods; (3) progressive depletion in the O and H stable isotopic compositions of aquifers with increasing distance from the Red Sea Hills basement outcrops, indicating modest recharge during prevailing dry conditions; and (4) the presence of relatively fresh (TDS: 800–2800 mg/L) and non-radioactive (〈sup〉226〈/sup〉Ra + 〈sup〉228〈/sup〉Ra 〈 0.185 Bq/kg) water in western RAKAS. Findings suggest that sustainable agricultural development is achievable at current extraction rates in western RAKAS and provide a replicable and cost-effective model.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Hai Zhou, Wenzhi Zhao, Zhibin He, Jialiang Yan, Gefei Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mongolian pine (〈em〉Pinus sylvestris var. mongolica〈/em〉) has been widely used in vegetation restoration and for windbreaks in sandy regions of northern China where water is the principal factor limiting tree survival and growth. An understanding of water use in Mongolian pine plantations is critical for effective vegetation restoration. To determine water sources in a Mongolian pine plantation, we investigated the stable isotopic ratios of 〈em〉δ〈/em〉〈sup〉18〈/sup〉O and 〈em〉δ〈/em〉D in precipitation, groundwater, in soil water in different soil layers, and in tree xylem at different tree ages along a precipitation gradient and in different micro-landforms. The results indicated that the main water sources for Mongolian pine were precipitation-derived shallow soil water in semi-humid regions and that the contribution proportion decreased with an increase in tree age. With reduced precipitation in semi-arid and arid regions, contribution of deep soil water to Mongolian pine water use gradually increased, and differences in soil water contribution among trees due to tree age also significantly increased. Water use patterns in trees planted in different micro-landforms (e.g. sand dune crest or inter-dune lowland) became more distinct as precipitation gradually decreased across humid to semiarid and arid regions. Moreover, Mongolian pine, including 15-, 20-, 25-, and 45-year-old trees, similar height and DBH without groundwater in semi-arid climate (in Ejin Horo banner), while trees planted in extremely arid climate (Linze) relied on irrigation for survival despite abundant and available groundwater at that study site. These results indicated that groundwater may be beyond reach to be a main water source for Mongolian pine trees. Soil water conditions determined the survival and sustainable growth of planted trees, especially at depths less than 1 m where soil layers were recharged mainly by precipitation. Although Mongolian pine exhibits strong ecological adaptability, a trait that makes it ideally-suited for controlling desertification in sandy regions of northern China, water stress, crown dieback, or even tree mortality are likely to occur under conditions of extremely low precipitation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Jungho Kim, Heechan Han, Lynn E. Johnson, Sanghun Lim, Rob Cifelli〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study introduces a novel hydrological assessment tool (HAT) based on hybrid machine learning (HML) framework. The HML framework combines an unsupervised clustering technique and a supervised classification technique, to determine reasonable performance ratings (unsatisfactory, satisfactory, good, and very good) and build a practical assessment tool. Hydrologically significant error indices are used to cluster the performance rating groups and train the HAT. The HAT was applied to the National Water Model (NWM), which is operated in real time for the continental United States (CONUS). For establishing, training, and validating the HAT, data from October 2013 to February 2017 were used, and a performance assessment was conducted on the NWM in the San Francisco Bay Area. As a result, the HAT determined the performance ratings that were reliable in terms of the statistics and hydrograph. It was confirmed that the HAT could perform an accurate hydrograph assessment as the concordance rate of the performance ratings was 98%. The NWM was evaluated against 57 USGS streamflow gauges using the HAT and was found to perform with 46% on average, good and very good ratings. The HML framework, an integral part of the HAT, is expected to be useful not only in hydrological analysis but also across all geophysical fields that deal with physical processes.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): J. Leandro, A. Gander, M.N.A. Beg, P. Bhola, I. Konnerth, W. Willems, R. Carvalho, M. Disse〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉River discharges flood forecasting is a complex task with multiple sources of uncertainty. Bayesian methods can incorporate multiple types of uncertainties by inferring the probability density function of ensemble forecasts based on past events. However, such methods lead to forecasts with large uncertainty bands. In order to reduce the uncertainty in the forecasts, we focus solely on the prediction of the upper and lower range of the uncertainty bands. Therefore, we develop three forecast methods in which we search for the indexes of the upper and lower forecast members of an ensemble (termed best-pairs), which provide the highest predictive skill. The results show for four distinct hindcasts of historical events in a case study in Bavaria (Germany) that the new methods have a higher predictive skill of the observations than probabilistic methods, at least for the first 4 out of 12 h’ forecasts. Moreover, the new methods are computational efficient because they considerably reduce the number of members of the ensembles required to produce a flood discharge forecast with high predictive skill.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉 〈p〉Conceptual representation of the probabilistic forecast (PF) (first two) and upper and lower forecast (ULF) (last three) methods: a) Ensemble, b) Relative error method, c) Discharge intervals, d) Rising and receding, and e) Slope intervals.〈/p〉 〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419305992-ga1.jpg" width="239" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Stephen Tuozzolo, Theodore Langhorst, Renato Prata de Moraes Frasson, Tamlin Pavelsky, Michael Durand〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The Surface Water and Ocean Topography Mission (SWOT) will generate global, spatially continuous maps of water surface elevation and extent for large inland water bodies when it launches in 2021. We present an analysis of water surface elevation, width, and bathymetry timeseries data from a medium-sized (average annual discharge 14 m〈sup〉3〈/sup〉/s) river to explore Manning’s equation, an empirical open channel flow equation, in the context of SWOT discharge algorithms. While this equation is in theory inapplicable to natural channels due to the non-uniform and spatially heterogeneous nature of river systems, we explored approaches to adapt it to this context using reach-averaged variables. At twenty sites along a 6.5 km stretch of the Olentangy River in Ohio, USA, we collected automated and manual measurements of water surface elevation and river width, undertook a full bathymetric survey of the study area, and built a hydraulic model. The stretch of river was divided into five reaches, and hydraulic variables were reach-averaged. Using these variables, we used a modified form of Manning’s equation to compute a reach-averaged roughness coefficient. Reach-averaged roughness coefficients varied nonlinearly with discharge and were 2-10 times larger at low flow than at high flow in the in-situ data, ranging from 0.06 to 0.61 in one of the study reaches. These results were compared with the output of an unsteady flow simulation using a calibrated 1-D hydraulic model which was run with constant roughness coefficients at each cross section. When reach-averaged data was used, model-derived roughness coefficient also varied by more than an order of magnitude, with a range of 0.02 to 0.82 for one reach. For both in-situ and model-derived datasets, using a two-parameter roughness coefficient which scaled with a power law on either discharge or stage reduced discharge estimation error, with error for one reach dropping from 81 % to 8 % relative root-mean square error (rRMSE) in the in-situ data and 58 % to 8 % nRMSE in the modeled data. These results imply that spatial averaging of hydraulic variables leads to large variations in reach averaged Manning’s 〈em〉n〈/em〉, which we term the reach’s “effective resistance”, and suggest that this variability can be accounted for with a simple parameterization in estimates of discharge that use spatially averaged data.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Lisa D. Olsen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The author read with much interest the publication by Mize et al. (2018) on the decrease in suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya Rivers between 1980 and 2015. Researchers interested in sediment dynamics in the lower Mississippi and Atchafalaya Rivers also should be aware that sediment data previously reported for the lower Mississippi-Atchafalaya River Basin by the U.S. Geological Survey (USGS) and U.S. Army Corps of Engineers (USACE) were affected by a systematic error in the fines fraction (particle sizes less than 0.063 millimeter) of the suspended-sediment concentration. This error affected results reported from October 1973 through February 2015 for two sites on the main stem of the Mississippi River, three sites on the Atchafalaya River, one site on the Old River Outflow Channel, and one site on the Red River. The USGS and USACE identified the error and have revised the results for samples collected from October 1989 through February 2015, as reported by Norton et al. (2019a) and Norton et al. (2019b). The significant conclusions of Mize et al. (2018) and sediment loads modeled using the Weighted Regressions on Time, Discharge, and Season (WRTDS) method were unaffected by the systematic error because the models used data from unaffected sites; however, the background information provided in tables 1 and 2 of Mize et al. (2018) included references to several previous studies that contained results affected by the error. This comment paper identifies which references in Mize et al. (2018) were affected by the error and alerts readers to implications of the data revision.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Alejandro García-Gil, Enric Vázquez-Suñé, Carlos Ayora, Corrado Tore, Álvaro Henríquez, José Yáñez〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The skin effect is an important issue associated with a loss of hydraulic efficiency in pumping systems. In this paper, a comprehensive study is conducted to determine how the evolution of the skin effect over time affects the productivity and functionality of brine exploitation systems in a crystalline halite aquifer. Several double-packer system tests have been interpreted via groundwater modeling to hydrogeologically characterize the investigated aquifer. A numerical groundwater flow model that accounts for the heterogeneity of the multilayer halite aquifer and the transient well skin effect on the brine exploitation system is presented to explain the continuous drawdown during three months of constant-rate brine extractions. Numerical results obtained suggested that an exponential decay function of permeability over time was required in a wellbore skin zone to reproduce numerically experimental observations during brine exploitation. The empirical exponential function obtained specifically for this case study was generalized, and coefficients considered were discussed to infer their physical and geochemical dimensions related to the mixing process triggering heterogenous reactions responsible for the hydraulic loses. Our results will be useful for predicting the spatial and temporal losses of hydraulic efficiency and for evaluating the lifetimes of brine exploitation infrastructure.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Yingxue Xuan, Changyuan Tang, Yingjie Cao, Rui Li, Tao Jiang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Knowledge about the origin and transformation of nutrients at different temporal scales in river ecosystems can provide a better understanding of carbon (C) and nitrogen (N) cycles in rivers and bear important implications for regional and global C and N cycling. In this study, stable isotopes of C and N (δ〈sup〉13〈/sup〉C and δ〈sup〉15〈/sup〉N) and a radioactive isotope of 〈sup〉210〈/sup〉Pb were used to investigate the factors affecting seasonal and long-term changes in N source apportionment and C and N biogeochemical processes in the Beijiang River located in the Pearl River basin, China. Source apportionment by a Bayesian model (stable isotopic analysis in R, SIAR) showed significant seasonal variations. During the flood season, the dominant origins were non-point sources, such as soil N for dissolved nitrogen (DN, accounting for 38%), soil organic matter for particulate organic matter (POM, 58%) and sedimentary organic matter (SOM, 31%), due to intense precipitation. During the non-flood season, fertilizer became the dominant nitrate source (48%), and effluent detritus prevailed in the POM (47%) and SOM (32%) pools. N transformation between the DN, POM and SOM was influenced by seasonally variable hydrology. Our data suggested that low discharge was more favorable for the vertical mixing of the water column and sedimentation, which was supported by similar δ〈sup〉15〈/sup〉N values in the DN, POM and SOM in the non-flood season. A sedimentary history record of 65 years (1951–2015) showed that the variation of N in the sediment was mainly affected by human activities. From 1999 to 2005, a decreasing trend in the δ〈sup〉15〈/sup〉N values was observed due to the promotion of aquatic plant cultivation after reservoir impoundment. From 2005 to 2011, the enrichment in the δ〈sup〉15〈/sup〉N values was caused by increases in manure and sewage due to the development of the tourism industry. From 2011 to 2015, the increase in pollution treatment funds from the government improved the water environment, resulting in δ〈sup〉15〈/sup〉N depletion in the sediment. At the 65-year temporal scale, increased temperature and CO〈sub〉2〈/sub〉 concentration had less impact on the C and N cycles in river ecosystems, however, high discharge could increase the C and N contents, and flood events might increase the δ〈sup〉15〈/sup〉N values in the sediment. This study provided more detailed information regarding the nutrient sources and improved our understanding of the C and N cycling processes at different temporal scales in river ecosystems.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419306468-ga1.jpg" width="433" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Tuo Xie, Gang Zhang, Jinwang Hou, Jiancang Xie, Meng Lv, Fuchao Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate and reliable short-term runoff prediction is of great significance to the management of water resources optimization and reservoir flood operation. In order to improve the accuracy of short-term runoff forecasting, a hybrid model-based “feature decomposition-learning reconstruction” named VMD-DBN-IPSO was proposed. In this paper, variational mode decomposition (VMD) is first used to decompose the original daily runoff series into a set of sub-sequence for improving the frequency resolution. Partial autocorrelation function (PACF) is then applied to determine the input variables of each sub-sequence. The improved particle swarm optimization (IPSO) algorithm is combined with the deep belief network (DBN) model to predict each sub-sequences and finally reconstruct the ensemble forecasting result. Three quantitative evaluation indicators, mean absolute error (MAE), root mean square error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSE), were used to evaluate and compare the established models using the historical daily runoff data (1/1/1988-31/12/2017) at Yangxian and Ankang hydrological station in the Han River Basin of China. Meanwhile, a comparative analysis of the performance of VMD-DBN-IPSO model under different forecast periods (1-, 3-, 5- and 7-day lead time) was performed. In addition, the prediction ability of peak runoff of the VMD-DBN-IPSO model is further verified by analyzing the 10 peak flows during the testing data-series. The results indicate that the VMD-DBN-IPSO model can always achieve the best performance in the training and testing stage, and has good stability and representativeness, the NSE coefficient remains above 0.8, and the prediction error of peak flow is within 20%. It is a preferred data-driven tool for forecasting daily runoff.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Jianying Jiao, Ye Zhang, Liqiang Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A new solute transport inverse method is proposed for estimating plume trajectory and source release location under unknown solute transport boundary conditions in a steady-state, non-uniform groundwater flow field. Solute concentration is modeled by proposing a set of local approximation solutions (LAS) of transport that are discretized over the problem domain. At a given time step, the inverse method imposes continuities of concentration and total solute mass flux at a set of collocation points in the inversion grid, whereas the LAS are conditioned to measured breakthrough concentrations. By enforcing transport physics at selected points in space and time, the inverse problem becomes well-posed and a single system of inversion equations is assembled and solved with a parallel iterative solver. Unlike most of the inversion techniques that minimize a model-data mismatch objective function, the inverse method does not require the simulation of a forward transport model for optimization, thus both solute initial and boundary conditions can be recovered. Assuming dispersivity estimates are available, the method was demonstrated using synthetic breakthrough data from various sampling densities and designs, i.e., irregular versus uniformly spaced well networks. Different measurement errors and source release histories (e.g., uniform-in-time, single, and multiple pulses) were also investigated. Results suggest that for the source release histories tested, 1) inversion is stable under increasing measurement errors up to 5% of the maximum observed concentration; 2) accurate plume trajectory and source release location can be estimated from solute breakthrough concentrations; 3) inversion accuracy appears the most sensitive to sampling well density and its information content.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Chongli Di, Tiejun Wang, Erkan Istanbulluoglu, A.W. Jayawardena, Siliang Li, Xi Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Soil moisture systems generally exhibit complex spatiotemporal patterns due to their nonlinear interactions with surrounding environments. In this paper, the possible existence of chaotic behaviors in soil moisture time series was investigated using the chaos theory, specifically based on the techniques of phase space reconstruction, correlation dimension (CD), largest Lyapunov exponent (LLE), and local approximation prediction (LAP) methods. Daily soil moisture data for six years along with different influencing factors were obtained for 35 Nebraska Mesonet (NM) stations with varying hydroclimatic conditions and soil properties. The results of CDs and LLEs revealed the presence of chaos in soil moisture systems, implying that soil moisture dynamics was controlled by deterministic systems with a limited number of governing variables. The results obtained by the LAP method offered further evidence on the chaotic behavior of soil moisture systems. Specifically, Median of CD values of 4.51, 4.06, 3.23, and 1.40 were obtained for soil moisture time series at the depths of 10, 25, 50, and 100 cm, respectively, indicating that the complexity of soil moisture systems decreased with increasing depth. Moreover, the correlations of CDs with different influencing factors showed that the dominant controls on soil moisture dynamics switched at different depths. At shallower depths (e.g., 10 and 25 cm), CDs were more correlated with meteorological forcings, while stronger correlations emerged between CDs and soil texture in deeper soil layers (e.g., 50 and 100 cm). As the first attempt to analyze the complexity of soil moisture systems from the perspective of the chaos theory, the results of this study offer additional avenues for understanding chaotic behaviors of soil moisture dynamics.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): W. Hu, Y.Q. Wang, H.J. Li, M.B. Huang, M.T. Hou, Z. Li, D.L. She, B.C. Si〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Knowledge of spatio-temporal groundwater recharge (〈em〉GR〈/em〉) is crucial for optimizing regional water management practices. Daily potential 〈em〉GR〈/em〉 at 58 sites over the Chinese Loess Plateau (CLP) during 1981–2099 was simulated using the HYDRUS-1D and robust model inputs. The objective was to explore the impacts of soil, vegetation, and climate on potential 〈em〉GR〈/em〉 at a regional scale. The median potential 〈em〉GR〈/em〉 over the CLP during 1981–2010 was 1.8 cm, accounting for 4.1% of the annual precipitation (〈em〉P〈/em〉). As dominated by 〈em〉P〈/em〉, the annual potential 〈em〉GR〈/em〉 decreased from 18.8 cm (28% of 〈em〉P〈/em〉) at the southeast to 0.0 cm at the northwest. Temporally, consistent low-intensity of 〈em〉GR〈/em〉 interspersed with extreme rainfall-induced high 〈em〉GR〈/em〉, being episodic or seasonal depending on sites and years. The lag (average of 5 months) between deep drainage at 3 m depth and rainfall was controlled by climate (i.e., 〈em〉P〈/em〉). From 1981 to 2010, annual potential 〈em〉GR〈/em〉 significantly decreased as a result of increased 〈em〉ET〈sub〉p〈/sub〉〈/em〉 and leaf area index (〈em〉LAI〈/em〉) over time. A warmer and wetter CLP at the end of this century as predicted by the HadCM3 model may decrease the potential 〈em〉GR〈/em〉 because of the increased 〈em〉ET〈sub〉p〈/sub〉〈/em〉. This study highlights the dominance of water input factor (〈em〉P〈/em〉) on the spatial 〈em〉GR〈/em〉 and water output factors (〈em〉ET〈sub〉p〈/sub〉〈/em〉 and 〈em〉LAI〈/em〉) on the temporal 〈em〉GR〈/em〉. Measures such as water-saving practices and land use optimization should be taken to mitigate climate change effect on groundwater recharge.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Lu Chen, Hongya Qiu, Junhong Zhang, Vijay P. Singh, Jianzhong Zhou, Kangdi Huang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Daily stochastic streamflow simulation is widely used for the design of reservoirs, evaluation of reservoir operation rules, and risk evaluation of operation of water resources systems. The major difficulties and challenges of daily streamflow are that there are 365 days that need to be simulated, which entails much more calculation than does monthly streamflow simulation. Since lag-2 auto-correlation is usually large, the lag-2 correlations should be considered. This paper therefore proposes a copula-based method for daily stochastic streamflow simulation. The contribution and novelty of this paper are that: (a) the proposed method can consider lag-2 correlations, compared with the currently used copula based method; (b) the conditional copulas are used to build high dimensional copulas, which make calculations easier; and (c) the method can be used for daily streamflow simulation because of the simplified model structure and effective parameter estimation method. Seven gauging stations on the upper Yangtze River and Pearl River in China were selected as case studies. Results demonstrated that the proposed method preserved the basic statistics (including mean daily flow, standard deviation, and coefficient of skewness) of observed data of each day well. Comparison with the currently used seasonal autoregressive model (SAR(2)) and bivariate copula-based method considering lag-1 autocorrelation indicated that the proposed method produced smaller relative errors and was better overall. Therefore, the proposed method can be regarded as an effective way for stochastic daily streamflow simulation, and can be used for the design of reservoirs and risk analysis of water resources systems.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Rosanna Margalef-Marti, Raúl Carrey, Daniel Merchán, Albert Soler, Jesús Causapé, Neus Otero〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A surface flow constructed wetland (CW) was set in the Lerma gully to decrease nitrate (NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉) pollution from agricultural runoff water. The water flow rate and NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 concentration were monitored at the inlet and the outlet, and sampling campaigns were performed which consisted of collecting six water samples along the CW flow line. After two years of operation, the NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 attenuation was limited at a flow rate of ~2.5 L/s and became negligible at ~5.5 L/s. The present work aimed to assess the feasibility of using rural waste products (wheat hay, corn stubble, and animal compost) to induce denitrification in the CW, to assess the effect of temperature on this process, and to trace the efficiency of the treatment by using isotopic tools. In the first stage, microcosm experiments were performed. Afterwards, the selected waste material was applied in the CW, and the treatment efficiency was evaluated by means of a chemical and isotopic characterization and using the isotopic fractionation (〈em〉ε〈/em〉) values calculated from laboratory experiments to avoid field-scale interference. The microcosms results showed that the stubble was the most appropriate material for application in the CW, but the denitrification rate was found to decrease with temperature. In the CW, biostimulation in autumn-winter promoted NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 attenuation between two weeks and one month (a reduction in NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 between 1.2 and 1.5 mM was achieved). After the biostimulation in spring-summer, the attenuation was maintained for approximately three months (NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 reduction between 0.1 and 1.5 mM). The 〈em〉ε〈/em〉〈sup〉15〈/sup〉N〈sub〉NO3/N2〈/sub〉 and 〈em〉ε〈/em〉〈sup〉18〈/sup〉O〈sub〉NO3/N2〈/sub〉 values obtained from the laboratory experiments allowed to estimate the induced denitrification percentage. At an approximate average flow rate of 16 L/s, at least 60% of NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 attenuation was achieved in the CW. The field samples exhibited a slope of 1.0 for 〈em〉δ〈/em〉〈sup〉18〈/sup〉O-NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 versus 〈em〉δ〈/em〉〈sup〉15〈/sup〉N-NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉, similar to those of the laboratory experiments (0.9–1.2). Plant uptake seemed to play a minor role in NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 attenuation in the CW. Hence, the application of stubble in the CW allowed the removal of large amounts of NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 from the Lerma gully, especially when applied during the warm months, but its efficacy was limited to a short time period (up to three months).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Mayank Suman, Rajib Maity〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Interaction between meteorological and hydrologic processes is challenging to model owing to their high spatio-temporal variability. The understanding of their associations can help to ensure future fresh water security with changing climate. In this study, due to continuously evolving nature of these interactions, the hydrological and meteorological variables are studied on wavelet component level. Multi-Resolution Stationary Wavelet Transformation (MRSWT) is used to transform the independent (climatic variable) and dependent (hydrological variable) time series into their components. The components of the dependent time series are modeled using a kernel-based auto-regressive (AR) model for separating their memory part. The residuals are hypothesized to be the effect of interaction of predictor variables and thus, are modeled using the MRSWT components of meteorological variables in an auto-regressive model with exogenous inputs (ARX). Finally, the predicted residuals (effect of climatic variables) are added to the component estimated by kernel-based AR estimator (memory of dependent series components) to obtain the predicted components of the dependent hydrologic variable, which are then inverse-transformed to obtain the predicted dependent hydrologic variable. The developed hybrid Wavelet-ARX is found to capture the information about relationship between synthetically generated data better than a simple ARX model. The model is then applied to predict total monthly rainfall over Upper Mahanadi Basin and is found to effectively extract the information from the poorly associated hydro meteorological variables. While the potential of Wavelet-ARX is found to be impressive for hydro meteorological applications, additionally, discarding some climatic inputs on the basis of their relative importance may lead to better prediction by the developed model. The developed model is suitable for extracting climatic forcings and is desirable in a changing climate.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Hongxiang Zhou, Xiuling Yu, Cheng Chen, Shenggao Lu, Laosheng Wu, Lingzao Zeng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Biochar has been increasingly used as an amendment to enhance soil structure and improve soil hydraulic properties. Nevertheless, there are very limited physically based studies to investigate solute transport in biochar-amended soils at pore scale. In this study, for the first time, synchrotron-based X-ray micro-computed tomography (SR-μCT) was used to obtain high-resolution pore geometries of two clayey soils and their biochar amended samples, then the three-dimensional lattice Boltzmann (LB) method was implemented to simulate solute transport using the pore structure information. By using the innovative method of combining SR-μCT and LB simulation, we found that biochar amendment reduced the spatial variability of pore water velocity and increased the dispersion coefficient by one order of magnitude. In addition, we observed that anomalous dispersion was more likely to occur in soils with biochar amendment. Furthermore, soils after biochar amendment had relatively higher thresholds of both the transition zone and advection-dominated zone for the dispersion coefficients. These results are crucial in understanding nutrient transport processes and contaminant migration occurring at pore scale.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Miriam Bertola, Alberto Viglione, Günter Blöschl〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Flood changes may be attributed to drivers of change that belong to three main classes: atmospheric, catchment and river system drivers. In this work, we propose a data-based attribution approach for selecting which driver best relates to variations in time of the flood frequency curve. The flood peaks are assumed to follow a Gumbel distribution, whose location parameter changes in time as a function of the decadal variations of one of the following alternative covariates: annual and extreme precipitation for different durations, an agricultural land-use intensification index, and reservoir construction in the catchment, quantified by an index. The parameters of this attribution model are estimated by Bayesian inference. Prior information on one of these parameters, the elasticity of flood peaks to the respective driver, is taken from the existing literature to increase the robustness of the method to spurious correlations between flood and covariate time series. Therefore, the attribution model is informed in two ways: by the use of covariates, representing the drivers of change, and by the priors, representing the hydrological understanding of how these covariates influence floods. The Watanabe-Akaike information criterion is used to compare models involving alternative covariates. We apply the approach to 96 catchments in Upper Austria, where positive flood peak trends have been observed in the past 50 years. Results show that, in Upper Austria, one or seven day extreme precipitation is usually a better covariate for variations of the flood frequency curve than precipitation at longer time scales. Agricultural land-use intensification rarely is the best covariate, and the reservoir index never is, suggesting that catchment and river drivers are less important than atmospheric ones. Not all the positive flood trends correspond to a significant correlation between floods and the covariates, suggesting that other drivers or other flood-driver relations should be considered to attribute flood trends in Upper Austria.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Rahim Barzegar, Mahsa Ghasri, Zhiming Qi, John Quilty, Jan Adamowski〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉River ice plays an important role in biophysical and socio-economic systems in northern regions and is related to climate variability at both regional and global scales. The objective of this study was to estimate river ice thickness using several new machine learning methods: extreme learning machine (ELM), least squares support vector machine (LSSVM), and their bootstrap versions (BELM and BLSSVM, respectively). To explore the usefulness of these methods, we chose two stations, Mackenzie River and Yellowknife River in the Mackenzie River Basin in the Northwest Territories, Canada. The variables used to develop the river ice thickness (cm) estimation models included: water flow (m〈sup〉3〈/sup〉/s), snow depth (cm) and mean air temperature (°C) (with a time period of 1981–2016). Two techniques, namely the Kendall-Theil Robust Line (KTRL) and the regularized expectation maximization (RegEm) methods, were utilized to fill in the missing values in the time series records. The performance of the developed models was measured using several statistical indicators (correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), their normalized equivalents expressed as a percentage (root mean square percentage error (RMSPE) and mean absolute percentage error (RMPE)), bias error (BIAS) and Willmott’s Index (WI)). Results indicated that the bootstrap ELM model outperformed the ELM, LSSVM and BLSSVM models in the testing phases based on a number of statistical measures. For the BELM using RegEM at the Mackenzie River station, the results were: 〈em〉r〈/em〉 = 0.826, RMSE = 19.756 cm, RMSPE = 33.011%, MAE = 15.364 cm, MAPE = 35.988%, BIAS = 1.199 cm and WI = 0.818. For the BELM using KTRL at the Yellowknife River station, the results were: 〈em〉r〈/em〉 = 0.856, RMSE = 15.444 cm, RMSPE = 19.468%, MAE = 12.006 cm, MAPE = 19.045%, BIAS = 0.966 cm and WI = 0.868. The findings of this study indicate that the BELM machine learning approach using meteorological variables is a promising new tool for river ice thickness estimation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Majid Dehghani, Akram Seifi, Hossien Riahi-Madvar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate influent flow forecasting plays a significant role in management, operation, scheduling and utilization of the sewage treatment plants. In design and operate such plants, it is essential to measure and forecast the influent flow rate in wastewater plants. In this paper, the Very immediate-short-term to long-term influent flow rate are modeled and forecasted by a new developed hybrid model of ANFIS and Grey Wolf Optimizer (GWO). The objective of this study is the integration of GWO with ANFIS in forecasting multi-ahead influent flow rate. The forecast horizon of the model is from 5 min up to 10 days bases on Gamma Test (GT) feature selection of input combinations. As the parameters of ANFIS have effect on the forecasting accuracy, these parameters are adjusted and optimized by using Grey Wolf Optimizer (GWO). Then the choice of appropriate input parameters at different prediction horizons from Very immediate-short-term (5-min ahead) to long-term (10 days ahead) was discussed for influent forecasting. The statistical indices of RMSE, NSE, MAE, RAE, R〈sup〉2〈/sup〉, d, CI and graphical evaluations such as scatter-plots with confidence bounds, error distributions, Taylor diagrams, box-plots and empirical cumulative distribution function (ECDF) were implemented for assessing the performance of all models in prediction horizons. Furthermore as another novelty in the present paper, recursive forecasting models based on previous forecasted values is used to improve the accuracy and applicability of ANFIS-GWO in recursive predictions. Our Results showed that: (1) the hybrid of ANFIS-GWO significantly improved the prediction accuracy. (2) ANFIS-GWO performs more efficiently than the ANFIS in almost all of the prediction horizons (ANFIS-GWO1: 5 min ahead; ANFIS-GWO11: 1–2 days ahead; ANFIS-GWO8: one week ahead). (3) The performance of models in influent flow forecasting is significantly influenced by the prediction horizon. The computational results confirmed that the ANFIS-GWO performs well in all of prediction horizons. Equally the true values and the trends are precisely forecasted by the ANFIS-GWO. Results of this novel study demonstrate that reliable estimates of influent flow rate from 5-min up to 10 days in advance can be achieved using the developed direct and recursive hybrid GWO models.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419306122-ga1.jpg" width="293" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): O. Sracek, J.-J. Rahobisoa, J. Trubač, F. Buzek, S.A. Andriamamonjy, R.A. Rambeloson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Thermal waters in the Central Highlands of Madagascar around Antsirabe were investigated using a combination of hydrogeochemical and isotopic methods, geochemical speciation and inverse geochemical modeling. Thermal waters at Antsirabe have temperatures from 35.2 to 47.7 °C, are highly mineralized (EC up to 5.87 mS/cm) are of Na-HCO〈sub〉3〈/sub〉-Cl type and have elevated concentrations of arsenic (up to 0.597 mg/l), Sr (up to 8.05 mg/l) and Li (up to 2.83 mg/l). About 25 km west of Antsirabe, a thermal spring at Betafo has a temperature of 53.6 °C, but its mineralization is much lower (EC 0.72 mS/cm) and its water is of Na-HCO〈sub〉3〈/sub〉-SO〈sub〉4〈/sub〉 type. Concentrations of As, Sr, and Li at Betafo are much lower, only 0.006 mg/l, 0.72 mg/l, and 0.063 mg/l, respectively. Calculated reservoir temperatures using quartz and chalcedony geothermometers are up to 153 °C at Antsirabe and 108 °C at Betafo. Values of δ〈sup〉2〈/sup〉H and δ〈sup〉18〈/sup〉O are above the WMWL, indicating exchange with silicates like micas. Values of δ〈sup〉13〈/sup〉C(DIC) are very enriched (up to −0.45‰) in Antsirabe samples, but depleted with a value of −21.52‰ in a Betafo sample. Values of δ〈sup〉34〈/sup〉S(SO〈sub〉4〈/sub〉) are close to −4.0‰ in all samples, suggesting an origin of sulfate from a Na-sulfate mineral. Values of 〈sup〉87〈/sup〉Sr/〈sup〉86〈/sup〉Sr ratios in Antsirabe samples suggest interactions with reservoir rocks. The principal difference between both sites seems to be in the significant input of magmatic-origin CO〈sub〉2〈/sub〉 at the Antsirabe site (up to 61.4 mmol/l as determined by inverse geochemical modeling) with resulting higher dissolution rates of As-containing silicate minerals such as micas. There is probably no such input at the Betafo site. In spite of relatively lower As concentrations compared to geothermal waters at global tectonic plate margins, concentrations of As at Antsirabe can represent a serious environmental problem.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419306134-ga1.jpg" width="268" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Michael G. Hutchins, Olivia E. Hitt〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The severity of river eutrophication is influenced by multiple stressors which reflect a wide-ranging variety of drivers encompassing land management, population growth and climatic effects. Experimental studies have successfully identified response to single or paired stressors under controlled conditions in small streams but have limited capability to characterise larger systems influenced by a wider variety of stressors. Here, a physics-based water quality model of the River Thames (UK) is used to explore the impacts of water temperature, phosphate concentration, river flow, urbanisation and riparian shading on indicators of chlorophyll and dissolved oxygen concentration by way of a sensitivity analysis. To understand the impact of model structural uncertainty, results are presented from two alternative formulations of the biological response. All outputs from each unique combination of stressors are presented in one graphic comprising multiple sub-plots that display the results of thousands of model runs simultaneously. Consequently, graphical analysis allows us to pinpoint under what circumstances reductions in key variables representing management-related stressors (i.e. lowering phosphorus concentrations and establishing riparian shading) may act synergistically, antagonistically or simply in an additive manner. Furthermore, we identify how these relationships may vary under different river flow and water temperature regimes and changes in abstraction and effluent discharge rates, to indicate the likely influence of future climate and population growth. Response can vary markedly depending on the choice of biological model and also changes considerably downstream along the river system. Chlorophyll indicators consistently show antagonistic responses to reduction in stressors whereas dissolved oxygen indicators show varied and complex responses. As expected, increases in phosphorus loading are detrimental, but so too are large decreases. Whilst the analysis suggests that urbanisation impacts are in general not expected to be large, changes in water demand brought about by population growth have disproportionate effects at low flows. These may result in increased incidence of very low dissolved oxygen concentrations which damage the health of the ecosystem.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419306377-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Hui Dong, Yifan Zhao, Xiuzi Jiang, Qian-Feng Gao, Zhichao Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The stability of a residual gravelly soil slope during heavy rainfall is closely related to the seepage field, which is directly affected by the seepage boundaries of the slope. To examine the boundary effect, a novel model flume that can implement permeable and impermeable boundary conditions was designed. With this flume, hydraulic model tests of a gravelly soil slope considering those two seepage boundaries were carried out. The results show that distinct spatial morphology of seepage fields is reflected by the hydraulic characteristics of the slope models with different seepage boundaries. The slope with permeable boundaries generally exhibits a larger average infiltration rate as well as a relatively smaller moving speed of wetting front in the lower part compared to the slope with impermeable boundaries. The residual moisture content in the deep-lower part of the slope with permeable boundaries is 6.6% cm〈sup〉3〈/sup〉/cm〈sup〉3〈/sup〉 smaller than that of the slope with impermeable boundaries. Nevertheless, the maximum pore water pressure in the middle part of the slope with permeable boundaries is 1.2 kPa higher than that in the corresponding part of the slope with impermeable boundaries. It is noted that regional pore water pressures in the shallow-lower and shallow-middle parts of the slope with impermeable boundaries exhibit large fluctuations with an amplitude over 0.5 kPa. The seepage field in the slope with permeable boundaries presents a multi-dimensional development, which may lead to a local failure of the slope. The results are of great significance in studying the similarity of seepage boundary condition in the field of similarity theory on landslide model tests and provide an experimental basis for establishing rainfall-induced landslide theory.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Zijun Li, Qingchun Yang, Yuesuo Yang, Honhyun Ma, Hui Wang, Jiannan Luo, Jianmin Bian, Jordi Delgado Martin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Groundwater resources are increasingly exploited for industrial and agricultural purposes in many arid/semi-arid regions globally. In order to gain a harmonious development among groundwater resources and economic benefits, urgent investigation of the impacts of anthropogenic activities on the groundwater chemistry is required. Understanding hydrochemical mechanism of groundwater in Yinchuan Plain, arid and semi-arid area in Northwestern China, plays a significant role in water resources planning in this ecologically sensitive area. In this paper, a total of 460 phreatic water samples were collected, including 58 water samples containing isotopic data (D and 〈sup〉2〈/sup〉H). Results demonstrate that water chemistry type and isotopic data of phreatic water presents a zonation characteristic from west to east and from south to north. In the eastern part of the Helan Mountain (A〈sub〉1〈/sub〉 zone), the type of hydrochemistry is mainly HCO〈sub〉3〈/sub〉·SO〈sub〉4〈/sub〉-Ca·Mg, SO〈sub〉4〈/sub〉·HCO〈sub〉3〈/sub〉-Ca·Mg, which is mainly recharged by the bedrock fissure water of Helan Mountain. However, in the southern Qingtongxia (A〈sub〉2〈/sub〉 zone) are HCO〈sub〉3〈/sub〉-Na HCO〈sub〉3〈/sub〉-Ca·Mg, which receives irrigation and spring water recharge. Phreatic aquifer in Multi-layered structure zone (A〈sub〉3〈/sub〉 zone) reflect multiple recharge sources to the aquifer, the water chemistry demonstrates diverse variations. The anion was dominated by the HCO〈sub〉3〈/sub〉, while the cation is dominated by sodium. The predominant controlling factors of phreatic water hydrochemistry are divided into anthropogenic activities and natural conditions. Natural conditions mainly include the existence form and lithology of the aquifer, sources of groundwater recharge, soil salinity, and evaporation, mineral dissolution, ion exchange and adsorption and mixing effect. Meanwhile, among natural factors, minerals dissolution in groundwater is the main process dominating the hydrochemical evolution of the groundwater. The other is anthropogenic activities which can be classified as groundwater pollution, excessive exploitation or excretion of groundwater, and excessive groundwater recharge.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419305840-ga1.jpg" width="381" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Ali Abdollahi-Nasab, Xiaolong Geng, Michel C. Boufadel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A combined field and numerical study of water flow and solute transport was conducted along a clean transect of a tidal gravel beach in Smith Island, Prince William Sound (PWS) that was heavily polluted after the Exxon Valdez oil spill. Water table and pore water salinity were directly measured in the field. The numerical model MARUN, validated with the field observations, was used to simulate subsurface flow and dissolved salt transport processes. Our study identified a two-layer hydraulic structure in the beach, a high-permeability upper layer and a low-permeability layer at the bottom. Numerical simulations indicated that the density gradient between the saltwater and freshwater strongly affects solute transport in the intertidal zone of the beach. A sensitivity study indicated that depth to and slope of the bedrock had major effects on solute transport in the lower layer, but minor effects in the upper layer. A deep bedrock caused the water particles travelling in the lower layer to penetrate deeper in the beach. Our study revealed high terrestrial freshwater recharge to the transect which promotes the removal of oil in two-layer beaches by maintaining the water table at or above the interface of the two layers. The study presented in this paper has strong implications on the oil persistence and associated removal strategies along the Alaskan coastline polluted with oil. Findings from this work in relation to oiled beaches include: 1) oil tends to persist at locations of small freshwater recharge and 2) Prior to oil arriving to the shoreline, one could minimize oil penetration into the beach by releasing water onto the beach at the high tide line during low tides.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Christiane Zoghbi, Habib Basha〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Most karst aquifers are characterized as a dual-flow system comprised of a highly conductive conduit network embedded in a low porosity matrix. The conduits are hydraulically connected to the matrix and behave either as a drain or a source depending on the recharge conditions. Simplified physically based models are herein employed to simulate the spring outflow for such aquifer systems. The processes consist of a free-surface flow in the conduit that is interacting laterally with a laminar groundwater flow in the surrounding matrix. The conduit is subject to a concentrated recharge at its upstream end while the groundwater aquifer is subject to a diffuse recharge over its contributing surface area. The flow system is described by a coupled system of partial differential equations: the conduit flow is approximated by the kinematic wave equation and the groundwater flow by the linearized Boussinesq equation. The governing equations are solved using the Laplace transform method after an appropriate linearization of the nonlinear coefficient. The derived spring discharge models are a function of three dimensionless parameters: the time lag parameter 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si6.svg"〉〈mi〉ξ〈/mi〉〈/math〉, the lumped conduit parameter 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.svg"〉〈mi〉λ〈/mi〉〈/math〉, and the aquifer parameter 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si8.svg"〉〈mi〉η〈/mi〉〈/math〉. The simulation results highlight the contrast between pressure-driven and gravity-driven flows and the importance of the conduit-matrix interaction on the response of the karst system. Application of the models on real karst aquifers demonstrates their effectiveness in simulating the observed spring hydrograph using lumped physical parameters of the karst system.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 23 February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Anil Kumar Singh, J.N Tripathi, K.K. Singh, Virendra Singh, M. Sateesh〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, effort is made to estimate weekly rainfall over India at 36 meteorological subdivisions during monsoon 2016 (June to September) by using several precipitation products from different satellites which include Indian National Satellite System (INSAT) INSAT-3D derived Hydro Estimate (HE), INSAT Multi-Spectral Rainfall Algorithm (IMSRA) rainfall products, Integrated Multi-satellite Retrievals for GPM (IMERG) derived from JPL, NASA, and National Center for Medium Range Weather Forecasting (NCMRWF) Merged Satellite Gauge (NMSG) of IMD. Different satellite estimates, and rain gauge satellite merged products have been compared with gridded rainfall products prepared by India Meteorological Department (IMD). HE at 4 km pixel resolution and IMSRA at 0.10〈sup〉0〈/sup〉 × 0.10〈sup〉0〈/sup〉 resolution are derived rainfall products from Indian satellite INSAT-3D.GPM (IMERG) product is derived at 0.10〈sup〉0〈/sup〉 × 0.10〈sup〉0〈/sup〉 resolution from Global Precipitation Mission (GPM) satellite jointly operated by JAXA (Japan) and NASA (USA). NCMRWF Merged Satellite-Gauge (NMSG) rainfall data has been generated at a 0.25° × 0.25° grid resolution by IMD & NCMRWF. The data is analyzed preliminarily for the southwest monsoon season of 2016 at weekly temporal resolution. The overall comparison shows that GPM (IMERG) estimates better rainfall over the coastal and plain region, however, HE estimates better rainfall over the hilly region, in general, and for Kerala region, particularly. NMSG product needs improvement over the hilly region and considerable improvement is required in IMSRA product. For all 36 meteorological subdivisions, NMSG product has 0.56 average Nash-Sutcliffe efficiencies (NSE) for 17 weeks with IMD Gridded rainfall data. However, for satellite-derived rainfall by GPM (IMERG), HE and IMSRA have 0.29, 0.1 and −0.8 average NSE at 17 weeks, respectively. Based on this study, it is concluded that NMSG daily rainfall product is best, however, amongst satellite-derived rainfall, overall GPM gives a better result with a few exceptions and IMSRA need more modifications.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Gaofeng Zhu, Kun Zhang, Huiling Chen, Yunquan Wang, Yonghong Su, Yang Zhang, Jinzhu Ma〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Following the scheme of the groundwater-soil-plant-atmosphere continuum (GSPAC), a simple process-based model (SiTH; Simple Terrestrial Hydrosphere) was developed to estimate the dynamics of terrestrial evapotranspiration (ET) at the daily step. The input data include net radiation, air temperature, precipitation, leaf area index, vegetation type and soil data, most of which are readily available. Locally, the model performed well in simulating the dynamics of ET and soil moisture over selected FLUXNET sites. Globally, the daily 0.25° ET and groundwater table depth estimations in year 2005 were determined using available gridded datasets. The spatial pattern was reasonable and the range of values corresponded well with other global ET and groundwater table depth products. In future studies, we will produce a long-term daily 0.25° global ET and groundwater table depth products that spans from 1984 to present by using different input datasets.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Zhongwang Wei, Xuhui Lee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study explores the utility of observations of deuterium excess (dx) of water vapor for attribution of vapor to remote source regions and local influences. A Lagrangian back trajectory model was combined with various parameterizations of the dx of ocean evaporation and land evapotranspiration to simulate daily vapor dx at a continental site, a marine site and a coastal site. The model reproduced reasonably well the observed variabilities in the vapor dx at the coastal and the marine site when water vapor at these sites were primarily influenced by large-scale advection from ocean sources. The simple parameterization relating dx of the ocean evaporation to relative humidity is a robust representation of the ocean isotopic evaporation. On the other hand, the model did poorly for the continental site and during the land evapotranspiration dominated months at the coastal and the marine site, confirming the published findings that the water vapor dx near the Earth’s surface can be significantly altered by land evapotranspiration and therefore is not a conserved tracer of humidity from the marine moisture source region. Several parameterizations for the dx of land evapotranspiration suggested by previous studies were tested with the trajectory model, but none brought improvement to the simulation of the dx at the continental site. Our study emphasizes that a fundamental challenge in isotopy hydrology is the lack of understanding of the different fractionation processes of 〈sup〉18〈/sup〉O and D associated with land evapotranspiration.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 3 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Kai Germer, Jürgen Braun〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉The aim of the study was the comparison of the soil hydraulic properties determined based on two different experimental methods of four large and macroporous soil samples. An undisturbed cylindrical soil column (h = 60 cm and d = 30 cm) was obtained at a natural slope and quartered horizontally in the laboratory. The four sub-samples were saturated and subsequently drained using the extended multi-step outflow method (XMSO). Retention curves and unsaturated hydraulic conductivity curves were derived via inverse modeling based on the measured drainage and corresponding pore water pressure. After resaturation the evaporation method (EVA) was used on the same four samples. The samples were exposed to evaporation and the effective water contents and the average pore water pressures were recorded over time to determine soil hydraulic functions.〈/p〉 〈p〉While both methods yielded similar results in the medium moisture range, the advantage of the XMSO-method is its higher information content with respect to the hydraulic conductivity close to water saturation whereas the advantage of the EVA-method is its fast execution. Moreover, the EVA-method is easier to handle and has significantly lower computational requirements than the XMSO-method.〈/p〉 〈p〉Furthermore, since the four soil samples represent a soil profile in the field, a depth dependent characterizing of the soil profile was possible and showed that the soil properties near saturation are greatly dominated by the ratio of macropores in the sample and that a decrease in the macropore ratio with soil depth was clearly reflected in the hydraulic functions.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Parsa Pouladi, Abbas Afshar, Mohammad Hadi Afshar, Amir Molajou, Hamid Farahmand〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study proposes a novel socio-hydrological modeling framework for assessing the performance of complex water resources systems. It employs and integrates agent-based modeling (ABM) and the theory of planned behavior (TPB) into the socio-hydrological modeling framework to account for agents’ behaviors. Due to farmers’ major role in anthropogenic droughts, this paper mainly focuses on farmers’ behavior. The TPB framework and the agents’ behavioral rules in ABM are structured based on the data obtained from field questionnaires and interviews by the farmers in the Zarrineh River Basin as the main river feeding the Urmia Lake. The proposed modeling framework, including the TPB and ABM structures and rules, are validated by comparing the results of the proposed socio-hydrological simulation model with the actual data on the simulation period. To assess the ability of the proposed framework, root mean square error (RMSE) and the determination coefficient (DC) were computed. The results show the acceptable performance of the proposed model by RMSE = 0.18 and DC = 0.92. Analysis of the results indicates that financial conditions, farmland size, farmers’ age, and farmers’ education are among the major factors in farmers’ decision-making process, respectively.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Dong Hun Kang, Tae Sup Yun〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study describes immiscible fluid displacement near a transitional boundary at which inertial effect occurs. We simulated two-phase fluid flow in a 2D micromodel using the lattice Boltzmann method with varying Reynolds numbers (〈em〉Re〈/em〉) (log 〈em〉Re〈/em〉 = −2 to 2) and viscosity ratios (〈em〉M〈/em〉) (log 〈em〉M〈/em〉 = −2 to 0). To highlight the role of inertial force rather than capillary and viscous forces, the capillary number (〈em〉Ca〈/em〉) was kept constant at log 〈em〉Ca〈/em〉 = −5. As 〈em〉Re〈/em〉 and 〈em〉M〈/em〉 increased, development in the preferential flow became more pronounced with tortuous paths. We found the transitional boundary exists near log 〈em〉Re〈/em〉 = −1 to 1 at which residual saturation of the displaced fluid starts to fluctuate and changes 5%–14% in the transitional regime. In particular, this boundary describes the effect of inertia on immiscible fluid displacement before an increase in the work done due to inertial force occurs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Mojtaba Izadmehr, Mahdi Abbasi, Mohammad Hossein Ghazanfari, Mohammad Sharifi, Alireza Kazemi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉An exact analytical solution for one-dimensional fluid flow through rock matrix block is presented. The nonlinearity induced from flow functions makes the governing equations describing this mechanism difficult to be analytically solved. In this paper, an analytical solution to the infiltration problems considering non-linear relative permeability functions is presented for finite depth, despite its profound and fundamental importance. Elimination of the nonlinear terms in the equation, as a complex and tedious task, is done by applying several successive mathematical manipulations including: Hopf-Cole transformation to obtain a diffusive type PDE; an exponential type transformation to get a convective-diffusive type PDE with suitable boundary conditions; Laplace transformation; Integral transformation to homogenize the boundary condition in the Laplace domain; and finally Laplace inversion method to find the time domain solution. The obtained solution is used for developing a new matrix-fracture transfer function. The developed analytical equations are used for prediction of drying front in the case of evaporation from deep water table. The model results are in close agreement with the experimental data and numerical simulation of the process. Results of sensitivity analysis of different parameters on recovery rate and ultimate production based on design of experiment method are also discussed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Xi Chen, Melissa M. Motew, Eric G. Booth, Samuel C. Zipper, Steven P. Loheide, Christopher J. Kucharik〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lake level regulation is commonly used to manage water resources and mitigate flood risk in watersheds with linked river–lake systems. In this study, we first assess exposure, in terms of both population and land area, to flooding impacts in the Yahara Watershed’s chain of four lakes in southern Wisconsin as affected by minimum lake level management. A flooding exposure assessment shows that the areas surrounding the upstream lakes, Mendota and Monona, have dense urban areas with high populations that are exposed to flooding; Waubesa has low elevations along its lakeshore, resulting in a large potential flooding area; and the most downstream lake, Kegonsa, has a large area of surrounding cropland that is exposed to flooding but impacts a limited population. We then use a linked modeling framework of a land surface model (Agro-IBIS) and a hydrologic-routing model (THMB) to simulate daily lake level over a study period of 1994–2013 in the Yahara Watershed with different minimum lake level management strategies. Modeling results show that the peak lake levels and corresponding exposed land area and population to flooding will decrease under a lower target minimum lake level. However, at the same time, the number of days that the lake level is below winter minimum will increase, which may adversely affect ecosystem health. In addition, our sensitivity analysis indicates that reducing target minimum lake levels will help mitigate flood risk in terms of both flood magnitude and frequency. Nevertheless, this must be balanced against the need to maintain adequately high lake levels for ecosystem services and recreational functions of the lakes.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Wei Zhou, Jiaoyong Fang, Chuan Tang, Genyun Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The Wenchuan area has become highly susceptible to landslides and debris flows since the earthquake occurred on 2008. A detailed debris flow hazard assessment is necessary to provide information for future risk management. Debris flow runout on a depositional fan is an important factor for assessing debris flow hazard, and its estimate becomes essential for the planning of the mitigation works that must be built. We therefore developed two simple empirical relationships based both on univariate and multivariate approaches, which provide the runout distance using the data for 134 channelized debris flow events in 134 catchments in the Wenchuan earthquake zone. We generated a correlation matrix of the debris flow runout distances and the relevant variables. Because of the high correlations, the independent variable debris flow volume (〈em〉V〈/em〉〈sub〉D〈/sub〉) was selected for the univariate approach. Using a multicollinearity analysis and a stepwise regression technique, the catchment (basin) internal relief (〈em〉H〈/em〉), and 〈em〉V〈/em〉〈sub〉D〈/sub〉 were used to develop a multivariate runout relationship. The coefficients of the variables were obtained using 80% of the dataset (training dataset); the remaining 20% was used for test of estimated performance by comparing the computed runout distances with observed values. The validation demonstrated that the proposed relationships are suitable for estimating the runout distances of debris flows on depositional fans in the Wenchuan earthquake zone. The univariate runout relationship has the advantage of being simple, whereas the multivariate runout relationship provides higher accuracy. Additionally we rearranged and reformulated existing relationships using the same training dataset and compared the results with those from the relationships here proposed. The estimations provided by our relationships were the closest to the observed values. The presented approaches may be applied to estimate debris flow runout distances in other areas after they are retrained using local datasets.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 576〈/p〉 〈p〉Author(s): Wencong Yang, Hanbo Yang, Dawen Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Catchment classification aids in the identification of homogeneous regions in which catchments have similar flood timing and corresponding climatic drivers. As a new classification scheme from complex network theory, the community detection method is introduced to classify 242 catchments in the United States based on flood seasonality. The robustness of this method is tested by calculating the Adjusted Rank Index between the classification results from different random subsets of the 242 catchments and different flood sampling methods. In addition, three network metrics (network density, centrality, and 〈em〉k〈/em〉-core nucleus) are used to further unravel the hydrological connections within each community of catchments. Catchments with similar flood seasonality cluster into six large communities, while catchments in sparsely gauged areas or with unique physiographic properties are isolated from large communities. High values of the Adjusted Rank Index show the robustness of the community detection method for catchment classification. The results indicate that the complex network is valid for use in classifying catchments based on flood seasonality. Moreover, for each community, the network metrics are potential descriptors of: (a) the degree of homogeneity, (b) the representativeness of any catchment, and (c) the spatial scale of synchronized floods. Therefore, the complex network is able to characterize the interconnections between catchments within the community.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Wei Wang, La Zhuo, Meng Li, Yilin Liu, Pute Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Improved spatial and temporal resolutions in quantification enable the water footprint (WF) in crop production to be a comprehensive indicator of water consumption in agricultural water management. In general, existing literature focus on the impact of water-saving irrigation techniques on crop yield and water consumption during the growth period at sites or experimental units, few studies yet that explicitly addresses the effect of developments in water-saving irrigation techniques on large-scale WF accounting and benchmarking. Here, we fill this gap through a case study for wheat in China over 2000–2014, during which the micro-irrigated wheat area expanded 14 times. The green and blue WFs of China’s wheat per year are estimated at a 5 arc-minute resolution. For irrigated wheat, we distinguish three irrigation techniques: furrow, sprinkler and micro-irrigation. The WF benchmarks by irrigation type are further estimated separately for arid and humid zones. Irrigation accounted for 70% of annual WF in China’s wheat land, while furrow irrigation dominated the national total WF. The occupation by WF under micro-irrigation was the smallest but jumped by 14 times in quantity whereas that under sprinkler halved. China’s average WF per ton of wheat under sprinkler irrigation was 21% higher than that under micro-irrigation in 2014. The 20th percentile WF benchmarks of wheat under micro-irrigation was 13% and 31% smaller than that under furrow and sprinkler irrigation, respectively, in arid zones. Meanwhile, high provincial heterogeneities in terms of WF under varied distribution of irrigation techniques were also shown. The study shows possibility and importance to account for developments of water-saving techniques in large-scale crop WF estimations.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract:〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419306365-ga1.jpg" width="280" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Zhengke Pan, Pan Liu, Shida Gao, Lei Cheng, Jie Chen, Xiaojing Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hydrological processes became non-stationary under the influences of climate change and human activities. This non-stationarity highlights the need to adopt time-varying parameters in hydrological models. The majority of existing literature quantifies time-varying parameters by incorporating real observations of single basin into a hydrological model. They are limited in their information on catchment characteristics and climatic factors to constrain time-varying parameters. Thus, models are difficult to apply for hydrological predictions outside the calibration periods. This paper formulated the time-varying parameters for a lumped hydrological model as explicit functions of physically-based covariates that captured the catchment characteristics. Then, it used a hierarchical Bayesian framework to incorporate the similarity of adjacent basins to reduce the uncertainty of the assumed functions for time-varying parameters. Four modeling scenarios were developed to explore the spatial coherence between different characteristics of adjacent basins. Five criteria were adopted to evaluate the performance of assumed functional forms. Four spatially adjacent catchments in the central United States were selected as case studies to examine the validity of the proposed method. Results showed that (1) the proposed method succeeded in reducing the uncertainty of time-varying parameters, and (2) the seasonality of the catchment storage was more coherent between adjacent basins, indicated by the largest increase in model prediction performance (i.e., 9%). This study improved the understanding of the spatial coherence of time-varying parameters, which helps improve hydrological predictions in the future.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Zhuo Cheng, Bofu Yu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Dramatic land clearing occurred in Central Queensland of Australia in the 1960s–1980s, and its impacts on streamflow are of great importance for regional water resources inventory and management. Paired catchment studies at the small scale (around 10–20 ha) have shown conclusively that clearing forests for agriculture has more than doubled the streamflow in the region. Two previous investigations at the large scale (the Comet basin with an area of 16,460 km〈sup〉2〈/sup〉) have drawn quite different conclusions about the land clearing effect on streamflow, varying from 40% increases in streamflow due to land clearing to all the changes in streamflow occurring as a result of climate variability. To further examine the effect of land clearing on streamflow at the large scale in Central Queensland, this study attempts to resolve the discrepancy of the two previous studies by applying the same set of methods (double mass curves, flow duration curves, Budyko framework, Tanh function and conceptual hydrologic model SimHyd) for three distinct periods, namely pre-clearing, transitional and post-clearing periods, and for two neighbouring large basins. The main conclusions of this study are: 1) the effect of land clearing on streamflow of large basins in Central Queensland are unmistakably detectable; 2) the impact of land clearing manifested itself mostly during wetter years or for wetter basins; 3) for a given basin, the greater the extent of land clearing the larger the effect on streamflow; and 4) a lack of consistent conclusions about the land use change effect on streamflow at the large scale for this region and for several other large basins around the world are likely a result of the different methodologies used, different contrasting periods, and the differing effect on streamflow in relation to the underlying climate variability.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Shuyuan Wang, Dennis C. Flanagan, Bernard A. Engel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Reliable estimation of sediment transport capacity is essential for soil erosion modeling. The objective of this study was to evaluate the performance of twelve widely used transport capacity functions with a wide range of hydraulic conditions and soil properties. The comparisons with observed data indicated that none of the selected twelve functions gave satisfactory results for transport capacity prediction over all overland flow datasets in this study, and all of them gave very poor predictions for loess soil. Therefore, a new equation was developed for sediment transport capacity estimation. Among these twelve functions, the Ali equation gave the best fit for the whole dataset, but calibration was necessary when using it for large sediment grains (〉2 mm) or loess soil. The Yalin equation and the simplified Yalin equation worked better for soils than sands, and predictions for smaller sands (∼0.2 mm) were acceptable. The Govers equation had relatively uniform performance for all datasets. The performance of empirical equations changed dramatically for different datasets. A new function developed in this study was generated based on dimensional analysis and gave good predictions within the range of hydraulic conditions and particle sizes in the datasets considered in this study. The results provide a summary of the transport capacity functions evaluated and suggest an improved function for modeling overland flow sediment transport capacity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Olivier Champagne, M. Altaf Arain, Paulin Coulibaly〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Flooding is a major concern for Canadian society as it is the costliest natural disaster type in Canada. Southern Ontario, which houses one-third of the Canadian population, is located in an area of high vulnerability for floods. The most significant floods in the region have historically occurred during the months of March and April due to snowmelt coupled with extreme rain events. However, during the last three decades, there has been a shift of flooding events to earlier months. The aim of this study was to understand the impacts of atmospheric circulation on the temporal shift of streamflow and high flow events observed in southern Ontario over 1957–2013 period. Predominant weather regimes over North America, corresponding to recurrent meteorological situations, were identified using a discretization of daily geopotential height at 500HpA level (Z500). A regime-normalized hypothetical temperature and precipitation dataset was constructed to quantify the contribution of atmospheric circulation on streamflow response. The hypothetical dataset was used as input in the Precipitation Runoff Modeling System (PRMS), a rainfall-runoff semi-distributed hydrological model, and applied to four watersheds in southern Ontario. The results showed an increase in the temporal frequency of the regime identified here as High Pressure (HP) close to eight occurrences per decade. Regime HP, characterized by a northern position of the polar vortex, is correlated with a positive phase of the NAO and is associated with warm and wet conditions over southern Ontario during winter. The temporal increase in HP contributed more than 40% of the increase in streamflow in winter and 30–45% decrease in streamflow in April. This atmospheric situation also contributed to increase the number of high flows by 25–50% in January. These results are important to improve the seasonal forecasting of high flows and to assess the uncertainty in the temporal evolution of streamflow in the Great Lakes region.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Pengju Cheng, Qingchun Yu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The breakthrough pressures of shale fractures are of great significance for the understanding of shale gas seepage or accumulation, CO〈sub〉2〈/sub〉 geological sequestration and radioactive waste storage in shale, and pollution problems caused by gas leakage. In this study, three shale cores taken from the eastern Qaidam Basin in China were used to investigate the breakthrough pressures of partially saturated shale fractures. The fractured shale core had a single longitudinal fracture across the core along the axis. A quantitative description of the relationship between the breakthrough pressure and the water content in the fracture is difficult because of the difficulty in the measurement of the water volume in the fracture. We propose a method to describe this relationship. In this method, the water content in the fracture is described by the matric potential. Cores with different matric potentials were prepared by moistening the cores in different humidity environments. Methane breakthrough experiments were conducted on three core samples under six different matric potentials. The six matric potential levels were −51.38 MPa, −39.08 MPa, −23.45 MPa, −8.55 MPa, −2.33 MPa, and 0 MPa. Based on the experimental results, we apply a conceptual model to qualitatively describe the relationship among the matric potential, water distribution in the fracture, and breakthrough pressure. At a low matric potential, water forms very thin water films on fracture surfaces, and the effect of water on the breakthrough pressure is not notable. As the matric potential increases, the thickness of water film in the fracture increases, and the increase in the breakthrough pressure become notably. We establish a mathematical model to quantitatively describe the relationship between the breakthrough pressure and matric potential. The experimental data show that the increase in breakthrough pressure with the matric potential is a process that proceeds from slow to fast, and there is a critical value of matric potential in this process. When the critical value is reached, the connected gas passages are gradually sealed by water films, and the breakthrough pressure begins to increase significantly.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Gonzalo Carrasco, Jose-Luis Molina, María-Carmen Patino-Alonso, Marisela Del C. Castillo, María-Purificación Vicente-Galindo, María-Purificación Galindo-Villardón〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Water quality is a sensitive topic of worldwide concern that is defined by a series of physical, chemical and biological characteristics. The complex nature for studying water quality requires finding simple models to identify the variables that influence it the most. Therefore, the use of multivariate analysis techniques will be of immense help to find relationships and conclusions which aid us to determine the state of water quality through biological, physical and chemical indicators. In this investigation, the following variables were evaluated: Temperature, pH, transparency, turbidity, nitrates, orthophosphates, phosphorus, total nitrogen, chlorophyll 〈em〉a〈/em〉, solar radiation, dissolved oxygen and microcystins. These determined water quality at the sample sites, Gamboa and Paraiso. The results obtained through the application of a two-way multivariate analysis method called HJ-Biplot reflect variableś relationships of chemical, physical and biological compositions. Furthermore, results conform two clusters of sample points that satisfactorily match to the region seasons. Cluster 1 is characterized by the presence of the following variables: pH, transparency, chlorophyll 〈em〉a〈/em〉, oxygen and temperature. On the other hand, cluster 2 comprises the following variables: nitrate, orthophosphates, turbidity and P-total. They are all parameters that suffer variations in the rainy season, and that, in turn, can influence the presence of ciabobacteria with toxigenic potential. Furthermore, this study demonstrates that the multivariate statistical methods are valuable for interpreting complex data sets, specifically, for water quality monitoring network.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Maria Angela Serio, Francesco Giuseppe Carollo, Vito Ferro〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Empirical relationships linking kinetic energy to rainfall intensity are commonly used to estimate rainfall erosivity. In this paper, using the drop-size distribution (DSD) proposed by Marshall and Palmer, a relationship for calculating the rainfall kinetic power was firstly deduced. This equation requires the simultaneous measurement of both the median volume diameter and the rainfall intensity and its application also reveals the drawback of needing the measurement of the whole DSD by an expensive disdrometric technique.〈/p〉 〈p〉Then, using a fictitious precipitation, which is both constituted by droplets having the same diameter (mean volume diameter) and having the same volume of the actual rainfall, a new expression of the rainfall kinetic power was deduced. This last equation has the advantage of allowing the estimate of the rainfall kinetic power by using the measurements of both rainfall intensity and the total number of droplets, reaching a horizontal unit area in an unit time, which can be acquired by a cheap device using a piezoelectric force transducer.〈/p〉 〈p〉This new relationship for estimating the rainfall kinetic power was tested using disdrometric measurements carried out at two experimental sites in Italy (Palermo) and in Spain (El Teularet). These experimental tests demonstrated that the rainfall kinetic power estimated by the mean volume diameter has an accuracy similar to the literature relationships proposed by Wischmeier and Smith, Brown and Foster and McGregor et al.〈/p〉 〈p〉Finally this investigation also showed that this novel approach can be applied estimating the median volume diameter by the mean volume diameter and the standard deviation of the measured drop diameters, whose measurement can be obtained by a force transducer.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Dongnan Li, Jianshi Zhao, Rao S. Govindaraju〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Rapid economic development and population growth in the Lancang-Mekong River Basin makes it imperative for water resources to be used fairly and efficiently among all stakeholders. This paper proposes an integrated model framework to assess the water benefits sharing schemes among the five stakeholders in the basin, namely, China, Thailand, Laos, Cambodia, and Vietnam. Three objectives are considered for this assessment—hydropower (HP), eco-index (EI), and agricultural water use (AW). The hydrologic model, optimization model, and cooperative game theory methods are jointly used to analyze the water benefits of stakeholders under different scenarios. According to the model, cooperation can bring more incremental benefits in dry years when water resources are scarce. Three cooperative game theoretical methods, namely, the Shapley value, the Gately point, and the Nash–Harsanyi solution, are employed to find the possible benefit sharing solutions. The results show that China and Laos need to operate their reservoirs for downstream countries’ beneficial uses under cooperation, and thus, compensation by reallocating the incremental benefit from cooperation is necessary no matter which method is used. It is found that all of the future damming plans would enhance the basin-level cooperation in most cases. In particular, according to the analysis, damming in the basins of the Sesan, Srepok, and Sekong rivers would have more effect than damming in the upper Lancang-Mekong River Basin after 2030. Based on some verified assumptions, the results of this paper can offer real-world preferences, but the uncertainties need to be further explored.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Guozheng Zhi, Zhenliang Liao, Wenchong Tian, Xin Wang, Juxiang Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The urban drainage model is an important tool for the management and decision-making around an urban drainage network. Owing to urban drainage networks’ complex distribution, existing model analysis methods have gradually exposed problems of insufficient utilization of spatial information, weak coupling and analytical capacity of multi-source heterogeneous data, and poor human-computer interaction. By coupling an urban drainage model with 3D GIS technology and 3D visualization technology, this study presents a 3D dynamic visualization method of an urban drainage model (3DDVM-UDM). A case study from Chaohu, China, is used to demonstrate the method. The environmental information and distributions of pipe network objects in 3D space were presented. The urban drainage model can be edited and simulated in the 3D environment, and a 2D flooding simulation method was also established. Multiple model results were dynamically and simultaneously visualized in the pipe network entity models. By coupling and comparing the model results under different rainfall return periods, various information was intuitively analyzed, such as the water level and water quality differences of each pipe and node, and the spatial distribution differences of fully filled pipes, overflowed nodes and buildings influenced by node overflow. The operation state of a drainage pipe network can be systematically analyzed by intuitively combining with the attribute information of a pipe network, 3D spatial information and other relevant data. This study provides a feasible theory and method to assist in environmental management and decision-making, to facilitate communication between different fields, and to promote a shift in analysis from 2D to the combination of 2D and 3D.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Wei Fang, Shengzhi Huang, Qiang Huang, Guohe Huang, Hao Wang, Guoyong Leng, Lu Wang, Pei Li, Lan Ma〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Frequent droughts in a warming climate may exert more negative influences on ecosystems. Unlike previous studies that have investigated the vegetation response to drought generally in a deterministic way, a copula-based model is developed for quantifying drought impacts on terrestrial vegetation and identifying drought-vulnerable regions for mainland China from a probabilistic perspective in this study. The Normalized Difference Vegetation Index (NDVI) is firstly correlated with the Standardized Precipitation Evapotranspiration Index (SPEI) at varying timescales from 1 month to 24 months to determine the response time of vegetation to water variability. Then, the dependence structure of vegetation vigor and water availability is modeled through the bivariate copula analysis. Furthermore, conditional probabilities of vegetation decline under moderate, severe and extreme drought scenarios are systematically estimated using copula-based conditional probability distributions. Results indicate that spatial patterns of vegetation response time present distinct seasonality, with faster response to water variation in the southern part than in the northern proportion of mainland China during the non-growing season while the inverse pattern is observed for the growing season. The higher conditional probabilities of the below-average vegetation status in the dry condition evidence that water deficits overwhelming water surplus play a more profound role in diminishing vegetation vigor across more than 80% of mainland China. Specifically, when moderate droughts develop into extreme ones, the average probability of vegetation status below the 50th percentile escalates by 6.9%. Moreover, extreme droughts are noted to exaggerate probabilities of vegetation activity falling below the increasingly lower (40th, 30th, 20th and 10th) percentiles by 8.8%, 10.8%, 12.7% and 13.7% in comparison with moderate counterparts, thereby suggesting higher likelihood of the deteriorating drought conditions inducing vegetation losses, especially major vegetation decline. As for the drought-vulnerable region, North China, particularly the central Inner Mongolia, is recognized with vegetation decline probabilities being 28.1% and 68.8% greater than the mainland average given drought conditions (quantified as SPEI ≤ −1), respectively. Results of the study may improve our understanding of climatic extreme influence on vegetation status and benefit the effective drought preparedness and mitigation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Qinggao Feng, Xiang Yuan, Hongbin Zhan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A general analytical model for the problem of variable discharge of groundwater from a well in an anisotropic two-layered aquifer system is developed by taking account of the interface flow between the two layers. The well of infinitesimal radius partially penetrates the lower layer and is pumped at a variable discharge. The horizontal as well as vertical flows in both layers are included, and importantly, the effects of constant-head (Case 1) and no-flux (Case 2) boundaries at the top of the upper layer are considered. Laplace domain solutions for drawdown in dimensionless form are derived with the help of Hankel transform, and are inverted to the time domain numerically. The drawdown characteristics induced by an exponentially decayed rate of pumping are discussed, and sensitivity analysis is also performed to explore the influence of different parameters on drawdown characteristics. The results show that the drawdown around a partially penetrating well in the lower pumped layer induced by an exponential decreasing pumping rate usually contains three stages. The effect of anisotropy and well configuration have great influences on the drawdown distribution near the pumping well, and the horizontal flow and storativity of the upper (unpumped) layer cannot be ignored in determining the upper aquifer drawdown. The sensitivity analysis also illustrates that the dimensionless drawdown in the lower pumped layer is very sensitive to well configuration parameters all the time. It is only sensitive to the hydraulic parameters of the lower aquifer for Case 1 and to the hydraulic parameters of the lower layer and the specific storage of the upper layer at late times. The dimensionless drawdown of the upper layer is not sensitive to the variable well discharge parameters over the whole pumping period, and is not sensitive to the storage parameters of both layers for Case 1. However, the drawdown in the upper layer is sensitive to all the hydraulic parameters and well configuration parameters for Case 2 at late times.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Zidong Luo, Huade Guan, Xinping Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electrical resistivity (ER) tomography is a useful nondestructive tool to visualize and estimate moisture content distribution in soil and wood. Wood ER is a function of both moisture and temperature, however, it is not known yet how the temperature effect should be corrected in order to use ER tomography to monitor wood moisture variations. This study aims to break this technical barrier. The ER of three trunk sections of different Australian native tree species was measured at varying temperature (control experiments), and for different moisture contents. The results show that wood ER decreases with an increase of temperature in a nonlinear manner, and that the exponential model performs the best to represent the temperature effect on ER in comparison to two other models (the linear model and power function model). The key parameter in the exponential model for sapwood, reflecting temperature sensitivity, fluctuates in a narrow range between 0.032 and 0.036 °C〈sup〉−1〈/sup〉. It appears to be independent of tree species, but significantly different from the value recommended in the literature for temperature correction in soil electrical resistivity. The temporal variations of temperature-corrected ER capture wood moisture variations in time. We suggest that it is better to have wood temperature monitoring while ER tomography is taken for living trees so that the temperature effect can be removed from ER tomograms using the exponential model for wood moisture estimation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Pankaj Dey, P.P. Mujumdar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Understanding response of temporal distribution, timing, frequency and amount of high and low intensity rainfall to warming is important in water resources management. In this paper, Relative Entropy is used to investigate the spatial variability and change in uniformity of rainfall distribution over India. Temporal trends in atmospheric temperature can alter the frequency and amount of high and low intensity rainfall events, which influence the uniformity of rainfall distribution. The study is divided into two time periods, 1951–1980 and 1981–2010 based on time trend in annual mean temperature. The sensitivity of rainfall uniformity and high and low intensity rainfall events to annual mean temperature and the degree of coherence between them are investigated. The uniformity of rainfall distribution shows a significant spatial variability. Significant changes are observed in both the amount and timing of rainfall across India. A significant association between rainfall uniformity and low intensity of rainfall is observed in the recent past over a larger aerial extent compared to the distant past. It is concluded that rise in temperature modifies both high and low intensity rainfall events, thus altering the uniformity in rainfall distribution. A regionally varied strength of coherence between rainfall uniformity and high and low intensity rainfall is observed which may be due to regionally dependent soil moisture-precipitation feedbacks.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Michael R. Rosen, Karen R. Burow, Miranda S. Fram〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Concentrations of uranium (U) 〉30 µg/L in groundwater are relatively uncommon in drinking water in the United States but can be of concern in those areas where complex interactions of aquifer materials and anthropogenic alterations of the natural flow regime mobilize U. High concentrations (〉30 µg/L) of U in the southeastern San Joaquin Valley, California, USA, have been detected in 24 percent of 257 domestic, irrigation, and public-supply wells sampled across an approximately 110,000 km〈sup〉2〈/sup〉 area. In this study we evaluated mechanisms for mobilization of U in the San Joaquin Valley proposed in previous studies, confirming mobilization by HCO〈sub〉3〈/sub〉 and refuting mobilization by NO〈sub〉3〈/sub〉 and we refined our understanding of the geologic sources of U to the scale of individual alluvial fans. The location of high concentrations depends on the interactions of geological U sources from fluvial fans that originate in the Sierra Nevada to the east and seepage of irrigation water that contains high concentrations of HCO〈sub〉3〈/sub〉 that leaches U from the sediments. In addition, interactions with PO〈sub〉4〈/sub〉 from fertilized irrigated fields may sequester U in the aquifer. Principal component analysis of the data demonstrates that HCO〈sub〉3〈/sub〉 and ions associated with high total dissolved solids in the aquifer and the percentage of agriculture near the well sampled are associated with high U concentrations. Nitrate concentrations do not appear to control release of U to the aquifer. Age dating of the groundwater and generally increasing U concentrations of the past 25 years in resampled wells where irrigation is prevalent suggests that high U concentrations are associated with younger water, indicating that irrigation of fields over the past 100 years has significantly contributed to increasing concentrations and mobilizing U. In some places, the groundwater is supersaturated with uranyl-containing minerals, as would be expected in roll front deposits. In general, the interaction of natural geological sources high in U, the anthropogenically driven addition of HCO〈sub〉3〈/sub〉 and possibly phosphate fertilizer, control the location and concentration of U in each individual fluvial fan, but the addition of nitrate in fertilizer does not appear control the location of high U. These geochemical interactions are complex but can be used to determine controls on anomalously high U in alluvial aquifers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Chen-Wuing Liu, Ming-Zhe Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉High arsenic concentrations (average 0.1 mg/L) of groundwater were found in Lanyang plain of Taiwan. In this study, 39 groundwater samples from 23 wells were collected and 14 hydro-geochemical parameters were analyzed. Factor analysis was applied to determine major influence factors of the arsenic enriched groundwater quality, and PHREEQC was used to calculate the distribution of aqueous species and saturation index of which affected the hydrogeochemistry of groundwater. 393 geological core samples from 9 drilling wells were collected and analyzed the contents of total arsenic and iron. Moreover, core samples associated with high arsenic concentration groundwater were selected, mineralogical phases were analyzed using X-ray fluorescence (XRF), high resolution X-ray photoelectron (XPS) and scanning electron microscope and energy dispersive spectrometer (SEM-EDS). Results of the arsenic enrichment factor determined by factor analysis indicated that infiltration of the organic and nitrogen pollutants from anthropogenic activities to shallow groundwater, and the reductive dissolution from iron oxyhydroxides in the deep aquifer were the main processes of arsenic release to groundwater from the sediment. Total arsenic and iron contents of the core samples were well correlated in marine sequences. The presence of clay layer within the subsurface may increase in the As contamination in groundwater aquifer. However the time for As release from clay layer to lower aquifer may require tens or hundreds years to complete under natural environment condition. Surface analyses of core sample performed by XPS showed that arsenic was adsorbed or co-precipitated with non-crystalline iron oxyhdroxides and sulfides. After a long term burial of sediment, microbial metabolism of organic matter creates a more reducing environment, arsenic may then be gradually released from iron oxyhydroxides by reductive dissolution or desorption to aqueous phase. The framboidal-diagenetic type phase was identified by XPS and the groundwater is supersaturated with respect to pyrite and orpiment determined by PHREEQC are suggesting sulfide minerals co-precipitate As. Arsenic in sediments is released into groundwater primarily by the reductive dissolution of As-bearing Fe-oxyhydroxides in reducing environment in the Lanyang plain.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Hazhar Sufi Karimi, Balasubramaniam Natarajan, Chris L. Ramsey, Jeffrey Henson, Joshua L. Tedder, Errin Kemper〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Situational awareness in sanitary sewer systems requires accurate flow information at different spatial locations in a city. It is especially desirable to predict flows across a wastewater network in response to heavy rainfall events in addition to regular consumption patterns. Typically, complicated hydraulic models that suffer from difficulties in parameter identification and high computational burden are used for flow prediction. Recently, data-driven approaches have been employed for flow prediction. In this paper, we first design and then compare the performance of three data-driven methods to predict flow: (1) Artificial Neural Network (ANN); (2) Long-Short Term Memory (LSTM); (3) Least Absolute Shrinkage and Selection Operator (LASSO). We test the performance of these machine and statistical learning techniques using data gathered from the City of Springfield. While, all three data-driven methodologies provide acceptable prediction performance, we observe that LSTM outperforms ANN due to the inherent memory integrated with a feedback structure. The statistical learning approach, i.e., LASSO regression not only offers good prediction performance, but also helps identify the key spatial and temporal features that influence flow at any specific location. This added information could aid in remediation activities. Another key contribution of this paper is that we quantify the value of groundwater data in flow prediction. Specifically, including groundwater data as an additional input enhances flow prediction performance in all three methods. Lastly, to better predict flows corresponding to rare events (e.g., 50 or 100 year rainfall events) we use a resampling approach (known as SmoteR) to modify the training dataset. Simulation results indicate that the resampling technique is effective in improving prediction performance.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Lei Guo, Yu Liu, Gao-Lin Wu, Ze Huang, Zeng Cui, Zhen Cheng, Rui-Qi Zhang, Fu-Ping Tian, Honghua He〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Soil water infiltration is an important part of the land surface hydrological cycle, and plays an important role in the hydrological response of the soil, such as soil erosion. High infiltration rates favor an increase in the soil water storage capacity that allows maintaining vegetation restoration in arid and semi-arid regions. Alfalfa (〈em〉Medicago sativa〈/em〉 L.) is a quality perennial legume grassland, which is widely planted in semi-arid areas. In this study, the effects of the root channels formed by the decay of alfalfa on preferential flow were evaluated as a driving force to improve soil water infiltration and soil water supply. A double-ring infiltrometer (30-cm inner diameter and 60-cm outer diameter) was used to measure the infiltration process with the falling head method. Methylene blue was used to visualize the pathways followed by the infiltrated water. The results showed that the initial infiltration rate in the alfalfa grassland increased by 27.7%, compared with the control bare land, and the total cumulative infiltration was 1.13 times higher. The steady infiltration rate of the grassland increased by 31.8% compared to the bare land. The root channel diameters were measured with a Vernier caliper, and the average root channel area (RCA) was calculated through the average root channel diameter (ARCD). The values of ARCD and RCA were significantly and positively correlated with the infiltration rates, being the coefficients of determination 0.815 and 0.789, respectively. Our results indicated that root channels formed by the decayed roots of alfalfa played an important role in increasing soil water infiltration and soil water supply under semi-arid conditions. Our research improves the understanding of the hydrological cycle processes at the plant-soil interface in semi-arid areas.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Daniel Jato-Espino, Nora Sillanpää, Shray Pathak〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉By changing the hydrological cycle, urbanisation has led to frequent flooding worldwide. These phenomena, combined with Climate Change, threaten the capacity of sewer networks for safe conveyance of runoff. In this context, there is a need for efficient methods of modelling sewer networks, which are the main drainage systems used to deal with runoff accumulation. Hence, this research emerged to provide an efficient alternative to specialised stormwater software in terms of time and input requirements to model urban flooding. This was achieved through a methodology consisting of the combination of dependence measures in the form of factor and correlation analyses with machine learning classifier systems. The use of dependence measures enabled minimising the number of variables required by learning classifiers to perform as predictors in estimating node flooding in sewer networks. The proposed approach was tested in an urban catchment in Espoo (Finland), whose hydrological response had been previously calibrated and validated with the Storm Water Management Model (SWMM). The comparison of the node flooding distribution across the catchment was carried out under different rainfall events associated with Climate Change. As a result, the methodology was demonstrated to be capable of reproducing the flooding results obtained both with SWMM and Multiple Regression Analysis (MRA) approaches with high accuracy.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Hoang-Minh Nguyen, Deg-Hyo Bae〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study proposes a method for improving the capability of rainfall and flood forecasts by generating ensemble precipitation predictions (EPPs) associated with radar-based rainfall prediction by considering spatial rainfall errors. The EPPs are generated as a kind of Monte-Carlo simulation based on the performance of the numerical weather prediction (NWP) model in the previous time step window. The generated EPPs continue to be blended with radar-based rainfall predictions to produce hybrid rainfall forecasts that perform better than each system could perform individually. The hybrid forecasts are then adjusted by reducing the spatial rainfall errors, which have considerable contributions to the accuracy of the flood forecasts. To validate the performance of the proposed method, this method was applied to improve the capability of the coupled Local Data Assimilation and Prediction system (LDAPS) and Sejong University Rainfall – Runoff (SURR) model for rainfall and flood forecasts during two flood events that occurred in 2013 and 2016 in the Yeongwol watershed. EPPs were generated from the deterministic LDAPS rainfall events and were then blended with the McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE) rainfall predictions to produce hybrid rainfall forecasts. Each ensemble member of the hybrid model was then corrected before it was forced as an input for the SURR model to obtain ensemble streamflow predictions. The results showed that the capability of the coupled model was improved sustainably step by step and exhibited the best skills after applying the final step. For rainfall forecasts, the proportion correct (PC), root mean square error (RMSE), correlation coefficient (CC), and Brier score (BS) were improved dramatically by 59%, 32%, 32% and 48% for flood events in 2013 and by 39%, 15%, 33% and 37% for flood events in 2016, respectively. For flood forecasting, the Nash – Sutcliffe efficiency (NSE) and absolute relative error in volume (AREV) were improved substantially by 63% and 24% for flood events in 2013 and by 42% and 53% for flood events in 2016, respectively. The success of this case study proved the viability of the method proposed in this study.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Wenting Jin, Jianxia Chang, Yimin Wang, Tao Bai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Water-sediment regulation (WSR) is an effective non-engineering measure to alleviate the problem of suspended river and bring benefit to flood control security in sediment-laden river. However, WSR may decrease the socio-economic benefit of reservoirs, for example, reduction of hydropower production and water supply. In order to satisfy the practical requirement of WSR and other utilization objectives, this paper presents a multi-objective operation model for a cascade reservoirs simultaneously considering the maximization water volume for WSR and power generation and water supply, as well as various complex constraints. Then, the Non-dominated Sorting Genetic Algorithm (NSGA-II) is improved to solve the aforementioned model and key control indicators of WSR are analyzed. Meanwhile, a sediment transport model has been introduced to quantify the effect of WSR. The models are applied to the cascade reservoirs in the Upper Yellow River. The following conclusion can be drawn from results (1) Pareto fronts of the model solution demonstrate a strong competition between WSR and water supply, water supply and power generation, a low sensitivity between WSR and power generation; (2) the ability of WSR in Upper Yellow River is 6 times in 24 years, which means the frequency of WSR is four years averagely; (3) 233.77 million tons of sediments are transported by long-term WSR in the Ningxia-Inner Mongolia reaches, account for 19.10% of sediment deposition; (4) the risk-free conditions of LYX and LJX reservoirs’ water volume for WSR are 137.42 × 10〈sup〉8〈/sup〉 m〈sup〉3〈/sup〉 and 41.08 × 10〈sup〉8〈/sup〉 m〈sup〉3〈/sup〉, respectively, which could be used as a reference in actual operation. The research results have an important practical significance and application for sediment control and governance of suspended river, and the multi-objective operation model of WSR proposed in this study can be effectively and suitably used in sediment regulation with similar conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): A.J. Siade, B. Rathi, H. Prommer, D. Welter, J. Doherty〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Water resources management often involves models that simulate physical/chemical processes to make predictions of future system behavior. These predictions often contain uncertainty that must be considered in order to make robust decisions. The quantification of this uncertainty is often not conducted in practice due to computational limitations and a lack of flexible software capabilities. To bridge this gap, we have developed a heuristic, multi-objective, model-independent optimization methodology using TCP/IP network communications for parallel run management on high-performance computing systems. The proposed optimization methodology is based on Particle Swarm Optimization (PSO), where the memory-like nature of PSO makes it ideal for tracing a Pareto front that graphically illustrates the trade-off between competing objective functions. Although the focus of this study is on addressing the likelihood of an undesirable or contested model prediction, the proposed methodology can be extended to any multi-objective optimization context, and is also able to handle inequality constraints that reflect additional conditions that must be met along the front. We have demonstrated the algorithm on two important real-world case studies. The first case study involved water allocation issues in Antelope Valley, California, USA, where the uncertainty in total natural recharge into the valley has raised significant debates over water management. The second case study involved the re-injection of coal seam gas co-produced water into deep aquifers in the Surat Basin, Queensland, Australia, where the potential impact of an undesired mobilization of arsenic concentrations needed to be understood and managed. This case study required a highly nonlinear field-scale reactive transport model, and an inequality constraint was also necessary to maintain consistency with a laboratory-scale geochemical model. The efficiency at which the proposed methodology solved these complex case studies demonstrates its effectiveness for a broad range of applications.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Sandra Karanitsch-Ackerl, Konrad Mayer, Tobias Gauster, Gregor Laaha, Franz Holawe, Rupert Wimmer, Michael Grabner〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Atmospheric and streamflow drought back to 1600 were reconstructed with provenance-verified regional 〈em〉Pinus-sylvestris〈/em〉 and 〈em〉Pinus-nigra〈/em〉 chronologies of earlywood, latewood and ring width, detrended by signal-free regional curve standardization, from the Weinviertel, a dry region in Eastern Austria. Linear regression models with Weinviertel latewood indices as predictor variables were used to estimate regional April–August precipitation totals (R〈sup〉2〈/sup〉 = 0.47) and seven-day minimum flow from May to October (best fit: R〈sup〉2〈/sup〉 = 0.65). As a novelty, the well-known dendrochronology quality measure “Expressed Population Signal” in a modified version is used to define a scaling factor for empirically estimating the reconstructions’ time-varying reliability.〈/p〉 〈p〉For the detection of drought years in the reconstructed time series, four stages of drought of increasing intensity were defined as conditions below median, and below the 33rd, 20th, and 5th percentile—representing 2-year, 3-year, 5-year and 20-year recurrence intervals.〈/p〉 〈p〉The method for the extension of time series of low flows into the past is applicable in the Weinviertel and can be a useful source of historical hydrological and meteorological information restricted by the uncertainties coming along with proxy records. Of the analyzed period back to 1600, the 19th century is the driest one closely followed by the 18th century, sharing the overall driest period from 1775 to 1813. The phase with the longest continuous atmospheric dry period is 1807–1811. The longest hydrological drought lasted from 1832 to 1839.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Fenge Zhang, Guanxing Huang, Qinxuan Hou, Chunyan Liu, Ying Zhang, Quan Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Industrialization and urbanization expansion may change the groundwater quality in the Pearl River Delta (PRD). The aims of this study were to evaluate the groundwater quality in various aquifers and areas with different urbanization levels in the PRD, to extract the main impact indicators, and to discuss the driving forces for the groundwater quality. Nearly 400 groundwater samples were collected and 23 indicators were analyzed. In the PRD, 83% groundwater was drinkable (good-quality) by using a fuzzy synthetic evaluation method. Groundwater in karst aquifers was drinkable, and its quality was better than those in granular and fissured aquifers. In the latter two aquifer types, groundwater quality in non-urbanized areas was much better than those in peri-urban and urbanized areas. In granular aquifers, Mn + Fe, I〈sup〉−〈/sup〉 + Ni + Mn, and Mn + As + I〈sup〉−〈/sup〉 were the main impact indicators for poor-quality groundwater in urbanized areas, peri-urban areas, and non-urbanized areas, respectively. Correspondingly, reductive dissolution of Fe/Mn (oxy)hydroxides, infiltration of industrial wastewater and reductive dissolution of I〈sup〉−〈/sup〉 and Mn, and reductive dissolution of Mn, As, and I〈sup〉−〈/sup〉 were likely responsible for poor-quality groundwater in these areas, respectively. By contrast, in fissured aquifers, NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉, NO〈sub〉3〈/sub〉〈sup〉−〈/sup〉 + Pb, and I〈sup〉−〈/sup〉 were the main impact indicators for poor-quality groundwater in urbanized areas, peri-urban areas, and non-urbanized areas, respectively. Correspondingly, infiltration of domestic sewage, infiltration of domestic sewage and industrial wastewater, and mineralization of I-rich organic matter were probably responsible for poor-quality groundwater in these areas, respectively. Industrialization was one of the main driving forces for groundwater quality in granular and fissured aquifers in peri-urban areas, while urbanization was one of the main driving forces for groundwater quality in fissured aquifers in urbanized and peri-urban areas in the PRD.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307243-ga1.jpg" width="348" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Jiefeng Wu, Xiaohong Chen, Zexing Yu, Huaxia Yao, Wei Li, Dejian Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although previous studies have estimated the effects of human regulations on hydrological drought, few studies have examined the impacts from the perspective of the development and recovery processes of hydrological drought. This study uses the Dongjiang River Basin in south China as an example and focuses on the influence of reservoir operation on hydrological drought. The Standardized Streamflow Index (SSI) and run theory were applied to determine the development and recovery processes of hydrological drought. A semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was used to simulate long time series (〉30 years) monthly streamflow data; the SWAT model was calibrated and validated using the monthly streamflow data from periods with less human regulations. Streamflow was then simulated and compared by using the same model parameters, as well as the sub-surface features, to simulate the streamflow during the human regulation periods. The “simulated-observed” comparative approach (i.e., a comparison of the characteristics of the hydrological drought obtained from the simulation-based SSI and observation-based SSI) was used to assess the impacts of human regulations on hydrological drought development and recovery. The results showed that the ‘simulated-observed’ comparison approach based on the SWAT model exhibited a good ability to ascertain the impacts of human regulations on hydrological drought development and recovery. The reservoir operation was the dominant factor affecting the hydrological drought propagation in the lower reaches of the Dongjiang River basin and had mostly a short-term effect by decreasing the duration and severity of drought development (or recovery). However, the reservoirs tended to release water during the development process and to store water during the recovery process during a long-term hydrological drought in the study area, leading to an increase in average recovery duration and severity. The results of this study may further optimize water resources management system during drought for effective drought prevention and mitigation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): S. Díaz-Alcaide, P. Martínez-Santos〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Fecal contamination poses a threat to groundwater supplies in low income regions. This is often due to the coexistence of pit latrines with domestic wells in densely populated areas. In this context, developing alternative methodologies to map fecal pollution in shallow wells is needed. A thorough survey of over 240 domestic wells and 570 pit latrines was conducted in a rural town of southern Mali. Water samples were collected from all wells and tested for temperature, pH, electric conductivity, total dissolved solids, turbidity and thermotolerant coliforms. The outcomes of the field survey were incorporated into a GIS database. Thirteen machine leaning classifiers, including different statistical algorithms, instance-based learners and tree-based models, were used to determine the spatial distribution of fecal pollution as per five explanatory variables (latrine density, distance to the closest latrine, borehole yield, water table depth and population density). The best performing classifiers, selected on test scores, were then used to develop predictive maps. Random forest and logistic regression rendered prediction scores for fecal pollution in excess of 0.90. Multilayer perceptrons, support vector machines and quadratic discriminant analyses also proved adept at forecasting fecal pollution. Ensemble mapping shows that 30–50 m buffers around domestic wells may be sufficient to prevent contamination of domestic supplies in most instances. This demonstrates that machine learning may provide a versatile methodological alternative to traditional Darcian approaches. On the other hand, the practical difficulties involved in maintaining wellhead protection areas suggests the need to implement piped water supplies.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307267-ga1.jpg" width="500" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Maryam Adhami, Seyed Hamidreza Sadeghi, Rainer Duttmann, Majid Sheikhmohammady〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The changes in runoff and sediment load due to various approaches in land use management have recently received considerable attention. In the present paper, the impact of land use change under collaborative management framework on water and sediment load was investigated by combined usage of hydrologic modelling and land use maps. Three groups of stakeholders viz. residents, policy makers and executive organizations were involved in decision making process. Three prioritization procedures of Condorcet, Borda scoring and Fallback bargaining were elected to rank sub-watersheds and managerial practices. The impact of different managerial scenarios was assessed by applying time-area concept and through analyzing changes in important components of output hydrographs and sediment graphs. Results demonstrated significant agreement among stakeholder’s attitudes and quantitative outcomes. The results illustrated obvious impact on runoff and sediment resulted from scenarios for land use management. So that, the impact on sediment load (with maximum reduction benefit of 19.41%) was significantly greater than that of runoff (with maximum reduction benefit of 8.07%). Manipulation of farmlands and poor rangelands and afforestation caused recognizable reduction on runoff and sediment. Rangelands restoration also satisfied socioeconomic status and environmental criterion of the study area. Considering basic differences in prioritization procedures, there were considerable agreement among stakeholders in land use management and practice prioritization. The results further indicated that the watershed management projects should focus on remediation of vegetation cover of the rangelands, which simultaneously tackles land degradation and improves economic condition. However, the present study revealed lack of proper connection between residents and authorities. Nevertheless, as a pioneer comanagement endeavor, the present qualitative and quantitative results facilitate group decision making and participated planning procedure at the watershed scale.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307218-ga1.jpg" width="178" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Chenkai Cai, Jianqun Wang, Zhijia Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The precipitation forecasts from numerical weather prediction have a variety of potential uses in flood forecasting and reservoir operation, but suffer from relatively poor performance due to the uncertainty of the hydrometeorological system. In this study, the control forecasts of four global weather centres were selected and assessed against the measured data using several verification metrics during the flood season (May–September) over the Shihe River catchment in the Huaihe River basin of China. The results show that the daily rainfall forecasts have low prediction ability and cannot meet the demand of reservoir regulation. To describe the uncertainty of precipitation forecasts for the safety of flood control, a new model was proposed using fuzzy probability and Bayesian theory on the basis of the generalized probability density function (GPDF). The performance of the new model is examined by using various probability measures and compared with the ensemble forecasts generated by the weather centres. It is proved that the fuzzy Bayesian model can generate the conditional probability distribution of actual precipitation from a single predicted value based on the historical observation and forecast data, and has strong generalization ability. Compared with the ensemble forecasts, although the fuzzy Bayesian model shows a slightly improvement in accuracy, it has better performance in sharpness and reliability. Meanwhile, the new model is easy to update with new samples by modifying its likelihood function, which is favourable for real-time reservoir regulation. In addition, the uncertainty of the precipitation forecast was analysed with the model in different lead times. Generally, the uncertainty increases with the growth of lead time, and the probability distribution of the rainfall forecast within 3 days is an acceptable result for a risk and benefit analysis of the flood control system. To be more specific, a fuzzy Bayesian model based on the GPDF is an efficient way to generate the probability distribution of the precipitation with forecast data for the uncertainty analysis, and makes it possible to provide a reference for reservoir managers to plan regulation strategies with a lead time of at least 3 days.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Jian Song, Yun Yang, Gan Chen, Xiaomin Sun, Jin Lin, Jianfeng Wu, Jichun Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The robust optimization of groundwater quality monitoring network is subject to many conflicting objectives and high level of uncertainty in hydraulic conductivity. This study develops a two-stage stochastic optimization framework including the uncertainty quantification using a cheap-to-evaluate surrogate model and an improved epsilon multi-objective noisy memetic algorithm (〈em〉ε〈/em〉-MONMA) for monitoring network design. The surrogate model based on sparse polynomial chaos expansion (PCE) is constructed to replace expensive simulation model in the uncertainty quantification of concentrations at the pre-defined monitoring locations for reducing huge computational cost. Additionally, the scenario discovery strategy using sparse PCE model is applied to filter a typical scenario set and the centroid of contaminant plume is used as the diversity metric, which avoids enumerating all possible contamination plumes caused by the uncertain 〈em〉K〈/em〉-field in the optimization. The proposed algorithm is then employed to solve stochastic management model to achieve robust monitoring design, indicating the insensitivity of monitoring design to plume uncertainty no matter which of the many possible scenarios becomes the true distribution of contamination under the true 〈em〉K〈/em〉-field. A synthetic aquifer considering uncertainty in hydraulic conductivity is designed to optimize monitoring network design. The Pareto-optimal solutions to the synthetic example are achieved under three of plume scenario sets defined at deterministic scenario (Scenario A0), Monte Carlo based scenario discovery (Scenario A1) and surrogate assisted scenario discovery (Scenario A2), respectively. Comprehensive analysis demonstrates that the monitoring design based on Scenario A2 outperforms either of the two designs based on Scenarios A0 and A1 in terms of the improvement of robustness of designs evaluated against the typical scenario set. Meanwhile, the performance of monitoring network deteriorates as the uncertainty of plume (noisy strength) increases, indicating the significance of reducing parameter uncertainty in groundwater monitoring design. The research findings show that the developed stochastic optimization framework is a computationally efficient and promising tool for multi-objective design of groundwater monitoring network under uncertainty.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Minjune Yang, J. Antonio Yaquian, Michael D. Annable, James W. Jawitz〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Groundwater flow discharging to springs from carbonate aquifers is governed by the interaction of slow matrix flow and fast fracture/conduit flow, which creates highly complex flow and transport conditions. An important unknown is the relative contribution of matrix and conduit flow to the total discharge. This study experimentally investigated groundwater fluxes in the Floridan aquifer within the springshed of Silver Springs, FL, one of the largest freshwater springs in the world with mean discharge of approximately 20 m〈sup〉3〈/sup〉/s. Using 〈em〉in situ〈/em〉 passive flux meters (PFMs, n = 48 at 16 wells) and a new karstic borehole dilution (KBHD, n = 21 at 7 wells) technique we measured groundwater fluxes in rock matrix and non-matrix (conduit and fracture) zones of 0.06 ± 0.003 m/day and 3.05 ± 1.8 m/day (mean ± standard error). These data, combined with previously conducted tracer tests (n = 12 at 3 sites), were coupled with simple analytical and numerical solutions to identify the proportion of the aquifer that contributes most significantly to water flow to the spring with three different modeling scenarios: single domain, dual domain including matrix and non-matrix zones, and triple domain including matrix, fracture, and conduit zones. The analytical and numerical models coupled with the 〈em〉in situ〈/em〉 measured fluxes for the dual and triple domain scenarios showed good agreement with measured head profiles (Nash-Sutcliffe 〈em〉E〈/em〉 〉 0.90), when compared to the homogeneous porous domain scenario (〈em〉E〈/em〉 = −1.84). Conduit and fracture zones were estimated to represent between 2% and 22% of the aquifer cross-sectional area (at radial distance of 3 km from the spring outlet), yet these zones contributed between 75 and 96% of the total groundwater flow. The results of this study offer field-measured hydrogeologic data that can be used for active resource management in springsheds, and the simple modeling approach presented here may be applicable to other springsheds with fairly simple geometry to estimate the relative contributions of fast and slow water flow and solute transport pathways to the spring outlet.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Ferry Schiperski, Marcus Oertwich, Traugott Scheytt, Tobias Licha〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉TINOPAL CBS-X has been described in published literature as a fluorescent dye that is suitable for use as a tracer in groundwater investigations. However, several of these field tests have yielded unexpected results. In this study the influence that the complexation agent EDTA (ethylenediaminetetraacetate) and pH have on the solubility of TINOPAL CBS-X have been systematically investigated in the laboratory and the results obtained validated with thermodynamic calculations using the PhreeqC software. Modeling indicated that the amount of EDTA required for complete TINOPAL CBS-X dissolution is, in many aquifers, so great that its use is no longer feasible. However, softening the water by adding NaOH appears to be a promising way to increase TINOPAL CBS-X solubility. Water with a low availability of bivalent and/or trivalent ions yielded solubilities up to two orders of magnitude higher than waters from limestone aquifers with a high Ca〈sup〉2+〈/sup〉 ion content. Results revealed that the spectrum of TINOPAL CBS-X applicability as a conservative tracer in aquatic environments is limited to a limited range of specific water chemistries. The long tailing in the breakthrough curve and the retarded breakthrough of TINOPAL CBS-X in a previously reported carbonate karst aquifer field tracer test was accurately reproduced by a transport model with a modified input function based on solubility modeling. Travel times and attenuation by incompletely dissolved tracers are tend to be overestimated, which can be problematic with regard to predictions of contaminant transport, or the delineation of water protection zones. The use of TINOPAL CBS-X as a conservative tracer and the concentrations required needs therefore to be carefully evaluated with respect to water-hardness, pH, alkalinity, and dilution rates. An input script for PhreeqC is provided to help estimate appropriate concentrations of TINOPAL CBS-X, thus enhancing its potential and reliability for future groundwater research.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307528-ga1.jpg" width="320" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Shiliang Liu, Wenping Li, Wei Qiao, Xiaoqin Li, Qiqing Wang, Jianghui He〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Environmental engineering geological patterns (EEGPs) are the generalized manifestation of environmental engineering geology with the protection of phreatic water resources as the core, especially in mining areas with fragile eco-geological environment. Based on the formation mechanism of mining-induced EEGPs, with the aim of win-win between protection of phreatic water resources and exploitation of coal resources, this study presents a zoning method for EEGPs. Taking the Yushenfu mining area in northern Shaanxi, China, as a case study, four types of EEGPs (basically unaffected model, gradually restored model after destruction, gradually deteriorated model, and disaster model) were defined separately. On the basis of the degree of influence of mining activities on phreatic aquifer, the zoning method for EEGPs was proposed. Firstly, the height of water-flowing fractured zone (WFFZ) and the residual aquifuge thickness were calculated using multivariate linear regression method. Secondly, according to the relationship among phreatic water leakage, groundwater recharge, and variation in groundwater level, the thickness of laterite, loess and bedrock as the thresholds between the EEGPs were separately determined. Thirdly, based on the thresholds between EEGPs and the linear variation of residual aquifuge thickness combination, the zoning criteria for EEGPs were formulated. Finally, the zoning results were obtained. Furthermore, the verification of the types of EEGPs in coalfaces and the comparison between the zoning results obtained using variable weight theory and those given in the present study indicated that the zoning results presented in the current study are more accurate and reasonable. The research results can provide theoretical basis for solving the contradiction between coal resource exploitation and eco-geological environmental protection.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Ye Zhu, Yi Liu, Wen Wang, Vijay P. Singh, Xieyao Ma, Zhiguo Yu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Meteorological and hydrological droughts are inherently correlated, but with a time lag. A prolonged precipitation deficiency propagates to surface water bodies and may give rise to hydrological drought in the subsequent time period. Establishing links between these two drought types is of great significance for water resources planning and for developing drought resistant measures. This study proposes a copula-based method employing conditional probability distribution to depict the structure of dependence between the characteristics of meteorological and hydrological droughts. The time series of grid-based standardized precipitation evapotranspiration index (SPEI) and standardized runoff index (SRI) were derived from the simulations of the variable infiltration capacity (VIC) model over the Yellow River basin (YRB) during 1961–2012. Then, using a three-dimensional (time-latitude-longitude) drought identification method, three drought characteristics, including duration, area and severity, were extracted for meteorological and hydrological droughts. For analyzing drought characteristics, return periods and connection between meteorological and hydrological droughts, a probabilistic framework using the copula function, was developed. Results showed that there was a general drying tendency both for meteorological and hydrological droughts with longer duration and larger spatial extent. According to the trivariate joint distribution of duration, area and severity, the most severe meteorological and hydrological droughts over the YRB occurred around 1998–2000, with return periods exceeding 50 years. In terms of establishing the dependence between characteristics of meteorological and hydrological droughts, traditional statistical models like the linear, exponential, and power functions presented significant deviations, especially for severe or extreme drought conditions. In contrast, the copula based conditional distribution method provided a satisfactorily probabilistic prediction of hydrological drought characteristics given the information of meteorological drought characteristics. The stability test suggested compared to the length of data sample, the incorporation of typical major drought events with long persistence and wide spatial extent is more important for reliable drought prediction.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): C. Gualtieri, M. Ianniruberto, N. Filizola〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Confluences are common components of all riverine systems, and characterized by converging streamlines and potential mixing of separate flows. The fluid dynamics of confluences possess a highly complex structure with several common types of flow features observed.〈/p〉 〈p〉An investigation was carried out in both low and relatively high flow conditions at the confluence of the Negro and Solimões Rivers, Brazil, which ranks among the largest river junctions on Earth. During this field research, acoustic Doppler velocity profiling (ADCP) and water quality sampling were applied to investigate hydrodynamics, sediment transport and mixing characteristics at this confluence. It was found that the location and the width of the mixing interface were closely related to changes of the discharge ratio between the tributaries due to both seasonal and annual variations. Second, a timescales analysis was applied to comparatively identify the contribution to mixing at the Negro/Solimões confluence of four processes: difference in (1) velocity and (2) density between the rivers, (3) bed friction, including form drag, and (4) change in channel width. The analysis demonstrated that adjustments of confluence hydrodynamics and morphodynamics can modify the relative importance of each contribution. Immediately downstream of the junction the effects of differences in velocity and density were comparable, while farther downstream the latter was predominant and the role of bed friction was significant. At the end, this study suggests that mixing at the Negro/Solimões confluence can be explained as a combination of the four hydrologic and morphologic processes.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 578〈/p〉 〈p〉Author(s): Zeng Cui, Gao-Lin Wu, Ze Huang, Yu Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Soil water is the key limiting factor for achieving sustainable revegetation. Soil infiltration rate plays an important role in determining the inputs from precipitation, which is important for the plant growth and groundwater recharge in semi-arid regions. Soil infiltration rate is generally influenced by belowground biomass (BGB), soil water content (SWC) and other soil properties (total soil porosity, soil mean weight diameter and soil organic carbon). The aim of this study is to understand the effects of plant roots, SWC and other soil properties on soil infiltration rate, and to identify the main factor affecting soil infiltration rate. This study investigated the total soil porosity (TP), soil mean weight diameter (MWD), soil organic carbon (SOC), SWC and plant roots of five grasslands (〈em〉Bromus inermis〈/em〉, 〈em〉Trifolium repens〈/em〉, 〈em〉Panicum virgatum〈/em〉, 〈em〉Medicago sativa〈/em〉 and 〈em〉Miscanthus sinensis〈/em〉). An automatic measurement system of point source device was used to quantify the soil infiltration rate. Results showed that SWC significantly affected the initial infiltration rate (P 〈 0.05), but plant roots gradually became the main factor affecting soil infiltration rate as the increasing infiltration time. The percentage of root volume (PV) of 0–2 mm was positively correlated with infiltration rate, while the PV of 〉4.5 mm was negatively correlated with infiltration rate. Our results indicated that fine roots could increase soil organic matters and form soil pores, thus more determining the potential of soil infiltration than soil water content during the short-term vegetation restoration in semi-arid regions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Martin Binder, Diana Burghardt, Christian Engelmann, Felix Tritschler, Elisabeth Simon, Henning Prommer, Peter Dietrich, Rudolf Liedl, Falk Händel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study the suitability of precipitation waters as semi-artificial and multi-component groundwater tracers is investigated and potential applications as well as limitations are discussed. Specifically, we analyzed their migration behavior during laboratory-scale experiments with groundwater-saturated porous media. Artificially 〈sup〉2〈/sup〉H- and 〈sup〉18〈/sup〉O-labelled water as well as natural precipitation waters were injected into sediment-packed columns and traced via stable isotope analysis. Their migration behavior was compared to that of widely used tracers. These flow-through experiments were underpinned by a batch reactor study and by hydrogeochemical modeling. While most artificial isotope applications showed a high stability and conservative transport behavior for all tested sediments, the breakthrough curves observed in some experiments with rain and snowmelt were unsteady. This was most likely caused by the small ratio between the tracer’s isotopic difference compared to the background signal and the available analytical precision. The minimum ratio required for effectively reducing uncertainties during data evaluation showed to depend significantly on experimental conditions but should not decrease below ∼10 during peak breakthrough and preferably be higher. Furthermore, our study illustrates that measurements based on using the precipitation waters’ inherent low electrical conductivity can be significantly biased by water-sediment reactions. The batch study and reactive transport simulations confirmed this observation while revealing mineral reactions and, to a minor extent, also ion exchange as the underlying processes.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Julio Rodrigo-Naharro, Maria J. Herrero, Antonio Delgado-Huertas, Arsenio Granados, Luis Pérez del Villar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the framework of a natural CO〈sub〉2〈/sub〉 reservoir with CO〈sub〉2〈/sub〉 leakages as an analogue of a failed CO〈sub〉2〈/sub〉 deep geological storage, the current precipitation of travertines and the associated upwelling of CO〈sub〉2〈/sub〉-rich saline groundwater were analysed. This natural analogue is located in the Gañuelas-Mazarrón Tertiary Basin (SE Spain). The study comprises of the chemistry of both groundwater and travertines, including stable isotopes, mineralogy and petrography of the travertines, all this performed after a review of the geology of the basin. In this sense, the basin gathers the main features of a safe natural CO〈sub〉2〈/sub〉 reservoir in a deep saline aquifer sealed by a thick marl formation. The aquifer was artificially perturbed by the drilling of wells, inducing the travertines precipitation at these water discharge points. Groundwater is saline, slightly acid, oversaturated in aragonite and calcite and with significant concentrations of heavy elements, some of them toxic. From an isotopic viewpoint, the relative constant δ〈sup〉13〈/sup〉C-DIC values suggest that carbon is mainly inorganic in origin with minor organic and mantle contributions. Travertines are basically composed of aragonite or calcite, their precipitation being controlled by a sudden CO〈sub〉2〈/sub〉 degassing and minor biological activity. Their δ〈sup〉13〈/sup〉C signatures indicate that carbon mainly has an inorganic origin, although some contribution of organic carbon must be considered as well. Furthermore, these carbonate deposits did not precipitate in isotopic equilibrium, as determined by δ〈sup〉18〈/sup〉O values. Finally, it is suggested that the appearance of travertines along with their carbon isotopic signatures represent efficient tools for detecting CO〈sub〉2〈/sub〉 leakages from any CO〈sub〉2〈/sub〉 storage site.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Xiuquan Wang, Gary Kinsland, Durga Poudel, Adam Fenech〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Increasing city resilience to floods under climate change has become one of the major challenges for decision makers, urban planners, and engineering practitioners around the world. Accurate prediction of urban floods under heavy precipitation is critically important to address such a challenge as it can help understand the vulnerability of a city to future climate change and simulate the effectiveness of various sustainable engineering techniques in reducing urban flooding risks in real urban settings. Here, we propose a new model for urban flood prediction under heavy precipitation. The model divides an irregular urban area into many grid cells with no limitation on the spatial resolution as long as the DEM data of the same resolution are available. It is capable of reflecting the frequent inflow or outflow interactions among grid cells and capturing the rapid generation of surface runoff in urban areas during heavy rainfall. The model also accounts for typical characteristics of urban areas, such as large-scale impermeable surfaces and urban drainage systems, in order to simulate urban floods more realistically. In addition, the model uses both surface elevation and instantaneous surface water depth of all grid cells to dynamically determine the directions of horizontal inflow and outflow during each time step of model simulation. This enables the model to capture the reverse-flow phenomenon which is commonly seen in flat urban areas during heavy storms. By applying the proposed model for reproducing the 2016 flood in Lafayette Parish, Louisiana, we demonstrate its effectiveness in predicting real-world flood events.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Jiabiao Wang, Jianshi Zhao, Xiaohui Lei, Hao Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To manage a river sudden pollution incident, a fundamental task is to quickly identify when, where, and how much pollutant was released. The source identification of this kind of pollution incident due to instantaneously spilled pollutant from point source remains a challenging problem because of the limited observations and the ill-posedness. In this paper, the ensemble Kalman filter (EnKF) is coupled with the backward location probability (BLP) to improve its performance in identifying the river pollution source. When applied in practice, the proposed BLP-EnKF method has two important advantages. First, it supports on-line identification and can mitigate the limitation from shortage of observations in the sudden river pollution case. Second, BLP-EnKF performs much better than conventional EnKF in terms of computation time, because it can identify the pollution source without restart forecast process. The effectiveness and efficiency of BLP-EnKF is tested and demonstrated by a synthetic case study. The case results show that the BLP-EnKF can identify all the source parameters with a relative error approximately 1.00% or smaller. Its performance can be further improved with more accurate estimation of observational error or dispersion coefficient. A real-world case in Ganjiang River further demonstrates the applicability of BLP-EnKF in practice. The pollution source is identified successfully with relative errors smaller than 3.0% for all the source parameters, while the computation time is sharply shorted from 8.0 h of conventional EnKF to 22.0 s of BLP-EnKF.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0022169419307115-ga1.jpg" width="128" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Feng Xiong, Shenglian Guo, Pan Liu, C.-Y. Xu, Yixuan Zhong, Jiabo Yin, Shaokun He〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The hydrological regimes of downstream reservoirs have been significantly altered due to the operation and regulation of upstream cascade reservoirs. The original design flood quantiles, namely “design flood in construction period”, do not consider anthropogenic impacts in reservoir operation period, and have led to enormous conflicts between flood control and conservation. In this study, the “design flood and flood limited water level in operation period” are defined for practical application. We establish a general framework to measure the spatiotemporal pattern of streamflow and to estimate design floods of cascade reservoirs in operation period. The multivariate t-copula and a genetic algorithm strategy are proposed to solve the curse of dimensionality encountered in the derivation of most likely regional composition. The Jinsha River and Yalong River cascade reservoir system in China, which consists of 13 large reservoirs with the total storage capacity of 74.06 billion m〈sup〉3〈/sup〉 and hydropower capacity of 71.47 GW, is selected as a case study. Results indicate that: (1) The curse of dimensionality can be well addressed by applying multivariate t-copula to build high dimensional joint distribution and using the genetic algorithm to achieve the most likely regional composition. (2) Compared with the design floods in construction period, the design floods of downstream reservoirs in operation period have been significantly reduced due to the upstream reservoir regulation. The 1000-year design peak flood discharge, 3-day, 7-day and 30-day flood volumes of Xiangjiaba reservoir decrease by 38.7%, 37.4%, 34.2% and 13.8%, respectively. (3) The flood limited water level of these reservoirs can be raised without increasing flood control risks in operation period. The cascade reservoirs in the Jinsha River and Yalong River can generate 3.28 billion kW h more hydropower (or increase 4.3%) annually during flood season.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Xiaoyan Bai, Xiaoqing Wu, Peng Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Blending satellite-based precipitation estimation (SPE) data and in-situ gauge observation data can generate effective spatially-continuous-precipitation estimates with improved accuracy. This study assessed the improvement of the long-term SPE when blending with in-situ gauge observations for drought monitoring, using a simple but effective blending method named the geographical difference analysis (GDA) method and with the Precipitation Estimation from Remote Sensed Information by using Artificial Neural Networks-Climate Data Records (PERSIANN-CDR) as case study. In-situ precipitation observations from three meteorological station sets with different densities—the sparse (50), medium (200), dense (727) station set—were adopted to evaluate the effect of gauge density on the performance of SPE-gauge data blending. Two widely-used indices—standardized precipitation index (SPI) and self-calibrating Palmer drought severity index (SC_PDSI)—were used as case studies. Except the case of sparse 50-station subset, the SPE-gauge blending shows apparent improvement to the raw PERSIANN-CDR data, for both the accuracy of precipitation input and many aspects of drought monitoring, e.g. reproducing drought magnitude and revealing spatial pattern of drought, in which SC_PDSI shows more significant improvement than SPI. The dense 727-station set shows the largest improvement in the blending data, but the corresponding station-only interpolations also exhibit comparable performance to the blending data, indicating lower utilization value of the SPE data for these cases. Only the blending results of the medium-density 200-station set shows satisfactory drought monitoring performance as well as significant improvements relative to the station-only interpolations. According to the quantitative analyses, the medium density (about 50–75 gauges per 10〈sup〉6〈/sup〉 km〈sup〉2〈/sup〉 in our cases) might be the most economic gauge density for SPE-gauge blending, as it has satisfactory improvement in blending results, can make fullest use of the advantages of SPE data and requires relatively fewer gauges. Our results can help to understand how the SPE-gauge blending could improve the SPE-based drought monitoring and serves as a reference for applying drought monitoring under the data-limited conditions. Subsequent studies or applications should also carefully consider the effect of gauge density.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 577〈/p〉 〈p〉Author(s): Tao Bai, Jian Wei, Fi-John Chang, Wangwang Yang, Qiang Huang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Frequent occurrence of flood and ice disasters caused by river channel sedimentation in the Upper Yellow River of China has seriously threatened the lives and property of downstream residents, which has become the most challenging issues in harnessing the Yellow River. In this paper, we aim at optimizing water-sediment regulation that considers two cascade reservoirs (〈em〉Longyangxia〈/em〉 and 〈em〉Liujiaxia〈/em〉) as the regulatory bodies using one multi-objective model (sediment transport and hydropower generation) and two single-objective models (sediment transport only, and hydropower generation only). We propose an innovative approach (FSS-MOPSO) that hybrids the Feasible Search Space (FSS) with the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to search the optimal solutions for the multi-objective joint operation of cascade reservoirs. We analyze the transformation rules of water-sediment regulation among five objectives (hydropower generation, sediment transport, water supply, flood control and ice control) under various optimization schemes. The results indicate that the conflict between the hydropower generation objective and the sediment transport objective is prominent. An extreme case indicates that an increase in hydropower output by 2.31 billion kW·h (17.6% increase) would greatly reduce the amount of sediment transport (73.5% decrease) while only makes little effects on the other three objectives. The results demonstrate that the optimal water-sediment regulation not only can ensure to meet water demands in the future (2030) but can provide an important guideline to safely operate cascade reservoirs during ice and flood periods. The research findings contribute to the identification of the relationship among objectives and strategy recommendations on water-sediment regulation for efficient cascade reservoirs operation in the Upper Yellow River.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Shinju Park, Marc Berenguer, Daniel Sempere-Torres〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Monitoring continental precipitation over Europe with high resolution (2 km, 15 minutes) has been possible since the operational production of the OPERA composites from the European weather radar networks. The OPERA data are the essential input to a hazard assessment tool for identifying localized rainfall-induced flash floods at European scale, and their quality determines the performance of the tool. This paper analyses the OPERA data quality during the warm seasons of 2015-2017 by comparing the estimated rainfall accumulations with the SYNOP rain gauge records over Europe. To compensate the OPERA underestimation, a simple spatially-variable bias adjustment method has been applied. The long-term comparison between the OPERA and gauge point daily rainfall accumulations at the gauge locations shows the benefit of the bias adjustment. Additionally, the daily monitoring shows gradual improvement of the OPERA data year by year. The impact of the quality of the OPERA data for effective flash flood identification is demonstrated for the case of the flash floods that occurred from 29 May to 3 June 2016 in central Europe.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 573〈/p〉 〈p〉Author(s): Qiudong Zhao, Yongjian Ding, Jian Wang, Hongkai Gao, Shiqiang Zhang, Chuancheng Zhao, Junli Xu, Haidong Han, Donghui Shangguan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Analyzing the impacts of climate change on hydrology and future projections of water supplies is fundamental for the efficient management and planning of water resources in large river systems on the Tibetan Plateau (TP), which is known as the “water tower of Asia.” However, large uncertainties remain in the projections of streamflow and glaciers in these cryospheric catchments due to great uncertainties in climate change projection and modeling processes. In this work, we developed an extended Variable Infiltration Capacity (VIC) macroscale hydrological model (named VIC-CAS), which was coupled with glacier melting and glacier evolution schemes. A two-stage calibration procedure that used glacier inventory data and the observed streamflow was adopted to derive the model parameters. The calibrated VIC-CAS model was then used to assess the future change in glaciers and runoff using downscaled climate model data in the upstream regimes of the Yellow, Yangtze, Mekong, Salween, and Brahmaputra rivers on the TP. The results indicated that both temperature and precipitation were projected to increase, resulting in a greater than 50% decline of the glacier area by the end of the 21st century in the five catchments. Glacier runoff was already beyond its tipping point at the beginning of the 21st century with a greater than 20% loss of the glacier area except in the upstream of the Yangtze River, where glacier runoff was projected to decrease after the 2030 s. Annual streamflow was projected to increase significantly as a result of increased rainfall-induced runoff, compensating for the reduced glacier/snow melt water in the five major upstream river basins. The increasing rate of warm season streamflow was clearly less than that of annual runoff. A negative trend in warm season streamflow was expected if precipitation did not sufficiently increase. The annual hydrograph remained largely unchanged, except in the upstream of the Yellow River, where peak streamflow was predicted to occur 1 month earlier because of the earlier snowmelt and greater rainfall/precipitation ratio from May to June.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 573〈/p〉 〈p〉Author(s): Yen-Chen Huang, Chien-Ming Lee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Water security has become a priority for adaptive policy and measures taken in response to climate change around the world. This is an opportunity and a challenge for the Taiwan government to establish a climate-resilient water supply portfolio to ensure water security. This study incorporated the costs of water production, intermittency, and carbon dioxide emission reduction, as well as the currently available water sources and how they will be affected by climate change, and applied optimal control theory to establish a cost-effective model to plan a long-term (2031) climate-resilient water supply portfolio for Taiwan. The study then uses the Penghu area as an empirical case study for this water supply portfolio. The results showed that desalination will become the major source of water, accounting for 71.81% of the water supply by 2031. However, this high proportion of desalination water will result in a significant increase in the unit cost of water production and the carbon footprint. Therefore, water demand management is also needed, and is recommended to ensure sustainable water resources in the Penghu area.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 573〈/p〉 〈p〉Author(s): Guoping Tang, Shuping Li, Muzhen Yang, Zhenwu Xu, Yonglin Liu, Hui Gu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mountain watersheds serve as important water sources for socioeconomic activities in semiarid and arid regions. This study examined the streamflow response to snow regime shifts associated with climate variability in the US Great Basin. To this end, the coupled hydro-ecological simulation system (CHESS), a process-based and distributed model, was applied to four mountain watersheds in the US Great Basin. Historical weather records for the period of 1961–1990 were used to spin-up model simulations so that the soil water and vegetation reached the equilibrium state under long-term climate conditions; the period of 1991–2015 was selected as the study period. The model evaluation suggested that CHESS was able to simulate major hydrological processes in the four mountain watersheds. In addition, it was found that annual streamflow was more strongly correlated with snowfall than with rainfall during 1991–2015 and increased by 0.62–0.76 mm as snowfall increased by 1 mm in the study regions. Recent regional warming advanced the timing of the peak flow and shifts in the snow regime also affected the intra-annual pattern of the soil moisture content. Seasonally, spring rainfall and snowmelt were dominant factors in generating spring streamflow and summer baseflow. The mechanisms for flow generation were more complex and more variable in the four watersheds in autumn and winter than in spring and summer. On an annual basis, shifts in snowmelt resulting from climate variability accounted for more than 60% of the variability in the annual streamflow, surpassing the contribution of rainfall in the four watersheds. Overall, our results suggest that shifts in the snow regime due to climate variability have important implications for the intra-annual distribution and availability of water resources in semiarid and arid regions of the US Great Basin.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Aynalem T. Tsegaw, Knut Alfredsen, Thomas Skaugen, Tone M. Muthanna〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Streamflow data is important for studies of water resources and flood management, but an inherent problem is that many catchments of interest are ungauged. The lack of data is particularly the case for small catchments, where flow data with high temporal resolution is needed. This paper presents an analysis of regionalizing parameters of the Distance Distribution Dynamics (DDD) rainfall-runoff model for predicting hourly flows at small-ungauged rural catchments. The performance of the model with hourly time resolution has been evaluated (calibrated and validated) for 41 small gauged catchments in Norway (areas from 1 km〈sup〉2〈/sup〉 – 50km〈sup〉2〈/sup〉). The model parameters needing regionalization have been regionalized using three different methods: multiple regression, physical similarity (single-donor and pooling-group based methods), and a combination of the two methods. Seven independent catchments, which are not used in the evaluation, are used for validation of the regionalization methods. All the three methods (the multiple regression, pooling-group, and combined methods) perform satisfactorily (0.5 ≤ KGE 〈 0.75). The combined method (which combines multiple regression and pooling-group) performed slightly better than the other methods. Some model parameters, namely those describing recession characteristics, estimated by the regionalization methods, appear to be a better choice than those estimated locally from short period of hydro-meteorological data for some test catchments. The single-donor method did not perform satisfactorily. The satisfactory performance of the combined method shows that regionalization of DDD model parameters is possible by combining multiple regression and physical similarity methods.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Akhilesh S. Nair, J. Indu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Realistic representation of surface states using the land surface model (LSM) is extremely challenging owing to human-induced changes and uncertainty in forcing data. In this study, we focus on two crucial objectives pertaining to hydrology namely (a) to understand the ability of different soil moisture (SM) products to improve simulation of unmodeled irrigation processes through data assimilation process , and (b) to learn the feasibility of these SM products to correct the spatial surface soil moisture artifacts caused due to error in precipitation forcing. The utility of SM products evaluated in the present study are retrieved from different satellite sensors and algorithms such as the active satellite-based the Advanced Scatterometer (ASCAT), merged SM from European Space Agency Climate Change Initiative (ESA CCI V4.2) and the latest passive microwave-based SMOS INRA-CESBIO (SMOS-IC) SM product. The results presented for three years (2010, 2011 and 2012) suggest that assimilation of ASCAT and CCI based products effectively captures the SM changes due to irrigation. Similarly, it corrects the spatial artifacts caused due to precipitation errors. However, the single sensor based products have a limitation in spatial samples per day which is critical to capture dynamic SM products over a larger area. Hence, blended products are more effective on a larger area to capture the dynamics in a more effective manner at daily temporal resolutions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology〈/p〉 〈p〉Author(s): Sarah R. Parker, Stephen K. Adams, Roderick W. Lammers, Eric D. Stein, Brian P. Bledsoe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉River flows exert dominant controls on in-stream biota. Quantifying linkages between hydrology and biology is important for assessing the effects of flow alteration on ecological functions. Hydrologic models are often used to quantify these flow-ecology relationships and guide management actions. Traditional model calibration techniques typically focus on a best overall fit criterion that may not be suitable for environmental flow applications where certain elements of the flow regime exert a dominant influence on biotic composition. We present an approach for hydrologic model calibration that improves the accuracy of calculated flow metrics known to be significant drivers of ecosystem response. First, we developed regional flow-ecology relationships based on streamflow gage and benthic macroinvertebrate data from southern California to determine which streamflow metrics best explain variability in taxonomic and trait-based biotic indices. Next, we developed and calibrated a series of hydrologic models to minimize error in these important flow metrics. For our study sites, flow flashiness and low flow frequency (indicative of drying) were found to best explain biotic condition. Hydrologic models calibrated specifically to minimize errors in these flow metrics predicted macroinvertebrate indices better than models calibrated to maximize fit to the overall flow regime. This ecological-calibration approach requires some 〈em〉a priori〈/em〉 knowledge of flow-ecology relationships, but it produces results that can improve assessment of the impacts of changing flow regimes on biota and guide the development of strategies to mitigate ecological degradation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Journal of Hydrology, Volume 573〈/p〉 〈p〉Author(s): Youn-Young Jung, Dong-Chan Koh, Yoon-Yeol Yoon, Hong-Il Kwon, Joonghyeok Heo, Kyoochul Ha, Seong-Taek Yun〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study aims to clarify groundwater and stream water flow systems in the Geum River basin, Korea, which is an area with a crystalline basement using δ〈sup〉18〈/sup〉O, δ〈sup〉2〈/sup〉H, and 〈sup〉3〈/sup〉H. Stable isotopes of precipitation showed clear differences between dry and rainy seasons due to the Asian monsoon. Groundwater and stream water samples were collected in the dry and rainy seasons in three hydrographic zones of the upper, middle, and lower zones. The contribution of rainy season precipitation to groundwater recharge based on deuterium excess was 71–89%, far exceeding the amount fraction of the season in total precipitation. Stable isotopic compositions of groundwater and stream water showed little seasonal variation, and indicated the dominance of high-altitude recharge in the upper zone. Groundwater with lower 〈sup〉3〈/sup〉H was mainly observed in that area, indicating a contribution of intermediate flow with a longer residence time. In contrast, stream water and some groundwater samples in the lower zone showed seasonal variability and signatures of 10–20% evaporation in their stable isotopic composition. The 〈sup〉3〈/sup〉H content of groundwater in the lower zone was high, indicating that the local flow system is dominant. These regional features also influenced the relative contributions of rainy season precipitation, dry season precipitation, and local recharge with evaporation signature, as estimated from δ〈sup〉18〈/sup〉O and deuterium excess values, and 〈sup〉3〈/sup〉H in groundwater. Stream water from lower-order streams of the river had stable isotopic compositions similar to those in the upper zone, indicating a considerable contribution of groundwater discharge in the mountainous areas to the lower reach of the river. These results have implications for sustainable management of water resources in the basin during predicted changes in water usage and precipitation patterns due to climate change, as well as in regions with similar climatic and hydrologic conditions.〈/p〉〈/div〉 〈/div〉