ALBERT

Description: The daily rainfall-runoff relationship in an experimental watershed was modeled using a statistical method and an artificial neural network method. The estimations were examined and a performance evaluation was done. It was seen that the ANN method, FFBP (Feed Forward Back Propagation), provided closer flow estimations reproducing the shape of the observed hydrograph more realistic. The superiority of FFBP was reflected in the performance evaluation criteria. The extreme flows, i.e., high and low flows, were relatively better approximated by FFBP indicating its promise as a useful tool for hydrologic studies such as flood modeling. The Rational Method was also used, as a conventional tool, to predict the maximum discharge for selected return periods. It was found to be realistic for the forested watershed under consideration when the C coefficient was taken as 0.20 for the 10-year period.

Description: A procedure for optimal design of District Metered Areas (DMAs) within a water distribution network based on a multilevel balancing and refinement algorithm to partition the network and determine the optimal meter positions, coupled with a pressure driven hydraulic simulator to quantify the hydraulic performance of the districtualized system, is presented. Unlike other procedures based on graph partitioning techniques proposed in the scientific literature, the two main issues involved in the design of the DMAs, namely a) how to partition the nodes into the required number of districts, and b) which pipes linking districts to leave open, and fitted with an assigned number of flow meters, and which to close, are simultaneously resolved. The application of this procedure to a real case shows that this approach provides design solutions well adapted to different numbers of measuring points, yielding superior performance indicator values to similar procedures reported in the literature and used here for comparative purposes.

Description: Sustainable groundwater management requires approaches to assess the influence of climate and management actions on the evolution of groundwater systems. Traditional approaches that apply continuity to assess groundwater sustainability fail to capture the spatial variability of aquifer responses. To address this gap, our study evaluates groundwater elevation data from the Coachella Valley, California, within a groundwater sustainability framework given the adoption of integrative management strategies in the valley. Our study details an innovative approach employing traditional statistical methods to improve understanding of aquifer responses. In this analysis, we evaluate trends at individual groundwater observation wells and regional groundwater behaviors using field significance. Regional elevation trends identified no significant trends during periods of intense groundwater replenishment, active since 1973, despite spatial variability in individual well trends. Our results illustrate the spatially limited effects of groundwater replenishment occur against a setting of long-term groundwater depletion, raising concerns over the definition of sustainable groundwater management in aquifer systems employing integrative management strategies.

Description: Extreme rainfall events are among the natural hazards with catastrophic impacts on human society. Trend analysis is important to understand the effects of climate change and variability on extreme rainfalls. In this study, extreme rainfall (i.e., annual maximums) trends were investigated in Victoria (Australia) using data from 23 stations for storm durations of 10 and 30 min, and 1, 3, 6, 12, 24 and 48 h. The Mann-Kendal and Spearman’s Rho tests were employed for detection of temporal trends. Moreover, the spatial variability of extreme rainfall trends was investigated through interpolation of Theil-Sen’s estimator over Victoria. In general, increasing extreme rainfall trends were detected for short storm durations (i.e., 10 and 30 min, and 1 and 3 h), whereas decreasing extreme rainfall trends were found for long storm durations (i.e., 6, 12, 24 and 48 h). Increasing trends for short storm durations were mostly statistically significant, while decreasing trends for long storm durations were statistically insignificant. Trend analysis with respect to the four regions (i.e., Western, Northern, Central and Gippsland) in Victoria showed that increasing trends were present in general in the Northern and east Central Region, whereas decreasing trends were detected in the Western and west Gippsland Regions.

Description: To make full use of water captured by reservoirs in flood seasons, methods such as forecast-based reservoir flood control (i.e., reservoir operation during flood periods based on precipitation or inflow forecasts) have been developed in China in the past few decades. The success of forecast-based reservoir flood control depends heavily on the precision of the precipitation or inflow forecasts. This study analyzes the sources of uncertainty and quantifies it in the process of reservoir flood control based on forecasts. First, flood inflow series is regarded as a random process with the forecasted flood inflows as its expectation process; the flood inflow error series, which is the difference between the observed inflow process and the forecasted inflow process, is obtained according to the statistical characteristics of the flood forecasts. Second, reservoir flood routing simulations are carried out using the Monte Carlo method with the flood inflow error series as an input to obtain output water level and discharge series. Finally, the frequency distributions of the maximum water level (MWL) reached during the passage of floods are used to evaluate the uncertainties and the corresponding risks associated with forecast-based flood control. These uncertainties and risks are what the operators of the reservoirs care about the most.

Description: This paper introduces a reservoir design optimization model adapted to incorporate performance norms so that the active storage capacity can be determined assuming that failures may occur during the reservoir operation. The model is able to find the optimal reservoir capacity admitting either a predefined minimum number of failure periods or a maximum failure magnitude, or both. It is formulated as a mixed integer linear program that properly manages reservoir spills and includes evaporation losses. The procedure performs effectively for an example problem and Monte Carlo simulations and shows that lower accepted reliabilities and higher accepted vulnerabilities require less active storage.

Description: Increased groundwater accessibility resulting from the expansion of deep and shallow tube wells helped Bangladesh attain near self-sufficiency in rice, with national output increasing over 15 million tons in the last two decades. However, problems associated with the excessive exploitation of groundwater notably declining water tables, deteriorating water quality, increasing energy costs and carbon emissions are threatening the sustainability of Bangladesh’s groundwater irrigated economy. The forefront challenge, therefore, is to shift the focus from development to management of this precious resource. To ease out pressure on groundwater resources, attention must be diverted to further develop surface water resources. In addition to increasing supplies, water demand also need to be curtailed by increasing water use efficiency through the adoption of water conserving practices such as reduced tillage, raised bed planting, and the right choices of crops. Decreasing water availability both in terms of quantity and quality suggest that the unchecked expansion of dry season boro rice cultivation may not be a long-term option for Bangladesh. Therefore less thirsty wheat and maize crops may be promoted as feasible alternatives to boro . In addition to technical solutions, strong linkage between different institutions will be needed to evaluation strategic options and effective implementation of national policies for the management of groundwater resources.

Description: Since 2001, a rising water table occurred in the eastern part of the city of Naples (Italy), leading to flooding of the foundations of many buildings and of the underground infrastructures (garages, subway tracks, etc.). This resulted from the reduction in the exploitation of water for industrial use and drinking water in the central part of the groundwater body of the eastern plain of Naples: the groundwater withdrawal decreased from up to 3 m 3 /s in 1990 to a few hundred litres per second in 1998. The variation of piezometric levels led to flooding of foundations of many buildings and of underground infrastructures, this is a big amount of water lost by the aquifer system and that should be evaluated. In order to assess aquifer hydraulic features and the groundwater quantitative status, a 3D hydrostratigraphic model reconstruction was developed to support the groundwater flow modeling and the evaluation of the groundwater balance. The 3D hydrostratigraphic model reconstructed the subsoil of the study area: layers of tuff and lenses of peat, which play an important hydrogeologic role as aquitard and aquiclude, are faithfully defined. Indeed, the model allows the depiction of the horizontal extension and of the thickness of each hydrofacies, even if strongly heteropic. The groundwater flow model was defined using the 3D hydrostratigraphic model in the construction of the geometry and assignment of hydrodynamic parameters. The calibration and sensitivity analysis prove the goodness of the assigned hydraulic conductivity values. The model, together with a detailed computation of the paved areas with reduced infiltration, evaluated the recharge in 0.101 m 3 /s. The model calibration assessed an evapotranspiration rate lower than the prefixed value, probably due to the absence of vegetation that restricts the phenomenon almost exclusively to evaporation. Moreover, the calibration of the model confirmed: − the assumed groundwater flow towards the sea in 0.313 m 3 /s; − the hypothesized amount of the subsurface inflow from upstream in 0.504 m 3 /s. A considerable amount of water lost by the aquifer system, about 0.315 m 3 /s, could be used by Municipality for different public uses.

Description: Structural and operational management methods are used to meet water demands in watersheds around the world. Most river systems are affected by reservoirs, dams, or other engineering structures, and decisions regarding their construction and operation are made in advance of knowing what water demands will be. Numerical models are used to predict future water needs and evaluate the effectiveness of water management strategies. It is important to consider a variety of management methods and future environmental conditions to ensure future demands can be met. In this work, a coupled surface water operations and hydrologic model of the Lower Republican River Basin in portions of Nebraska and Kansas, USA is used to evaluate the ability of several water management strategies, including structural and operational, to meet future demands of a water-stressed agricultural basin under a variety of future climate scenarios. Simulations indicate recent administrative and operational changes to the distribution of water between Nebraska and Kansas have significantly decreased water shortages for irrigation districts in Kansas and will continue to do so. Simulations also indicate that structural alternative of reservoir expansion is most effective at minimizing shortages to demands under a repeat of historical climate conditions. However, an operational alternative of increasing water supplies for Kansas' exclusive use, such as those historically purchased under the Warren Act (US Code 43 Section 523–524), is most effective at minimizing shortages to demands under a hotter and drier climate, demonstrating how optimal water management strategies can vary significantly depending upon climate scenario.

Description: In this article we propose a new method - the Most Probable Precipitation Method (MPPM) - for estimating the precipitation at regional scale. Comparisons with the Thiessen polygons methods (TPM), inverse distance weighting interpolation (IDW) and ordinary kriging (OK) on annual, monthly, seasonal and annual maximum monthly precipitation are provided. In all cases MPPM performs better than IDW and OK, and in most of them, better than TPM.

Description: As various technologies are used for water and wastewater treatment, a global strategy with the objective of comparing and containing the price of water in the future is required. A study was carried out for this reason on production cost component of the price of water. This paper extends the concept of previously reported Water Price Index (WPI) as a metric for the cost of water production that can be adapted to water and wastewater treatment plants to evaluate their performance. Equations that define the contribution of capital and operational expenditure to the WPI are presented. Case studies from Eraring Power Station, Marquette Water Filtration Plant, Perth Desalination II and a theoretically modelled plant demonstrated the applicability of WPI and the benefit it brings to water practitioners.

Description: Forecasting flow in rivers has special significance in surface water management, especially in agricultural planning and risk reduction of floods and droughts. In recent years, studies have shown the superiority of forecasting models based on artificial intelligence, using artificial neural networks (ANN) and genetic programming (GP), over time-series models. In this paper, continuous and discrete historical flow records are used for monthly river flow forecasting of the Saeed-Abad river in East Azarbaijan province, Iran. Auto regressive moving average with exogenous inputs (ARMAX), ANN, and GP models are used in both continuous and discrete flow series. For both flow series, results of the ARMAX, ANN, and GP models are then compared and results of each method are evaluated relative to each other. Two quantitative standard statistical performance evaluation measures, coefficient of determination (R 2 ) and root mean square error (RMSE), are employed to evaluate the performance of the aforementioned models. Results show that for the two methods, the GP model is more effective with respect to accuracy than ARMAX and ANN. For continuous time-series forecasting, GP is a more precise model ( R 2  = 0.7 and RMSE  = 0.172) than either ANN ( R 2  = 0.627 and RMSE  = 0.193) or ARMAX ( R 2  = 0.595 and RMSE  = 0.243). For discrete time-series forecasting, the superiority of the GP model is evident in most months. For monthly flow forecasting, results indicate that the discrete time-series forecasting method is superior to the continuous time-series forecasting method.

Description: The variability of the relationship between precipitation and runoff is of vital importance to study the characteristics of regional water cycle and water resource management and planning. In this study, in order to explore the relationship between precipitation and runoff of the different hydrological patterns, the analysis of bivariate precipitation and runoff distributions and the simultaneous occurrence probability was analyzed by employing the Archimedean copula, based on the monthly runoff and precipitation data during 1960 ~ 2000 in the upper Huai river basin, China. The results indicated that: (I) the study region could be classified into four hydrological patterns, namely the Huai river valley zone, Huaibei plain zone, Huainan mountain zone and Huaibei mountain zone, with Xixian, Zhuanqiao, Meishan and Zhaopingtai as the maximal loading subbasin respectively. (II) There were positive dependence structure between precipitation and runoff in the study area, and the bivariate frequency distributions could be fitted best by the Gumbel-Hougaard copula. (III) The simultaneous occurrence probability of bivariate drought events was remarkable higher than that of corresponding classification of bivariate flood events; besides, the simultaneous occurrence probability of bivariate extreme events was maximum in the Huainan mountain zone, followed by the Huai river valley zone and Huaibei mountain zone, while that was minimum in the Huaibei plain zone. These results would be of essential guiding significance for water resource management and planning, flood and drought control and layout optimization of water conservancy projects in the study region.

Description: In this study a novel configuration of the Water Level Difference Error method is introduced to speed up the error sharing in the context of Model Predictive Control (MPC). The potential application of the controller is examined. The main objective of this controller is fair distribution of water between upstream and downstream users in main canals suffering from water shortages. The scheme uses the Integrator-Delay (ID) model for canal pool responses in a model predictive controller. The designed controller is tested on an accurate simulation model of a large canal system, using four test scenarios. The scenarios suffer from limited water supply conditions that are imposed by a limitation on the canal inflow. The results show fast reactions in equitable sharing of water level deviations from target throughout the canal. Since, all the pools are involved in optimally managing the water shortage, significant improvements in operational performance of the canal are achieved. In addition, the operational performance of the designed controller is remarkably improved by applying a new strategy of target-bands instead of target-levels in the canal pools as it increases the flexibility of the controller in making appropriate decisions.

Description: The importance of the groundwater management of karst aquifers relatively to their complexity requires the knowledge of the subsurface flow and storage behavior. In this study, a methodological approach based on the exploitation of daily spring’s discharge data was developed and tested. The methodology makes use of the hydrograph recession curves, the correlograms output, and the logarithmically structured duration curves. This methodological approach was applied to the complex karst system of Louros basin. The Louros karst system consists of individual karst units discharged by respective springs which are distributed on three levels and form three easily distinguishable groups. The application results revealed a well organized karst system with conduits of slow and fast flow. It also revealed the uniformity and the complexity of the different units, as well as the properties, such as the storativity and the evolutionary process. This approach demonstrates the benefits of interpreting different methods in a hydrologically meaningful way for the recharge data evaluation.

Description: The ecological flow requirement (EFR) during special life stages of species, for instance the fish spawning period, concerns not only the flow rate, but also daily changes in the flow rate. Therefore, it is more appropriate to optimize ecologically-friendly reservoir operation on a daily base. Directly formulating and solving a daily-based optimization model would involve a large number of decision variables as well as constraints, which may lead to unfavourable time consumption and unreliable solutions. This study proposes a time-nested approach to derive an optimal daily reservoir operation scheme with consideration of the downstream ecological hydrograph. It scales down the decision variables from monthly-base to 10-day base and finally to daily-base. The proposed method was applied to two cascaded reservoirs in the Yalong River in southwest China, where a daily ecological flow is required to conserve the habitats of an indigenous fish Schizothorax chongi ( S. chongi ). The results showed that the developed method could efficiently derive a daily optimal operational scheme with the consideration of downstream EFR for fish habitat conservation. In addition, the method greatly improves global searching ability in dealing with complex optimization problems.

Description: Bidirectional inter-basin water transfer is a special form of inter-basin water transfer, which can create a win-win outcome between two basins by utilizing the differences in flow regime from different basins. The objective of the research is to develop operating rules that consider both water transfer and water supply of water distribution system simultaneously for guiding the operation of multi-reservoir system in bidirectional inter-basin water transfer-supply system. The proposed rules include threefold: (1) triggering mechanisms for water transfer based on the storages of two equivalent reservoirs are presented for regulating the bidirectional water transfer between two basins, (2) water supply policy in the form of operating rule curves coupled to multiple hedging rules is proposed for guiding the water supply operation of multi-reservoir system, and (3) allocation approach of system release based on different priority demands is developed for determining the release from each reservoir. To obtain the optimal operating rules, the quantum-behaved particle swarm optimization algorithm (QPSO) is applied to a bidirectional inter-basin water transfer-supply system located in Liaoning province of northeast China. The results demonstrate that the obtained operating rules can guide the joint operation of multi-reservoir in bidirectional inter-basin water transfer-supply system in a mutually beneficial way.

Description: This paper develops a new method for real-time operation of reservoir systems. Genetic programming (GP) and a developed fixed length gene GP (FLGGP) are applied and compared in two approaches of static and dynamic operation rules with the aim of hydroelectric supply of Karun3 reservoir in Iran. Results are compared with those of genetic algorithm (GA) and nonlinear programming (NLP) method, indicating that GP and FLGGP have a higher efficiency (on average, 5 %) than GA and NLP operation methods. In addition, results showed that the FLGGP method is a powerful and efficient tool without the limitations of GP and can be used as a suitable replacement to GP. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rules and this approach has an average superiority of 10 % to static operation rules in all methods.

Description: Drought is a slow and creeping phenomenon that occurs more frequently in arid and semi-arid regions. In recent decades, among natural disasters influencing human societies the number or frequency of drought event has increased more than others. In this context, the prediction of drought intensity, duration and frequency can help to take the necessary precautions and reduce drought risk. This study employs Markov chains of different orders (0, 1, 2 and 3) to analyze hydrological drought characteristics. Hydrological drought is identified based on the streamflow drought index (SDI) at 3-, 6-, 9- and 12-month time scales using data from 21 hydrometric stations located in the Karkheh River Basin in Iran. According to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), first-order Markov chain models are adequate to reproduce the statistical structure of SDI-based hydrological droughts. Moreover, the steady state probabilities and expected residence time of drought severity for all time scales increase as the degree of severity decreases. The results also indicate that the expected frequency of drought occurrence is higher for smaller time scales (i.e., 3-month and 6-month).

Description: This study proposed an inexact double-hand-side chance-constrained programming (IDCCP) method for nonpoint-source water quality management within an agricultural system. The IDCCP model can express interval parameters and double-hand-side random variables (e.g. nitrogen requirement of crop and nitrogen content of manure) simultaneously. To handle the double-sided random variables, a linear form of sufficient conditions for the IDCCP was deduced and proved. The performance of IDCCP was testified in the water quality management study case at three individual probabilities ( θ i  = 0.1, 0.05 and 0.01), and compared with the corresponding ILP model. The results demonstrated that, the net benefit of the agriculture system decrease with a decreasing violating probability ( θ i ) , an increasing satisfaction of constraint (1- θ i ), or a lower risk of the system. Although it is the first application of the IDCCP method to nonpoint-resource water quality management, the IDCCP could also be applied to other environmental issues under such uncertainties.

Description: Natural and reconstructed monthly streamflow records from 172 river basins in Romania (143 with full records and 29 with less than 10 % missing values) have been analyzed for trends with the nonparametric Mann-Kendall test for the period 1956–2005. The statistical significance of trends was tested for each station on a monthly basis. Changes in the streamflow regime in Romania are demonstrated. The monthly flow presents upward trends from August to January, and predominantly downward trends from February to June. The most important changes are the increasing streamflow trends from September till November, which are well explained by the increase in autumn precipitation. The annual streamflow shows a dependence on latitude, with increasing trends in the northern part, and decreasing in the south. Strong negative correlations between the North Atlantic Oscillation and the mean annual streamflow have been found in western and southern Romania, highlighting the influence of the large-scale atmospheric circulation on Romanian annual streamflow in these areas, as well as the important orographic role of the Carpathian Mountains.

Description: The nonlinear form of the Muskingum model has been widely applied to river flood routing. There are four variants of the nonlinear Muskingum model based on alternative formulations of the nonlinear storage equation. This paper proposes a new Muskingum model with an improved, seven-parameter, nonlinear storage equation. The proposed model provides more degrees of freedom in fitting observed hydraulic data than other nonlinear Muskingum models. The proper estimation of the proposed Muskingum nonlinear model’s parameters is essential to achieve accurate flood-routing predictions. This paper introduces a hybrid method for the estimation of Muskingum parameters. The parameter-estimation method combines the shuffled frog leaping algorithm (SFLA) and the Nelder-Mead simplex (NMS). The proposed Muskingum model and parameter estimation method were applied to the routing of several hydrographs. Our results indicate improved performance of the methodology described in this work when compared with those of other Muskingum models.

Description: An integrated geophysical investigation viz., Vertical Electrical Sounding (VES), Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) were carried out in a coastal terrain at Vizag Steel Plant (VSP), Visakhapatnam, Andhra Pradesh., India for locating fresh water locations. The entire area was underlain by recent alluvial of varying thickness consists of sand, clay and silt with basement as Kondalite rock formation consisting of saline water in some parts of the area. Locating favorable groundwater locations in such a terrain is a difficult task. The area consists of saturated clay, saturated silt and saline water has the same resistivity signature and misleads resistivity data interpretation for identifying and recommending the suitable groundwater locations in a coastal terrain. To overcome these uncertainties, a second geophysical approach or combinations of geophysical methods become necessary to resolve these resistivity ranges in a more reliable and better fruitful interpretation of sub-surface layers. In order to pin-point the groundwater locations at VSP; VES, ERT and GPR investigations were carried out. Interpreted results of VES, ERT pseudo-section and GPR images (radargram) were correlated with each other to ascertain confidently the geophysical signature of the sub-surface. Combination of geophysical methods gives better resolution or interpretation of sub-surface information before made any recommendations for drilling of borewell. Based on integrated geophysical investigation few borewell sites were recommended and drilled. The observed drilled lithologs was well correlated with the VES, ERT and GPR data. Besides, this hydrochemical analysis of water samples was carried out from the existing borewells and dugwells. Total Dissolved Solids (TDS) and chloride concentration were ranges from 189 to 3398 mg/l and 5 to 1610 mg/l. The eastern and north-eastern part of the area has elevated concentration of TDS and chloride indicating intrusion of saline water. TDS concentration of drilled borewell was found to range from 400 to 500 mg/l. The observed yield of drilled borewells ranges from 104 to 3623 gal/hr.

Description: The most important piece of legislation towards integrated water management in Europe is the Water Framework Directive 2000/60/EC (WFD) based on the river basin. During its implementation each Member State (MS) should prepare a River Basin Management Plan (RBMP) accompanied with the Programme of Measures (PoMs) aiming at achieving good quality for all water bodies. The paper aims at presenting a summary of the progress regarding the RBMPs developed by each EU27 MS and special focus is given in Greece. The paper attempts a comparative analysis of the 12 Greek RBMPs highlighting the problems occurred and the drawbacks identified. Special focus is given in the economic analysis assessment where different methodologies are used to estimate the full water cost. Finally suggestions are given that can be taken into consideration during the second WFD implementation cycle in Greece.

Description: EPANET 2 has been used previously to simulate pressure-deficient operating conditions in water distribution systems by: (a) executing the algorithm repetitively until convergence is achieved; (b) modifying the source code to cater for pressure-dependent outflows; or (c) incorporating artificial elements e.g., reservoirs in the data input file. This paper describes a modelling approach that enables operating conditions with insufficient pressure to be simulated in a single execution of EPANET 2 without modifying the source code. This is achieved by connecting a check valve, a flow control valve and an emitter to the demand nodes. Thus the modelling approach proposed enhances an earlier formulation by obviating the need for an artificial reservoir at the nodes with insufficient pressure. Consequently the connecting pipe for the artificial reservoir (for which additional data must be provided) is not required. Also, we removed a previous limitation in the modelling of pressure-dependent nodal flows to better reflect the performance of the nodes with insufficient flow and pressure. This yields improved estimates of the available nodal flow and is achieved by simulating pressure-deficient nodal flows with emitters. The emitter discharge equation enables the nodal head-flow relationship to be varied to reflect the characteristics of any network. The procedure lends itself to extended period simulation, especially when carried out with the EPANET toolkit. The merits of the methodology are illustrated on several networks from the literature one of which has 2465 pipes. The results suggest the procedure is robust, reliable and fast enough for regular use.

Description: The cold river water inflow often plunges below the ambient dam reservoir water and becomes density underflow through the reservoir. The hydrodynamics of density currents and plunging are difficult to study in the natural environment and laboratory condition due to small-scale, entrainment and turbulent flows. Numerical modeling of plunging flow and defining of the plunging depth can provide valuable insights for the dam reservoir sedimentation and water quality problem. In this study, an adaptive neuro-fuzzy (NF) approach is proposed to estimate plunging flow depth in dam reservoir. The results of the NF model are compared with two-dimensional hydrodynamic model, artificial neural network (ANN), and multi linear regression (MLR) model results. The two-dimensional model is adapted to simulate density plunging flow simulation through a reservoir with sloping bottom. The model is developed using nonlinear and unsteady continuity, momentum, energy and k-ε turbulence model equations in the Cartesian coordinates. Density flow parameters such as velocity, plunging points, and plunging depths are determined from the simulation and model results. Mean square errors (MSE), mean absolute errors (MAE) and determination coefficient (R 2 ) statistics are used as comparing criteria for the evaluation of the models’ performances. The NF model approach for the data yields the small MSE (1.18 cm), MAE (0.86 cm), and high determination coefficient (0.95–0.98). Based on the comparisons, it was found that the NF computing technique performs better than the other models in plunging flow depth estimation for the particular data sets used in this study.

Description: The paper presents semi-analytical mathematical model to estimate unsteady groundwater recharge resulting from variable depth of water in a large water body, influenced by time variant inflows and outflows. The model has been derived by integrating Hantush’s ( 1967 ) analytical expression for water table rise due to recharge from a rectangular spreading basin into the water balance equation of the water body. The model has been applied to a test study site in Raipur (India) for assessing viability of Managed Aquifer Recharge (MAR) from a lake located on an area dominated by the massive limestone formation. The components of the water balance equation have been carried out by the comprehensive analysis of the hydrological and hydrogeological aspects of the lake. The hydrological components include analysis of rainfall-runoff, evaporation rate, lake water quality and the hydrogeological components include aquifer characterization, parameters estimate, ambient groundwater level and quality. The time variant depth of water resulting from the interaction of water balance components, computed using the model, has been compared with the measured data and found a satisfactory match, as revealed from RMSE analysis. Compared to the inflows and lake storages, the recharge rates from the lake found very less, which ranged between 3.75 and 4.82 mm/day for depth of water ranged between 2.5 and 3.36 m. The lake water quality indicated contamination by bacteriological parameters (viz. Fecal coliform and Total coliform), turbidity and COD, exceeding the permissible limit of drinking water standards ( IS-10500:2012 ). The aquifer formations below the lakebed and around possess thick limestone formation - a limiting factor for MAR-ASTR proposition, and hence no engineered hydrogeological intervention has been found viable to enhance the recharge rate.

Description: Most of the transboundary river basins are contested due to the overlapping water demands of their riparian countries. Hence, these border crossing river basins are under immense pressure from the rising water demand. Thus, most of these essential fresh water resources could face water bankruptcy scenario in the future. The Nile river basin is one of these contested river basins. The demand for the river’s water is rising rapidly. Research studies indicated that the river basin could become water bankrupt in the near future. In this article the authors applied the classical bankruptcy water allocation rules for allocating the predicted available water of the river basin. In addition, the authors proposed an innovative way of accounting the water contribution of riparian states and also a mechanism for weighing the water deficit allotted to them. Generally, the authors hope that this article shades some light on allocation of water under water scarcity in the Nile river basin and in other border crossing river basins which could help for avoiding water conflicts and ensuring the sustainability of these crucial freshwater resources.

Description: Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an irrigation canal located in Spain. First, a discrete time linear model of the process is described and its parameters are experimentally identified. The model is well validated within the usual canal operating range and is used to formulate a predictive control law with an incremental formulation. Finally, experimental and simulation results are presented in which predictive control has shown better performance than a well-tuned proportional, integral and derivative controller to automatically manage demanded water discharges.

Description: This paper deals with uncertainty estimation and knowledge enhancement in water distribution networks (WDNs). A new three steps data assimilation approach is introduced, which in combination with multi-objective optimization, allows selecting effective and affordable monitoring networks. An innovative cascade of Ensemble Kalman Filters is used to assimilate the information deriving from sensors measuring pressure heads, flow in pipes and demands, with the objective of increasing knowledge while preserving at the same time the structural relationships among state variables. Selection of the most appropriate and economically affordable measurement network, is then based on the derivation of a Pareto front using the NSGA-II algorithm in conjunction with the data assimilation approach. The front is obtained by compromising between the overall sensors cost and the uncertainty reduction (or knowledge enhancement), which is expressed as a function of the Total Variance of state variables. The operational use of the proposed data assimilation approach as well as the effectiveness of the chosen observation network is also demonstrated by showing the reduction of uncertainty deriving from successive assimilations of real-time observations.

Description: The assessment of the suspended sediment (SS) amount in rivers has an importance because it specifically affects the design and operation of numerous hydraulic structures such as dams, bridges, etc. This paper proposes an adaptive neuro-fuzzy embedded fuzzy c-means clustering (ANFIS-FCM) approach for estimating SS concentration. The accuracy of ANFIS-FCM models was compared with classical ANFIS, artificial neural networks (ANNs) and sediment rating curve (SRC). Daily streamflow and SS data from two stations, Muddy Creek near Vaughn and Muddy Creek at Vaughn, operated by the United States Geological Survey were used in the study. Applied models were compared with each other based on root mean square errors and correlation coefficient. Based on comparison, ANFIS-FCM performed superior to the other two models for modeling complex non-linear behavior of the suspended sediment concentration. The ANFIS-FCM model increased the performance (RMSE) of the optimal MLP model by 10 % and 16 % in estimating SSC for the downstream and upstream stations, separately. ANFIS-FCM model provided improvements in performance and parsimonious and took lesser time in calibration than the classical ANFIS model.

Description: Accurate and reliable stream-flow forecasting has a key role in water resources planning and management. Most recently, soft computing approaches have become progressively prevalent in modelling hydrological variables and most specifically stream-flows. This is due to their ability to capture the non-linearity and non-stationarity characteristics of the hydrological variables with minimum information requirements. Despite this, they present several challenges in the modelling architecture, as there is a need to establish a suitable pre-processing method for the stream-flow data and an appropriate optimization model has to be integrated in order re-adjust the weights and biases associated with the model structure. On top of that, artificial intelligent models require “trial and error” procedures in order to be properly tuned (number of hidden layers, number of neurons within the hidden layers and the type of the transfer function). However, soft computing approach experienced several problems while calibration such as over-fitting. In this research, the Response Surface Method (RSM) is improved based on high-order polynomial functions for forecasting the river stream-flow namely; High-Order Response Surface (HORS) method. Several higher orders have been examined, second, third, fourth and fifth polynomial functions in order to figure out the best fit that able to mimic the pattern of stream-flow. In order to demonstrate the effectiveness of the proposed model, monthly stream-flow time series data located in Aswan High Dam (AHD) has been examined. A detailed analysis of the overall statistical indicators revealed that the proposed method showed outstanding performance for monthly stream-flow forecasting at AHD. It could be concluded that the fifth order polynomial function outperforms the other orders of the polynomial functions especially with May model who achieved minimum MAE 0.12, NRMSE 0.07, MSE 0.03 and maximum SF and R 2 (0.97, 0.99) respectively.

Description: This study focuses on assessing trends of reference evapotranspiration (ET o ) considering aridity. Weather data sets of 54–62 years of Inner Mongolia, a Chinese Province where climate varies from hyper-arid in the West to wet sub-humid in the East, were used. Trends were analyzed for ET o computed with the FAO Penman-Monteith method (PM-ET o ) using full data sets of maximum and minimum temperature (T max and T min ), sunshine duration (SD) used to compute net radiation, relative humidity (RH) and wind speed (WS). Trends were also assessed for ET o computed with the Hargreaves-Samani temperature eq. (ET o HS ) and the Penman-Monteith equation with temperature estimates of solar radiation and actual vapour pressure (ET o PMT ). In addition, trends relative to T max , T min , SD, RH and WS were assessed. Trends for PM-ET o show to vary with aridity, with decreasing trends in the areas marked by aridity in the West and increased trends in less arid and sub-humid areas in the East. The detected trends are well explained by the trends in weather variables which consist of large increasing trends of T max and T min and of decreasing trends for SD, RH and WS. Therefore, negative trends of ET o occur where impacts of increases in temperature and decreases in RH are smaller than impacts of declining SD and WS; otherwise, when warming influences are larger it results a positive trend for ET o . Trends were coherent when considering seasonality influences. Contrarily, results for the temperature methods, ET o PMT and ET o HS, always identified increased trends for ET o due to warming effects. These results show that it is inappropriate to assess ET o trends when using simplified temperature methods.

Description: Accurate prediction of surface runoff is critical to watershed management. In this research a semi-analytical model was adopted to solve the kinematic wave equation based on the assumption that the rate of overland-flow depth change is proportional to the rainfall excess. Simulations were compared with the results from laboratory experiments at various rain intensities. Parameters of infiltration rate and Manning’s roughness coefficient were determined. The accuracy of the semi-analytical model was evaluated by numerical simulations. The predicted outflow rates from the numerical simulations agreed well with the observed data. Further, our study indicated that the ratio ( c ) of the overland-flow depth change to the rainfall excess was a power function of the rain intensity. The depth and velocity of water flow at any time and distance could be calculated with the semi-analytical model. Hydraulic parameters including Reynolds number, Froude number, hydraulic shear stress, stream power and Darcy-Weisbach friction factor characterizing the dynamic features of overland flow of rainwater were calculated based on calculated overland-flow depth and velocity. The proposed analytical method can provide a new way to predict infiltration and runoff over sloped land.

Description: The optimal hydropower operation of reservoir systems is known as a complex nonlinear nonconvex optimization problem. This paper presents the application of invasive weed optimization (IWO) algorithm, which is a novel evolutionary algorithm inspired from colonizing weeds, for optimal operation of hydropower reservoir systems. The IWO algorithm is used to optimally solve the hydropower operation problems for both cases of single reservoir and multi reservoir systems, over short, medium and long term operation periods, and the results are compared with the existing results obtained by the two most commonly used evolutionary algorithms, namely, particle swam optimization (PSO) and genetic algorithm (GA). The results show that the IWO is more efficient and effective than PSO and GA for both single reservoir and multi reservoir hydropower operation problems.

Description: Water scarcity and the poor quality of water resources are leading to a wider diffusion of desalination plants using the Reverse Osmosis (RO) process. Unfortunately, the cost of a cubic meter of fresh water produced by an RO plants is still high and many efforts are in progress to increase the efficiency of the membranes used in osmotic plants and to limit the energy required by the process. A further reduction of the energy cost could be obtained by an optimal operation of the desalination plant so reducing the hourly energy cost, or by coupling the RO plant with an energy production plant based on direct osmosis (Pressure Retarded Osmosis PRO). The economic viability of the desalination process has been analyzed until now without accounting for the integration of the RO plant with the existing water network. This analysis is developed in the present paper with reference to a hypothetical change of water supply in a real network, where a desalination plant is used to satisfy the fresh water demand. Several scenarios will be analyzed to assess the minimum cost of fresh water production and water supply to the network, including the use of energy recovery systems, such as an integrated use of RO and PRO processes, or the regulation of pressure at the network intake by a micro hydro power plant.

Description: Quantifying reference evapotranspiration (ET 0 ) is essential in water resources management. Although, many methods have been developed with different level of accuracy, in this study, two new equations were developed and optimized for estimating ET 0 using Honey-Bee Mating Optimization (HBMO) algorithm. The first eq. estimates ET 0 from extraterrestrial radiation (R a ), relative humidity (RH) and mean daily temperature (T mean ), while the second uses the same parameters except that mean daily temperatures is replaced with maximum daily air temperature (T max ). Both equations were developed using climatic data from eight weather stations in Western Australia and subsequently verified using data from ten sites across Australia. The estimated ET 0 values from both equations versus the FAO56-Penman-Monteith have a coefficient of determination, R 2 , of larger than 0.96. Moreover, the performance of six commonly used methods of estimating ET 0 including Hargreaves-Samani, Thornthwaith, Hamon, Mc Guinness-Bordne, Irmak and Jensen-Haise were assessed and the Hargreaves-Samani method performed better than others. An attempt was made to calibrate the Hargreaves-Samani equation; however, its overall performance did not improved and the two newly proposed equations are suggested to be used in Australia.

Description: Balancing human demands for water with environmental requirements to maintain functioning ecosystems requires the quantification of ecological water requirements. In arid regions, high spatial variability of vegetation cover and different water consumption of plant species make it different to estimate reasonable ecological water requirements. We developed a simple and practical approach that estimates the vegetation water requirements (VWRs) of desert riparian ecosystems. This model is species-specific and spatially-explicit; it considers the water consumption characteristics required by different species and highlights the impacts that high vegetation cover spatial variability has in arid regions on evapotranspiration. The model was parameterized based on the observation of the water consumption of two typical desert riparian species, Populus euphratica and Tamarix spp., in the lower basin of the Tarim River in northwestern China. Comparisons between the modeling results and measured data for two mature Populus and Tamarix stands indicate that the model is reasonable predictive. A case study in the lower basin of the Tarim River demonstrated the model’s practicality and transferability. This model could run based on near real-time or forest weather data and spatial vegetation patterns, and provides a continuous estimation of the temporal and spatial variations of the VWR. Particularly, this model forecasts VWRs under different vegetation spatial distribution and coverage scenarios, and evaluates the impacts and consequences of different management actions. This model can serve as a useful tool for management agencies interested in improving their decisions to allocate river water between human activities and natural ecosystems in arid regions.

Description: This study develops and applies three hybrid models, including wavelet packet-artificial neural network (WPANN), wavelet packet-adaptive neuro-fuzzy inference system (WPANFIS) and wavelet packet-support vector machine (WPSVM), combining wavelet packet decomposition (WPD) and machine learning models, ANN, ANFIS and SVM models, for forecasting daily river stage and evaluates their performance. The WPANN, WPANFIS and WPSVM models using inputs decomposed by the WPD are found to produce higher efficiency based on statistical performance criteria than the ANN, ANFIS and SVM models using original inputs. Performance evaluation for various mother wavelets indicates that the model performance is dependent on mother wavelets and the WPD using Symmlet-10 and Coiflet-18 is more effective to enhance the efficiency of the conventional machine learning models than other mother wavelets. It is found that the WPANFIS model outperforms the WPANN and WPSVM models, and the WPANFIS14-coif18 model produces the best performance among all other models in terms of model efficiency. Therefore, the WPD can significantly enhance the accuracy of the conventional machine learning models, and the conjunction of the WPD and machine learning models can be an effective tool for forecasting daily river stage accurately .

Description: A detailed regional drought study is carried out in the southern peninsula of India to characterize the spatio-temporal nature of droughts and to predict the drought magnitudes for various probabilities in the homogeneous drought regions. The method of several random initializations of the cluster centres of the K-means algorithm is suggested for the identification of the initial regions in the context of drought regionalization, which is shown to perform better than the initialization from the Ward’s algorithm and the Ward’s algorithm itself. The peninsula is classified into seven spatially well-separated homogeneous drought regions. The robust L-moment framework is used for the regional frequency analysis of drought magnitudes computed using the standardized precipitation index. The Pearson type III is found to be appropriate for regional drought frequency analysis in six of the regions, while the robust Wakeby distribution is suggested for one region. Low magnitude droughts are frequent and dominant in the northern part of west coast, the north-eastern coast and its adjoining inland region, while high magnitude droughts are less in number and are experienced in semi-arid central part, southern part of western coast, south-eastern part and north-western inland region. The spatial maps of drought magnitudes indicate that at higher return periods (100 and 200 years) the south-eastern part of the peninsula is likely to encounter high magnitude droughts, while the central region is likely to experience the same at lower return periods (10 and 50 years). Hence these regions need to be given special importance in the drought mitigation planning activities.

Description: When weather data sets available for computing the reference evapotranspiration are incomplete or of questionable quality, there is the need to replace the FAO Penman-Monteith (PM-ET o ) method by approaches requiring reduced sets only, particularly maximum and minimum temperature. The Hargreaves-Samani (HS) equation and the PM-ET o using only temperature data (PMT) are considered in this study and their results are compared with those of the PM-ET o using full datasets. Daily data sets refer to the period 1981–2012 and to a network of 50 meteorological stations covering the wide range of climates of Inner Mongolia. For both the PMT and HS methods, the solar radiation coefficients k Rs were calibrated and have shown to be similar for both methods and to vary with climate aridity. For the PMT, the estimation of the dew point temperature (T dew ) was performed using the minimum temperature corrected for site aridity or, for humid climates, from a value near the average temperature. This improved estimation of T dew was essential for a good performance of the PMT method in arid conditions and when temperatures are extremely low. RMSE 〈1 mm day −1 was obtained for both HS and PMT methods, and the modeling efficiency generally exceeded 0.85. The worse results correspond to windy and arid locations. The principal components analysis (PCA) in R-Mode have shown that the spatial variability of ET o computed with PM-ET o or with the HS and PMT methods were coherent. PCA supported the interpretation of ET o results. Overall, PMT performed better than HS for most locations.

Description: Drought is one of the main natural hazards affecting the economy and the environment of large areas. Droughts cause crop losses, urban water supply shortages, social alarm, degradation and desertification. In this study, the spatial characteristics of annual and seasonal drought were evaluated based on climate data from 16 synoptic stations during the period of 1980–2010 in south of Iran. To estimate the drought severity used modified Reconnaissance Drought Index (RDI) and to prepare maps, ArcGis10.2 software was used. Results showed in annual drought, percent of areas with normal condition, severe dry and extreme dry condition have had significant increasing trend (0.95 level). In winter drought, the percentage of areas with severe dry and extreme dry condition have had significant increasing trend (0.95 level). In spring drought, percent of areas with moderate dry has had significant increasing trend (0.95 level), in summer drought, percent of areas with moderate dry has had increasing trend (insignificant) and in autumn drought, percent of areas with severe dry has had significant increasing trend (0.95 level). Other classes of drought in different time scales had not significant trend. Result showed that the percentage of area with dry condition is increasing, this can be effective on the agricultural activities, agricultural productions, water resource management and other activities.

Description: Sanitary sewer overflows (SSOs) is the unintentional discharge of untreated sewage from the sanitary sewer system and pose serious risk to public health and to the environment. Rehabilitation plans to reduce SSOs involve increasing conveyance capacity and shaving peak flow using detention storages. Identifying the best location for rehabilitating the sanitary sewer network is a difficult task because of the great length of sanitary sewer systems. This study utilized single and multiobjective genetic algorithms (GAs) to design rehabilitation strategies for SSOs reduction in an existing sewer network. The Nondominated Sorting Genetic Algorithm II was linked to the EPA-SWMM to generate non-dominated sets of solutions that characterizes the tradeoffs between reduction in number of SSOs and cost (Case I), and the tradeoff between of volume of SSOs and cost (Case II). The results show that, when maximizing the reduction of number SSOs, the algorithm target first regions of the network with higher density of SSOs. When maximizing the reduction of volume of SSOs, the solutions prioritize the nodes with the largest overflow volumes. The tested approach provides a range of options to decision makers that seek to reduce or eliminate SSOs in an existing sanitary sewer system.

Description: In Taiwan’s humid climate, proximal fan groundwater (PFG) is mainly sourced from local precipitation (LP), mountain front recharge (MFR), and mountain block recharge (MBR). This study evaluates the relative importance of the above sources’ respective contributions to the PFG of the Langyang alluvial plain (LAP), northeastern Taiwan. To this end, we first identify stable isotopic characteristics of these target waters and evaluate the hydrological relations among them. Further, we employ ternary end member mixing analysis (EMMA) based on δ 18 O and electrical conductivity to semi-quantitatively calculate contributing fractions and amounts of water for respective LP, MFR, and MBR end members. EMMA results indicate that the respective contribution fractions of LP, MFR, and MBR to PFG at the LAP are approximately 28, 60, and 12 %, respectively. Further, we employ the obtained contribution fractions to understand the corresponding water amounts of each end-member contributed to PFG. In total, 325 × 10 6  m 3 of water recharges PFG annually; of which, 226 × 10 6  m 3 /yr. is from MFR, 76 × 10 6  m 3 /yr. from LP, and 23 × 10 6  m 3 /yr. from MBR. MFR is clearly the greatest source of water at the LAP and local water resource management and protection authorities should concentrate their energies on this important contributor to groundwater. To keep these results in context, limitations to the EMMA approach are evaluated in the text.

Description: This research investigates five reference evapotranspiration models (one combined model, one temperature-based model, and three radiation-based models) under hyper-arid environmental conditions at the operational field level. These models were evaluated and calibrated using the weekly water balance of alfalfa by EnviroSCAN to calculate crop evapotranspiration (ET c ). Calibration models were evaluated and validated using wheat and potatoes, respectively, on the basis of weekly water balance. Based on the results and discussion, the FAO-56 Penman-Monteith model proved to be superior in estimating ET c with a slight underestimation of 2 %. Meanwhile, the Hargreaves-Samani (HS) model (temperature-based) underestimated ET c by 20 % and the Priestley-Taylor (PT) and Makkink (MK) models (radiation-based) had similar performances underestimating by up to 35 % of the measured ET c . The Turc (TR) model had the lowest performance compared with other models, demonstrating values underestimated by up to 60 % of the measured ET c . Local calibration based on alfalfa evapotranspiration measurements was used to rectify these underestimations. The surprisingly good performance of the calibrated simple HS model, with a new coefficient 0.0029, demonstrated its favorable potential to improve irrigation scheduling. The MK and PT models were in third and fourth rank, respectively, reflecting minor differences between one another. The new coefficients obtained for the MK and PT models were 1.99 and 0.963, respectively. One important observation was that the calibrated TR model performed poorly, with an increase in its coefficient from 0.013 to 0.034 to account for hyper-arid environmental conditions; moreover, it required additional seasonal calibration to adequately improve its performance.

Description: This paper describes the development and application of a new multi-objective evolutionary optimization approach for the design and upgrading of water distribution systems with multiple pumps and service reservoirs. The optimization model employs a pressure-driven analysis simulator that accounts for the minimum node pressure constraints and conservation of mass and energy. Pump scheduling, tank siting and tank design are integrated seamlessly in the optimization without introducing additional heuristic procedures. The computational solution of the optimization problem is entirely penalty-free, thanks to pressure-driven analysis and the inclusion of explicit criteria for tank depletion and replenishment. The model was applied to the Anytown network that is a benchmark optimization problem. Many new solutions were achieved that are cheaper and offer superior performance compared to previous solutions in the literature. Detailed and extensive simulations of the solutions achieved were carried out. Spatial and temporal variations in water quality were investigated by simulating the chlorine residual and disinfection by-products in addition to water age. The hydraulic requirements were satisfied; efficiency of pumps was consistently high; effective operation of the new and existing tanks was achieved; water quality was improved; and overall computational efficiency was high. The formulation is entirely generic.

Description: Geographic Information System (GIS) are an intelligence technique skilled to extract, store, manage and display the spatial information for various applications of water resources management. Practically, arid and semi-arid environments suffer from several restrictions (e.g., lack of socio-economic and physical data, limited precipitation, and poor rain water management). In this research, Remote Sensing (RS) approach was integrated with GIS conducted to estimate the physical variables of reservoir system (i.e., elevation-area-volume curve). First and foremost, computing an accurate and reliable elevation-area-volume curve is a challenging task for the purpose of identifying the optimal depth, minimum surface area and maximum reservoir storage. Accordingly, a field study consisting of three constructed small earth dams were demonstrated the use of the geospatial approach in the western desert of Iraq, where the elevation-area-volume curve was extracted. The surface areas and the reservoir volumes that were obtained from field survey and spatial intelligence techniques were compared. A comprehensive analysis have been carried out for the evaluation purposes. The results indicate that the proposed approach efficiently applied with remarkable level of accuracy.

Description: Water level prediction of rivers, especially in flood prone countries, can be helpful to reduce losses from flooding. A precise prediction method can issue a forewarning of the impending flood, to implement early evacuation measures, for residents near the river, when is required. To this end, we design a new method to predict water level of river. This approach relies on a novel method for prediction of water level named as RBF-FFA that is designed by utilizing firefly algorithm (FFA) to train the radial basis function (RBF) and (FFA) is used to interpolation RBF to predict the best solution. The predictions accuracy of the proposed RBF–FFA model is validated compared to those of support vector machine (SVM) and multilayer perceptron (MLP) models. In order to assess the models’ performance, we measured the coefficient of determination ( R 2 ), correlation coefficient ( r ), root mean square error ( RMSE ) and mean absolute percentage error ( MAPE ). The achieved results show that the developed RBF–FFA model provides more precise predictions compared to different ANNs, namely support vector machine (SVM) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real time water stage measurements. The results specify that the developed RBF–FFA model can be used as an efficient technique for accurate prediction of water stage of river.

Description: This study investigated the effects of urbanization predicted using the SLEUTH urban growth model (an acronym taken from Slope, Landuse, Exclusion, Urban extent, Transportation and Hillshade) under four landuse policy scenarios on the hydrological response of Ayamama watershed using the Hydrologic Engineering Center Release 1 (HEC-1) hydrological model. The SLEUTH model was calibrated based on the Brute Force Monte Carlo iteration technique using the urban extents of Istanbul in 1987, 2000, 2009 and 2013 and was verified by considering Kappa coefficient as evaluation criteria. HEC-1 was calibrated and verified using observed rainfall-runoff event and based on the coefficient of determination (R 2 ), Nash-Sutcliffe coefficient of efficiency (CE) and percentage of bias (PBIAS) as performance indicators. The urbanization prediction results showed that the urban extent of Ayamama watershed would reach 50.3 km 2 , 44 km 2 , 63 km 2 and 60 km 2 under Scenarios 1, 2, 3 and 4, respectively, in 2050. The hydrological simulation results under these urban extents showed that the urban extent of Ayamama watershed under Scenario-3, a scenario that allows unrestricted growth with the implementation of Project Canal Istanbul (PCI), resulted in the highest peak discharge and the shortest time to peak. Such an increase in the peak discharge and reduction in the time to peak will increase the risk of flooding and, therefore, extreme care needs to be taken before and during the implementation of PCI.

Description: This research investigated the optimum on-farm water management methods for a summer crop (Maize). Water equity and productivity were optimized simultaneously by using genetic algorithms in Doroodzan Irrigation Network. Increase in water reduction fraction (WRF) (0.0 to 0.8) has the incremental effect on water equity (on average 19.4 %), however by increasing WRF, water productivity initially increased (on average 25.3 % at WRF = 0.4) and then decreased. With increasing irrigation application efficiency (E a ) (40 to 90 %), the values of water equity and productivity increased by on average 52.8 and 91.5 %, respectively. Increment of conveyance efficiency of channels (E c ) (70 to 90 %) resulted in minimum incremental effect on water equity and productivity (on average 18.5 and 11.9 %, respectively). Furthermore, the values of performance measure decreased from wet water year to drought water year. Tape irrigation system was considered as the best choice at low quantities of WRF (〈=0.4), however for higher values of WRF (〉 = 0.6), sprinkler irrigation system was considered as the best choice for achieving higher values of water equity and productivity. Meanwhile, when equity and productivity were considered together for a specific method of deficit irrigation scheduling, under specified quantity of irrigation water, with increasing equity the water productivity reduction was negligible.

Description: At the coastline of the Carey Island, mangroves provide natural protection against the wind-driven coastal waves. The area is located at the west Malaysia within the waters of the Straits of Malacca . Recently, its coastline has been exposed to increasing rates of coastal erosion due to mangrove deforestation. In order to provide mitigating measures, it is necessary to study wave characteristics in this region. For this purpose, we collected 5 years (2009 to 2013) of hourly measurements for wind direction, wave height, wind speed and wave period. Moreover, we used the adaptive neuro-fuzzy inference system (ANFIS) to estimate the wave period and height. The model was trained using the measured data. The validation of the model gave satisfactory R 2 values of 0.8484 and 0.9496 for wave height and wave period, respectively. The findings from this study suggest that fuzzy logic based technique satisfactorily predicts the differences between multiple inputs and single output in terms of non-linear relationship. The developed model can be used to further study the effect of non-linear wind-driven waves on the depleting coastal mangrove forests in similar tropical and sub-tropical areas. We suggest further research to test the model in different geographical locations, such as in deep-ocean, narrow straits and other coastal sites, which were not covered in this study.

Description: With the wavelet transform method, the multi-resolution analysis of runoff and sediment load at Huaxian hydrological station located in the lower reaches of the Weihe River in China is presented to find the varying quasic-periodic waveforms existing in different decomposed time scales. The cointegration theory is introduced to reveal the long-term balance relationship and short-term fluctuations of the original and decomposed runoff and sediment load time series. Thus, considering the decomposed sediment load components in different time scales as the input data series, and the corresponding decomposed runoff component acting as the output data series, the multi-resolution cointegration method is produced. The results show that the multi-resolution cointegration method has the higher prediction accuracy, and the prediction errors are almost less than 5 %.

Description: An increase of urban flood risks is expected for the following decades not only because climate is becoming more extreme, but also because population and asset densities in cities are increasing. There is a need for models that can explain the damage process of urban flooding and support damage prevention. Recent improvements in flood modeling have highlighted the importance of urban topography to properly describe the built environment. While such modeling has mainly focused on the hazard components of urban pluvial floods, the understanding of damage processes remains poor, mainly due to a lack of flood impact information. Citizen’s reports about flood incidents can be used to describe urban flooding impacts. In this study a database of such type of reports and a digital elevation model are used as main inputs to analyze the relationships between urban topography and occurrence of pluvial flood impacts. After a delineation of urban subwatersheds at a district level, the amount of reports along the overland flow-paths is studied. Then, the spatial distribution of reports is statistically assessed at district and neighborhood levels, in Euclidean and network-constrained spaces. This novel implementation computes the connections of a network of subwatersheds to calculate overland flow-path gradient distances, which are used to test whether the location of reports is constrained by those gradients. Results indicate that while reports have a clear clustered spatial distribution over the study area, they are randomly distributed along overland flow-path gradients, suggesting that factors different from topography influence the occurrence of incidents.

Description: Water demand prediction is essential in any short or long-term management plans. For short-term prediction of water demand, climatic factors play an important role since they have direct influence on water consumption. In this paper, prediction of future daily water demand for Al-Khobar city in the Kingdom of Saudi Arabia is investigated. For this purpose, the combined technique of Artificial Neural Networks (ANNs) and time series models was constructed based on the available daily water consumption and climatic data. The paper covers the following: forecast daily water demand for Al-Khobar city, compare the performance of the ANNs [General Regression Neural Network (GRNN) model] technique to time series models in predicting water consumption, and study the ability of the combined technique (GRNN and time series) to forecast water consumption compared to the time series technique alone. Results indicate that combining time series models with ANNs model will give better prediction compared to the use of ANNs or time series models alone.

Description: This study developed Mamdani-type fuzzy logic model to simulate daily discharge as a function of soil moisture measured at three different depths (10, 20 and 40 cm) and rainfall. The model was applied to 13 km 2 size Colorso Basin in central Italy for a period from October 2002 to April 2004. For each variable of soil moisture, rainfall, and discharge, 9 fuzzy subsets were employed while 30 fuzzy rules, relating the input variables (soil moisture and rainfall) to the output variable (discharge), were optimized. The model employed the min inferencing, max composition, and the centroid method. The model application results revealed that Mamdani-type fuzzy logic model can be employed to incorporate soil moisture along with rainfall to simulate discharge. Using soil moisture measured at 40 cm soil depth along with rainfall produced better simulation of discharge with NS   = 0.68 and R  = 0.82. The performance of the model was also tested against a conceptual rainfall-runoff model of MISDc (Modello Idrologico Semi-Distribuito in continuo). MISDc couples an event-specific component with a module for continuous time soil water balance for taking into account the variable antecedent wetness conditions. The MISDc model requires estimation of seven parameters and the measurements of the hydrometeorological variables such as rainfall and air temperature. The comparative study revealed that fuzzy model performs better in capturing runoff peak rates and overall trend of high and small flooding events.

Description: This paper presents a novel multi-objective evolutionary optimization approach for the active control of intermittent unsatisfactory discharges from combined sewer systems. The procedure proposed considers the unsteady flows and water quality in the sewers together with the wastewater treatment costs. The distinction between the portion of wastewater that receives full secondary treatment and the overall capacity of the wastewater treatment works (including storm overflow tanks) is addressed. Temporal and spatial variations in the concentrations of the primary contaminants are incorporated also. The formulation is different from previous approaches in the literature in that in addition to the wastewater treatment cost we consider at once the relative polluting effects of the various primary contaminants in wastewater. This is achieved by incorporating a measure of the overall pollution called the effluent quality index. The differences between two diametrically opposed control objectives are illustrated, i.e. the minimization of the pollution of the receiving water or, alternatively, the minimization of the wastewater treatment cost. Results are included for a realistic interceptor sewer system that show that the combination of a multi-objective genetic algorithm and a stormwater management model is effective. The genetic algorithm achieved consistently the frontier optimal control settings that, in turn, revealed the trade-offs between the wastewater treatment cost and pollution of the receiving water.

Description: The functional zoning of groundwater is the basis for the rational development and utilization, scientific management and effective protection of groundwater. Based on the distribution, type, hydrogeological condition and exploitation status of groundwater in Tianjin, and considering the resource supply, ecological environment maintenance and geological environment stability simultaneously, the function zoning of shallow groundwater has been divided into the non-central water supply area in built-up zones, the fragile marsh zones, the fragile nature reserve zones, the polluted groundwater zones and the salt water zones. And the deep groundwater has been divided into the non-central water supply area in built-up zones, the central supply area in built-up zones, the land subsidence zones, polluted groundwater zones and the salt water descending zones. Firstly, this paper selected dominant factors of groundwater development and utilization risk based on the different groundwater function zoning results, distinguished them into natural factors and human factors, and developed the risk assessment index systems. Secondly, the risk assessment systems for shallow and deep groundwater were built according to the characteristics of respective aquifers, and the weight of each evaluation index was calculated by AHP (Analytic Hierarchy Process) method. Then, each of the unit risk grade was determined by the method of fuzzy synthetic evaluation on basis of these index attributes and the corresponding weights, and results were distributed in space using ArcGIS to obtain the groundwater risk grade map of various aquifers in different groundwater function zones of Tianjin city. Finally, the risk grade in each district of Tianjin was determined by superimposing the district boundaries on these maps. Groundwater development and utilization risk grades based on the functional zoning of groundwater can provide a scientific basis for management of groundwater and a method for determining groundwater level.

Description: The Azzaba City located in the North East of Algeria has undergone rapid urbanization during the past few years. Infrastructure development has further enhanced the land use change process in the area. Bad land use management practices are thought to be the cause of increased flooding. While the characteristics of the precipitation are tied to the climatology of the region, and can change only over the long term, the urbanization, an antropic factor, changes more rapidly and plays a non negligible role in modifying the land use. It is thus very important to assess the runoff changes due to land-use changes. Moreover, the knowledge of the rainfall runoff relationship is an essential tool in modelling and design of urban drainage networks. In this paper two hydrological models, namely WBNM and HEC-HMS, and a GIS procedure are used to predict runoff hydrographs of a small urban catchment located in Azzaba city. The aim was to test the effect of catchment size and time steps on runoff hydrograph shape, and to evaluate the catchment reaction to a given rainfall event obtained from the established IDF Curves. Furthermore a sensitivity analysis of the parameters of the models is carried out. In addition the results of the models are compared with the observed runoff data, measured during a storm event that occurred in 11th of Mars, 2014. This calibration is performed by applying different situations of catchment size and time steps. Then, characteristics of calculated hydrographs were compared with the same characteristics of the same observed hydrographs and analyzed statistically. The results indicate that HEC-HMS provide acceptable simulations in the flood events, which WBNM fail to simulate. Finally, hydrographs simulated by the HEC-HMS model have the best fit with the real situation. It is necessary to generalize this study and build up the data base for the further application of rainfall runoff model in Algeria.

Description: Recently suspended river, where formed both in tributary and in main stream of Ningxia-Inner Mongolia reaches in the Upper Yellow River, severely threatens people’s lives and property safety downstream. In this paper, taking Ningxia-Inner Mongolia reaches for the example, water and sediment are regulated by cascade reservoirs upstream, which can form artificial controlled flood, to improve the relationship of water-sediment and slow down the speed of sedimentation rate. Then, multi-objective optimal operation model of cascade reservoirs is established with four objectives: ice and flood control, power generation, water supply, water and sediment regulation. Based on optimization technique of feasible search space, the non-dominated sorting genetic algorithm (NSGA-II) is improved and a new multi-objective algorithm, Feasible Search Space Optimization-Non-dominated Sorting Genetic Algorithm (FSSO-NSGA-II) is innovatively proposed in this paper. The best time of water and sediment regulation is discussed and the regulation index system and scenarios are constructed in three level years of 2010, 2020 and 2030. After that regulation efforts and contribution to sediment transportation are quantified under three scenarios. Compared with history data in 2010, the accuracy and superiority of multi-objective model and FSSO-NSGA-II are verified. Even more, four-dimensional vector coordinate systems are proposed innovatively to represent each objective and sensitivity of three scenarios are analyzed to clarify the impact on regulation objectives by regulation indexes. At last, relationships between four objectives are revealed. The research findings provide optimal solutions of multi-objectives optimal operation by FSSO-NSGA-II, which have an important theoretical significance to enrich the methods of water and sediment optimal operation by cascade reservoirs, guiding significance to water and sediment regulation implementation and construct water and sediment control system in the whole Yellow River basin. Research Highlights We establish an multi-objective optimal operation model with four regulation objectives. We proposed a improved multi-objective algorithm (FSSO-NSGA-II) based on feasible search space optimization. Regulation index system and three scenarios are constructed. Four-dimensional vector coordinate systems are proposed to represent each objective and sensitivity of scenarios are analyzed. Relationships between four objectives are revealed.

Description: The increasing demand for energy, especially from renewable and sustainable resources, encourages the development of small hydropower plants (SHPs). Earlier hydropower studies were time consuming and less effective due to maximum involvement of the ground based and handheld surveys. This study aimed to present a new multi-criteria approach for harnessing hydropower through establishing small hydropower projects (SHPs) (≤25 MW) instead of large hydropower projects. The multi-criteria approach is based on an integration of advance raster/grid based preparation of geospatial data layers, hydrological modeling and weighted sum overlay analysis. The hydrological data simulation and parameterization were done in SWAT (soil and water assessment tool) model by utilizing 17 years long duration real time hydro-meteorological data sets. For this reason, we selected an Inland based Hamp river catchment, which is a part of Mahanadi river basin of India. The outcomes of this study allow spotting identification of four hydropower potential zones and 10 suitable sites location for SHPs along the stream network by characterizing whole catchment into different sub-catchments. Slope, soil, landuse/landcover (LULC), ET (evapotranspiration), water yield, and rainfall were identified as most important variables for hydropower assessment.

Description: The Reconnaissance Drought Index (RDI) is obtained by fitting a lognormal probability density function (PDF) to the ratio of accumulated precipitation over potential evapotranspiration values (α k ) at different time scales. This paper aims to address the question of how a probability distribution may fit better to the α k values than a lognormal distribution and how RDI values may change in shorter (i.e.,3-month, and 6-month) and longer (i.e., 9-month, and annual) time scales during 1960–2010 period over various climate conditions (arid, semi-arid, and humid) in Iran. For this purpose, the series of RDI were initially computed by fitting a lognormal PDF to the α k values and the Kolmogorov–Smirnov (K-S) test was implemented to choose the best probability function in different window sizes from 3 to 12-months. The corresponding RDI values for the best distribution were then deriven based on an equiprobability transformation function. The differences between RDI values (the lognormal (RDI log ) and the best (RDI App ) distributions) were compared based on Nash-Sutcliffe efficiency (NSE) criterion. The results of goodness of fit test based on threshold value in the K-S test showed that the goodness of fit in the lognormal distribution may not be rejected at 0.01 and 0.05 significance levels while may only be rejected in a short term (Apr.-Jun.) period at humid station (Rasht station), and three-month (Oct.-Dec. and Apr.-Jun.) and six-month (Apr.-Sep.) periods in semi-arid station (Shiraz station) at significance levels of 0.10 and 0.20, correspondingly. Further a difference between RDI log and RDI App performed that RDI values may change if the best distribution employs and this may therefore lead to significant discrepant and/or displacement of drought severity classes in the RDI estimation.

Description: Individual impacts of climate change, land use/coverage change, the regulation of water reservoir and water use to intra-annual distribution of streamflow of the Dongjiang River basin, South China, are quantitatively separated. Data on precipitation, streamflow, regulation of water reservoirs, and water use are used in the analysis. Changes in the concentration degree and non-uniformity coefficient of intra-annual distribution of streamflow over time scales from daily to monthly are evaluated. Trend and change point analyses are applied to determine characteristics of intra-annual distribution of streamflow. By comparison with the difference among region precipitation, naturalized streamflow and observed streamflow, the contribution of main impact factors to the intra-annual distribution of streamflow are quantified. Results demonstrate the non-uniformity coefficient decreases with a negative logarithmic linear function of the time scale. Change points of the concentration degree and non-uniformity coefficient occurred in 1973 exhibited a significant downward trend. In the period posterior to the change point the former and the latter decrease approximately by 15–34 % and by 29–40 %, respectively. The decrease in concentration degree and non-uniformity coefficient is due to the regulation of water reservoirs and land use/cover change; while the increase is the result of water use and climate change. The individual contributions to the impact on the intra-annual distribution of streamflow from regulation of water reservoirs, land use/cover change, water use, and climate change are approximately −33.5, −9.0, 4.5 and 1.0 %. It is observed that the impacts of the regulations of the Xinfengjiang, Fengshuba, and Baipenzhu reservoirs account for −21, −10, and −2 %, respectively. There is an increasing tendency in the impacts of land use/cover change and water use in the past 30 years.

Description: So far a huge number of dynamic game models, both discrete and continuous, have been developed for reservoir operation. Most of them seek to overcome potential conflicts while allocating limited water among various users in reservoir systems. A number of them have successfully provided efficient approaches to tackle the problem of optimal water allocation. There are, however, still weaknesses in determining optimal policies. By taking account of the random nature of the inflow while producing monthly operating policies for a reservoir in a dynamic non-discrete framework, many of these deficiencies can be eliminated. In this study, considering the randomness in reservoir inflow, a continuous dynamic game model for water allocation in a reservoir system was developed. A corresponding monthly-basis solution based on collocation was then structured. This collocation method does not rely on first and second degree approximations. Instead, in order to evaluate the uncertainty triggered by the random variable, a discrete approximant was applied to quantify the random variable in the state transition function. A case study was carried out at the Zayandeh-Rud river basin in central Iran to identify the efficiency of the proposed method and evaluate the effect of uncertainty on decision variables. The results of the presented model (i.e., monthly-basis operating rules and value functions) proved to be more practical and reliable than similar continuous dynamic game models working on an annual basis. Moreover, the results show that bringing the stochasticity associated with inflow into the equation has an impact on the value functions and operating polices. Indeed, applying the mean of the random variable of inflow (deterministic form) reduce consistancy in monthly reliability indices throughout the year.

Description: A nonlinear programming (NLP) optimization model has been developed for the minimum cost design of infiltration basins and infiltration trenches. The focus of this optimization model and approach is to provide a functional and versatile tool to simultaneously determine the peak inflow and runoff from a design storm event based on watershed parameters, and to optimize the size of an infiltration basin based on the design storm parameters, infiltration characteristics, basin capacity, and mounding. Two optimization models are developed, one is based upon the rational method and the second is based upon the modified rational method. Both approaches use the Green-Ampt method for infiltration, in addition to a method for defining the mounding effects. The various hydrologic concepts are defined through constraints in the optimization models. No previous optimizations models for infiltration basin design have been developed that can accomplish the detail of this new model. The nonlinear programming model is solved using the GAMS (General Algebraic Modeling system) software which is readily available.

Description: Assessing suspended sediment loads in rivers is important since it affects water quality, hydraulic-facility design, and many other sediment-induced problems. Sediment-load estimation heavily depends upon empirical approaches such as a sediment rating curve, which is the empirical relationship between sediment load and river discharge. However, the sediment rating curve is insufficient to describe the inevitable scatter between sediment and discharge. This study aims to develop a probabilistic estimation scheme for daily and annual suspended sediment loads using quantile regression. All recorded daily suspended sediment load and discharge data are employed to construct quantile-dependent sediment rating curves. The empirical probability distribution of daily suspended sediment load is then built by integrating the conditional estimations associated with the corresponding quantiles for a given discharge. The probability distribution of a cumulative sediment load over a longer period can also be derived by the obtained daily sediment-load probability distributions and convolution theorem. The proposed approach is applied to the Laonung station located in southern Taiwan. The results indicate that the proposed approach provides not only the probabilistic description for daily and annual suspended sediment loads, but also the single estimations including the mean, median, and mode of the derived probability distribution. For the 1,110 recorded data of Laonung station during the 1959–2008 period, the proposed mean and median estimation schemes outperform the traditional sediment-rating-curve approach for less mean absolute errors.

Description: Recent increases in life loss, destruction and property damages caused by flood at global scale, have inevitably highlighted the pivotal considerations of sustainable development through flood risk management. Throughout the paper, a practical framework to prioritize the flood risk management alternatives for Gorganrood River in Iran was applied. Comparison between multi criteria decision making (MCDM) models with different computational mechanisms provided an opportunity to obtain the most conclusive model. Non-parametric stochastic tests, aggregation models and sensitivity analysis were employed to investigate the most suitable ranking model for the case study. The outcomes of these mentioned tools illustrated that ELimination and Et Choice Translating Reality (ELECTRE III), a non-compensatory model, stood superior to the others. Moreover, Eigen-vector’s performance for assigning weights to the criteria was proved by the application of Kendall Tau Correlation Coefficient Test. From the technical point of view, the highest priority among the criteria belonged to a social criteria named Expected Average Number of Casualties per year. Furthermore, an alternative with pre and post disaster effectiveness was determined as the top-rank measure. This alternative constituted flood insurance plus flood warning system. The present research illustrated that ELECTRE III could deal with the complexity of flood management criteria. Hence, this MCDM model would be an effective tool for dealing with complex prioritization issues.

Description: The potential of a copula model for the description of the joint probability distribution of two agricultural drought characteristics, the relative onset RO and the relative severity RS , is investigated in Perugia (Central Italy) in reference to a sunflower crop. The 1924–2009 time series of daily precipitation and maximum and minimum temperature were used to simulate, by means of the AquaCrop model, the root-zone soil water dynamics ( SW t ) and the crop yield under rainfed conditions. The seasonal values of RO and RS were quantified, by applying the theory of runs to SW t (assumed as the drought reference variable), with a threshold equal to the crop critical point. The analysis shows that the best-fitting marginal distribution for both RO and RS is a truncated Gumbel distribution. The dependence structure of RO and RS , investigated by graphical and analytical techniques, was modeled by a Student copula, which is able to adequately reproduce both the overall and upper tail dependence among variables. Lastly, the Student copula was applied to obtain joint probabilities and bivariate return periods for RO and RS . These results, compared with the expected estimated yields, provide useful information for drought planning and management. For example, for the case study considered, it was found that the condition RO  ≥ 0.43 (i.e., onset before the end of June) and RS  ≥ 0.22 has a 5-year return period and is frequently associated with critical yields, and that the condition RO  ≥ 0.47 (i.e., onset before mid-June) and RS  ≥ 0.25 has a 10-year return period and is almost certainly associated with critical yields.

Description: This paper discusses research on the optimal design of looped water distribution networks with complex layouts. It focuses on incorporating uncertain hydraulic constraints in the optimal design of networks which includes tanks and pumping facilities. The Fuzzy Decision System is utilized to define the hydraulic constraints uncertainty. Using Fuzzy Genetic Algorithm, the genetic algorithm selects the cost efficient network, while fuzzy reasoning evaluates the water delivery quality of each potential solution. This paper includes an overview of the selection of design variables to determine siting and sizing of tanks and pumps, define initial water level and daily operational schedules for tanks; and define the total number of parallel pumps and their operational schedule. This is followed by a new method to optimally design a water distribution network in two stages of consumption and tank filling periods. The performance of the proposed algorithm is evaluated using Anytown network, which includes pumps and tank facilities. It is concluded that the Fuzzy Genetic Algorithm is able to optimally design water distribution networks under multi uncertain hydraulic constraints. Moreover, conducting the optimal design procedure in two stages (consumption and filling period) would substantially decrease the computational costs and improve the performance of the designed network.

Description: The AquaCrop model was used to simulate maize growth and soil water content under full and deficit irrigation managements as 1.2, 1, 0.8, and 0.6 of the potential crop water requirement. Generally, the RMSEs in simulating soil water content in calibration and validation were 0.01–0.039 and 0.012–0.037 m 3 m −3 , respectively, that overall corresponds to 3–14 % error. For the in-season biomass development, the RMSEs in calibration varied between 2.16 and 2.73 Mg ha −1 , while they varied between 1.97 and 5.19 Mg ha −1 in validation for the four irrigation managements. The model showed poor performance for simulating biomass late in the season under deficit irrigation managements. The RMSEs of final grain yield simulation were 0.71 and 1.77 Mg ha −1 that corresponded to 7 and 18 % error in calibration and validation, respectively. Likewise, the RMSEs for simulating the final biomass in calibration and validation were 1.29 and 2.21 Mg ha −1 that equals to 6 and 10 % error, respectively. Results demonstrated that AquaCrop is a useful decision-making tool for investigating deficit irrigations and maize growth in the region. However, in agreement with the findings in earlier studies on AquaCrop, the model showed insufficient accuracy in simulating final grain yield and biomass under moderate to severe water stresses. It is suggested that AquaCrop would benefit of including some calibrating parameters about the root distribution pattern in the soil because it is a water-driven model and highly depends on the accurately simulated water uptake from the soil profile.

Description: Impacts of flood management alternatives are mostly assessed by inundation depth. Other inundation parameters such as velocity and duration are rarely taken into consideration. In this paper, a multi-criteria decision making (MCDM) based framework is used to analyze the effects of inundation velocity and duration on evaluation of flood management alternatives. The framework incorporates a two-dimensional (2D) flood model, Flood2D-GPU and a spatial MCDM (SMCDM) method, Spatial Compromise Programming (SCP). Flood2D-GPU is employed to simulate floods and SCP is applied to rank a set of flood management alternatives. Assessment of flood management options is conducted with multiple different weight set scenarios. First, alternatives are ranked without consideration of inundation velocity and duration. Then, the importance of these parameters increases and the alternatives are ordered in each weight set and a GIS map showing the best alternative in each grid cell is generated in each case. Best alternative maps (BAMs) are compared to investigate the impacts of inundation velocity and duration on selection of best strategy using F fit measure and κ analysis. The framework applicability is illustrated on the Swannanoa River watershed located in the state of North Carolina, US. Case study results indicate up to 49.7 % change of BAM by taking into account inundation velocity and duration. The presented approach addresses the change in selection of flood management strategies resulted by considering other inundation parameters rather than inundation depth. This can potentially reduce the uncertainties associated with the decisions made without consideration of inundation velocity and duration.

Description: Rapid and accurate inundation modelling in large floodplains is critical for emergency response and environmental management. This paper describes the development and implementation of a floodplain inundation model that can be used for rapid assessment of inundation in very large floodplains. The model uses high resolution DEM (such as LiDAR DEM) to derive floodplain storages and connectivity between them at different river stages. We tested the performance of the model across several large floodplains in southeast Australia for estimating floodplain inundation extent, volume, and water depth for a few recent flood events. The results are in good agreement with those obtained from high resolution satellite imageries and MIKE 21 two-dimensional hydrodynamic model. The model performed particularly well in the reaches that have confined channels with above 85 % agreement with the flood maps derived from Landsat TM imagery in cell-to-cell comparison. While the model did not performance as well in the flat and complex floodplains, the overall level of agreement of the modelled inundation maps with the satellite flood maps was still satisfactory (60–75 %). The key advantage of this model is demonstrated by its capability to simulate inundation in large floodplains (over 2000 km 2 ) at a very high resolution of 5-m with more than 81 million cells at a reasonably low computational cost. The model is suitable for practical floodplain inundation simulation and scenario modelling under current and future climate conditions.

Description: Using input–output table of China in 2007, this paper built an input–output model and tested the effect of variation of water-use efficiency on the structure of virtual water trade. As the final water consumption coefficient increases (i.e., water-use efficiency decreases) in some department, the proportion of this department’s virtual water outflow/inflow increases while those of all the other departments decrease. As the direct water consumption coefficient increases (i.e., water-use efficiency decreases), the proportion of this department's virtual water outflow/inflow increases while the sum but not each of the other departments’ proportions decreases. The final water consumption coefficient of any department is bigger than the direct one, implying indirect water consumption exists and final water consumption coefficient is a better indicator for water-use efficiency. The paper shows that China is a net exporter of virtual water, but the departments of agriculture, mining, petrochemical are the net importers of virtual water. According to the results, China should use the strategy of virtual water trade to alleviate water shortage. Also, China should adopt water-saving technology in production, and improve the level of self-sufficiency of products in order to reduce reliance on foreign trade correspondingly.

Description: The channel design problem can be treated as an optimization problem in which the objective function is minimization of construction cost. In this definition, the optimum values of section variables, i.e. side slope, bottom width, flow depth and radius, can be computed by minimizing the total cost subjected to a hydraulic flow constraint formula, i.e. the Manning’s equation. In a general scope, the total cost comprises lining, earthwork cost and the additional excavation cost accounting for the depth of earthwork under the ground surface. In this paper, a novel optimization technique, invariably called the Modified Honey Bee Mating Optimization (MHBMO) algorithm, was utilized to solved the defined design problem. By investigation of the affection of different cost values on the optimal results, a new explicit model for common channel shapes, i.e. triangular, rectangular, trapezoidal and circular, was proposed utilizing the MHBMO algorithm to directly design the channel cross sections. The proposed model was compared to the present models in literature using four design examples. The results demonstrate that, despite of simplicity of the new model, it achieves more precise values than the present models for all common channel shapes.

Description: The natural rivers in developing countries have not been meeting their desirable water quality objectives due to discharge of untreated wastewater from domestic and industrial sources for a long time; and thus need to implement rational water quality management (WQM) plans. Overall sustainability of proposed WQM options should not be overlooked during the planning phase due to lack or absence of data. In this research, a framework is proposed for the evaluation of different WQM options to meet the water quality objectives of natural rivers. Five main sustainability criteria (SSC) are considered, including cost (capital, land and operational), land requirements, operation and maintenance issues, environmental impacts, and socio-economic impacts. In addition, several sub-criteria (impacts) have also been included to rationally justify the assessment of SSC by the decision makers (DM). The values of cost and land requirement criteria are calculated; whereas, the other SSC are subjective in nature. However, both types possess uncertainties associated with calculation errors, inherent assumptions, and the differences in DM’s opinions. Further, due to data limitations in developing countries, the ranking order of WQM options established by the DM should be preferred. To deal with such uncertainties and the DM preferences, the Fuzzy UTASTAR multicriteria analysis method (based on linear programing) has been used for sustainability evaluation. To appraise the practicality of the proposed framework, it has been applied to the WQM of the Ravi River in Pakistan. The minimal difference between the DM’s top ranked options affirms the effectiveness of the proposed framework.

Description: The management transfer of irrigation districts from the public to the private sector became a broad strategy throughout the world. Although the extent to which the process is being implemented, there is little information available on the results of these transfer programs. In addition, there is no established procedure to analyze economic feasibility and general performance of the irrigation districts. In this context, the aim of this research was to develop a model to evaluate the performance of self-managed irrigated areas transferred from public sector to private irrigator associations. A list of performance indicators proposed by the Brazilian Federal Court of Accounts to monitor the public perimeters and pre-classification information from two public companies, San Francisco and Parnaiba Valleys Development Company (CODEVASF) and National Department of Works Against Droughts (DNOCS) were used in this research. A statistical multivariate model with discriminant analysis (MDA) was performed to identify the indicators importance in order to discriminate the current level of the irrigation areas. The data resulting from multivariate discriminant analysis was used to create an artificial neural network (ANN) that classifies the irrigated areas related to management. It was observed that the indicator Generated Revenue per Hectare (GRH) was the most important in the discriminating process regarding self-management. The neural network created from the values of the performance function resulted from multivariate discriminant analysis showed be capable of assessing the performance of Irrigated Perimeters over time and also be adequate as a tool for resource allocation and evaluation of self-managed irrigated areas.

Description: In this work, the efficiency of water markets in an irrigation district is put under consideration. This efficiency is referred to the private economic losses arising from a reduction in the availability of water, so the most efficient or optimal allocation will be the one that minimizes these losses or the one that provides the maximum private benefit. On this view, the optimal allocation has been studied in an irrigation community, and it has been compared with the rule of fixing a same quota and the proportional reduction. Besides, from the water allocation made by these last two rules, a water market has been simulated. Formulation for all of them is provided. Results show that water markets will improve the suboptimal allocation made by the rule of fixing a same quota and the proportional rule, even when transaction costs are high. They also show that, mostly, the greater the water restrictions, the greater are the gains from trade. It can be inferred too that, as long as all determinants have been taken into account and transaction costs are low enough, the aggregate losses of income ensuing from any prescribed water reduction will be the lowest both by means of the optimal allocation as with a market. Anyhow, results and conclusions clearly dependent on the relations made between allocations and crop yields.

Description: In this paper, an integrated detection scheme is developed to simultaneously address a leakage, a partial blockage and unknown branched pipeline elements. Expressions for the pressure head and discharge for a branched pipeline system having both a leakage and a blockage are derived in frequency domain. Boundary conditions for a reservoir and a branched dead-end allow the development of impedance formulations. The condition for a pipeline junction can be addressed using either a common condition for the pressure head combined with a continuity condition of discharge or a connectivity condition for impedance. In order to consider the unsteady friction’s impact, the impedance development process studied both the impact resulting from velocity profiles with two-dimensional distributions and the impact resulting from local and convective accelerations. Impedance expressions are derived for two distinct branched pipeline systems at different abnormality conditions. Based on drived formulations describing these systems, response functions were derived in the frequency domain and their corresponding time domain representations were integrated into a meta-heuristic calibration scheme for inverse transient analysis. Using an objective function for minimization of root-mean-square-errors between the observed and computed pressures, the calibration based one impulse response can simultaneously predict locations and magnitudes of abnormalities as well as parameters for a branched pipeline. The strength of the impedance-based approach for inverse transient analysis arises mainly from its feasibility to address different conservation conditions for pressure and discharge and for combining these conditions into a unified impedance connectivity condition.

Description: A successful water management scheme for irrigated crops requires an integrated approach, which accounts for water, soil, and crop management. SIMETAW# is a user friendly soil water balance model that assesses crop water use, irrigation requirements, and generates hypothetical irrigation schedules for a wide range of crops experiencing full or deficit irrigation. SIMETAW# calculates reference evapotranspiration (ET o ), and it computes potential crop evapotranspiration (ET c ), and the evapotranspiration of applied water (ET aw ), which is the amount of irrigation water needed to match losses from the effective soil root zone due to ET c that are not replaced by precipitation and other sources. Using input information on crop and soil characteristics and the distribution uniformity of infiltrated irrigation applications in full or deficit conditions, the model estimates the mean depth of infiltrated water (IW) into each quarter of the field. The impact of deficit irrigation on the actual crop evapotranspiration (ET a ) is computed separately for each of the four quarters of the cropped field. SIMETAW# simulation adjusts ET o estimates for projected future CO 2 concentration, and hence the model can assess climate change impacts on future irrigation demand allowing the user to propose adaptation strategies that potentially lead to a more sustainable water use. This paper discusses the SIMETAW# model and evaluates its performance on estimating ET c , ET a , and ET aw for three case studies.

Description: This paper seeks to contribute to the current debate about public versus private management of urban water supply services. The main purpose of urban water supply is to ensure the provision of a sufficient quantity of good quality water to users. This article examines water quality by using a subjective indicator: user satisfaction with tap water quality. The goal of the paper is to determine whether users perceive a difference in tap water quality supplied by public operators on the one hand, and by private-sector operators on the other. Data is sourced from a survey carried out in 64 Spanish cities. A number of different subjective determinants of water quality have been considered: the socio-economic characteristics of those surveyed, objective indicators of water quality, as well as environmental and economic factors of urban water services. Data analysis, using an ordered logit regression model, shows that when urban water services are in the hands of a private company, the quality of the tap water, as perceived by users, deteriorates.

Description: The globe is facing an increase in water demand associated with an increase in the world population especially in developing countries. The increasing population urges an additional agricultural land and irrigation water. Traditional system of irrigation water supplier is open canals which allow a high percentage of water dissipation and evaporation. This paper presents a new approach to evaluate design alternatives of Improved Field Irrigation Canals (IFIC) using Life Cycle Cost (LCC) methods. LCC is a methodology for calculating the total cost of a system from inception to disposal taking into account the time value of money. The main objective of this paper is using LCC to evaluate irrigation improvement canals to save water and increase agricultural production. Four methods such: i) Net Present Value (NPV); ii) Benefit/Cost ratio (BCR); iii) Internal Rate of Return (IRR), and iv) Pay Back Period (PBP) are used to compare between three IFIC design alternatives. These alternatives are i) pipeline with one pump at canal head, ii) pipeline with one pump at the head and one pump at the middle, and iii) lined open canal and compared to the reference case; i.e. open canal. Results show that the best economic alternative for IFIC is pipeline with one pump at the intake of the canal.

Description: The efficient utilization of hydropower resources play an important role in the economic sector of power systems, where the hydroelectric plants constitute a significant portion of the installed capacity. Determination of daily optimal hydroelectric generation scheduling is a crucial task in water resource management. By utilizing the limited water resource, the purpose of hydroelectric generation scheduling is to specify the amount of water releases from a reservoir in order to produce maximum power, while the various physical and operational constraints are satisfied. Hence, new forms of release policies namely, BSOPHP, CSOPHP, and SHPHP are proposed and tested in this research. These policies could only use in hydropower reservoir systems. Meanwhile, to determine the optimal operation of each policy, real coded genetic algorithm is applied as an optimization technique and maximizing the total power generation over the operational periods is chosen as an objective function. The developed models have been applied to the Cameron Highland hydropower system, Malaysia. The results declared that by using optimal release policies, the output of power generation is increased, while these policies also increase the stability of reservoir system. In order to compare the efficiency of these policies, some reservoir performance indices such as reliability, resilience, vulnerability, and sustainability are used. The results demonstrated that SHPHP policy had the highest performance among the tested release policies.

Description: This study proposes intelligent water resources allocation strategies for multiple users through hybrid artificial intelligence techniques implemented for reservoir operation optimization and water shortage rate estimation. A two-fold scheme is developed for (1) knowledge acquisition through searching input–output patterns of optimal reservoir operation by optimization methods and (2) the inference system through mapping the current input pattern to estimate the water shortage rate by artificial neural networks (ANNs). The Shihmen Reservoir in northern Taiwan is the study case. We first design nine possible water demand conditions by investigating the changes in historical water supply. With the nine designed conditions and 44-year historical 10-day reservoir inflow data collected during the growth season (3 months) of the first paddy crop, we first conduct the optimization search of reservoir operation by using the non-dominated sorting genetic algorithm-II (NSGA-II) in consideration of agricultural and public water demands simultaneously. The simulation method is used as a comparative model to the NSGA-II. Results demonstrate that the NSGA-II can suitably search the optimal water allocation series and obtain much lower seasonal water shortage rates than those of the simulation method. Then seasonal water shortage rates in response to future water demands for both sectors are estimated by using the adaptive network fuzzy inference system (ANFIS). The back-propagation neural network (BPNN) is adopted as a comparative model to the ANFIS. During model construction, future water demands, predicted monthly inflows (or seasonal inflow) of the reservoir in the next coming quarter and historical initial reservoir storages configure the input patterns while the optimal seasonal water shortage rates obtained from the NSGA-II serve as output targets (training targets) for both neural networks. Results indicate that the ANFIS and the BPNN models produce almost equally good performance in estimating water shortage rates, yet the ANFIS model produces even better stability. The reliability of the proposed scheme is further examined by scenario analysis. The scenario analysis indicates that an increase in public water demand or a decrease in agricultural water demand would bring more impacts of water supply on agricultural sectors than public sectors. Similarly, a bigger decrease in inflow amount would obviously bring more influence on agricultural sectors than public one. Consequently, given predicted inflow, decision makers can pre-experience the possible outcomes in response to competing water demands through the estimation models in order to determine adequate water supply as well as preparedness measures, if needed, for drought mitigation.

Description: The Muskingum model is a popular method for flood routing in river engineering. This model has several parameters, which should be estimated. Most of the techniques have applied to estimate these parameters to reduce the distance between observed flow and estimated flows. In this paper, for the first time, the parameters of a novel form of the nonlinear Muskingum model are estimated by the Particle Swarm Optimization (PSO) algorithm. The new Muskingum model, which have four parameters, is applied for three benchmark examples and one real case in Iran. The sum of the squared (SSQ) or absolute (SAD) deviations between the observed and estimated outflows was considered as objective functions. The results showed that although the new Muskingum model became more complex but this model by using PSO technique can improve the fit to observed flow especially in multiple-peak hydrographs.

Description: Estimation of suspended sediment loads ( SSL ) in rivers is an important issue in water resources management and planning. This study proposes a hybrid double feedforward neural network (HDFNN) model for daily SSL estimation, by combining fuzzy pattern-recognition and continuity equation into a structure of double neural networks. A comparison is performed between HDFNN, multi-layer feedforward neural network (MFNN), double parallel feedforward neural network (DPFNN) and hybrid feedforward neural network (HFNN) models. Based on a case study on the Muddy Creek in Montana of USA, it is found that the HDFNN model is strongly superior to the other three benchmarking models in terms of root mean squared error (RMSE) and Nash-Sutcliffe efficiency coefficient (NSEC). HDFNN model demonstrates the best generalization and estimation ability due to its configuration and capability of physically dealing with different inputs. The peak value of SSL is closely estimated by the HDFNN model as well. The performances of HDFNN model in low and medium loads are satisfactory when investigated by partitioning analysis. Thus, the HDFNN is appropriate for modeling the sediment transport process with nonlinear, fuzzy and time-varying characteristics. It explores a practical alternative for use and can be recommended as an efficient estimation model for SSL.

Description: River ecosystems are facing a diversity of threats in many parts of the world. To restore and preserve riverine environments, human societies have established water governance and management responses. However, the means by which a satisfactory environmental state can be achieved in light of different regional contexts is still poorly understood. This article explores whether or not good environmental performance can be achieved through water governance and management in combination with further context factors. To this end, we applied fuzzy set Qualitative Comparative Analysis to examine data on water governance, water management, and environmental performance from a recent international study together with context data on per capita income, corruption, hydro-climate, and use pressure from other datasets. Results demonstrate that the combination of polycentric governance, high per capita income, and low levels of corruption is sufficient for achieving good water management practice. However, a good environmental state in river basins seems to primarily depend upon the overall level of pressure from human use rather than the quality of water management. This demonstrates that water governance and management should be seen as part of a broader societal transformation towards sustainability that focusses on a reduction of pressures in river basins instead of mitigating their impacts.

Description: Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may be trapped in local optima as the population diversity is progressively reduced. This study proposes a computational strategy that operates several parallel populations to maintain the diversity of the candidate solutions. An improved version of the NSGA-II, called c-NSGA-II is implemented by incorporating multiple recombination operators. The parallel strategy is then coupled into the routine of the c-NSGA-II and applied to the operation of the Qingshitan reservoir (Southwest of China) which includes three eco-environmental and two social-economic objectives. Three metrics (convergence, diversity, and hyper volume index) are used for evaluating the optimization performances. The results show that the proposed parallel strategy significantly improves the solution quality in both convergence and diversity. Two characteristic schemes are identified for the operation of the Qingshitan reservoir for trade-off between the eco-environmental and social-economic objectives.

Description: In meteorology and engineering, the prediction of quantitative precipitation and streamflow during typhoon events is a vital research topic. In Southern Taiwan, typhoons often occur in the summer. The interaction between the typhoon circulation and southwesterly monsoon flow frequently transports abundant moisture into Southern Taiwan leading to the substantial pouring rains. This study proposes a rainfall-runoff prediction methodology for addressing the complicated inflow forecasts of southwest monsoon rainfall during typhoons in the upper Tsengwen River in Southern Taiwan. This paper is novel in that it incorporates various data types (reservoir inflows, watershed rainfalls, typhoon information, and ground-weather characteristics) that were applied as model inputs. The most frequently used support vector regressions were employed to construct the rainfall-runoff models on the basis of three designed data combination scenarios. Typhoons Kalmaegi (2008), Fung-wong (2008), Jangmi (2008), and Morakot (2009) were used as validation typhoons. The model cases, involving lead times of 1 h to 6 h, were evaluated. Six performance criteria were used in the three scenarios to highlight the scenario capable of identifying the optimal performance level. In addition, this study compared the error rates between accumulation observations and accumulation predictions. The results showed that Scenario 3, which considered typhoon information and ground-weather characteristics simultaneously, had superior watershed rainfall and runoff predictions to those of the other scenarios. Thus, this study demonstrated the feasibility of using the proposed methodology to increase the accuracy of rainfall-runoff predictions.

Description: Recent efforts to influence the efficiency and timing of urban indoor water use through education, technology, conservation, reuse, economic incentives, and regulatory mechanisms have enabled many North American cities to accommodate population growth and buffer impacts of drought. It is unlikely that this approach will be equally successful into the future because the source of conservation will shift from indoor to outdoor use. Outdoor water is climate sensitive, difficult to measure, hard to predict, linked to other components of complex and dynamic urban resource systems, imbued with behavioral and cultural dimensions, and implicated in societal conflicts about climate risk, modern lifestyles, social justice, and future growth. Outdoor water conservation is not a traditional management problem focused on the water sector, assuming a stationary climate, and set aside from public debate. Instead, outdoor water is an adaptation problem, involving complex and uncertain system dynamics, the need for cross-sector coordination, strategies for dealing with climatic uncertainty, and mechanisms for engaging stakeholders with differing goals. This paper makes the case for treating outdoor water as an adaptation problem and offers a six-point strategy for how cities can better prepare their water systems for the uncertainties of climate and societal change.

Description: This article presents a methodology for statistical downscaling using local polynomial regression for obtaining the future projections of rainfall in a catchment. Local polynomial regression offers a method to catch the nonlinearities in the input–output relationship compared to traditional regression by identifying the nearest neighbors of the predictor point for a specified band width. It fits a low degree polynomial model to the subset of the data at each point by weighted least squares. The local regression fit is complete when the regression function values are calculated for all the data points. A smooth curve through the data points is obtained by this method. Mean sea level pressure, geopotential height 500 mb, air temperature, relative humidity and wind speed are identified as the potential predictors for predicting the rainfall. Monthly data on the predictors for nine grid points around the study area are obtained from National Centre for Environmental Prediction (NCEP)/ National Centre for Atmospheric Research (NCAR) Re-analysis data. The model was applied to forecast the rainfall in the catchment of Idukky reservoir in Kerala, India. The model performance was compared with that of multiple linear regression and artificial neural network models. It is seen that the local polynomial regression model gives a better performance in forecasting the rainfall. The new methodology adopted is computationally simple, easy to implement and it captures the linear and non linear features in the data set preserving the dynamics of the atmosphere and the properties of the historical series.

Description: This study is aimed on successful modeling of Ajichay River Suspended Sediment Load (SSL) which is significant object in watershed planning and management. Therefore, a two-stage modeling strategy was proposed in order to handle spatio-temporal variation of SSL. At temporal stage, Support Vector Machine (SVM) was utilized for three stations located on the Ajichay River to find the non-linear relationship of SSL in time domain. Different input sets were examined for the SVM via sensitivity analysis. Results of temporal modeling stage were used in spatial modeling. In spatial modeling stage, firstly semi-variogram of monthly SSL data was calculated and then theoretical semi-variogram model was fitted to the empirical variogram. It was found that Gaussian model is the best fitted model for the study case. The obtained results of semi-variogram were imported into Geostatistic tool for spatial estimation of SSL in sites where there is not any measurement. Results of temporal modeling stage demonstrated that input data as combination of SSL and discharges at 1 month and 12 monthes ago employing RBF based SVM could lead to the best performance for each station. Spatial modeling performance was improved relatively using streamflow dataset. The obtained results show that the hybrid of SVM and Spatial statistics methods could predict and simulated SSL appropriately by enjoying unique features of both approaches.

Description: To overcome the shortcomings of the conventional variable fuzzy set assessment (VFSA) method in the dynamic water quality assessment, the functional data analysis (FDA) theory is introduced into VFSA method to develop a dynamic variable fuzzy set assessment (DVFSA) model. The procedure of DVFSA is: (1) generating continuous concentration curves through smoothing method, (2) calculating relative membership curves of indicators, (3) generating comprehensive relative membership curves, (4) making dynamic water quality assessment through calculating the ranking feature curve. DVFSA is the generalization of the conventional VFSA from discrete finite time points into continuous time domain through FDA method. DVFSA keeps the property of VFSA in fuzzy domain constructing and comprehensive classification recognizing; and absorbs the advantages of FDA in dealing with different sampling time and missing values, and representing the varying process of aquatic environment comprehensively and intuitively. Furthermore, DVFSA avoids the potential logical error by banning the least square optimization method in comprehensive relative membership generation. The dynamic water quality condition of Jiangdu hydro-junction in 2013 is assessed using DVFSA and the result shows that it belongs to classification “I” from January to April and “II” in other months. To further improve the water quality condition of Jiangdu hydro-junction, it is suggested to strengthen the environment protection in Lixiahe region and New Tongyang Canal.

Description: The contamination of water resources by non-point pollution of agricultural origin, primarily nitrates and pesticides, has become a major issue in water policies. In France, the national consultation of the Grenelle of the Environment in 2007 led to project approaches, aimed at protecting Water Catchment Areas (WCA). Based on the implementation of preventive management, WCA projects aim at negotiating changes in farming practices in these zones, including conversion to organic farming. But difficulties occur in creating links between WCA and organic farming in these projects. Beyond the conflicts between different stakeholders often put forward, we suggest adopting a geographical approach on the interactions between WCA and the action territories of three types of stakeholders. A combination of statistical, GIS-processing and comprehensive methods was used to study the cross-referencing between WCA, defined according to hydrogeological bases, and action territories of farmers, collection companies and local authorities. The results show how the demarcation of the water catchment areas on biophysical bases struggles to be effective for action, in particular for the agricultural question and the development of organic farming. In taking account of organisational levels and spatial patterns, the article illustrates the discrepancy between WCA and action territories of farmers, collectors and local authorities. These results call for better integration of the concept of territory project in WCA projects, allowing interests to be combined and reflection to be directed towards local governance in the field of water quality.

Description: An explicit second-order finite-difference computer model was developed and optimized for solution of the Shallow Water Equations. The model was applied to the Feather River below the Oroville Dam and Thermalito Afterbay near Gridley, California. Two versions of the computer model were constructed to run on either Central Processing Units or Graphical Processing Units, utilizing Fortran, C, C++, and the NVIDIA Compute Unified Device Architecture (CUDA) parallel computing platform. The underlying algorithm utilizes a structured grid and is capable of handling the wetting and drying of cells. It was developed with view to maximizing stability while maintaining accuracy, and allowing for flexibility of the computational domain. Comparisons with analytical and observed results showed the proposed methodology to be robust, accurate, and efficient. The models were applied to a section of the Feather River where observations of flow depths and volumetric flow rates are available for multiple flood events. The domain surface was partially developed using high-resolution photogrammetric data obtained through use of unmanned aerial vehicles. Runtimes and results were compared to the United States Bureau of Reclamations’ implicit finite-volume numerical method and with field observation with generally good correspondence.

Description: The problem of drought probability has been investigated by several authors, who have usually analysed droughts using various drought indices such as the Standard Precipitation Index. Various aspects of time series of such indices (intensity, severity and duration) were investigated by several authors using a copula method. Because such analysis is based on only one basic climatic variable, this paper addresses a different approach, i.e., joint analysis of the severity and duration of the most demanding potential annual irrigation periods by a bivariate copula method. Characteristics of these periods are derived from both temperature and precipitation. Maximum annual duration of the potential irrigation period and corresponding rainfall deficit were inferred from these basic variables as inputs to two-dimensional probability analysis by the copula method, because this offers more direct answers to questions of irrigation needs. Results indicate the suitability of the proposed method for analysis of irrigation needs, with greater benefits than the typical one-dimensional analysis of individual climatic variables. A case study for testing the method was done for southwestern Slovakia, for which the frequency of irrigation needs was estimated. Example results indicate that every second year, a one-month period can be expected in which temperatures are 〉25 ∘ C and there is a moisture deficit of ∼30 mm. Even more significant periods of drought can be expected, for example, with a 5 or 10-year return period. These phenomena significantly damage agriculture yields, so requirements for irrigation structures in the study area are indicated by the proposed method.

Description: Strengthening the planning of hydrological resources to optimize the use of water in agriculture is a key adaptation measure of the Chilean agricultural sector to cope with future climate change. To address this challenge, decision-makers call for tools capable of representing farmers’ behaviours under the likely stresses generated by future climate conditions. In this context, of special concern are the effects of water variability on small-scale farmers, who commonly operate with narrow profit margins and who lack access to financial resources and technological knowledge. This paper sheds light on the economic impacts of changes in water availability on small-scale agriculture. We provide a hydro-economic modelling framework that captures the socio-economic effects of water shocks on smallholders in the Vergara River Basin, Chile. This approach links a farm risk-based economic optimization model to a hydrologic simulation model adjusted for the basin. Our results indicate that at the aggregated level, there will be minor economic impacts of climate change on the basin’s small-scale agriculture, with small decreases in both expected utility and wealth. However, large differences in the economic impacts of wealthy and poor small-scale farmers are found. Changes in water availability, reduce the options of land reallocation to increase farmer’s expected utility, being the poor small-scale farmers the most negatively affected.

Description: Remote Sensing (RS) and Geographical Information System (GIS) play a crucial role to understand the division of groundwater, an important resource of water supply all over the world. In this present study, groundwater potential and recharge zone maps, are delineated for Loni and Morahi watersheds, Unnao and Rae Bareli district, Uttar Pradesh, India using RS, GIS and Multi-Criteria Decision Making (MCDM) techniques. The Satty’s Analytical Hierarchical Process (AHP) is used as a MCDM technique to normalise the weights of various thematic layers and their classes for delineating the groundwater potential and recharge zone maps. Thematic layers were integrated using weighted overlay in a GIS environment to generate groundwater potential and recharge zone maps. The output potential map is further classified into five zones on the basis of their histograms, viz., ‘very poor’, ‘poor’, ‘good’, ‘very good’ and ‘excellent’. The area falling in the excellent zone is about 150.93 km 2 (7.06 % of the total study area), which covers a major portion of the Ganga river. It discriminates the areas where the terrain is suitable for groundwater storage. However, the area falling in the very poor zone is about 372.03 km 2 (17.42 % of the total study area) and covers the Loni river south-eastern portion and some areas in north-eastern sides. Groundwater recharge map is classified into four zones namely; ‘most suitable’, ‘moderately suitable’, ‘poorly suitable’ and ‘not suitable’. Yield data of the 40 pumping wells are used to verify the groundwater potential zone map, and the results were found to be good.

Description: Water distribution in transboundary rivers is a complex issue since it involves a number of environmental, socio-economic, technical, and national security factors. Based on the analysis of the characteristics of water distribution in transboundary rivers, this paper develops a generalized uncooperative planar game theory model to aid in analyzing transboundary river water distribution scenarios, in which the concept of diplomatic cost is proposed originally. The existence of a Nash equilibrium solution has been proved in terms of the model’s Nikaido–Isoda function. Then, the optimal water quantity exploited from the transboundary river, and that obtained in other ways are solved with the first-order optimality conditions. A proper method for determining the ratio of exploited river water to the whole used water is proposed. Finally, a case study is used to analyze the influences of the Nash equilibrium solution’s parameters on the solution itself.

Description: In this study, a new framework was developed for the estimation of groundwater recharge based on a hybrid method. In this regard, the homogeneous recharge zones were determined by the analytical hierarchy process (AHP). The recharge rates in these zones were calculated using the Thornthwaite and Mather’s method. These zones and their recharge rates were entered into the MODFLOW model. Next, the modeling processes, modification of recharge, and calibration of empirical models were interactively continued in the MODFLOW. This way, one of the most important disadvantages of conventional empirical models, i.e., ignoring the physical properties of the aquifer, was resolved by considering the main parameters such as soil properties, unsaturated thickness, land cover, irrigation, and precipitation in the resulting nonlinear equations. The low root mean square error values (less than 5.2) for all equations and high values of the coefficient of determinations indicated the accuracy and reliability of the models. The results of this hybrid method were a series of independent, cost-effective, rapid, and simple to use empirical equations for recharge estimation. As an example for the application of this method, the effects of climate change on groundwater recharge were evaluated in the study area. The obtained results showed that climate change would reduce the recharge rates of the homogeneous zones differently. Moreover, the recharge rate had a general decreasing trend in all regions. Overall, the total annual recharge rate would decrease in the plain. This reduction, especially in the west of the plain which is one of the most important sources of recharge supply, is considerable and will turn the entire plain vulnerable. In general, little reduction in rainfall or increase in temperature would have significant effects on groundwater recharge in the region. Therefore, due to the high dependence of this plain on groundwater resources, special planning is required for the exploitation of groundwater resources in the region.

Description: A nowcast and forecast system for providing real-time water information of a River Chain of Lakes (RCL) is developed. The system infrastructure comprises a web portal to retrieve and display observations that are used to drive models under a high performance computing server. Water level and flow discharge information are obtained from a suite of models that be directly simulate the RCL system. A new data assimilation technique based upon flow routing algorithm and nested-mesh domain reduction is developed to update the Manning’s roughness. It is demonstrated that the INFOS can reliably and effectively model real-time reverse flows due to sustained wind forcings or tranisent seiches, and flow choking due to channel constriction. Applications of the developed system are illustrated. Specifically water level planning scenarios provide a quantitative measure for lake management to reduce floods under extreme rainfall events. Alternative management philosophies to minimize exceeding the water level orders are evaluated. Overall, the Integrated Nowcast and Forecast Operation System (INFOS) provides reliable and timely water information for the RCL for sharing information to the community, planning for water use and delivery, and management of the Yahara RCL.

Description: To present an alternative simple equation for reference evapotranspiration ( ET o ) estimation, the symbolic regression (SR) method was applied to establish equations with the same inputs to simple Hargreaves-Samani (HS) equation in arid China. For most of the equations derived by SR method for each station, their performance increased with an increase in the equation complex index (CI). The most precise equation performed well although it was always complex and greatly varied in form. On the other hand, the simplest one was uniform in equation structure and performed slightly better than the HS equation for all the five stations, and sometimes better than the local calibrated HS equation. A trade-off equation was selected with almost the same equation form for all the five stations and low CI index. The site-specific trade-off equation performed better than the simplest one and the locally calibrated HS equation. Then parameters in the trade-off equation were unified for all the five stations, it did not perform as good as the site-specific one, but performed better than the HS equation and unified local calibrated HS equation. Thus, the SR method is suitable to determine both the site-specific and the unified equation among stations for daily ET o calculation in arid regions.