ALBERT

Description: Abstract As drought phenomenon involves diverse natural and human‐made processes in hydrologic cycles, it is necessary to track a process‐specific variable for efficient drought risk management. In this study, we employed a state‐of‐the‐art formulation of the generalized complementary relationship (GCR) to estimate terrestrial evapotranspiration (ET). The GCR ET estimates were used to assess historical droughts over the contiguous United States (CONUS) in relation to long‐term natural fluctuations. Results showed that the GCR provided strong performance in reproducing water‐balance ET estimates and correlations to the El‐Niño Southern Oscillation, when compared to observation‐driven estimates and land surface models (LSMs). The GCR yielded better performance than LSMs even with estimated radiation inputs and no wind speed variations for 1982–2011. The Standardized Evapotranspiration Deficit Index (SEDI) based on the GCR provided a consistent drought assessment with precipitation‐based drought identification and remotely‐sensed vegetation conditions. The SEDI seems to capture the heat‐wave‐driven flash drought together with water‐deficit‐driven droughts. In the CONUS, the La Niña‐like conditions were likely to trigger extensive vegetation droughts with extreme severity. This study found the three long‐term environmental factors that affect the general trend of ET deficits over the CONUS, which are the Atlantic Multi‐decadal Oscillation, the mean air temperature, and the Pacific Decadal Oscillation. Especially, the Atlantic Oscillation seems to be the most significant predictor that could explain the long‐term variation of vegetation droughts over the CONUS. This study highlights that the GCR‐based SEDI could be useful for monitoring and assessment of drought risks at a continental scale.

Description: Abstract Depressional wetlands are dominant features in many low‐gradient landscapes, where they provide water storage and exchange. Typical basin morphology enables water storage during drier periods, when surface flow paths are disconnected and exchange is limited to slower groundwater flow paths. Under wetter conditions, wetland stage can exceed surface connection thresholds, activating surface flow paths to downstream waters. Empirical methods are needed to quantify these dynamics and thus to assess their role in landscape hydrology and associated functions. We developed a new water budget‐based approach to enumerate connectivity thresholds and flows from stage measurements. We propose that this approach, termed Connectivity and Flow from Stage (CFS), has broad applicability across wetlandscapes. We applied the CFS method in the Big Cypress National Preserve, where we hypothesized that surface connectivity episodes control water and solute flux, with consequences for exported carbonate weathering products and thus for karst landform evolution. Across five study wetlands, this analysis detected surface connectivity thresholds and assessed temporal flow dynamics. Imputed connectivity thresholds were clear from stage‐dependent net flow dynamics and aligned well with LiDAR‐derived thresholds. Water export occurred overwhelmingly when stage exceeded these thresholds, indicating that water and solute export from these wetlands is dominated by periods of enhanced landscape connectivity. Notably, the presented CFS method can quantify wetland connectivity thresholds from stage data, even without supporting geomorphic information. This approach is useful for understanding hydrologic controls on biogeomorphic evolution in this particular karst landscape, and more broadly for inferring wetland connectivity patterns and magnitudes in other wetlandscape settings.

Description: Abstract Evaporation ‐ a key process for water exchange between soil and atmosphere ‐ is controlled by internal water fluxes and surface vapor fluxes. Recent studies demonstrated that the dynamics of the water flow in corners determine the time behavior of the evaporation rate. The internal water flux of the porous media is often described by capillary flow assuming complete wetting. Particularly, the crucial influence of partial wetting, i.e. the non‐linear contact‐angle dependency of the capillary flow has been neglected so far. The focus of the paper is to demonstrate that SiO2‐surfaces can exhibit contact angles of about 40°. This reduces the internal capillary flow by one order of magnitude compared to complete wetting. First, we derived the contact angle by inverse modelling. We conducted a series of evaporation experiments in a 2D‐square lattice microstructure connected by lognormal distributed throats. We used an explicit analytical power‐series solution of the single‐square‐capillary (SSC)‐model. A contact angle of 38° ± 1° was derived. Second, we directly measured the contact angle of the Si‐SiO2‐wafer using the Drop Shape Analyzer Krüss 100 and obtained an averaged contact angle of 42° ± 2°. The results support the SSC‐model as an appropriate model for the description of the evaporation process in an ideal square capillary.

Description: Abstract The external drivers and internal controls of groundwater flow in the thawed “active layer” above permafrost are poorly constrained because they are dynamic and spatially variable. Understanding these controls is critical because groundwater can supply solutes such as dissolved organic matter to surface water bodies. We calculated steady‐state three‐dimensional supra‐permafrost groundwater flow through the active layer using measurements of aquifer geometry, saturated thickness, and hydraulic properties collected from two major landscape types over time within a first‐order arctic watershed. The depth position and thickness of the saturated zone is the dominant control of groundwater flow variability between sites and during different times of year. The effect of water table depth on groundwater flow dwarfs the effect of thaw depth. In landscapes with low land‐surface slopes (2‐4%), a combination of higher water tables and thicker, permeable peat deposits cause relatively constant groundwater flows between the early and late thawed season. Landscapes with larger land‐surface slopes (4‐10%) have both deeper water tables and thinner peat deposits; here, the commonly‐observed permeability decrease with depth is more pronounced than in flatter areas, and groundwater flows decrease significantly between early and late summer as the water table drops. Groundwater flows are also affected by microtopographic features that retain groundwater that could otherwise be released as the active layer deepens. The dominant sources of groundwater, and thus dissolved organic matter, are likely wet, flatter regions with thick organic layers. This finding informs fluid flow and solute transport dynamics for the present and future arctic.

Description: Abstract Reservoirs along rivers have the potential to act as nutrient sinks (e.g., denitrification and sedimentation) or sources (e.g., decomposition and redox changes), potentially reducing or enhancing nutrient loads downstream. This study investigated the spatial and temporal variability of water and lakebed sediment chemistry for an agricultural reservoir, Carlyle Lake (Illinois, U.S.), to assess the role of sediments as nutrient sinks or sources. Samples were collected across the reservoir over a 2‐year period. We measured N‐ and P‐species in water at the sediment‐water interface, in sediment porewaters, and loosely bound to sediment exchange sites. Total N, total P, total C, organic matter, Fe, Mn, and grain size were measured in bulk sediments. We observed a strong gradient in sedimentary total N, total P, total C, organic matter, and metals along the reservoir, with the lowest concentrations at the river mouth and the highest concentrations near the dam. Additionally, we did a long‐term nutrient mass balance using historical water quality data for streams entering and exiting the reservoir and the reservoir itself. Mass balance calculations showed that Carlyle Lake, on average, removed 2,738 Mg N/year and released 121 Mg P/year over the multidecadal observation period. While N was consistently removed from the system over time, P was initially stored in, but later released from, the reservoir. The subsequent release of legacy P from the reservoir led to higher outgoing, compared with incoming, P loads. Thus, reservoirs in intensively managed landscapes can act as sinks for N but sources for P over decadal timescales.

Description: Abstract Groundwater‐level changes after earthquakes provide insight into changes in hydrogeological properties such as permeability and pore pressure. Quantifying such changes, both their location and magnitude, is usually hindered by limited data. Using extensive high‐resolution water‐level monitoring records, we provide direct evidence of significant groundwater drawdown (4.74‐m maximum) over a 160‐km2 area along crustal ruptures after the Mw 7.0, 2016, Kumamoto earthquake. Approximately 106 m3 of water disappeared within 35 min after the main shock. The loss of water was not caused by static‐strain driven pore‐pressure decrease nor by releasing of water through structural pathways, but most likely by water transfer downwards through open cracks. Such changes may impact the security of water resources, the safety of underground waste repositories, and contaminant transport in seismically active areas.

Description: Abstract Catchment storage sustains ecologically important low flows in headwater systems. Understanding the factors controlling storage is essential in analysis of catchment vulnerability to global change. We calculated catchment storage and storage sensitivity of streamflow for 61 boreal headwater catchments in Finland. We also explored the connection between computed storage indices and low flow conditions. The relationships between selected climate, snow, and catchment characteristics and calculated storage properties and low flows were investigated, in order to assess the importance of different factors that render catchments vulnerable to climate and environmental change. We found that the most sensitive areas to climate change were located in the southern boreal coastal zone, with fine‐grained soils and agricultural areas. In contrast, catchments in the middle and northern boreal zone, with till and peatland soils and higher snow water equivalent values, were less sensitive under current conditions. In addition, we found a threshold at a snow to precipitation ratio of 0.35. Above that threshold, summer low flows were generally sensitive to changes in snow conditions, whereas below that threshold catchment characteristics gained importance and the sensitivity was more directly related to changes in temperature and timing of rainfall. These findings suggest that a warming climate will have pronounced impacts on hydrology and catchment sensitivity related to snow quantity and snow cover duration in certain snow to precipitation ratio zones. Moreover, land use activities had an impact on storage properties in agricultural and drained peatland areas, resulting in a negative effect on low flows.

Description: Abstract The one‐dimensional advection dispersion equation (1D ADE) is commonly used in practice to simulate pollutant transport processes for assessment and improvement of water quality conditions in rivers. Various studies have shown that the longitudinal dispersion coefficient used within the 1D ADE is influenced by a range of hydraulic and geomorphological conditions. This study aims to quantify the impact and importance of the parameter uncertainty associated with the longitudinal dispersion coefficient on modeled pollutant time‐concentration profiles and its implications for meeting compliance with water quality regulations. Six regression equations for estimating longitudinal dispersion coefficients are evaluated, and commonly used evaluation criteria were assessed for their suitability. A statistical evaluation of the regression equations based on their original calibration data sets resulted in percent bias (PBIAS) values between −47.01% and 20.78%. For a case study, uncertainty associated with the longitudinal dispersion coefficient was propagated to time‐concentration profiles using 1D ADE and Monte Carlo simulations, and 75% confidence interval bands of the pollutant concentration versus time profiles were derived. For two studied equations, the measured peak concentration values were above the simulated 87.5th percentile, and for the other four equations it was close to the 87.5th percentile. Subsequent uncertainty propagation analysis of four diverse rivers show the potential considerable impact on concentration‐duration‐frequency‐based water quality studies, with 1D ADE modeling producing predictions of quality standard compliance which varied over hundreds of kilometers.

Description: Abstract In nature, aquatic vegetation is one of the important factors—along with hydraulic characteristics and geometric configuration—determining the dispersion of scalars. Previous research has studied the effects of vegetation on longitudinal dispersion, varying plant population with uniform arrangement. However, since vegetation grows more often in clumped and heterogeneous rather than uniform patterns, the present work investigates the effects of the vegetation arrangement on the flows characteristics such as longitudinal dispersion, mean velocities, and drag coefficients. Several types of vegetation arrangement are described with the isometric and allometric concept and quantified with the standardized Morisita index. Laboratory experiments were performed to investigate variations of hydraulic parameters and longitudinal dispersion coefficients according to vegetation arrangements, which were quantified with the standardized Morisita index. The hydraulic parameters of mean velocity, turbulent kinetic energy, and drag depend on the vegetation arrangements, and in particular, the longitudinal dispersion coefficient varies with these arrangements by a factor of 4 or more.

Description: Abstract We employ direct numerical simulations in order to analyze the role of double‐diffusive salt fingering in halite precipitation from hypersaline lakes. Guided by field observations from the Dead Sea, which represents the only modern deep stratified lake that precipitates halite under hydrological crisis, we consider a saturated layer of warm, salty brine (epilimnion) overlying a layer of colder, less salty brine (hypolimnion) that is also saturated. The double‐diffusive instability originating in the metalimnion gives rise to an asymmetrical pattern of less salty ascending fingers, accompanied by descending salt fingers that lose heat as they propagate through the metalimnion. The net result is a strong, downward salinity flux that leads to the undersaturation of the epilimnion, while the hypolimnion becomes oversaturated and precipitates halite. These interfacial processes within deep, hypersaline water columns in warm and dry regions suggest a potential route toward the formation of thick halite layers found in the geological record.

Description: Abstract Boreal forest regions are a focal point for investigations of coupled water and biogeochemical fluxes in response to wildfire disturbances, climate warming, and permafrost thaw. Soil hydraulic, physical, and thermal property measurements for mineral soils in permafrost regions are limited, despite substantial influences on cryohydrogeologic model results. This work expands mineral soil property quantification in cold regions through soil characterization from the discontinuous permafrost zone of interior Alaska, USA. Values extend beyond the range of prior measurement magnitudes in analogous regions, highlighting the importance of this data set. Rocky and silty upland soil landscape classifications and wildfire disturbance provided guiding frameworks for the sampling and analysis for potential implications for the hydrologic response to thawing permafrost. Bulk density (ρb), soil organic matter, soil‐particle size distributions (sand, silt, and gravel fractions), and soil hydraulic properties of van Genuchten parameters alpha and N had moderate evidence of differences between silty and rocky classifications. Burned and unburned sites had only moderate evidence of differences for silt fraction. Field‐saturated hydraulic conductivity (Kfs) was more variable at burned sites compared to unburned sites, which corresponded to observations of greater rooting depths at burned sites and observations of root paths in soil cores for Kfs measurement. Soil thermal properties suggested that gravel content may reduce the accuracy of commonly used estimation methods for thermal conductivity. This work provides soil parameter constraints necessary for hypothesis testing and site‐specific prediction with cryohydrogeologic models to examine controls on active layer and permafrost dynamics in upland boreal forests.

Description: Abstract Rivers and their hyporheic zones play an important role in nutrient cycling. The fate of dissolved inorganic nitrogen is governed by reactions that occur in the water column and streambed sediments. Sediments are heterogeneous both in term of physical (e.g., hydraulic conductivity) and chemical (e.g., organic carbon content) properties, which influence water residence times and biogeochemical reactions. Yet few modeling studies have explored the effects of both physical and chemical heterogeneity on nutrient transport in the hyporheic zone. In this study, we simulated hyporheic exchange in physically and chemically heterogeneous sediments with binary distributions of sand and silt in a low‐gradient meandering river. We analyzed the impact of different silt/sand patterns on dissolved organic carbon, oxygen, nitrate, and ammonium. Our results show that streambeds with a higher volume proportion of silt exhibit lower hyporheic exchange rates but more efficient nitrate removal along flow paths compared to predominantly sandy streambeds. The implication is that hyporheic zones with a mixture of inorganic sands and organic silts have a high capacity to remove nitrate, despite their moderate permeabilities.

Description: Abstract Land use change and agricultural intensification have increased food production but at the cost of polluting surface and groundwater. Best management practices implemented to improve water quality have met with limited success. Such lack of success is increasingly attributed to legacy nutrient stores in the subsurface that may act as sources after reduction of external inputs. However, current water‐quality models lack a framework to capture these legacy effects. Here we have modified the SWAT (Soil Water Assessment Tool) model to capture the effects of nitrogen (N) legacies on water quality under multiple land‐management scenarios. Our new SWAT‐LAG model includes (1) a modified carbon‐nitrogen cycling module to capture the dynamics of soil N accumulation, and (2) a groundwater travel time distribution module to capture a range of subsurface travel times. Using a 502‐km2 Iowa watershed as a case study, we found that between 1950 and 2016, 25% of the total watershed N surplus (N Deposition + Fertilizer + Manure + N Fixation − Crop N uptake) had accumulated within the root zone, 14% had accumulated in groundwater, while 27% was lost as riverine output, and 34% was denitrified. In future scenarios, a 100% reduction in fertilizer application led to a 79% reduction in stream N load, but the SWAT‐LAG results suggest that it would take 84 years to achieve this reduction, in contrast to the 2 years predicted in the original SWAT model. The framework proposed here constitutes a first step toward modifying a widely used modeling approach to assess the effects of legacy N on the time required to achieve water‐quality goals.

Description: Abstract Stormwater ponds can serve as retention hotspots for phosphorus (P) moving out of the urban environment. This retention may be reduced by P speciation that reduces the bioavailability of P to primary producers and alters its mobility in sediments. Here we examined the mobility and fate of dissolved P in urban stormwater ponds with a set of complementary field measurements and short‐term laboratory and field experiments. We measured the types and amount of P in water column and sediments of urban stormwater ponds. We further assessed the mobility of different P types in pond sediments in the field and rates of P release from sediment cores maintained under laboratory conditions. Finally, we assessed P uptake rates by pond algal communities using short‐term bioassay experiments. We found that dissolved organic P was highly prevalent in urban pond water and sediments and that this type of P was mobile within sediments and could be released under high or low O2 conditions. We also found highly variable P demand by algae among stormwater ponds and that algal growth responses to P was correlated to water column N:P ratios. Altogether, our results indicate an important role for organic phosphorus cycling in urban stormwater ponds, which likely constrains the overall retention efficiency in these aquatic ecosystems.

Description: Abstract Flow prediction in ungauged catchments is a major unresolved challenge in scientific and engineering hydrology. This study attacks the prediction in ungauged catchment problem by exploiting advances in flow index selection and regionalization in Bayesian inference and by developing new statistical tests of model performance in ungauged catchments. First, an extensive set of available flow indices is reduced using principal component (PC) analysis to a compact orthogonal set of “flow index PCs.” These flow index PCs are regionalized under minimal assumptions using random forests regression augmented with a residual error model and used to condition hydrological model parameters using a Bayesian scheme. Second, “adequacy” tests are proposed to evaluate a priori the hydrological and regionalization model performance in the space of flow index PCs. The proposed regionalization approach is applied to 92 northern Spain catchments, with 16 catchments treated as ungauged. It is shown that (1) a small number of PCs capture approximately 87% of variability in the flow indices and (2) adequacy tests with respect to regionalized information are indicative of (but do not guarantee) the ability of a hydrological model to predict flow time series and are hence proposed as a prerequisite for flow prediction in ungauged catchments. The adequacy tests identify the regionalization of flow index PCs as adequate in 12 of 16 catchments but the hydrological model as adequate in only 1 of 16 catchments. Hence, a focus on improving hydrological model structure and input data (the effects of which are not disaggregated in this work) is recommended.

Description: Abstract We develop and test algorithms for rapidly and consistently analyzing water quality profile data such as temperature and fluorescence that are used to identify lake thermostratification and deep chlorophyll layers (DCL). Currently, the processing of profile data and identification of key features are manual and subjective, and thus, the results are not comparable from one sampling event to another. In this study, we develop a method to approximate vertical temperature profiles with linear segments using a piecewise linear representation algorithm, from which stratification patterns can be extracted. We also propose an automated peak detection algorithm to identify the location and magnitude of DCL. The algorithms are applied to water quality profile data collected by the United States Environmental Protection Agency Great Lakes National Program Office, which conducts annual depth profiling using conductivity, temperature, depth profilers at fixed locations in the Great Lakes. The algorithms generate similar results to human judgments, with some outliers that show expert errors, algorithm limitations, and ambiguities in defining layers. We also show how the algorithms can analyze the shape of temperature and fluorescence profiles to detect unusual patterns. Lake Superior is used as a case study to reveal spatial and temporal trends of the thermocline, DCL, and the heat storage change from spring to summer. The results reveal that more heat was stored in the eastern basin of the lake. The methods proposed here will help take full advantage of historical depth profiling data and benefit future sampling processes by providing a consistent method.

Description: No abstract is available for this article.

Description: Abstract Agricultural production is accompanied by a large amount of water consumption, nonpoint source pollution, and greenhouse gas emissions. However, the comprehensive and quantitative analysis of associated impacts on regional water, the environment, and the economy caused by variations in agricultural distribution is insufficient. This paper evaluates the evolution of grain production distribution and its effects on water resources, the economy, and the environment in China by using virtual water theory. The results show that the grain production area located in northern China is characterized by scarce water resources and a less developed economy. Due to the imbalance between grain supply and demand, virtual water embedded in grain will transfer among regions. These flows have formed a pattern where virtual water transfers from the water‐scarce northern region to the water‐rich southern region, increasing from 72.99 Gm3 in 1997 to 124.64 Gm3 in 2014. Evolution of grain production distribution changes the spatial pattern of grain production and consumption, and it exacerbates water resource pressure, the gray water footprint, and greenhouse gas emissions in the area that exports grain virtual water. The gray water footprint and carbon emissions in the grain export area increased by 10.66% and 31.06% during the study period, respectively. Meanwhile, the distribution of regional grain production influences the allocation of water resources in agriculture and other industries. Due to the difference between the economic benefits created by industry and agriculture, grain virtual water flow will have effects on the regional economic development.

Description: Abstract Biofilm‐induced dynamic evolution of streambed permeability commonly concurs with the transition from connection to disconnection between surface water and groundwater in arid regions. However, in most previous studies, static streambeds were assumed to examine the evolution of disconnection, or despite dynamic streambeds being considered, the feedbacks between nutrients transport and microbial growth were ignored. In this study, we developed an innovative coupled variably saturated flow, microbial growth, biogeochemical reactions, and bioclogging model. We applied this model to investigate the feedbacks between nutrients transport and microbial growth and their controls on infiltration evolution. Our results showed that a new clogging layer can naturally develop due to these feedbacks and does not require prior clogging. The development of the new clogging layer promotes the occurrence of disconnection. These results illustrate that as bioclogging is a dominant process, previous static disconnection conditions cannot be used as criteria to predict whether disconnection can occur in a stream‐aquifer system. Furthermore, different from the previous assumption of constant specific microbial growth rates, biomass growth, and streambed permeability evolution are self‐limiting. Accordingly, due to initial low growth rate, infiltration increases when the water table declines, and it then decreases and reaches a minimum while a stable biofilm is developed. These trends coincide with the infiltration variations reported in previous field investigations. After reaching the minimum, infiltration increases again with decline of the water table until achieving a constant at the moment of disconnection. This stage was missing in previous studies because constant specific growth rates were assumed.

Description: Abstract The footprint of catchment properties on water flow is reflected into hydrological signals, such as stream discharge. Here we demonstrate that it is possible to constrain catchment properties from the spectral analysis of hydrological signals but only when an appropriate transfer function (TF) is used for interpretation. We show that the appropriate theoretical TF, newly derived, is the only one to robustly describe a large diversity of experimental TFs that could be encountered in nature, because it entails the role of diffuse overflow and flow through the vadose zone, which have never been considered in spectral approaches before. The properties that may be estimated are the characteristic time scales of transfer in each compartment (surface, vadose zone, and aquifer) and the flow partitioning between surface and subsurface. We validate our approach by comparing the new and previous theoretical TFs to experimental TFs generated by a physically based distributed hydrological model, for a wide range of properties. The results confirm that without the use of the new TF, the interpretation of observed spectra may often lead to severe misestimations of catchment properties. The potential of the new TF to constrain catchment characteristics is exemplified by analyzing real hydrological signals from two watersheds with distinct behaviors. We finally discuss the broad implications of our findings and how they may contribute to a variety of topics in hydrology, thereby opening the way to a more widespread and robust use of spectral analysis to describe hydrosystems from effective rainfall, river discharge, and piezometric data.

Description: Abstract Identification of a groundwater contaminant source simultaneously with the hydraulic conductivity in highly heterogeneous media often results in a high‐dimensional inverse problem. In this study, a deep autoregressive neural network‐based surrogate method is developed for the forward model to allow us to solve efficiently such high‐dimensional inverse problems. The surrogate is trained using limited evaluations of the forward model. Since the relationship between the time‐varying inputs and outputs of the forward transport model is complex, we propose an autoregressive strategy, which treats the output at the previous time step as input to the network for predicting the output at the current time step. We employ a dense convolutional encoder‐decoder network architecture in which the high‐dimensional input and output fields of the model are treated as images to leverage the robust capability of convolutional networks in image‐like data processing. An iterative local updating ensemble smoother algorithm is used as the inversion framework. The proposed method is evaluated using a synthetic contaminant source identification problem with 686 uncertain input parameters. Results indicate that, with relatively limited training data, the deep autoregressive neural network consisting of 27 convolutional layers is capable of providing an accurate approximation for the high‐dimensional model input‐output relationship. The autoregressive strategy substantially improves the network's accuracy and computational efficiency. The application of the surrogate‐based iterative local updating ensemble smoother in solving the inverse problem shows that it can achieve accurate inversion results and predictive uncertainty estimates.

Description: Abstract For numerous hydrological applications, information on snow water equivalent (SWE) and snow liquid water content (LWC) are fundamental. In situ data are much needed for the validation of model and remote sensing products; however, they are often scarce, invasive, expensive, or labor‐intense. We developed a novel nondestructive approach based on Global Positioning System (GPS) signals to derive SWE, snow height (HS), and LWC simultaneously using one sensor setup only. We installed two low‐cost GPS sensors at the high‐alpine site Weissfluhjoch (Switzerland) and processed data for three entire winter seasons between October 2015 and July 2018. One antenna was mounted on a pole, being permanently snow‐free; the other one was placed on the ground and hence seasonally covered by snow. While SWE can be derived by exploiting GPS carrier phases for dry‐snow conditions, the GPS signals are increasingly delayed and attenuated under wet snow. Therefore, we combined carrier phase and signal strength information, dielectric models, and simple snow densification approaches to jointly derive SWE, HS, and LWC. The agreement with the validation measurements was very good, even for large values of SWE (〉1,000 mm) and HS (〉 3 m). Regarding SWE, the agreement (root‐mean‐square error (RMSE); coefficient of determination (R2)) for dry snow (41 mm; 0.99) was very high and slightly better than for wet snow (73 mm; 0.93). Regarding HS, the agreement was even better and almost equally good for dry (0.13 m; 0.98) and wet snow (0.14 m; 0.95). The approach presented is suited to establish sensor networks that may improve the spatial and temporal resolution of snow data in remote areas.

Description: Abstract The knowledge of the annual cycle of rainfall is of primary concern for many socioeconomic activities such as agricultural planning, electricity generation, and flood and other disaster management. The annual cycle of rainfall in Colombia has been studied so far using monthly or quarterly information, identifying zones with the unimodal regime (one wet season and one dry season) over the Caribbean, the Amazon, and the Pacific regions and zones with the bimodal regime (two wet and two dry seasons) in the Andes. This paper explores the annual rainfall cycle in Colombia on a daily basis using historical records of 1,706 rain gauges and the Climate Hazards Group Infrared Precipitation with Station data precipitation data set. We found four types of annual precipitation regimes: unimodal, bimodal, mixed, and aseasonal. The unimodal regime predominates in the low‐altitude zones of the east and the north, the bimodal and mixed regimes over the Andes mountain range, and the aseasonal in the Pacific region. These results improve the statistical diagnosis of the spatial variability of the rainfall seasonality in Colombia. This phenomenon, however, is still far from being fully understood in its hydroclimatic context. The annual migration of the Intertropical Convergence Zone is not enough to explain the diversity of rainfall regimes in Colombia. Local factors such as topography and land cover could play an important role in the occurrence and duration of rainfall seasons.

Description: Abstract Understanding concentration‐discharge (C‐Q) relationships are essential for predicting chemical weathering and biogeochemical cycling under changing climate and anthropogenic conditions. Contrasting C‐Q relationships have been observed widely, yet a mechanistic framework that can interpret diverse patterns remains elusive. This work hypothesizes that seemingly disparate C‐Q patterns are driven by switching dominance of end‐member source waters and their chemical contrasts arising from subsurface biogeochemical heterogeneity. We use data from Coal Creek, a high‐elevation mountainous catchment in Colorado, and a recently developed watershed reactive transport model (BioRT‐Flux‐PIHM). Sensitivity analysis and Monte‐Carlo simulations (500 cases) show that reaction kinetics and thermodynamics and distribution of source materials across depths govern the chemistry gradients of shallow soil water and deeper groundwater entering the stream. The alternating dominance of organic‐poor yet geo‐solute‐rich groundwater under dry conditions and organic‐rich yet geo‐solute‐poor soil water during spring melt leads to the flushing pattern of dissolved organic carbon and the dilution pattern of geogenic solutes (e.g., Na, Ca, and Mg). In addition, the extent of concentration contrasts regulates the power law slopes (b) of C‐Q patterns via a general equation . At low ratios of soil water versus groundwater concentrations (Cratio = Csw/Cgw 〈 0.6), dilution occurs; at high ratios (Cratio 〉 1.8), flushing arises; chemostasis occurs in between. This equation quantitatively interprets b values of 11 solutes (dissolved organic carbon, dissolved P, NO3−, K, Si, Ca, Mg, Na, Al, Mn, and Fe) from three catchments (Coal Creek, Shale Hills, and Plynlimon) of differing climate, geologic, and land cover conditions. This indicates potentially broad regulation of subsurface biogeochemical heterogeneity in determining C‐Q patterns and wide applications of this equation in quantifying b values, which can have broad implications for predicting chemical weathering and biogeochemical transformation at the watershed scale.

Description: Abstract Under current global warming and accelerated population growth scenarios, cropland irrigation water consumption has become a central issue limiting the sustainability of coupled human‐natural systems. This study proposes a new estimate of recent global cropland water consumption constrained by observations and provides attributions for its recent trend. By incorporating observations, including extracted cropland leaf area index and irrigation threshold data, this study provides improved estimates of recent global cropland evapotranspiration and transpiration as well as irrigation water consumption and withdrawal. The global annual consumption and withdrawal of irrigation water are estimated to be approximately 874 and 1,867 km3 (in 2005), respectively. From 2000 to 2014, a rapid increase in cropland irrigation was detected, especially in water‐deficient areas (i.e., hyperarid, arid, and semiarid regions). Climate change, which mainly consists of rising temperature and reduced moisture conditions, is usually distinguished as the major driving factor. Human‐induced increases in crop canopy cover have also contributed to more irrigation in hyperarid and arid regions. This study also provides suggestions for water‐savings‐targeted cropland management in water‐deficient areas based on the transpiration ratio (i.e., ratio of transpiration to evapotranspiration).

Description: Abstract The direct flow simulation using high‐resolution micro‐computed tomographic (μ‐CT) images of porous rock can be used to help understand the flow characteristics at the pore‐scale and to estimate fluid properties; however, segmentation of pore space in grayscale 3‐D μ‐CT images, a necessary step in this process, is challenging because of issues related to the image resolution and pore‐filling matrix in the gray‐level images. We present a novel process for determining the voxel porosity and permeability of the gray‐level regime and evaluating the bulk permeability using the Brinkman force lattice Boltzmann method. In this study, μ‐CT images of Berea sandstone are acquired with two spatial resolutions. After the pore size distribution curve is experimentally obtained, the “apparent pore” voxels and “gray pore” voxels are determined based on the designated gray‐level values in the gray‐level (CT number) histogram, the cumulative and fractional pore volumes, and the linear relationship between CT number and individual voxel porosity. The results show that the boundary between apparent and gray pores in terms of size determines the volumetric fraction and specific surface area. Additionally, the permeability computed by considering the gray pore regime based on the proposed method is more similar to the experimentally measured value than the results of other segmentation methods because the gray pore domain is fully incorporated into the flow domain while preserving the pore connectivity. The proposed sequence of pore segmentation presents a method for handling gray‐level pore space without compromising pore connectivity.

Description: Abstract In the semiarid interior western USA, where a majority of surface water supply comes from mountain forests, high‐resolution aerial lidar‐based surveys are commonly used to study snow. These surveys provide rich information about snow depth, but they are usually not accompanied with spatially explicit measurements of snow density, which leads to uncertainty in the estimation of snow water equivalent (SWE). In this study, we use a novel approach to distribute ~300 field measurements of snow density with artificial neural networks. We combine the resulting density maps with aerial lidar snow depth measurements, bias corrected with a very large and precisely geolocated array of field‐measured snow depths (~4,000 observations), to create and validate maps of snow depth, snow density, and SWE over two sites along Arizona's Mogollon Rim in February and March 2017. These maps show differences between midwinter and late‐winter snow conditions. In particular, compared to that of snow depth, the spatial variability of snow density is smaller for the later snow survey than the earlier snow survey. These gridded data also show that the representativeness of Snow Telemetry and other point measurements is different for the midwinter and late‐winter snow surveys. Overall, the lidar artificial neural network SWE estimates can be as much as 30% different than if Snow Telemetry density were used with lidar snow depths to estimate SWE.

Description: Abstract This study proposes a new mathematical model for describing the drawdown distribution due to a constant rate pumping (CRP) in an unconfined aquifer considering the lagging theory. We introduce two lag times in Darcy's law and in turn in a free surface equation to reflect the effects of the capillary fringe and the capillary suction on the water table motion. The present free surface equation can reduce to those used in previous studies. The Laplace and Weber transform methods are used to derive the semianalytical solution to the model including the effect of wellbore storage. The algorithm of numerical Laplace inversion is applied to obtain the transient solution of the model. We find that the delay index, commonly used in the literature, is equivalent to the lag time associated with the effect of the capillary suction. The sensitivity analysis is performed to assess the drawdown behavior in response to the change in each aquifer parameter. The drawdown distributions predicted by the present solution agree fairly well to the field data taken from CRP tests at Cape Cod, Massachusetts; the Canadian Forces Base Borden, Ontario; and Saint Pardon de Conques, Gironde (France). The lag times determined by both CRP tests seem to decrease linearly with increasing distance on the logarithmic scale from the pumping well. The consideration of two lag times considerably improves the accuracy in estimated specific yields.

Description: Abstract Root‐zone soil moisture (0–110 cm) was monitored at 21 sites within a cold‐region semiarid prairie grazing pasture over multiple growing seasons. There were large differences in the moisture dynamics for different sites, which was related to local‐scale impacts of sodium‐induced clay dispersion. Sites with high exchangeable sodium percentages, indicative of sodic soils, were characterized by small changes in soil moisture storage. The sites with the largest soil moisture changes had negligible exchangeable sodium percentage. We used this difference to divide the area into sites that participate in the field‐scale water balance and those that do not. As a result of this heterogeneity, a unique soil moisture variability‐mean relationship was observed; the spatial variability of root‐zone soil moisture was lowest during intermediate wetness conditions and highest for wet and dry conditions. Furthermore, the shape of the variability‐mean relationship depended on the depth over which soil moisture was integrated. The persistent differences in soil moisture dynamics were also responsible for the presence of two distinct spatial patterns of root‐zone soil moisture, representing early and late growing season (i.e., wet and dry conditions). The participating versus nonparticipating framework may be applicable broadly to sodic soils and to other soil types and has practical implications for parameterizing the water balance in hydrological models and for designing representative soil moisture monitoring networks in such environments.

Description: Abstract Extensive research has evaluated virtual water trade, the water embodied in traded commodities. However, relatively little research has examined virtual water storage or the water embodied in stored commodities. Just as in physical hydrology, both flows and stocks of virtual water resources must be considered to obtain an accurate representation of the system. Here we address the following question: How much water can be virtually stored in grain storage in the United States? To address this question, we employ a data‐intensive approach, in which a variety of government databases on agricultural production and grain storage capacities are combined with modeled estimates of grain crop water use. We determine the virtual water storage capacity (VWSC) in grain silos, map the spatial distribution of VWSC, calculate contributions from irrigation and rainwater sources, and assess changes in VWSC over time. We find that 728 km3 of water could be stored as grain in the United States, with roughly 86% coming from precipitation. National VWSC capacities were 777 km3 in 2002, 681 km3 in 2007, and 728 km3 in 2012. This represents a 6% decline in VWSC over the full 10‐year period, mostly attributable to increased water productivity. VWSC represents 62% of U.S. dam storage and accounts for 75–97% of precipitation receipts to agricultural areas, depending on the year. This work enhances our understanding of the food‐water nexus, will enable virtual water trade models to incorporate temporal dynamics, and can be used to better understand the buffering capacity of infrastructure to climate shocks.

Description: Abstract The capillary length (λs) and time (ts) are dynamic scalars that emerge routinely in the infiltration problem when gravitational and pressure gradients forces are involved. During drainage, however, capillary gradients oppose gravity and retain soil moisture close to surface. In this case, the pull of capillary gradients increases with drainage time and offsets gravity resulting in a quasi‐hydrostatic pressure distribution and negligibly small drainage flux in the profile. In this paper, it is proposed to anchor the dynamic concept of field capacity—the attainment of a small negligible drainage flux—in the physics of soil moisture redistribution as influenced by gravity and capillary forces. Similar to infiltration, this dynamic approach grounds the concept of field capacity in soil hydrology and allows its estimation from readily measured intrinsic physical characteristics such as λs, ts, and Ks. Finally, we exploit an analytical solution by Broadbridge and White (1988, https://doi.org/10.1029/WR024i001p00145) to track the drainage front as soil water redistributes in an initially saturated soil profile. While initially large, the downward migrating drainage front decelerates with time reaching near steady state condition at t ≈ 1,000ts. Quasi‐hydrostatic pressure matric head and water content profiles develop above the drainage front.

Description: Abstract We investigate the effects of geological stress on fluid flow and tracer transport in natural fracture networks. We show the emergence of non‐Fickian (anomalous) transport from the interplay among fracture network geometry, aperture heterogeneity, and geological stress. In this study, we extract the fracture network geometry from the geological map of an actual rock outcrop, and we simulate the geomechanical behavior of fractured rock using a hybrid finite‐discrete element method. We analyze the impact of stress on the aperture distribution, fluid flow field, and tracer transport properties. Both stress magnitude and orientation have strong effects on the fracture aperture field, which in turn affects fluid flow and tracer transport through the system. We observe that stress anisotropy may cause significant shear dilation along long, curved fractures that are preferentially oriented to the stress loading. This, in turn, induces preferential flow paths and anomalous early arrival of tracers. An increase in stress magnitude enhances aperture heterogeneity by introducing more small apertures, which exacerbates late‐time tailing. This effect is stronger when there is higher heterogeneity in the initial aperture field. To honor the flow field with strong preferential flow paths, we extend the Bernoulli Continuous Time Random Walk model to incorporate dual velocity correlation length scales. The proposed upscaled transport model captures anomalous transport through stressed fracture networks and agrees quantitatively with the high‐fidelity numerical simulations.

Description: Abstract We studied the influence of the diffusion contrast between species on the dynamics of Rayleigh‐Bénard (RB) convection in porous media. The onset time of buoyancy‐driven instabilities and convective dissolution flux was quantified using linear stability analysis and direct numerical simulations. The parametric analysis indicates eight distinct instability regions. Different stability mechanisms were characterized over the given range of diffusivity and relative buoyancy ratios. In particular, transition from instabilities solely by double diffusion to RB convection was identified using linear stability analysis and confirmed using nonlinear simulations. The parametric analysis on the onset also indicates that double diffusion has a potential to accelerate or slow down the RB convection depending on the solutes diffusion contrast. This study provides new insight into the effect of diffusion contrast and can be used to develop strategies for acceleration and deceleration of buoyancy‐driven instabilities.

Description: Abstract We used a depth‐averaged reactive transport model to simulate transport of a supersaturated fluid through fractures and considered two models of precipitation‐induced surface alterations: (1) a localized 1‐D alteration of the surface and (2) a 3‐D alteration of the surface using the level‐set method. Comparing simulation results to a simple analytical solution for precipitation in a homogeneous (aperture and mineralogy) fracture demonstrated both models predict the alteration process reasonably well. However, comparing simulation results from both models to results from a recent experimental study of precipitation in a mineralogically heterogeneous fracture (Jones & Detwiler, 2016, https://doi.org/10.1002/2016GL069598) demonstrated that the ability of the 3‐D model to predict mineral growth across the aperture and in the fracture plane leads to much better agreement with the experimental observations. To quantify the role of reaction kinetics on the precipitation process, we ran additional simulations using the 3‐D evolution model for reaction rate constants ranging over 3 orders of magnitude. When the kinetics were much faster than the advective flux through the fracture, precipitation was focused near the inlet, which led to a transition from preferential flow near the inlet to more uniform flow near the outlet. When reaction kinetics were slow relative to advection, reaction sites grew uniformly throughout the fracture leading to the eventual formation of a single preferential flow path from inlet to outlet. Regardless of reaction rate, localization of precipitation reactions led to significant increases (3 to 20 times) in the time scale required to seal the fracture relative to a mineralogically homogeneous fracture.

Description: Abstract We present analytical solutions for transport with bimolecular reactions in a single fracture embedded within an infinite rock matrix. The fracture and matrix are initially assumed to contain one aqueous species (B) at a uniform concentration. A second aqueous species (A) is injected into the fracture and reacts with B and an additional immobile species (N) in the rock matrix. Under these conditions, moving reaction fronts form and propagate along the fracture and into the rock matrix. We employ a composite similarity variable involving two space variables to derive analytical solutions for all species concentrations and the geometry of reaction fronts in the fracture and matrix. The behavior of the reaction‐diffusion equations in the rock matrix is posed as a Stefan problem. For uniform advection in the fracture, our analytical solutions establish that the reaction fronts propagate as the square root of time in both the matrix and the fracture. Our analytical solutions agree very well with numerical simulations. We extend our analytical solutions to nonuniform flows in the fracture by invoking a travel‐time transformation. We present applications of our analytical solutions to in situ chemical oxidation of dense nonaqueous phase liquids in fractured rock, wherein an oxidant (A, e.g., permanganate) is injected through fractures and consumed by bimolecular reactions with dissolved dense nonaqueous phase liquids (B, e.g., trichloroethylene) and natural organic matter (N) in the fracture and rock matrix. Our analytical solutions are also relevant to a broad class of reactive transport problems in fracture‐matrix systems where moving reaction fronts occur.

Description: Abstract The U.S. Corn Belt is highly productive with respect to grain and livestock commodities but often neglects to deliver other benefits such as soil stability, nutrient retention, and clean water. New precision technologies and conservation planning frameworks offer opportunities to adapt the current agricultural system to meet environmental goals along with production by strategically placing best management practices (BMPs) to target and address specific in‐field resource concerns. To understand farmers' and farmland owners' willingness to participate in such targeting schemes, we conducted in‐depth interviews with 18 farmers and farmland owners whose fields were targeted for soil and nutrient loss in two watersheds in central Iowa. We examined their current application of BMPs and opportunities and constraints to further adoption. We found that farmers and farmland owners often recognized the importance of producing a diverse suite of on‐ and off‐farm environmental benefits but lacked the context, information, certainty, and strong incentives to manage for them. Interviewees were generally receptive to using technologies to target BMPs to areas with resource concerns but expressed concerns about applications on their own land. They specifically perceived challenges related to cost, management complexity, coordination with government programs, and loss of autonomy. For broad acceptance, a spatially targeted conservation approach would need to be paired with expanded partnerships, trusted technical service, and adaptation incentives to reduce farm‐level economic trade‐offs.

Description: Abstract We conducted laboratory experiments to measure the sound produced during water‐by‐gas and kerosene‐by‐water displacements in samples of Indiana limestone and sandstones with different permeabilities. In water‐by‐gas displacement experiments, intensive sound was detected during the injection of hundreds of pore volumes and even when mobile water saturation was small (~1%). The sound was produced in a wide frequency range starting with frequencies less than 1 kHz; the upper frequencies varied from approximately 15 kHz for high‐permeability sandstone to almost 50 kHz for low‐permeability sandstone. In contrast to the experiments with gas flow through the dry rock samples, where sound appears only at high gas rates corresponding to the Forchheimer flow regime, the displacement produces sound at lower rates, corresponding to Darcy regime. Both the drop rate of sound emission and the sound intensity at the same mobile water saturation were determined to inversely depend on the rock permeability. We found that sound produced by sandstones shows a power law relationship between the number of events and their amplitudes, where the absolute value of the exponent also inversely depends on the rock permeability. In kerosene‐by‐water displacement experiments, the signal was observed at lower frequencies (up to 5 kHz) and only during injection of the first several pore volumes. A model describing the sound generation was suggested; the model considers acoustic events as a train of random pressure pulses corresponding to a Poisson point process. Simulation results demonstrated that the model reasonably reproduces the general trend of sound spectra produced by sandstones.

Description: Abstract Ovsinsky (1899, https://www.rulit.me/books/novaya‐sistema‐zemledeliya‐read‐193251‐1.html) suggested and tested a water conserving soil no‐till technology for rain‐snow‐fed field crops in a semiarid environment in southern Russia. We model Ovsynsky's unsaturated flow fragment, in which 1‐D steady evaporation and evapotranspiration through a two‐layered soil from a horizontal static water table to a dry soil surface takes place. Gardner's exponential and algebraic functions are used for the unsaturated hydraulic conductivity‐suction head relations. The vertical evaporation flux depends on the dyads and triads (correspondingly) of the parameters of these functions, for example, the saturated hydraulic conductivity and the sorptive number of the two layers. The flux, as a function of the relative thickness of the upper stratum, is analytically found from the solution of one or two nonlinear equations. This relation can be nonmonotonic and exhibits either a minimum or maximum depending on whether this stratum is coarser or finer than the subjacent stratum fed from a horizontal isobar. HYDRUS‐1D simulations confirm these extrema. This explains the experimental results from the literature on mulching/tillage/soil crusting‐sealing, which can increase, decrease, or have no impact on evaporation from a shallow water table. Alterations of the soil's homogeneity to reduce evaporation losses can improve the hydrological balance of soil profiles.

Description: Abstract Water vapor is a key element of the water regime in unsaturated profiles above deep aquifers in hyper‐arid regions. However, the interactions between water phases and the resulting evaporation and condensation are poorly understood under such conditions. The main driver for vapor condensation in deep vadose zone profiles is the geothermal gradient, displaying a decrease in temperatures toward the soil surface, thereby promoting condensation. We have analyzed the water regime in deep unsaturated profiles, with and without the geothermal gradient, and considered two types of hydrological scenarios: (1) assuming hydraulic continuity of liquid water over the entire profile and (2) assuming the presence of an evaporative front in the profile above which water flows to the surface in the vapor phase. We considered homogeneous profiles of two soil types, investigating the distribution with depth of the different state variables: temperature, relative humidity, water potential, and vapor pressure and concentration. We found that during evaporation, only extreme conditions of high relative humidity near the surface could lead to condensation. In addition, even when hydraulic continuity of liquid water is assumed over the entire soil profile, potential condensation amounts are very small, practically negligible. For the case of a water table at 200‐m depth, condensation occurs only when the relative humidity at the surface is above 95% and is less than 1.5% of the amount of water in the vapor phase in the profile.

Description: Abstract Agricultural expansion and intensification is occurring in seasonally dry regions of Central America, while droughts are intensifying due to increasing water demand and climatic change. Empirical measurements of water consumption of major crops in this region are scarce but crucial to assess agricultural water use dynamics in the light of increasing regional water conflicts. We empirically quantify total crop water use (CWU) and water footprints (WFs) of rainfed upland rice (wet season) and groundwater‐irrigated melons (dry season) grown sequentially as a double cropping system, one of the major cropping systems in the seasonally dry province of Guanacaste in northwestern Costa Rica. Data for this study cover 2 years and were measured with a state‐of‐the‐art eddy covariance water and carbon flux station. Upland rice only consumed green water (CWUgreen = 383 L/m2), while melons only consumed blue water (CWUblue = 177 L/m2). Irrigation was found to be 1.5 times larger than the actual melon water consumption, with better irrigation efficiencies than reported for melon farms in Brazil but slightly inferior to farms in Spain. Melon WFblue was 79 m3/t, a much lower value than global and regional estimates reported but similar to values reported for melons produced in Brazil or Spain. Upland rice WFgreen (681 m3/t) was reported for the first time and was proven to be much lower than flood irrigated‐rice WFblue‐green. Our results demonstrated lower overall water demand for upland rice‐melon double crop compared to the two other major monocultures of the region (flood‐irrigated rice and irrigated sugar cane).

Description: Abstract Abiotic carbonate precipitation has garnered significant interest as a mechanism for mineral trapping of carbon dioxide (CO2) in geologic carbon storage, as a natural diagenetic process frequently occurring in marine environments, and as an engineering approach for soil improvement. This study explored pore‐scale precipitation of calcium carbonate (CaCO3) and its effect on the permeability of porous media, using X‐ray computed microtomography (CMT). In a column experiment, CaCO3 was precipitated in a sand pack from a supersaturated CaCO3 solution, while porosity, pore volume fraction of carbonate, and permeability were being monitored and X‐ray CMT images were being acquired. Permeability reduction by ~99.94% was observed when precipitated carbonate occupied ~46–47% of pore volume. The X‐ray CMT images showed that carbonate crystals were initially nucleated onto sand grain surfaces, which facilitated subsequent precipitation, indicating a predominantly grain‐coating behavior. The scanning electron microscopy revealed the carbonate crystals of ~1–20 μm in size and the presence of internal pores in the carbonate layers at the submicrometer scale. Variations in carbonate layer thickness and geometric tortuosity, and preferential carbonate precipitation behavior with local clogging were examined through morphological analysis and phase segmentation. Particularly, the pore‐scale precipitation pattern and hence the pore geometry were found to evolve with continued precipitation from a grain‐coating behavior, through a pore‐filling behavior, and finally into a dramatic pore‐throat‐clogging behavior. Our results provide unique experiment data for predictive modeling of long‐term CO2 transport and provide new insights into the changes in physical and transport properties during CO2 mineral trapping.

Description: Abstract The widespread uncertainty regarding future changes in climate, socioeconomic conditions, and demographics have increased interest in vulnerability‐based frameworks for long‐term planning of water resources. These frameworks shift the focus from projections of future conditions to the weaknesses of the baseline plans and then to options for reductions in those weaknesses across a wide range of futures. A consistent challenge for vulnerability‐based planning is how to assess the relative likelihood of the occurrence of the multidimensional and codependent uncertainties to which the system or plan is vulnerable. This work proposes a methodological solution to the problem, demonstrated in this case as an extension to Decision Scaling framework. The proposed approach first generates a wide range of futures using stochastic simulators, and then stress tests the system across those futures to identify vulnerabilities relative to stakeholder‐defined performance thresholds. The relative likelihood of the vulnerabilities is then explored using a Bayesian belief network of the knowledge domain of the water resources system. The Bayesian network provides a formal representation of the joint probabilistic behavior of the system conditioned on the uncertain but potentially useful sources of information about the future, including historical trends, expert judgments, and model‐based projections. The proposed approach is applied to compare four design options for a dam project in the Coastal Province of Kenya with respect to the reliability and net present value metrics. Results show that incorporation of belief information helps better distinguishing of the available options, principally by magnifying the differences between the computed net present values.

Description: Abstract Delta progradation over segmented two‐slope bedrocks is prevalent in nature, where the bedrock slope upstream or downstream of the slope‐break knickpoint is steepened by continued tectonic uplift or subsidence. Understanding the morphodynamics of the most common types of delta in different slope settings is important for interpreting the observed delta progradation into reservoir and predicting delta evolutions under future tectonic/climate scenarios or anthropogenic interventions. Here, we present an experimental and analytical study demonstrating the morphological responses of Gilbert‐type and hyperpycnal deltas to variations of bedrock slopes. Steepening the upstream slope accelerates shoreline migration; steepening the downstream slope decelerates shoreline migration. In either case, the subaqueous volume is enhanced yet the subaerial volume is reduced. Both types of delta exhibit self‐similar morphologies when evolving over segmented bedrocks. Hyperpycnal deltas, through enhanced sediment fluxes driven by dense underflows, develop larger subaqueous volumes. We further demonstrate the underlying self‐similarities in sediment flux and bed growth rate that come into play for attaining the self‐similar morphologies. The combined effect of flowrate (Q) and sediment supply rate (I) may be characterized by a dimensionless Q/I ratio. Increasing Q/I advances the entire delta. For Gilbert deltas, shoreline migration accelerates with Q/I. For hyperpycnal deltas, shoreline migration exhibits a “first‐accelerate‐then‐decelerate” trend with Q/I in a limited range of slope combinations close to the single‐slope setting, indicating that the effect of Q/I emerges only when the two‐slope effect is weak or absent. Away from this near‐single‐slope range, the two‐slope effect becomes dominant, thus suppressing the effect of Q/I.

Description: Abstract The pore‐scale flow of CO2 and water in 2‐D heterogeneous porous micromodels over a Ca range of nearly three orders of magnitude was explored experimentally. The porous geometry is a close reprint of real sandstone, and the experiments were performed under reservoir‐relevant conditions (i.e., 8 MPa and 21 °C), thus ensuring relevance to practical CO2 operations. High‐speed fluorescent microscopy and image processing were employed to achieve temporally and spatially resolved data, providing a unique view of the dynamics underlying this multiphase flow scenario. Under conditions relevant to CO2 sequestration, final CO2 saturation was found to decrease and increase logarithmically with Ca within the capillary and viscous‐fingering regimes, respectively, with a minimum occurring during regime crossover. Specific interfacial length generally scales linearly with CO2 saturation, with higher slopes noted at high Ca due to stronger viscous and inertial forces, as supported by direct pore‐scale observations. Statistical analysis of the interfacial movements revealed that pore‐scale events are controlled by their intrinsic dynamics at low Ca, but overrun by the bulk flow at high Ca. During postfront flow, while permeability is typically correlated with total CO2 saturation in the porous domain (regardless of its mobility), the saturation of active CO2 pathways in the current study correlated very well with permeability. This alternate approach to characterize relative permeability could serve to mitigate hysteresis in relative permeability curves. Taken together, these results provide unique insights that address inconsistent observations in the literature and previously unanswered questions about the underlying flow dynamics of this important multiphase flow scenario.

Description: Abstract Incentive‐based policies, such as the cap‐and‐trade system, have been shown to be useful in the context of groundwater management. This study compares the performance of a groundwater market with water quotas when assumptions of perfect information are violated due to climate change and hydrogeologic heterogeneity and explores how changes in future climate affect market performance. A subbasin of the Republican River Basin, overlying the Ogallala aquifer in the High Plains of the United States, is used as a case study. Building on a previously developed model, a multiagent system model simulating a groundwater market is developed where self‐interested agents can trade water use permits to maximize individual benefits subject to irrigation and land constraints. This economic model is coupled with a calibrated physically based groundwater model for the study region that allows for an evaluation of streamflow depletion impacts, which has been the focus of management efforts in the basin. Results show that trading of permits between farmers results in increased economic benefits and, in some cases, reduced environmental violations. However, the benefits of a groundwater market are distributed unequally resulting in “winners” and “losers” across the system. Future changes in climate are shown to significantly influence farmers willingness to pay for groundwater and thus increase the variation in groundwater price and pumping. These findings emphasize the importance of addressing hydroclimatologic variability and change in the design of groundwater markets.

Description: Abstract In many semiarid regions with irrigation, the depletion rate of groundwater resources has increased substantially during the last decades. A possible reason for this is that the price that users pay for their water does not reflect its scarcity and value. An alternative way to assess the perceived value of water is calculating its shadow price, which is defined here as the marginal value produced, and relates to the efficiency gain from current reallocation. Here we determine the shadow price of water used for irrigation for the most important groundwater‐depleting countries and for four staple crops and one cash crop. To quantify the shadow price, the relation between the output and the water input is represented using production functions. We use globally available panel data on country‐specific crop yields and prices together with crop‐specific water consumption, calculated with the global hydrological model PCR‐GLOBWB, to parameterize the production function by country and crop with econometric analyses. Our results show that the variation of shadow prices for staple crops within several countries is high, indicating economically inefficient use of water resources, including nonrenewable groundwater. We also analyze the effects of reallocating irrigation water between crops, showing that changes in water allocation could lead to either an increase in the economic efficiency of water use or large reductions in irrigation water consumption. Our study thus provides a hydroeconomic basis to stimulate sustainable use of finite groundwater resources globally.

Description: Abstract Accurate and widely available wetland inventories are needed for wetland conservation and environmental planning. We propose an open source, automated wetland identification model that relies primarily on light detection and ranging (LiDAR) digital elevation models (DEMs). LiDAR DEMs are increasingly available and provide the resolution needed to map detailed topographic metrics and areas of likely soil saturation, but the choice of smoothing and conditioning techniques can significantly impact the accuracy of hydrologic parameter extraction. So far, the effect of these preprocessing steps on wetland delineation has not been thoroughly analyzed. We test the response of a Random Forest wetland classifier, using topographic wetness index, curvature, and cartographic depth‐to‐water index as input variables, to combinations of smoothing techniques (none, mean, median, Gaussian, and Perona‐Malik) and conditioning techniques (Fill, Impact Reduction Approach, and A* least‐cost path analysis) for four sites in Virginia, USA. The Random Forest model was configured to account for imbalanced data sets, and manually surveyed wetlands were used for verification. Applying Perona‐Malik smoothing and A* conditioning yielded the highest accuracy across all sites and considerably reduced model runtime. We found that models could be further improved by individualizing the smoothing method and scale to each input variable. Using only topographic information, the wetland identification model could accurately detect wetlands in all sites (81‐91% recall). Model overprediction varied across sites, represented by precision scores ranging from 22 to 69%. In its current form, the wetland model shows strong potential to support wetland field surveying by identifying likely wetland areas.

Description: Abstract The understanding of the dynamics of Lagrangian velocities is key for the understanding and upscaling of solute transport in heterogeneous porous media. The prediction of large‐scale particle motion in a stochastic framework implies identifying the relation between the Lagrangian velocity statistics and the statistical characteristics of the Eulerian flow field and the hydraulic medium properties. In this paper, we approach both challenges from numerical and theoretical points of view. Direct numerical simulations of Darcy‐scale flow and particle motion give detailed information on the evolution of the statistics of particle velocities both as a function of travel time and distance along streamlines. Both statistics evolve from a given initial distribution to different steady‐state distributions, which are related to the Eulerian velocity probability density function. Furthermore, we find that Lagrangian velocities measured isochronally as a function of travel time show intermittency dominated by low velocities, which is removed when measured equidistantly as a function of travel distance. This observation gives insight into the stochastic dynamics of the particle velocity series. As the equidistant particle velocities show a regular random pattern that fluctuates on a characteristic length scale, it is represented by two stationary Markov processes, which are parametrized by the distribution of flow velocities and a correlation distance. The velocity Markov models capture the evolution of the Lagrangian velocity statistics in terms of the Eulerian flow properties and a characteristics length scale and shed light on the role of the initial conditions and flow statistics on large‐scale particle motion.

Description: Abstract Reforestation of degraded grasslands can increase the soil hydraulic conductivity and number of preferential flow pathways. However, it is not clear to what extent these changes affect streamflow responses and whether this depends on the event size. We, therefore, studied the hydrological response of two small catchments near Tacloban, Leyte (the Philippines): a degraded Imperata grassland catchment and a catchment that was reforested 23 years prior to our study. Precipitation, stream stage, and electrical conductivity were measured continuously from June to November 2013. Samples were taken from streamflow, precipitation, groundwater, and soil water for geochemical and stable isotope analyses. Streamflow and electrical conductivity changed rapidly during almost every event in the grassland catchment, but in the reforested catchment, these responses were much smaller and only occurred during large events. Streamflow was a mixture of groundwater and precipitation for both catchments, but the maximum event water contributions to streamflow were much larger for the degraded grassland than for the reforested catchment. The differences in the event water contributions and timing of the streamflow responses were observed across all event sizes, including a large tropical storm. Together with the low saturated hydraulic conductivity in the degraded catchment, these results suggest that overland flow occurred more frequently and was much more widespread in the degraded grassland than in the reforested catchment. We, therefore, conclude that reforestation of a degraded grassland can change the dominant flow pathways and restore the hydrological functioning if the forest soil is allowed to develop over a sufficiently long period.

Description: Abstract Accurate and reliable probabilistic forecasts of hydrological quantities like runoff or water level are beneficial to various areas of society. Probabilistic state‐of‐the‐art hydrological ensemble prediction models are usually driven with meteorological ensemble forecasts. Hence, biases and dispersion errors of the meteorological forecasts cascade down to the hydrological predictions and add to the errors of the hydrological models. The systematic parts of these errors can be reduced by applying statistical postprocessing. For a sound estimation of predictive uncertainty and an optimal correction of systematic errors, statistical postprocessing methods should be tailored to the particular forecast variable at hand. Former studies have shown that it can make sense to treat hydrological quantities as bounded variables. In this paper, a doubly truncated Bayesian model averaging (BMA) method, which allows for flexible postprocessing of possibly multimodel ensemble forecasts of water level, is introduced. A case study based on water levels for a gauge of river Rhine reveals a good predictive skill of doubly truncated BMA compared both to the raw ensemble and the reference ensemble model output statistics approach. Using rolling training periods, BMA considerably outerperforms ensemble model output statistics. However, this gap shrinks drastically when using analog‐based training periods.

Description: Abstract Variations in water supply and their impact on farm production in smallholder irrigation schemes are often associated with the location of irrigators at either the head or tail‐end, with tail‐enders usually considered to be at a severe disadvantage. However, it is rare that the impact of multidimensional proxies of water (capturing adequacy, timing, and location) on farm production and income have been evaluated in conjunction with other relevant variables. Using GIS analysis, this study combines irrigation household surveys, irrigation area characteristics, and cadastral data from two smallholder irrigation schemes in southern Tanzania. The results indicate that location at both the head‐end and tail‐end had a negative significant impact on farm yields, but not farm incomes. Also, being further downstream the secondary canals (but not necessarily away from the system's intake) had a significant negative effect on both yields and incomes. Surprisingly, increased tomato production drove a decline in incomes, thus raising the importance of crop selection and productivity barriers linked to markets and knowledge. In absence of actual quantitative measures of water supply, this study concludes that using a multidimensional water proxy can uncover important effects that would otherwise remain overlooked by the widespread head versus tail‐end dichotomy, commonly used in the study of water distribution within smallholder irrigation systems.

Description: Abstract The bias correction of the General Circulation Model (GCM) outputs has become a routine step that is taken in climate change impact assessments. To responsibly support the decision‐making processes, the climate‐modeling community has been debating about the conceptual requirements that bias‐correction methods should fulfill. Bearing in mind these requirements, we propose to decompose atmospheric variables into three temporal elements that represent the climate mean state, the interannual variability, and the daily variability. This decomposition is aimed at correcting the biases at one time scale without affecting the simulated climate (mean state) trend or the distributional properties at other time scales. The novelty of the proposed approach is, nevertheless, marked by the adjustment of interannual and daily variability that is made by replacing the GCM‐simulated data with synthetic samples drawn from Stable Distributions (SDs) that are fitted to the observed variability. The replacement prevents the transfer of the sampling variability of the calibration period and gives the corrected data the distributional properties of the observed climate. The employment of SDs was motivated by the fact that the climate‐change‐induced changes in the scale, the symmetry, and the frequency of extremes can be measured and applied to the SDs of the observed data. We correct the biases in the GCM‐simulated temperature and precipitation over northern South America using our proposed approach and two other existing ones. Our proposed method is capable of not only preserving the simulated climate trends but also reproducing the observed extremes as well as a more flexible method based on nonparametric distributions.

Description: Abstract River discharge estimation requires knowledge of bathymetry. However, aside from a few locations where surveys have been conducted, bathymetric data are unavailable, even for major rivers. It has been suggested that water surface elevation and flow width measurements from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission (planned launch 2021) may be used to infer the submerged channel geometry; however, the full potential of these measurements for inferring bathymetry has yet to be explored. We apply four different techniques, with varying assumptions about height‐width relationships, to predict unknown bathymetry. We call these “curve‐fitting methods” the linear, slope break, nonlinear, and nonlinear slope break (NLSB) methods. The linear and slope break methods are based on a linear height‐width relationship, while the nonlinear and NLSB methods are based on a height‐width relationship derived from hydraulic geometry equations. We generate SWOT‐like observations of height and width based on 5‐m gridded Upper Mississippi River data and evaluate the performance of each curve‐fitting method given the SWOT‐like observations. The NLSB method predicts bed elevation and low flow area with the least error, although the nonlinear method may be preferred in low data conditions. Additionally, we show that our method outperforms previously suggested methods, and we propose an NLSB‐based bathymetry prior for Bayesian discharge estimation algorithms.

Description: Abstract Quantitative evaluation of earthquake‐induced permeability changes is important for understanding key geological processes, such as advective transport of heat and solute and the generation of elevated fluid pressure. Many studies have independently documented permeability changes in either an aquifer or an aquitard, but the effects of an earthquake on both the aquifer and aquitard of the same aquifer system are still poorly understood. In this study, we use the well water‐level response to earth tides and atmospheric pressure to study the changes in hydraulic properties in an aquifer and an overlying confining layer in Beijing, China, following the 11 March 2011 Tohoku earthquake in Japan. Our results show that both the tidal response amplitude and the phase shift increased and that the phase shift changed from negative to positive after the earthquake. We identified increased permeability in both the aquifer and aquitard by the barometric response function method. The horizontal transmissivity of the aquifer increased by a factor of 6, and the vertical diffusivity of the aquitard doubled.

Description: Abstract We quantified groundwater stress worldwide by applying the global water resources and water use model WaterGAP 2.2b (Water ‐ Global Assessment and Prognosis) for current conditions (1981–2010) as well as for the 2050s under the worst‐case greenhouse gas emissions scenario RCP8.5. To improve global‐scale groundwater stress assessments, we suggest three new water quantity‐related groundwater stress indicators as well as a new way for communicating projected future groundwater stress at the grid‐cell level (~55 × 55 km) and for larger spatial units such as transboundary aquifers (〉20,000 km2). The new indicators encompass the ratio of net abstractions from groundwater to groundwater recharge, human‐induced changes in groundwater discharge, and human‐induced groundwater depletion. We compare them to four conventional indicators used in the Transboundary Waters Assessment Programme and show how they can add value to global‐scale studies or are even more suitable for indicating groundwater stress. We assess potentials and limitations of all indicators by addressing their level of process representation, data requirements, uncertainty, and the underlying different concepts of sustainable groundwater use. To support adaptation to climate change, we recommend showing both the ensemble mean and the worst‐case scenario of future groundwater stress that we derived from five climate and two irrigation scenarios. For characterizing groundwater stress in spatial units such as transboundary aquifers, areal fractions where a selected indicator threshold is exceeded should be considered. Finally, hot spots of future groundwater stress should be identified by combining relative changes from current conditions with absolute values of future groundwater stress.

Description: Abstract A critical study issue to incorporate imperfect forecast in real‐time reservoir operation is determining the forecast horizon. In this study, properties for the longest forecast horizon (LFH) and the effective forecast horizon (EFH) are derived from a multistage, deterministic optimization model for the operation of a single water supply reservoir with a concave benefit function. The LFH addresses the question of how long a forecast is sufficient to make an optimal reservoir release decision for the current stage if the effect of forecast uncertainty is not considered. The EFH represents a forecast horizon with the information for decision making as much as allowed by uncertainty effect control, which is set as prescribed decision reliability quantified by the error bound (i.e., the largest difference between the optimal release decisions made under any two inflow scenarios). The properties of LFH and EFH are used to specify the criteria and design the procedures for determining EFH and LFH. A hypothetical but typical case study is used to demonstrate the criteria and procedures. Both theoretical analysis and the case study results show that LFH and EFH are affected by multiple factors such as the reservoir capacity, inflow variability, forecast uncertainty, maximum allowable error bound, and ending storage estimate accuracy. LFH is longer with a larger capacity, smaller inflow variability, and smaller forecast uncertainty, and EFH is longer with smaller forecast uncertainty, larger error bound, and more accurate ending storage estimates.

Description: Abstract Calibration of stream gauging stations involves water velocity measurements at various water levels to obtain discharge and to determine the rating curve. This process is laborious, often logistically challenging, or even impossible for streams that are only accessible at low flow. Here, we present an alternative method to obtain mean stream velocity by matching temperature variation patterns measured at two positions in the stream. Such water temperature variations are caused by snow melt or rainfall events and serve as natural tracers. The method is successfully applied to a karst cave stream that is only accessible at lowest flow. The installed high‐precision data loggers provide sufficient data to obtain a relationship between water depth and mean velocity. The approximate rating curve, based on reach‐mean channel width, agrees well with results from dye tracer experiments. This cave stream shows the typical features of a steep step‐pool stream such as a power‐law relation between mean velocity and discharge.

Description: Abstract Hydrologic responses to earthquakes such as streamflow increases, water‐level changes, and changes in geyser eruption frequency often reflect changes in permeability caused by seismic waves. The dynamic nature of permeability, as revealed by co‐seismic hydrologic phenomena, holds implications for groundwater systems, geothermal resources, mineral resources, and geologic hazards. Analysis of water‐level responses to solid Earth tides and changes in atmospheric pressure provide a passive way to continuously monitor changes in permeability and storage properties in tectonically active regions.

Description: Abstract Turbulence causes rapid mixing of solutes and fine particles between open channel flow and coarse‐grained streambeds. Turbulent mixing is known to control hyporheic exchange fluxes and the distribution of vertical mixing rates in the streambed, but it is unclear how turbulent mixing ultimately influences mass transport at the reach scale. We used a particle‐tracking model to simulate local‐ and reach‐scale solute transport for a stream with coarse‐grained sediments. Simulations were first used to determine profiles of vertical mixing rates that best described solute concentration profiles measured within a coarse granular bed in flume experiments. These vertical mixing profiles were then used to simulate a pulse solute injection to show the effects of turbulent hyporheic exchange on reach‐scale solute transport. Experimentally measured concentrations were best described by simulations with a nonmonotonic mixing profile, with highest mixing at the sediment–water interface and exponential decay into the bed. Reach‐scale simulations show that this enhanced interfacial mixing couples in‐stream and hyporheic solute transport. Coupling produces an interval of exponential decay in breakthrough curves and delays the onset of power law tailing. High streamwise velocities in the hyporheic zone reduce mass recovery in the water column and cause breakthrough curves to exhibit steeper power law slopes than predictions from mobile‐immobile modeling theory. These results demonstrate that transport models must consider the spatial variability of streamwise velocity and vertical mixing for both the stream and the hyporheic zone, and new analytical theory is needed to describe reach‐scale transport when high streamwise velocities are present in the hyporheic zone.

Description: Abstract Pore development in natural porous media, as a result of mineral dissolution in flowing fluid, generates complex microstructures. Although the underlying dynamics of fluid flow and the kinetics of the dissolution reactions have been carefully analyzed in many scenarios, it remains interesting to ask if the preferentially developed flow paths share certain general petrophysical properties. Here we combine in situ X‐ray imaging with network modeling to study pore development in chalk driven by acidic fluid flow under ambient condition. We show that the trajectory of a growing pore correlates with the flow path that minimizes cumulative surface—the overall surface area available to fluid within the residence time—calculated along streamlines. This correlation is not a coincidence because cumulative surface determines conversion of reactant and thus defines the position of dissolution front. Model simulations show that, as fluid channelizes, the growth of the leading pore in the flow direction is guided by migration of the most far‐reaching dissolution front, even in an ever‐changing flow field. In addition, we present a complete tomographic time series of microstructure erosion and show a good accord between the in situ observation and the model simulation. Our results suggest that the microscopic pore development is a deterministic process while being sensitive to stochastic perturbations to the migrating dissolution front.

Description: Abstract Soil moisture spatial patterns with length scales of 1‐100 km influence hydrological, ecological, and agricultural processes, but the footprint or support volume of existing monitoring systems, for example, satellite‐based radiometers and sparse in situ monitoring networks, is often either too large or too small to effectively observe these mesoscale patterns. This measurement scale gap hinders our understanding of soil water processes and complicates calibration and validation of hydrologic models and soil moisture satellites. One possible solution is to utilize geostatistical techniques that have proven effective for mapping static patterns in soil properties. The objective of this study was to determine how effectively dynamic, mesoscale soil moisture patterns can be mapped by applying regression kriging to the data from a sparse, large‐scale in situ network. The fully automated system developed here uses several data sets: daily soil moisture measurements from the Oklahoma Mesonet, sand content estimates from the Natural Resource Conservation Service Soil Survey Geographic Database, and an antecedent precipitation index computed from National Weather Service multisensor precipitation estimates. A multiple linear regression model is fitted daily to the observed data, and the residuals of that model are used in a semivariogram estimation and kriging routine to produce daily statewide maps of soil moisture at 5‐, 25‐, and 60‐cm depths at 800‐m resolution. During over 3 years of operation, this mapping system has revealed complex, dynamic, and depth‐specific mesoscale patterns, reflecting the shifting influences of both soil texture and precipitation, with a mean absolute error of ≤0.0576 cm3/cm3 across all three depths.

Description: Abstract Occurrences of odorous bacterial metabolites, 2‐methylisoborneol (MIB) and geosmin (GSM) in drinking water supply reservoirs are considered as a nuisance by the water industry and a source of complaints from customers. In Eagle Creek Reservoir, routine monitoring programs of MIB and GSM highlight intense odorous outbreaks during the spring season when high inflow discharges occur. Cyanobacteria have always been assumed to be source of these metabolites even if no known producers are present in raw water. A copper‐based algaecide is often used to terminate the metabolite production and the algal growth in the reservoir. The current study was designed to investigate and identify other biological sources involved in the biosynthesis of MIB and GSM metabolites as well as environmental factors that could be important triggers for the growth of bacterial producers. The community structure of the bacterioplankton was determined using a 16S rRNA gene sequencing technique which showed that not only Cyanobacteria but Actinobacteria also were involved in the reservoir internal production. Planktothrix species was identified as the main source of GSM (p〈0.001) while Streptomyces (Actinobacteria) was very likely responsible of MIB (p〈0.01). Application of an algaecide disrupted GSM and the growth of Planktothrix but was less effective against MIB and Streptomyces. Statistical analyses revealed that MIB‐ and GSM‐causing bacteria were found abundant when the water was enriched with nitrogen, temperature cooler and, the water column mixed.

Description: Abstract Ecohydrological processes in semiarid shrublands and other dryland ecosystems are sensitive to discrete pulses of precipitation. Anticipated changes in the frequency and magnitude of precipitation events are expected to impact the spatial and temporal distribution of soil moisture in these drylands, thereby impacting their ecohydrological processes. Recent field studies have shown that in dryland ecosystems, transpiration dynamics and plant productivity are largely a function of deep soil moisture available after large precipitation events, regardless of where the majority of plant roots occur. However, the strength of this relationship and how and why it varies throughout the year remains unclear. We present eddy covariance, soil moisture, and sap flow measurements taken over an 18‐month period in conjunction with an analysis of biweekly precipitation, shallow soil, deep soil, and stem stable water isotope samples from a creosotebush‐dominated shrubland ecosystem at the Santa Rita Experimental Range in southern Arizona. Within the context of a hydrologically defined two‐layer conceptual framework, our results support that transpiration is associated with the availability of deep soil moisture and that the source of this moisture varies seasonally. Therefore, changes in precipitation pulses that alter the timing and magnitude of the availability of deep soil moisture are expected to have major consequences for dryland ecosystems. Our findings offer insights that can improve the representation of drylands within regional and global models of land surface atmosphere exchange and their linkages to the hydrologic cycle.

Description: Abstract Reductions in streamflow due to groundwater pumping (‘streamflow depletion’) can negatively impact water users and aquatic ecosystems but are challenging to estimate due to the time and expertise required to develop numerical models often used for water management. Here, we develop analytical depletion functions, which are simpler approaches consisting of (i) stream proximity criteria which determine the stream segments impacted by a well; (ii) a depletion apportionment equation which distributes depletion among impacted stream segments; and (iii) an analytical model to estimate streamflow depletion in each segment. We evaluate 50 analytical depletion functions via comparison to an archetypal numerical model and find that analytical depletion functions predict streamflow depletion more accurately than analytical models alone. The choice of a depletion apportionment equation has the largest impact on analytical depletion function performance, and equations that consider stream network geometry perform best. The best‐performing analytical depletion function combines stream proximity criteria which expand through time to account for the increasing size of the capture zone, a web squared depletion apportionment equation which considers stream geometry, and the Hunt analytical model which includes streambed resistance to flow. This analytical depletion function correctly identifies the stream segment most affected by a well 〉70% of the time with mean absolute error 〈 15% of predicted depletion and performs best for wells in relatively flat settings within ~3 km of streams. Our results indicate that analytical depletion functions may be useful water management decision support tools in locations where calibrated numerical models are not available.

Description: Abstract Flow and transport in three‐dimensional discrete fracture networks with internal variability in aperture and permeability is investigated using a numerical model. The analysis is conducted for three different texture types representing internal variability considering various correlation lengths and for an increase in domain size corresponding to an increase in network complexity. Internal variability in discrete fracture networks generally increases median travel times and delays arrival of bulk mass transport when compared against reference cases without texture, corresponding to smooth fractures. In particular, internal variability textures with weak connectivity increase travel times non‐linearly with domain size increase, further delaying bulk mass arrival. Textures with strong connectivity can however decrease median travel times, accelerating bulk mass arrival, but only for limited ranges of correlation length and domain size. As domain size increases, travel times of textures with strong connectivity converge towards travel times obtained for classical multi‐variant Gaussian textures. Thus, accounting for internal fracture variability is potentially significant for improving conservative estimates of bulk mass arrival, flow channeling, and advective and reactive transport in large scale discrete fracture networks. Further, early mass arrival can arrive significantly earlier for textures with strong connectivity and classical Gaussian textures corresponding to intermediate connectivity, but are only slightly affected by textures with weak connectivity. Thus accounting for internal variability in fractures is also important for accurate estimates of early solute mass arrival. The overall impact on predictive transport modelling will depend on the extent of, or lack of, internal fracture connectivity structure in real‐world fractured rocks.

Description: Abstract Water allocation regimes that adjudicate between competing uses are in many countries under pressure to adapt to increasing demands, climate‐driven shortages, expectations for equity of access, as well as societal changes in values and priorities. International authorities expound standards for national allocation regimes that include robust processes for addressing the needs of ‘new entrants' and for varying existing entitlements within sustainable limits. The claims of Indigenous peoples to water represents a newly recognised set of rights and interests that will test the ability of allocation regimes to address the global water governance goal of equity. No study has sought to identify public attitudes or willingness to pay for a fairer allocation of water rights between Indigenous and non‐Indigenous people. We surveyed households from the jurisdictions of Australia's Murray‐Darling Basin, a region undergoing a historic government‐led recovery of water, and found that 69.2% of respondents support the principle of reallocating a small amount of water from irrigators to Aboriginal people via the water market. Using contingent valuation, we estimated households are willing to pay A$21.78 in a one‐off levy. The aggregate value calculated for households in the basin's jurisdictions was A$74.5 million, which is almost double a recent government commitment to fund the acquisition of entitlements for Aboriginal nations of this basin. Results varied by state of residency and affinity with environmental groups. An information treatment that presented narrative accounts from Aboriginal people influenced the results. Insights from this study can inform water reallocation processes.

Description: Abstract Modifications to landscapes and flow regimes of rivers have altered the function, biodiversity, and productivity of freshwater ecosystems globally. Reestablishing geomorphological and hydrological conditions necessary to sustain ecosystems is a central challenge for restoration within highly altered systems. Meeting this challenge requires simultaneously addressing multiple and interacting stressors within the context of irreversible changes and socio‐economic constraints. Traditionally, river restoration approaches either physically change the landscape or channel (channel‐floodplain manipulation) or adjust hydrology (environmental flows), and such actions are often independent. We juxtapose these two subfields of river restoration, which have undergone parallel transformations, from goals of reproducing static representations of form and flow regime to goals of reestablishing processes. The parallel transformations have generated shared ideas, which point to benefits of coupling channel‐floodplain manipulation and environmental flow actions to achieve process‐based goals. Such coupling supports comprehensive river restoration efforts aimed at supporting resilient ecosystems within human dominated landscapes in a nonstationary climate. We identify four elements of coupled approaches for restoring highly modified rivers: (1) identify physical and ecological process potential given interactive effects of altered landscapes and flows; (2) consider capacity for sustaining identified processes under potential future change; (3) model alternatives for coupled restoration actions to support identified processes; and (4) evaluate alternatives using metrics representing integrative effects of coupled actions. We suggest these emergent elements contribute to the development of standard practices for restoring highly modified rivers and encourage an increasing number and quality of coupled applications.

Description: Abstract Reliable flood estimates are needed for designing safe and cost‐effective flood protection structures. Classical flood estimation methods applied for deriving such estimates focus on peak discharge and neglect other important flood characteristics such as flood volume and the interdependence among different flood characteristics. Furthermore, they do not account for potential nonstationarities in hydrological time series due to climate change. The consideration of both the interdependence between peak discharge and flood volume and its nonstationarity might help us derive more reliable flood estimates. A few studies have looked at changes in the general dependence of peak discharge and flood volume for small sets of catchments and explored ways of modeling such changes. However, spatial analyses of trends in this dependence or in their climatological drivers have not been carried out. The aim of this study was to help close this knowledge gap by first quantifying trends in the general dependence between peak discharge and flood volume as described by Kendall's tau on a spatially comprehensive data set of 307 catchments in Switzerland. Second, potential climatological drivers for changes in the dependence between peak discharge and flood volume were identified. Our results show that the dependence between peak discharge and flood volume and its trends are spatially heterogeneous. This pattern cannot be explained by one driver only but by an interplay of changes in precipitation, snowmelt, and soil moisture. Both the trends and the links between drivers and trends depend on the climate model chain considered and are therefore uncertain.

Description: Abstract We provide analytical (closed form) expression for a class of integrals that frequently arise into modeling well‐type flows through heterogeneous porous formations. In particular, these integrals are encountered when ensemble (second‐order) moments of the flow variables are computed by means of a perturbation approach that regards the variance  of the random field  (being K the hydraulic conductivity) as a small parameter.

Description: Abstract Mineral dissolution and precipitation reactions can significantly alter the porosity and permeability of porous media. While porosity generally increases with dissolution and decreases with precipitation, permeability is controlled by the spatial locations of reactions in discrete pores and pore‐throats and in the greater pore network. Geochemical reactions have been observed to occur both uniformly and non‐uniformly in porous media, driven by parameters such as mineral distribution, grain size, and Peclet and Damkohler numbers. Pore network modeling can be used to simulate the impact of pore scale alterations on permeability, requiring only pore and pore‐throat size distributions and pore connectivity. Here, the impact of variations in pore and pore‐throat size distributions on reactive permeability for uniform and non‐uniform spatial distributions of reactions is evaluated. A series of pore network models are created and populated with pore and pore‐throat size distributions of varying types (skewed, normal, uniform) to represent differences in network topology and characterization methods. The impacts of these distributions on reactive permeability are then simulated for uniform and non‐uniform reaction conditions by increasing or decreasing pore and pore‐throat sizes in a prescribed manner to reflect dissolution and precipitation, respectively. Overall, simulations reveal that porosity‐permeability evolution varies with reaction scenario and is qualitatively consistent for the different pore and pore‐throat size distributions. Common macroscopic porosity‐permeability relationships work well for some reaction scenarios but are unable to reflect size‐dependent reactions. A new modified version of the Verma‐Pruess relationship is created and able to successfully reflect the porosity‐permeability evolution for size dependent reactions.

Description: Abstract Gas generation and flow in soil is relevant to applications such as the fate of leaking geologically sequestered carbon dioxide, natural releases of methane from peat and marine sediments, and numerous electro‐thermal remediation technologies for contaminated sites, such as electrical resistance heating. While traditional multiphase flow models generally perform poorly in describing unstable gas flow phenomena in soil, Macroscopic Invasion Percolation (MIP) models can reproduce key features of its behavior. When coupled with continuum heat and mass transport models, MIP has the potential to simulate complex subsurface scenarios. However, coupled MIP‐continuum models have not yet been validated against experimental data and lack key mechanisms required for electro‐thermal scenarios. Therefore, the purpose of this study was to (a) incorporate mechanisms required for steam generation and flow into an existing MIP‐continuum model (ET‐MIP), (b) validate ET‐MIP against an experimental lab‐scale electrical resistance heating study, and (c) investigate the sensitivity of water boiling and gas (steam) transport to key parameters. Water boiling plateaus (i.e., latent heat), heat recirculation within steam clusters, and steam collapse (i.e., condensation) mechanisms were added to ET‐MIP. ET‐MIP closely matched observed transient gas saturation distributions, measurements of electrical current, and temperature distributions. Heat recirculation and cluster collapse were identified as the key mechanisms required to describe gas flow dynamics using a MIP algorithm. Sensitivity analysis revealed that gas generation rates and transport distances, particularly through regions of cold water, are sensitive to the presence of dissolved gases.

Description: Abstract The hyporheic zone, where surface water (SW) and groundwater (GW) interact in shallow sediments beneath rivers, is uniquely reactive and attenuates pollutants. Mixing of reactants from SW and GW enables mixing‐dependent (MD) reactions, which may be the last opportunity for GW contaminants to react before entering SW. Yet little is known about hyporheic MD reactions, particularly how they respond to daily or seasonal SW fluctuations or sediment heterogeneity. We used MODFLOW and SEAM3D to simulate non‐mixing‐dependent (NMD) aerobic respiration and MD denitrification in a riverbed dune with nitrate from SW and dissolved organic carbon from GW. We varied SW heads and heterogeneity of sediment hydraulic conductivity. For longer‐term fluctuations (i.e., seasons), increasing SW depth from 0.1 to 1.0 m increased NMD aerobic respiration by 270% and MD denitrification by 78% in homogeneous sediment. MD reactions thus were controlled by mixing zone length or size and would be stronger when SW stage is elevated, for example, during wintertime. Adding sediment heterogeneity to the long‐term scenarios, particularly by increasing hydraulic conductivity correlation length, increased flow focusing and consequently increased MD denitrification by 20–30%. By contrast, the net effect of daily SW fluctuations on MD denitrification in homogeneous sediment was minor. In sum, SW fluctuations are an important control on hyporheic MD reactions, primarily by controlling mixing zone length. The hyporheic zone may attenuate nitrate in upwelling GW plumes, but temporal fluctuations may be considerable as quantified above.

Description: Abstract Harmonic Pulse Testing (HPT) has been developed as a type of well testing applicable during ongoing field operations because a pulsed signal is superimposed on background pressure trend. Its purpose is to determine well and formation parameters such as wellbore storage, skin, permeability, and boundaries within the investigated volume. Compared to conventional well testing, HPT requires more time to investigate the same reservoir volume. The advantage is that it does not require the interruption of well and reservoir injection/production before and/or during the test because it allows the extraction of an interpretable periodic signal from measured pressure potentially affected by interference. This makes it an ideal monitoring tool. Interpretation is streamlined through diagnostic plots mimicking conventional well test interpretation methods. To this end, analytical solutions in the frequency domain are available. The methodology was applied to monitor stimulation operations performed at an Enhanced Geothermal System site in Pohang, Korea. The activities were divided into two steps: first, a preliminary sequence of tests, injection/fall‐off, and two HPTs, characterized by low injection rates and dedicated to estimate permeability prior to stimulation operations, and then stimulation sequence characterized by a higher injection rate. During the stimulation operations other HPT were performed to monitor formation properties behavior. The interpretation of HPT data through the derivative approach implemented in the frequency domain provided reliable results in agreement with the injection test. Moreover, it provided an estimation of hydraulic properties without cessation of stimulation operations, thus confirming the effectiveness of HPT application for monitoring purposes.

Description: Abstract The presence of well‐connected paths is commonly observed in spatially heterogeneous porous formations. Channels consisting of high hydraulic conductivity (K) values strongly affect fate and transport of dissolved species in the subsurface environment. Several studies have established a correlation between connectivity properties of the spatially variable K‐field and solute first arrival times. However, due to limited knowledge of the spatial structure of the K‐field, connectivity metrics are subject to uncertainty. In this work, we utilize the concept of the Minimum Hydraulic Resistance (MHR) and Least Resistance Path (LRP) to evaluate the connectivity of a K‐field in a stochastic framework. We employ a fast graph‐theory based algorithm to alleviate the computational burden associated with stochastic computations in order to investigate both the impact of the hydrogeological structural conceptualization and domain dimensionality (2D vs 3D) on the uncertainty of the MHR. Finally, we propose an iterative data acquisition strategy that can be utilized to identify the LRP (which is linked to preferential flow channels) in real sites. A synthetic benchmark test is presented, showing the advantages of the proposed sampling strategy when compared to a regular sampling strategy. By using the iterative data sampling strategy, we were able to reduce first arrival time uncertainty by 47% (when compared to the regular sampling strategy), while maintaining site characterization efforts constant.

Description: Abstract Numerical simulation of flow and transport in heterogeneous formations has long been studied, especially for uncertainty quantification and risk assessment. The high computational cost associated with running large‐scale numerical simulations in a Monte Carlo sense has motivated the development of surrogate models, which aim to capture the important input‐output relations of physics‐based models, but require only a fraction of the cost of full model runs. In this work, we formulate a conditional deep convolutional generative adversarial network (cDC‐GAN) surrogate model to learn the dynamic functional mappings in multiphase models. The cDC‐GAN belongs to a class of deep generative semi‐supervised learning methods that can be used to learn the data generation processes. Like the original GAN, a main strength of the cDC‐GAN is that it includes a self‐training scheme for improving the quality of generative modeling in a game theoretic framework, without requiring extensive statistical knowledge and assumptions on input data distributions. In particular, our cDC‐GAN model is designed to learn cross‐domain mappings between high‐dimensional input (e.g., permeability) and output (e.g., phase saturations) pairs, with the ability to incorporate conditioning information (e.g., prediction time). As a use case, we demonstrate the performance of cDC‐GAN for predicting the migration of carbon dioxide (CO2) plume in heterogeneous carbon storage reservoirs, which has both numerical and practical significance because of the safe storage requirements now mandated in many countries. Results show that cDC‐GAN achieves high accuracy in predicting the spatial and temporal evolution patterns of the injected CO2 plume, as compared to the original results obtained using a compositional reservoir simulator. The performance of cDC‐GAN models, trained using the same number of training samples, stays relatively robust when the level of spatial heterogeneity is increased. Our cDC‐GAN is pattern‐based and is not limited by the underlying physics. Thus it provides a general framework for developing surrogate models and conducting uncertainty analyses for a wide range of physics‐based models used in both groundwater and subsurface energy exploration applications.

Description: Abstract Quantifying the behavior and performance of hydrologic models is an important aspect of understanding the underlying hydrologic systems. We argue that classical error measures do not offer a complete picture for building this understanding. This study demonstrates how the information theoretic measure known as transfer entropy can be used to quantify the active transfer of information between hydrologic processes at various timescales and facilitate further understanding of the behavior of these systems. To build a better understanding of the differences in dynamics, we compare model instances of the Structure for Unifying Multiple Modeling Alternatives (SUMMA), the Variable Infiltration Capacity (VIC) model, and the Precipitation Runoff Modeling System (PRMS) across a variety of hydrologic regimes in the Columbia River Basin in the Pacific Northwest of North America. Our results show differences in the runoff of the SUMMA instance compared to the other two models in several of our study locations. In the Snake River region, SUMMA runoff was primarily snowmelt driven, while VIC and PRMS runoff was primarily influenced by precipitation and evapotranspiration. In the Olympic mountains, evapotranspiration interacted with the other water balance variables much differently in PRMS than in VIC and SUMMA. In the Willamette River, all three models had similar process networks at the daily time scale but showed differences in information transfer at the monthly timescale. Additionally, we find that all three models have similar connectivity between evapotranspiration and soil moisture. Analyzing information transfers to runoff at daily and monthly time steps shows how processes can operate on different timescales. By comparing information transfer with correlations, we show how transfer entropy provides a complementary picture of model behavior.

Description: Abstract Policy efforts to improve Baltic Sea water quality will be expensive if the ambitious targets agreed are to be achieved. The aim of this study is to evaluate the ex‐post cost‐effectiveness of nitrogen load reductions to the Baltic Sea made between 1996 and 2010. We first calculate the counterfactual change in nitrogen load to the Baltic Sea and compare to observed loads. The costs of the net reductions are evaluated using a Baltic‐wide cost‐effectiveness model, which includes a wide set of nitrogen abatement measures in the littoral countries. Results show that the net nitrogen reductions achieved through environmental policy, about 145,000 tons total nitrogen, could have been obtained at 12% of the realized cost, through reallocation of abatement between countries. The total budget spent on abatement could, if used in a cost‐effective manner, be sufficient for a doubling of the net nitrogen load reduction. Milestone targets, in combination with a compensation scheme between countries, could help to reduce policy costs.

Description: Abstract Stream temperature has been increasing in tandem with air temperature, with potentially negative impacts on cold‐water fish such as salmon. Assessing future stream temperature change is critical for developing effective management responses. Empirical models of stream thermal sensitivity generally predict less future warming compared to physically based models. Here we reconcile these discrepancies by using a process‐based hydrology and temperature model to simulate daily flow and water temperature for forested headwater catchments in a maritime region under both historic and projected future climatic conditions. The primary reason that the empirical approach underestimates thermal response to climate change is that it does not account for thermal memory in the catchment, especially related to the effect of snow cover. Empirical thermal sensitivities thus may underestimate stream temperature response to future climate warming. In addition, groundwater‐fed streams may only resist warming in the short‐medium term, due to lagged response of groundwater temperature. More process‐based understanding and modelling of stream thermal regimes is needed to effectively manage aquatic ecosystems.

Description: Abstract Accurate estimation of surface turbulent heat fluxes is important in numerous hydrological, meteorological, and agricultural applications. Recently, several studies have focused on estimating these fluxes via assimilation of land surface temperature (LST) observations into a surface energy balance model following the variational data assimilation (VDA) scheme. However, current VDAs suffer from the following issues: (1) they do not consider the inherent coupling between water and energy in the soil‐plant‐atmosphere continuum, (2) they tend to be ill‐posed, and (3) they do not explicitly compute the uncertainty of estimates. The goal of this study is to enhance the current VDAs in two major ways: (i) coupling water and energy balance equations, assimilating soil moisture (SM) data in addition to LST, and constraining the VDA estimates by the moisture diffusion equation in addition to the heat diffusion equation; and (ii) analyzing the second‐order information that guides toward a well‐posed estimation problem and provides uncertainty of parameters. The performance of the proposed VDA is examined through a set of experiments based on a synthetic data set. The results show that simultaneous assimilation of SM and LST improves the estimation of heat fluxes and reduces the sensitivity of VDA to the initial guess of parameters. Furthermore, by adding moisture diffusion equation as an additional constraint, the correlation between the estimated parameters is reduced and the VDA scheme is oriented toward well posedness. The feasibility of extending the proposed VDA in estimating large‐scale turbulent fluxes using spaceborne SM and LST data is examined, and promising results are obtained.

Description: Abstract This paper introduces a novel measure to assess similarity between event hydrographs. It is based on cross recurrence plots (CRP) and recurrence quantification analysis (RQA), which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multidimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to cross recurrence plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.

Description: Abstract Trees exert a fundamental control on the hydrologic cycle, yet previous research is unclear about the nuanced relationship between forest cover and riverine flood frequency. In the Northeastern US, warming air temperatures have resulted in a decline of Eastern Hemlock (EH), and subsequent increases in observed catchment water yield. We evaluated the possibility of EH loss leading to a changed flooding regime. We first investigated plant hydraulic regulation by root water uptake in EH and American Beech (AB; a candidate successional species) through stable isotope analysis of stream, soil water, and plant xylem water. EH xylem water showed evidence of deeper soil water uptake than AB during both wet and dry seasons, suggesting species succession may be an important mechanism for altering catchment “plant accessible water.” Next, we estimated catchment flood frequency with mechanistic hydrologic simulations for present conditions, and two hypothetical cases where all EH is succeeded by AB. The largest change to catchment extreme discharge after AB succession coincided with fall season tropical moisture export derived precipitation. We observed reduced sensitivity under future climatic forcing with an ensemble simulation of five LOCA downscaled GCMs. Thus, the influence of forest composition on the flood regime may be most related to the temporal alignment of the synoptic‐scale processes that generate Atlantic Basin tropical cyclones and regional plant phenology of the Northeast US. Our results provide a justification for using physically‐based hydrologic models incorporating plant hydraulic regulation when evaluating future flooding frequency.

Description: Abstract The majority of annual sediment flux is transported during storm events in many watersheds across the world. Using X‐ray diffraction (XRD), we analyzed the mineralogy of grab samples of suspended sediment during different stages of storm hydrographs in the Southern Piedmont. Mineralogy of suspended sediment changes drastically from quartz‐dominated during the rising limb to clay‐dominated during the late falling limb/baseflow. Changes in mineralogy can shed insight into turbidity relationships, suspended sediment sources, energy versus supply‐limited sediment transport, and other suspended sediment parameters such as anion exchange capacity and trace element chemistry. An unexpected key finding, confirmed by XRD and electron microscopy, is that both kaolinite and quartz are primarily transported as discrete crystalline minerals of different size classes in our watersheds; this contrasts with existing scientific literature stating that in most fluvial systems suspended sediment is transported primarily as composite particles composed of a heterogeneous mix of all particle sizes. Our findings also support existing literature that turbidity can be a good proxy for elements such as P, which are preferentially adsorbed onto iron oxide coatings thus in‐situ turbidity probes have great potential to provide relatively inexpensive estimates of P flux when calibrated for specific watersheds.

Description: Abstract Flume experiments are conducted to investigate the intrinsic links between time‐varying bed load transport properties for uniform sediments and bed surface morphology under unsteady hydrograph flows, in the absence of upstream sediment supply. These conditions are representative of regulated river reaches (e.g. downstream of a dam) that are subject to natural flood discharges or managed water releases, resulting in net degradation of the river bed. The results demonstrate that the hydrograph magnitude and unsteadiness have significant impacts on sediment transport rates and yields, as well as hysteresis patterns and yield ratios generated during the rising and falling limbs. A new hydrograph descriptor combining the influence of total water work and unsteadiness on bed load transport is shown to delineate these hysteresis patterns and yield ratios, whilst correlating strongly with overall sediment yields. This provides an important parametric link between unsteady hydrograph flow conditions, bed load transport and bed surface degradation under imposed zero sediment feed conditions. As such, maximum bed erosion depths and the longitudinal bed degradation profiles along the flume, are strongly dependent on the magnitude of this new hydrograph descriptor. Similarly, non‐equilibrium bed forms generated along the flume indicate that formative conditions for alternate bars, mixed bar/dunes or dunes are defined reasonably well by an existing morphological model and the new hydrograph descriptor. These findings provide a new framework for improved predictive capabilities for sediment transport and morphodynamic response in regulated rivers to natural or imposed unsteady flows, while their wider application to graded sediments are also considered.

Description: Abstract Climate models show that global warming will disproportionately influence high‐latitude regions and indicate drastic changes in, amongst others, seasonal snow cover. However, current continental and global simulations covering these regions are often run at coarse grid resolutions, potentially introducing large errors in computed fluxes and states. To quantify some of these errors, we have assessed the sensitivity of an energy‐balance snow model to changes in grid resolution using a multi‐parametrization framework for the spatial domain of mainland Norway. The framework has allowed us to systematically test how different parametrizations, describing a set of processes, influence the discrepancy, here termed the scale‐error, between the coarser (5 to 50 km) and finest (1 km) resolution. The simulations were setup such that liquid and solid precipitation was identical between the different resolutions, and differences between the simulations arise mainly during the ablation period. The analysis presented in this study focuses on evaluating the scale‐error for several variables relevant for hydrological and land surface modelling, such as SWE and turbulent heat exchanges. The analysis reveals that the choice of method for routing liquid water through the snowpack influences the scale‐error most for SWE, followed by the type of parametrizations used for computing turbulent heat fluxes and albedo. For turbulent heat exchanges, the scale‐error is mainly influenced by model assumptions related to atmospheric stability. Finally, regions with strong meteorological and topographic variability show larger scale‐errors than more homogenous regions.

Description: Abstract In many hydrological systems, groundwater is pumped from the aquifer onto the land surface, and a fraction of this water subsequently infiltrates to recharge the groundwater system (recirculated groundwater). Tracers that undergo different degrees of re‐equilibration with the atmosphere during this recirculation process can enable ambient groundwater and recirculated groundwater to be differentiated. In this paper, the recirculated groundwater has been pumped to dewater open pit mines, and discharged into ephemeral creeks. Some of this water subsequently recharged back into the aquifer. CFC‐12, 14C and 3H are used in a four end‐member mixing analysis to differentiate between (1) ambient groundwater, (2) recirculated groundwater, (3) river recharge from natural flows prior to commencement of mining operations (in 2007), and (4) natural river recharge post‐2007. Sampling of the surface water when discharge of mine water was the only source of river flow enabled the extent of re‐equilibration of both CFC‐12 and 14C to be accurately determined. Since CFC‐12 re‐equilibrates more rapidly than 14C, recirculating groundwater had a CFC‐12 concentration which was close to modern, but a 14C activity that was higher than the original groundwater, but less than modern recharge. As 3H does not re‐equilibrate, it enabled easy differentiation between recirculated groundwater and infiltration of natural creek flows. Uncertainty of end‐member compositions is due to changes in the end‐member concentrations over time in the case of natural river flows, uncertainty in the extent of tracer re‐equilibration for the groundwater recirculation end‐member, and spatial variations in the composition of the ambient groundwater end‐member.

Description: Abstract Layered heterogeneous media widely exist in subsurface environment. They commonly give rise to preferential flow that provides a fast path for water and solute transport in soils and aquifers. One‐dimensional (1‐D) double‐region models are frequently used to simulate solute transport in heterogeneous media by adopting a mass transfer coefficient, rather than transverse dispersion, to represent interaction between two zones. A two‐dimensional (2‐D) solute transport model considering transverse dispersion and linear reactions in a layered medium where water in the two regions is mobile was presented, and its semianalytical solution was derived. The solution was tested using a numerical solution and an existing analytical solution. The results indicated that the mass exchange between the two zones was induced by the contrast in properties of the two zones and determined by the transverse dispersion across the interface. When solutes pass through the two‐layer medium, part of the solutes in the fast flow zone will migrate into the slow flow zone in the beginning, and later this mass exchange will be reversed; that is, part of the solutes in the slow flow zone will migrate back to the fast flow zone. The magnitude of the mass exchange was determined by the property difference in the two zones. The reaction of the solute has significant impacts on the mass interaction between the two zones. The solution was applied to previous laboratory experiments and compared to the 1‐D double‐region model as well. The 2‐D model matched the observed breakthrough curves better than the 1‐D model.

Description: Abstract The Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 sensors (AMSR) have provided multi‐frequency microwave measurements of the global terrestrial water cycle since 2002. A new AMSR surface wetness index (ASWI) was developed by analyzing the near‐surface atmospheric vapor pressure deficit (VPD), surface volumetric soil moisture (VSM) and land surface fractional open water (FW) time series from an established AMSR Land Parameter Data Record (LPDR). The ASWI allows for multi‐component and independent satellite assessments of near‐surface drought conditions by exploiting the weighted anomalies of VPD, VSM and FW. Comparisons between ASWI and more traditional drought metrics, including the Palmer moisture anomaly index (PDSI‐Z) and the U.S. Drought Monitor (USDM), showed generally consistent classifications of drought severity for three major droughts over the Contiguous United States (CONUS) since 2002. The AWSI showed moderate (0.3≤R≤0.7 for 56% of area) to strong (R〉0.7 for 29% of area) correlations with the PDSI‐Z during the summer months (JJA) from 2002 to 2017. ASWI and PDSI‐Z differences were attributed to AMSR retrieval uncertainties and the different aspects of drought represented by the indices. Comparisons between ASWI and the Gravity Recovery and Climate Experiment drought severity index (GRACE‐DSI) showed strong correspondence (R=0.61) in regions where possible long‐term total water storage (TWS) changes occurred. The sole reliance of the ASWI on satellite microwave remote sensing and continuing AMSR2 operations enables effective global monitoring of drought conditions, while providing new information on the atmosphere, soil and surface water components of drought.

Description: Abstract This note provides a proof‐of‐concept modeling study to examine the theoretical feasibility of a new groundwater sampling approach, the high‐stress low‐flow approach, for improving the representativeness of groundwater samples and shortening the sampling duration. The approach consists of two‐phase pumping: an initial high pumping rate followed by low‐flow purging and sampling. We conceptualize the sampling process by pumping in a fully penetrating, large‐diameter well in a confined aquifer and mixing within the well screened zone, which are characterized by the aquifer‐responding time scale for aquifer water dominating the inflow ratio and the well‐mixing time scale, respectively. We derive an analytical solution to evaluate the sample concentration and representativeness. Results show that higher pumping rates in phase 1 create larger drawdowns and overstressed flow fields when switching to lower pumping rates in phase 2, thereby slowing down the drawdown within the well and preventing downward movement of the well casing water. As a result, the ratio of aquifer water into the well screened zone and in water pumped can rise sharply at the pumping‐switch moment, and the aquifer‐responding time scale and groundwater sampling duration can be significantly shortened. The proposed high‐stress low‐flow approach is particularly effective in systems limited by long aquifer‐responding time scales, which are typically encountered in low‐permeability aquifers. Based on the analytical solution, we also provide preliminary guidelines and graphic tools to select the pumping rate ratio and the switching time. Our proof‐of‐concept modeling study demonstrates great potential of the new groundwater sampling approach in field applications.

Description: Abstract Lake surface water temperature (LSWT) is an important factor of water ecological environment. In the context of global warming, the LSWT of global lakes generally reveals an upward trend. With a continuous intensification of human activities and a rapid expansion of the impervious surface, urbanization has exerted an increasing impact on the environment, so the impact of human activities on LSWT cannot be ignored. Because of the special geographical location, the change of LSWT in plateau lakes has important impacts on climate diversity, biodiversity, and cultural diversity. As a result, it is critical to monitor and model the variation characteristics of LSWT in the plateau area. Based on the data set of natural factors representing climate change and human factors representing human activities, this study proposes a classification of lake types by K‐Means clustering method. At watershed scale, 11 lakes in the study area are divided into three types: Natural Lake, Semi‐urban Lake, and Urban Lake (UL). Based on this classification, the variation characteristics of LSWT for the eleven lakes from 2001 to 2017 are analyzed. The causal relationship and contribution of climate change and human activities to the rise of LSWT are discussed. Results show that (1) from 2001 to 2017, the annual mean of LSWT‐day/night and near‐surface air temperature in the 11 lakes show a warming trend, a significant correlation (R = 0.82, α = 0.0164 〈 0.5) and a same periodicity, which indicates that near‐surface air temperature is one of the main influencing factors of LSWT warming in Yunnan‐Guizhou Plateau. (2) LSWT warming trend of UL is more obvious than those of Semi‐urban Lake and Natural Lake, indicating that human activities have more significant impact on LSWT of UL. The main driving factors are the impervious surface expansion and population increase. (3) The influence of human activities on the LSWT in Yunnan‐Guizhou Plateau is becoming more and more significant, and it is also the main factor in causing the deterioration of lake water environment in Yunnan‐Guizhou Plateau.

Description: Abstract Remotely sensed soil moisture products are ideal candidates for initializing soil moisture profiles of land surface models via data assimilation. This paper investigates the possibility of using a calibrated Integral Equation Model coupled with a hyperresolution land surface model, called Soil, Vegetation, and Snow (SVS) to simulate backscatter and compares the results with C‐band RADARSAT‐2 Synthetic Aperture Radar (SAR) backscatter signals in postharvest season when the field is considered bare soil or sparsely vegetated. Modifications to SVS evaporation scheme are shown to improve the comparison against SAR measurements. An improved effective soil roughness calculation scheme was also proposed to focus on the inversion of the root mean square height (Hrms) only. Soil dielectric constant compensation was suggested to reduce the inversion error and expand the dynamic range of Integral Equation Model. The combination of SVS soil moisture and effective roughness is found superior to the absence of either of them. This method is promising considering that it does not require any in situ measurements, and yet it still outperforms the original IEM model, which uses in situ measured soil moisture and soil roughness at point scale.

Description: Abstract Inferring the mechanisms causing river flooding is key to understanding past, present, and future flood risk. However, a quantitative spatially distributed overview of the mechanisms that drive flooding across Europe is currently unavailable. In addition, studies that classify catchments according to their flood‐driving mechanisms often identify a single mechanism per location, although multiple mechanisms typically contribute to flood risk. We introduce a new method that uses seasonality statistics to estimate the relative importance of extreme precipitation, soil moisture excess, and snowmelt as flood drivers. Applying this method to a European data set of maximum annual flow dates in several thousand catchments reveals that from 1960 to 2010 relatively few annual floods were caused by annual rainfall peaks. Instead, most European floods were caused by snowmelt and by the concurrence of heavy precipitation with high antecedent soil moisture. For most catchments, the relative importance of these mechanisms has not substantially changed during the past five decades. Exposing the regional mechanisms underlying Europe's most costly natural hazard is a key first step in identifying the processes that require most attention in future flood research.

Description: Abstract Leaf area index (LAI) is an important vegetation indicator widely used for simulating vegetation dynamics and quantifying biomass production. Spatial and temporal variability of LAI are often characterized using satellite remote sensing products. However, these types of satellite products often have relatively low quality when compared to in situ measurements. This work presents an approach for characterizing Moderate Resolution Imaging Spectroradiometer LAI observation errors in a Bayesian ecohydrological modeling framework using Moderate Resolution Imaging Spectroradiometer quality flags data. We introduce a novel ecohydrologic error model, which partitions observation and model residual error according to the estimated retrieval uncertainty of LAI and the quality flags for each pixel. We examine our approach in two study catchments in Australia with varying degrees of good and poor quality satellite LAI data. Results show improved LAI predictions and less model residual error for both catchments when accounting for satellite observational uncertainties in a Bayesian framework.

Description: Abstract Environmental and technical issues associated with hydraulic fracturing fluid leak‐off and its low recovery in clay‐rich shale reservoirs has challenged the energy sector. One of the main hypothesized mechanisms for the uptake of fracturing fluid is fluid imbibition due to capillary forces that are a strong function of the rock's wettability. However, shale wettability estimated by contact angle and spontaneous imbibition experiments are highly inconsistent throughout the literature. It is therefore critical to shed light on the possible reasons for such discrepancies and identify the superior technique. In order to characterize the physical processes from microscale to macroscale, the contact angles and spontaneous imbibition characteristics of shale samples were measured using aqueous ionic solutions (NaCl, KCl, CaCl2, and MgCl2) at different concentrations (0, 0.1, and 0.5 M) and oil (Soltrol‐130). The internal structure of the samples exposed to deionized water was imaged by three‐dimensional X‐ray micro‐computed tomography before and after spontaneous imbibition at both unconfined and confined stress states. Additionally, the structure of all samples exposed to each ionic solution was analyzed via environmental scanning electron microscopy. Experimental observations were further substantiated by combining digital image correlation with Poisson‐Boltzmann analysis to assess the hydration‐induced strains. It was shown that while spontaneous imbibition is a more realistic measurement for liquids, results obtained under unconfined condition can be highly biased due to additional forces acting (e.g., osmotic or hydration forces) and also potential microstructural alterations. Thus, spontaneous imbibition measured under reservoir stress condition is strongly recommended for shale wettability estimation.

Description: Abstract Regional scale transport models are needed to support the long‐term evaluation of groundwater quality and to develop management strategies aiming to prevent serious groundwater degradation. The purpose of this study is to evaluate the capacity of a previously developed upscaling approach to adequately describe the main solute transport processes, including the capture of late‐time tails under changing boundary conditions. Potential factors that impact the performance of upscaling methods, including temporal variations in mass transfer rates and mass distributions, were investigated. Advective‐dispersive contaminant transport in a 3D heterogeneous domain was simulated and used as a reference solution. The equivalent transport under homogeneous flow conditions was then evaluated by applying the Multi‐Rate Mass Transfer (MRMT) model. The random walk particle tracking (RWPT) method was used to solve the solute transport for heterogeneous and homogeneous MRMT scenarios under steady‐state and transient conditions. The results indicate that the MRMT model can capture the tails satisfactorily for plumes transported with ambient steady‐state flow fields at all studied scales using the same parameters. However, when the boundary conditions change in either local, plume or regional scale, the mass transfer model calibrated for transport under steady‐state conditions cannot accurately reproduce the tailings observed for the heterogeneous scenario. The deteriorating impacts of transient boundary conditions on the upscaled model are more significant for regions where the flow fields are dramatically affected, which highlights the poor applicability of the MRMT approach for complex field settings. This finding also has implications for the suitability of other potential upscaling approaches.

Description: Abstract In this study, we analyze the nonstationarity in meteorological droughts at the multidecadal scale in different parts of the contiguous United States during 1901–2017. We develop metrics to compare the drought risk calculated under the assumptions of stationarity and nonstationarity and identify their spatial and temporal patterns. By analyzing the variability of drought risk in the past and exploring its ongoing patterns, we evaluate in which regions of the contiguous United States the assumption of stationarity can be safely used for drought risk planning and management. We find statistically significant interdecadal changes in the probability distribution functions of drought severity in parts of the Northwest, upper Midwest, the Northeast, eastern parts of Great Plains and in parts of Arizona, New Mexico, Utah, and Nevada in the Southwest. In these regions, the nonstationary risk has been significantly higher than the stationary estimate of risk in the past, which shows that the assumption of stationarity can lead to the underestimation of drought risk in these regions. The multidecadal drought risk shows low variability in California, parts of northern and western Great Plains, Ohio Valley, and in the Southeast, since the statistical properties of droughts have not changed significantly in these regions during 1901–2017. However, the meteorological drought risk has increased in California and the Southeast in the recent decades due to the influence of global warming and hence the assumption of stationarity for risk estimation may lead to underestimation of drought risk in future in these regions if this effect of global warming persists.

Description: Abstract The study presents a data set of the interannual and intraannual snow depth distribution recorded by terrestrial laser scanning (TLS) scans at Weisssee snow research site in Austria between November 2014 and May 2018. The data set comprises 23 snow‐on digital elevation models, one snow‐off digital elevation model, and the difference raster calculated between a snow‐off and snow‐on scans. The relative accuracy of the TLS scans was determined by measuring the distance between snow‐free planes from the snow‐on and snow‐off scans and shows mean values smaller than 0.03 m and standard deviations ranging between 0.02 and 0.1 m. The reliability of the snow depths derived from TLS was further assessed by comparing snow depths from snow probing, Global Navigation Satellite System measurements, and continuous snow depth measurements from the weather station. Comparison of the different measurement methods shows average deviations of less than 0.1 m. The data can be used for analysis and modeling of snow distribution or for assessing the representativeness of snow sensors or other remote sensing products.

Description: Abstract The objective of the current study is to build a stochastic model to simulate climate indices that are teleconnected with the hydrologic regimes of large‐scale water resources systems such as the Great Lakes system. Climate indices generally contain nonstationary oscillations (NSOs). We adopted a stochastic simulation model based on Empirical Mode Decomposition (EMD). The procedure for the model is to decompose the observed series and then to simulate the decomposed components with the NSO resampling (NSOR) technique. Because the model has only been previously applied to single variables, a multivariate version of NSOR (M‐NSOR) is developed to consider the links between the climate indices and to reproduce the NSO process. The proposed M‐NSOR model is tested in a simulation study on the Rössler system. The simulation results indicate that the M‐NSOR model reproduces the significant oscillatory behaviors of the system and the marginal statistical characteristics. Subsequently, the M‐NSOR model is applied to three climate indices (i.e., Arctic Oscillation, El Niño‐Southern Oscillation, and Pacific Decadal Oscillation) for the annual and winter data sets. The results of the proposed model are compared to those of the Contemporaneous Shifting Mean and Contemporaneous Autoregressive Moving Average model. The results indicate that the proposed M‐NSOR model is superior to the Contemporaneous Shifting Mean and Contemporaneous Autoregressive Moving Average model for reproducing the NSO process, while the other basic statistics are comparatively well preserved in both cases. The current study concludes that the proposed M‐NSOR model can be a good alternative to simulate NSO processes and their teleconnections with climate indices.

Description: Abstract Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g. model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multi‐year flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large scale spatiotemporal patterns of flood dynamics, particularly in the presence of low accuracy elevation data.

Description: Abstract A comprehensive data set of extreme hydrological events (EHEs)—floods and droughts, consisting of 2,171 occurrences worldwide, during 1960‐2014 was compiled, and then their economic losses were normalized using a price index in U.S. dollar. The data set showed a significant increasing trend of EHEs before 2000, while a slight post‐2000 decline. Correspondingly, the EHE‐caused economic losses increased obviously before 2000 followed by a slight decrease; the post‐2000 decline could be partially attributed to the decreases in drought and flood‐prone area or climate adaptation practices. Spatially, Asia experienced most EHEs (969), corresponding to the largest share of economic losses (approximately $868 billion for floods and $50 billion for droughts, respectively), while Oceania had the least EHEs (102) and the least economic losses (approximately $19 billion for floods and $45 billion for droughts). The five countries with the highest EHE‐caused economic losses were China, United States, Canada, Australia, and India. Countries that suffered the highest flood‐caused economic losses were China, United States, and Canada. This data set provides a quantitative linkage between climate science and economic losses at a global scale, and it is beneficial for the regional climatic impact assessments and strategical development for mitigating climate change impacts.