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Micro‐continuum models are versatile and powerful approaches for simulating coupled processes in two‐scale porous systems. Initially oriented for modeling static single‐phase flow in microtomography images with sub‐voxel porosity, the concept has been extended over the years to multi‐phase flow, reactive transport, and poromechanics. This paper introduces an integrated micro‐continuum framework to model coupled processes in porous media. It reviews state‐of‐the‐art models and discusses applications in geosciences including Digital Rock Physics with sub‐voxel porosity, moving fluid‐solid interface at the pore‐scale due to geochemical reactions, fracture‐matrix interactions, and solid deformation. Finally, the paper discusses future developments in micro‐continuum models. Key Points: Micro‐continuum models are hybrid‐scale approaches for solving flow and transport in porous mediaState of the art micro‐continuum models handle full Temperature‐Hydrodynamics‐Mechanics‐Chemistry coupling in unsaturated environmentsApplications include Digital Rock Physics with sub‐voxel porosity, pore‐scale reactive transport, and poromechanics [ABSTRACT FROM AUTHOR]

This paper proposes a method for reducing the environmental impact of sewer network (SN) overflows. The main objective of the paper is to minimize the wastewater quantity and the pollutant loads that overflow from the SN. The proposed algorithm to achieve this goal is Model Predictive Control using Particle Swarm Optimization as optimization method. It was tested in simulation using a simplified model of the network based on Benchmark Simulation Modelsewer as prediction model, and a forecasted influent. Three cases have been considered: (a) the fitness function is defined as the global yearly overflow volume calculated using equal weights for each tank; (b) the fitness function uses different weights for each tank depending on the medium loads and (c) integrating a penalty term related to the system state at the end of the prediction horizon in the previous fitness function. The simplified model determined a significant reduction of the integration time minimizing the optimization time. Key Points: Model Predictive Control is used to reduce pollution caused by sewer network (SN) overflowsSimplified SN flow model decreases the optimization time of the control algorithmPollutant loads are assessed by the control algorithm by weighting overflow volumes with values calculated based on offline measurements [ABSTRACT FROM AUTHOR]

In recent years, as a result of emerging renewable energy markets, several developed regions have already launched Real‐Time Pricing (RTP) strategies for electricity markets. Establishing optimal pump operation for water companies in RTP electricity markets presents a challenging problem. In a RTP market, both positive and negative electricity prices are possible. These negative prices create economically attractive opportunities for Water Distribution System (WDS) to dispatch their energy consumption. On the other hand, excessively high prices may put WDS at risk of supply disruptions and reduced service levels. However, the continuous development of wind power and photovoltaics results in more volatile and unpredictable fluctuations in the price of renewable energy. The risk arising from uncertainty in electricity prices can lead to a significant increase in actual costs. To address this issue, this paper develops an a posteriori random forest (AP‐RF) approach to forecast the probability density function of electricity prices for the next day and provide a risk‐constrained pump scheduling method toward RTP electricity market. The experimental results demonstrate that the developed method effectively addresses the issue of increased costs caused by inaccurate electricity price forecasting. Plain Language Summary: With the emergence of renewable energy markets in recent years, several developed regions have introduced Real‐Time Pricing (RTP) strategies for their electricity markets. This has created a difficult challenge for water companies seeking to establish the optimal pump operation in RTP markets. This study investigates the use of a risk‐constrained optimization scheduling approach for water distribution networks to mitigate the risks associated with inaccurate real‐time electricity price forecasting. Our proposed method is designed to reduce the costs associated with inaccurate electricity price prediction. Key Points: A robust pump scheduling approach toward real‐time electricity price market is developedDeveloping a posteriori random forest algorithm to predict the probability density function of Real‐time electricity priceOptimal scheduling with risk constraints is an effective approach to mitigating the risks associated with inaccurate electricity forecasting [ABSTRACT FROM AUTHOR]

In this paper, a model is presented for modeling saturated granular‐liquid free‐surface flows, in which the volume‐averaged mixture bulk velocity is employed to derive the balance equations for the mass and momentum of mixture flow. Additionally, an evolution equation of the slip velocity between granular‐and liquid constituents is derived to describe the separation between these constituents. The frictional‐collisional constitutive relation for granular‐constituent is employed to determine the stress due to particles interaction. The governing equations for mixture flows are numerically solved by a finite difference two‐step projection method. The volume of fluid (VOF) method is employed to track the free surface of the mixture flow in the present numerical model. Good agreements between numerical results and experimental data are observed by modeling the dam‐break process of granular‐liquid mixture flow, dam‐break waves over the saturated erodible beds and surge waves induced by submarine landslides along an inclined plane. Furthermore, the difference between the volume‐averaged mixture bulk velocity and mass‐averaged mixture bulk velocity is found to vary as the instinct density ratio of granular‐constituent and liquid‐constituent and the volumetric concentration ns of the granular‐constituent, and the evolution in the slip velocity during the process of the settlement of sediments is numerically analyzed. Plain Language Summary: In this study, we developed a mathematical model for saturated granular‐liquid free‐surface flows, in which the volume‐averaged mixture bulk velocity is employed to describe the balance equations for the mass and momentum of the mixture flow of granular‐liquid flows and the evolution equation of the slip velocity between granular‐constituent and liquid‐constituent is derived to describe the separation between the granular‐constituent and liquid‐constituent. The stress due to the interaction of particles is determined based on the frictional‐collisional constitutive relations. The finite difference two‐step projection method is employed to numerically solve the governing equations and the volume of fluid (VOF) method is employed to track the free surface of the mixture flow in the present numerical model. Good agreements between numerical results and experimental data are observed. Finally, the role of slip velocity on the dynamics of granular‐liquid flows is analyzed. Key Points: A novel mathematical model for saturated granular‐liquid free‐surface flows is presentedGood agreements between the numerical results and experimental data are observedThe evolution of slip velocity plays a pivotal role in the dynamics of granular‐liquid flows [ABSTRACT FROM AUTHOR]

This study proposes a methodology for developing deterioration models and predicting the service lives of vertical assets of urban water systems (i.e., water storage tanks and pumping stations) using regression analysis. The main factors contributing to the deterioration of these assets are analyzed. Simple and multiple linear regression models of average and maximum deterioration are calculated for 22 water storage tanks and 17 wastewater pumping stations. Data on a set of four water storage tanks are used to validate the developed deterioration models. Service life prediction is carried out using the developed models and considering two maximum deterioration levels: the maximum recommended and admissible deterioration levels. Two water storage tanks are further studied to illustrate and discuss the effect of maintenance and rehabilitation interventions on asset service life by comparing the asset deterioration before and after the interventions. Results include simple linear regression models of average and maximum deterioration indices as a function of asset age and multiple linear regression models that incorporate other physical, operational and environmental factors. The results show that simple linear regression models of asset deterioration show a better predictive power than multiple regression models. Despite the higher data variability of multiple regression models, these models allow to include the random process of asset deterioration, through the calculation of the standard deviation. This study also shows that periodic interventions are a preferable maintenance and rehabilitation strategy over major sporadic rehabilitation interventions since it allows to maintain assets in good condition and to extend their service life almost indefinitely. Plain Language Summary: Urban water assets are continuously deteriorating and more investments are necessary to maintain adequate levels of service. However, investment budgets are often limited and appropriate deterioration models and reliably predicted service lives are essential for planning and scheduling maintenance actions. This paper develops deterioration models for water storage tanks and wastewater pumping stations based on the identification and classification of anomalies through visual inspection. Additionally, service lives (i.e., the period from the installation until the asset or its components fulfill the service requirements) were obtained and compared with reference values. Finally, the effect of maintenance actions and rehabilitation interventions on the service life of vertical assets was discussed. In order to maintain a good asset condition and extend its service life quasi‐indefinitely, periodic and well‐established interventions are a preferable maintenance and rehabilitation strategy over major sporadic rehabilitation interventions. Key Points: Physical, operational and environmental factors of asset deterioration are discussed and deterioration models are summarizedPredicted service lives are obtained and the effect of maintenance and rehabilitation interventions on asset service life are analyzedThe methodology for service life prediction can be applied to other water assets [ABSTRACT FROM AUTHOR]

Uncertainty arising from climate change poses a central challenge to the long‐term performance of many engineered water systems. Water supply infrastructure projects can leverage different types of flexibility, in planning, design, or operations, to adapt infrastructure systems in response to climate change over time. Both flexible planning and design enable future capacity expansion if‐and‐when needed, with flexible design proactively incorporating physical design changes that enable retrofits. All three forms of flexibility have not previously been analyzed together to explicitly assess their relative value in mitigating cost and water supply reliability risk. In this paper, we propose a new framework to evaluate combinations of flexible planning, design, and operations. We develop a nested stochastic dynamic optimization approach that jointly optimizes dam development and operating policies under dynamic climate uncertainty. We demonstrate this approach on a reservoir project near Mombasa, Kenya. Our results find that flexible operations have the greatest potential to reduce costs. Flexible design and flexible planning can amplify the value of flexible operations under higher discounting scenarios and when initial infrastructure capacities are undersized. This approach provides insight on the climate change and techno‐economic conditions under which flexible planning, design, and operations can be best leveraged individually or in combination to reduce climate change uncertainty risks in water supply infrastructure projects. Key Points: We develop a framework to compare the value of combinations of flexibility in water supply infrastructure planning, design, and operationsFlexible operations are more effective than flexible planning or design in addressing climate uncertainty in water‐limited environmentsFlexible planning and design are more useful when initial reservoir capacity is low, discounting is high, or the cost of shortages is high [ABSTRACT FROM AUTHOR]

With increasing demands for precise water resource management, there is a growing need for advanced techniques in mapping water bodies. The currently deployed satellites provide complementary data that are either of high spatial or high temporal resolutions. As a result, there is a clear trade‐off between space and time when considering a single data source. For the efficient monitoring of multiple environmental resources, various Earth science applications need data at high spatial and temporal resolutions. To address this need, many data fusion methods have been described in the literature, that rely on combining data snapshots from multiple sources. Traditional methods face limitations due to sensitivity to atmospheric disturbances and other environmental factors, resulting in noise, outliers, and missing data. This paper introduces Hydrological Generative Adversarial Network (Hydro‐GAN), a novel machine learning‐based method that utilizes modified GANs to enhance boundary accuracy when mapping low‐resolution MODIS data to high‐resolution Landsat‐8 images. We propose a new non‐saturating loss function for the Hydro‐GAN generator, which maximizes the log of discriminator probabilities to promote stable updates and aid convergence. By focusing on reducing squared differences between real and synthetic images, our approach enhances training stability and overall performance. We specifically focus on mapping water bodies using MODIS and Landsat‐8 imagery due to their relevance in water resource management tasks. Our experimental results demonstrate the effectiveness of Hydro‐GAN in generating high‐resolution water body maps, outperforming traditional methods in terms of boundary accuracy and overall quality. Plain Language Summary: This study addresses the imperative challenges of water resource management, including coastal zone oversight, detecting sea border shifts due to rising waters, and erosion tracking. Satellite data currently offers a choice between high spatial detail with infrequent updates or lower spatial detail with more frequent updates, presenting a trade‐off between data precision and frequency. To efficiently monitor environmental resources like water bodies, we require data with both high spatial detail and frequent updates. To meet this need, we introduce the Hydrological Generative Adversarial Network, a novel machine learning tool that enhances data clarity, particularly in outlining water bodies. In testing, we employed images from the Moderate Resolution Imaging Spectroradiometer satellite, providing less detailed images, and the Land Remote‐Sensing Satellite, offering highly detailed imagery. In essence, this study enhances water resource management by effectively combining data from multiple sources, even in adverse conditions, potentially advancing environmental protection and management efforts. Key Points: Remote sensing data augmentation for improving the accuracy of environmental assessments can be achieved using adversarial networksHigh spatiotemporal resolution of water bodies data enhances the precision of their areal forecastingShape and areal accuracies play an important role for efficient spatiotemporal data interpolation [ABSTRACT FROM AUTHOR]

Coupled simulations of surface and variably saturated subsurface flow, termed integrated hydrologic models (IHMs), can provide powerful insights into the complex dynamics of watersheds. The system of governing equations solved by an IHM is non‐linear, making them a significant computational burden and challenging to accurately parameterize. Consequently, a large fraction of the IHM studies to date have been "numerical hypothesis testing" studies, but, as parallel computing continues to improve, IHMs are approaching the point where they might also be useful as predictive tools. For this to become reality, the predictive uncertainty of such highly parameterized simulations must be considered. However, uncertainty is seldom considered in the IHM literature, likely due to the long runtimes of the complex simulations. The questions considered herein are how much uncertainty is there in an IHM for a common watershed simulation scenario, and how likely is it that any one realization of a system will give the same relative change as any other due to a perturbation in recharge? A stochastic ensemble of 250 permeability field realizations was used to show that uncertainty in a high‐mountain headwaters systems is dominated by the subsurface. Recharge perturbation scenarios echo these results, but the uncertainty of changes in streamflow or groundwater pressure heads were significantly smaller than the uncertainty in their base‐case values. The main finding is that IHMs do provide confident, predictive estimates of relative changes in watersheds, even when uncertainty in specific simulation outputs may be high. Plain Language Summary: Watershed simulations that consider stream‐groundwater interactions require the specification of lots of parameters to define the model but there is often little data to base those parameters on. Consequently, simulation results have uncertainty and if it is not quantified then any predictions made by these models have no "plus‐or‐minus" factors, giving an illusion of high confidence. The catch is that quantifying uncertainty is computationally expensive, which is why it is seldom done, yet at some point the uncertainty must be explored if these models are to be used for predictions. The work in this paper assesses the variability of predictions for a "typical" watershed simulation under three different rainfall scenarios using an ensemble of 250 random versions of the system. The results show that groundwater has higher variability than surface flows, meaning the latter is simulated with higher confidence. However, an important finding is that the relative changes due to the changes in the rainfall were generally consistent across the ensemble. The main point is that even with limited confidence in what an output will be, the relative change of that output (e.g., a 10% increase in recharge increases streamflow by 10%) can likely be inferred with much greater confidence. Key Points: Ensemble simulations of coupled surface‐subsurface flows in a high mountain watershed were performed using the numerical model ParFlowUncertainty throughout the simulation domain was significant and was dominated by the subsurface domainRelative changes in the surface‐ and groundwater values due to a perturbation had smaller confidence intervals than the base‐case values [ABSTRACT FROM AUTHOR]

In this Reply, we address the concerns of Knoben and Clark (2023, https://doi.org/10.1029/2022WR034294) or KC23 that "the assumptions needed to effectively use difference‐based variance estimation methods are not always met by hourly streamflow records." There should be little doubt that the assumptions of our difference‐based estimator will sometimes be violated in hourly streamflow records but the results from de Oliveira and Vrugt (2022, https://doi.org/10.1029/2022wr032263) and confirmed by the findings in our Reply show that such violations are sporadic enough not to affect much the error variance estimates. Snowmelt as pointed out by KC23 (https://doi.org/10.1029/2022WR034294) may not have received sufficient attention in our paper, yet their 365‐day record is simply not long enough to demonstrate bias of our discharge error variance estimates (and their dependence on flow level). This would require analysis of a much longer, multi‐year, streamflow record of a snowmelt‐driven watershed. The snowmelt catchment analyzed in dOV22 (https://doi.org/10.1029/2022wr032263) did not demonstrate bias in the discharge error variance estimates. We also provide additional clarification on the interpretation of the variance estimates obtained with the nonparametric estimator, and discuss the main issues in the test case presented in Knoben and Clark (2023, https://doi.org/10.1029/2022WR034294)). Key Points: We address the concerns of Knoben and Clark (2023) on the use of the nonparametric estimator with hourly discharge dataWe provide further clarification on the interpretation of the variance estimates obtained with the nonparametric estimator [ABSTRACT FROM AUTHOR]

The intermittent water supply (IWS) of water distribution systems is a common practice caused by the imbalance between available water resources and customers' demands. Transition to the continuous water supply (CWS) is desirable to reduce quality, equity distribution, and pipe integrity issues but is often practically unachievable in the short or medium term. The World Bank funded a laboratory activity at the Water Engineering laboratory of the University of Perugia, Italy, to investigate how remedies can be introduced to mitigate the impacts of IWS and preserve pipe integrity, facilitating the transition from IWS to CWS. The results of the tests with different feeding conditions, downstream outflows, and air valve dimensions and locations are described and discussed in this paper, culminating in typical interventions that can be implemented to reduce, if not completely eliminate, the undesirable consequences. Plain Language Summary: Almost one billion people worldwide are estimated to receive water intermittently, especially in low‐ and middle‐income countries. Intermittent supply has a significant impact on the water quality, equity of water distribution among users, accuracy of the customer meters, and the structural condition of the pipes. Water distribution systems are not usually designed for such an operating approach, and interventions are required to preserve the pipe integrity, particularly in the transition to a continuous water supply. The World Bank funded a laboratory investigation to assess in a controlled environment the causes of the harmful consequences and the remedies that can be introduced to alleviate their impact. This study is of importance not only in preserving existing networks in the transition to a continuous supply situation but also in ensuring that the large sums being invested in new infrastructure will not be wasted. Key Points: Transition from intermittent to continuous water supply of water distribution systems could be unachievableA laboratory investigation of effects and remedies that can be introduced to mitigate the impacts of intermittent water supply is presentedAir release valve design and location and control of the upstream conditions are crucial and must be properly analyzed [ABSTRACT FROM AUTHOR]

This paper focuses on deriving new approximate analytical solutions in wedge‐shaped aquifers. The proposed methodology is applicable to any type of aquifer namely, leaky, confined and unconfined, under both steady state and transient flow conditions. By applying the method of images and separating the flow field into sections using physical arguments, approximate analytical expressions are obtained for the drawdown function, which in contrast to the conventional theory, are applicable to any arbitrary wedge angle. Moreover, the solutions fully observe the boundary conditions, while they preserve the continuity of the drawdown, which can be calculated directly at any point of the flow field. Nevertheless, comparison of the results of the new approximate analytical solutions to numerical ones, has been considered necessary to check their validity. MODFLOW, a well‐known numerical tool is used to calculate the numerical results. The discrepancies between the numerical results and those of the approximate analytical solution are negligible. The main advantages of the proposed methodology are the following: (a) The model needs only finite number of terms compared to conventional analytical and numerical solutions that involve infinite series, (b) The computational load is low, so it can be easily used in conjunction with meta‐heuristic algorithms to solve groundwater resources optimization problems, (c) Stream depletion rate can be calculated rather accurately and (d) The method is applicable to related flow problems. Key Points: New functions for drawdown calculation in wedge‐shaped aquifers are presentedThe proposed functions are suitable to be used in conjuction with meta‐heuristic algorithms to solve groundwater optimization problemsConvergence of the results obtained from the set of functions and numerical methods (MODFLOW) point out the validity of the proposed solutions [ABSTRACT FROM AUTHOR]

Stochastic methods have been typically used for the design and operations of hydraulic infrastructure. They allow decision makers to evaluate existing or new infrastructure under different possible scenarios, giving them the flexibility and tools needed in decision making. In this paper, we present a novel stochastic streamflow simulation approach able to replicate both temporal and spatial dependencies from the original data in a multi‐site basin context. The proposed model is a multi‐site extension of the modified Fractional Gaussian Noise (mFGN) model which is well‐known to be efficient to maintain periodic correlation for several time lags, but presents shortcomings in preserving the spatial correlation. Our method, called Weighted‐mFGN (WmFGN), incorporates spatial dependency into streamflows simulated with mFGN by relying on the Cholesky decomposition of the spatial correlation matrix of the historical streamflow records. As the order in which the decomposition steps are performed (temporal then spatial, or vice‐versa) affects the performance in terms of preserving the temporal and spatial correlation, our method searches for an optimal convex combination of the resulting correlation matrices. The result is a Pareto‐curve that indicates the optimal weights of the convex combination depending on the importance given by the user to spatial and temporal correlations. The model is applied to a number of river basins in Chile, where the results show that the WmFGN approach maintains the qualities of the single‐site mFGN, while significantly improving spatial correlation. Key Points: Weighted modified Fractional Gaussian Noise model improves spatial correlations without significantly sacrificing temporal correlationThe method searches for an optimal convex combination of the spatial and temporal correlation matrices according on the user's priorityOur results in several Chilean basins demonstrate that Weighted‐modified Fractional Gaussian Noise (WmFGN) represents a significant improvement over the mFGN in preserving correlations [ABSTRACT FROM AUTHOR]

Operator choices, both in acquiring the video and data and in processing them, can be a prominent source of error in image‐based velocimetry methods applied to river discharge measurements. The Large Scale Particle Image Velocimetry (LSPIV) is known to be sensitive to the parameters and computation choices set by the user, but no systematic comparisons with discharge references or intercomparisons have been conducted yet to evaluate this operator effect in LSPIV. In this paper, an analysis of a video gauging intercomparison, the Video Globe Challenge 2020, is proposed to evaluate such operator effect. The analysis is based on the gauging reports of the 15 to 23 participants using the Fudaa‐LSPIV software and intents to identify the most sensitive parameters for the eight videos. The analysis highlighted the significant impact of the time interval, the grid points and the filters on the LSPIV discharge measurements. These parameters are often inter‐dependent and should be correctly set together to strongly reduce the discharge errors. Based on the results, several automated tools were proposed to reduce the operator effect. These tools consist of several parameter assistants to automatically set the orthorectification resolution, the grid and the time interval, and of a sequence of systematic and automatic filters to ensure reliable velocity measurements used for discharge estimation. The application of the assisted LSPIV workflow using the proposed tools leads to significant improvements of the discharge measurements with strong reductions of the inter‐participant variability. On the eight videos, the mean interquartile range of the discharge errors is reduced from 17% to 5% and the mean discharge bias is reduced from −9% to 1% with the assisted LSPIV workflow. The remaining inter‐participant variability is mainly due to the user‐defined surface velocity coefficient α. Key Points: Video‐based river discharge measurements are sensitive to both measuring conditions and user‐defined parameters and optionsThe sensitivity of Large Scale Particle Image Velocimetry discharge computations to operator choices is quantified through a video streamgauging intercomparisonProposed automatic settings and spurious velocity filters efficiently reduce discharge biases and inter‐operator variability [ABSTRACT FROM AUTHOR]

Water distribution systems (WDSs) are critical infrastructure used to convey water from sources to consumers. The mathematical framework governing the distribution of flows and heads in extended period simulations of WDSs lends itself to application in a wide range of optimization problems. Applying the classical mixed integer linear programming (MILP) approach to model WDSs hydraulics within an optimization framework can contribute to higher solution accuracy with lower computational effort. However, adapting WDSs models to conform to a MILP formulation has proven challenging because of the intrinsic non‐linearity of system hydraulics and the complexity associated with modeling hydraulic devices that influence the state of the WDS. This paper introduces MILPNet, an adjustable framework for WDSs that can be used to build and solve an extensive array of MILP optimization problems. MILPNet includes constraints that represent the mass balance and energy conservation equations, hydraulic devices, control rules, and status checks. To conform to MILP structure, MILPNet employs piece‐wise linear approximation and integer programming. MILPNet was implemented and tested using Gurobi Python API. Modeling accuracy was shown to be comparable to EPANET, a public domain software for hydraulic modeling, and sensitivity analyses were conducted to examine the impacts of the modeling assumptions on the performance of MILPNet. Additionally, application of the framework was demonstrated using pump scheduling optimization examples in single and rolling horizon scenarios. Our results show that MILPNet can facilitate the construction and solution of optimization problems for a range of applications in WDSs operations. Key Points: A mixed‐integer linear programming framework (MILPNet) for formulating and solving water distribution system optimization problems is presentedMILPNet models system dynamics, hydraulic devices, control rules, and status checks and is flexible to adding more devices and conditionsThe optimization model can be generated from a.INP file and case‐specific objectives and constraints can be specified via Python interface [ABSTRACT FROM AUTHOR]

Whole lake residence time has been associated with various water quality parameters, including harmful algal blooms. Despite observations of spatial variability in commonly measured lake water quality parameters, little attention is given to the spatial variability of residence time in lakes. In this paper we use water age as a surrogate for residence time and we examine its spatial and temporal distribution in 10 bays of varying size in Lake George, New York (USA). Using a validated hydrodynamic model against observations of water temperature and water currents, and using simulated water age, we show that the average residence time in most of the bays is less than 3 days. Timeseries of bay‐average water age shows that it can sharply decrease within 1 day due to a strong wind event. The average spatial distribution is shown to be non‐uniform, with only a small section of the bottom layer of the bays having a substantially greater age, which may be more than 1 week in certain bays. Snapshots of water age transects indicate that strong wind events substantially change the vertical distribution of water age in some bays, even to the extent of inverting the distribution. The substantial decreases of water age in the bays were associated with the shallowing and deepening of the thermocline. Our results highlight how variations in water residence times within lakes could introduce substantial variation in water quality attributes. Whole lake residence times may serve as a poor proxy to understand the dynamics of water masses, especially in large and morphologically complex waterbodies. Key Points: Simulation of water age with a validated hydrodynamic model against temperature and currentsAverage water age (surrogate to residence time) in bays is smaller than 6 daysSpatial distribution of water age within bays is not uniform and strong wind events lead to lower water age within 1 day [ABSTRACT FROM AUTHOR]

Groundwater pumping from wells, together with water uses such as agricultural irrigation have been converting formerly open groundwater basins into closed systems that accumulate total dissolved solids (TDS). This process of anthropogenic basin closure and salinization (ABCSal) would appear to pose a threat to groundwater sustainability that is at least as formidable as groundwater overdraft and contamination from the surface, yet has been little explored. Models of groundwater flow and solute transport herein show that groundwater basin openness itself should be considered a primary determinant of sustainability. Results show that groundwater basin closure is a threshold condition that sets the aquifer system on a path of increasing salinity that can only be halted by opening the basin. Further, the magnitude of groundwater pumping and degree of basin closure significantly influence the spatial distribution of salinity. In open basins, salinity approaches dynamic equilibrium over long‐term conditions. Stratification of higher‐TDS groundwater overlying lower‐TDS groundwater occurs below farmlands whose irrigation‐supplying wells are impacted by irrigation return flow from upstream farmlands, and act to redistribute relatively saline groundwater to the land surface. More intensive pumping leads to groundwater basin closure and more vertically‐oriented groundwater flow toward pumping wells. TDS retainment in the basin and repeated well capture, re‐distribution as irrigation water, and evapoconcentration lead to progressive salinization. Regardless of basin closure status, fresh recharge protects nearby downstream portions of the basin from salinization, indicating that managing or limiting the spread of contaminated groundwater may be achieved via managed aquifer recharge of good quality water. Plain Language Summary: This paper presents hydrologic basin openness, the degree to which inflow of groundwater is balanced by non‐evaporative outflow, as a new criteria for groundwater sustainability. Water use practices such as irrigation and groundwater pumping have in many cases been reducing groundwater basin openness, promoting accumulation of dissolved intrabasin salts. State‐of‐the‐art but simple groundwater models demonstrate the spatiotemporal dynamics of this Anthropogenic Basin Closure and groundwater Salinization (ABCSal) process. Simulations show that significant salinization with total dissolved solids concentration exceeding 1,000 to 6,000 mg/L can occur in large portions of a basin within two to six centuries. Strength of pumping and the degree of basin closure significantly influence spatial extent and organization of zones with different salinities. Structured salinization zones and relatively low salinity levels downstream of fresh recharge areas indicate viable water management strategies (e.g., managed aquifer recharge of good quality water) for coping with ABCSal consequences. However, maintaining sufficient groundwater basin openness is required to avoid ABCSal, necessitating a different paradigm of integrated water resources management with much greater emphasis on subsurface storage of water and more modern and intensive monitoring of the groundwater system state to ensure a sustainable evolution trajectory of both groundwater quantity and quality. Key Points: Groundwater pumping and irrigation cause progressive groundwater salinization that can be halted only by maintaining enough basin opennessGroundwater development strength influences groundwater flow pattern and salt load, and ultimately, the salinization pattern and intensityDistinct zones of different salinity levels establish under open and closed basin status [ABSTRACT FROM AUTHOR]

River networks are not steady blue lines drawn in a map, since they continuously change their shape and extent in response to climatic drivers. Therefore, the flowing length of rivers (L) and the corresponding catchment‐scale streamflow (Qsur) co‐evolve dynamically. This paper analyzes the relationship between the wet channel length and the streamflow of a river basin, formulating a general analytical model that includes the case of temporarily dry outlets. In particular, the framework relaxes the common assumption that when the discharge at the outlet tends to zero the upstream flowing length approaches zero. Different analytical expressions for the L(Qsur) law are derived for the cases of (a) a perennial outlet; (b) a non‐perennial outlet that dries out only when the whole network is dry; and (c) a temporarily dry outlet, that experiences surface flow for less time than other network nodes. In all cases, the shape of the L(Qsur) relationship is controlled by the distribution of the specific subsurface discharge capacity along the network. For temporarily dry outlets, however, the relation between L and Qsur might depend on an unknown shifting factor. Three real‐world examples are presented to demonstrate the flexibility and the robustness of the theory. Our results indicate that the whole shape of the L(Qsur) relation might not be empirically observable if a significant fraction of the network is perennial or some reaches in the network experience surface flow for longer than the discharge gauging station. The study provides a basis for integrating empirical L(Qsur) data gathered in diverse sites. Key Points: Active network length (L) versus catchment discharge (Qsur) relations are extended to temporarily dry outletsAll the L(Qsur) relations represent translations/truncations of the spatial cumulative distribution of the specific subsurface capacityThe L(Qsur) law is not fully visible if the outlet is less persistent than other network nodes (as in a spring‐fed stream drying upward) [ABSTRACT FROM AUTHOR]

Future water availability is threatened by changes in both climate and water demand. Water rights with differing priorities are an important foundation of demand‐side tools (e.g., buyback, water pricing, and water market) to improve water use efficiency and reduce water scarcity, especially in highly regulated river systems. This paper assesses the impact of climate change on water yields from carryover storage with dual‐priority (high/low) water rights allocation systems using a simple and rapid analytical method. The method characterizes reservoir inflows using readily available flow characteristics (annual mean and Cv). We evaluate this method against a water resource simulation model in the Goulburn River basin, Australia. In general, our analytical "dual‐priority" Gould‐Dincer model reproduces water allocation estimates from the simulation model. We further demonstrate this method across 12 Australian catchments to investigate the climate change impact on "dual‐priority" water rights yield at the catchment scale. The hydrological projections show decreasing mean annual runoff and increasing annual runoff variability, except for some catchments in northern Australia. Water yield for high‐priority water rights (HPWRs) and low‐priority water rights (LPWRs) decreases for most catchments except for some catchments in northern Australia. South Dandalup in the 2070s (RCP8.5) shows the largest percentage decrease in HPWR and LPWR yield (about −53.53% and −56.81%, respectively). Our results show that changes in mean annual inflow have a more significant influence on water yield of HPWR and LPWR than Cv. Overall, the simple method provides a rapid assessment of water yields with "dual‐priority" water rights which is applicable across multiple sites at regional or even global scale. Key Points: A simple analytical method is used to evaluate the impact of climate change on the yield of "dual‐priority" water rightsWater yield for both high‐ and low‐priority water rights generally decreases under future climate in AustraliaFuture change in mean annual inflow has a more significant influence on water yield than change in annual flow variability [ABSTRACT FROM AUTHOR]

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi‐objective and transferability studies by exploring the value of both multi‐basin and spatial pattern calibration of distributed hydrologic models as compared to single‐basin and single‐objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns. Several model validation experiments are performed through combinations of single‐ (temporal evaluation through discharge) and multi‐objective (temporal and spatial evaluation through discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi‐basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets. Plain Language Summary: Hydrological models typically require local observations of river flow to calibrate the models and test their predictive capability. This limits the possibility for predictions in ungauged basins. This study used holdout tests to investigate the robustness of hydrological predictions for ungauged basins. Particularly we investigate how adding more basins and observed spatial patterns of evapotranspiration in the calibration of these models impact this robustness and transferability of model parameters to basins not used for calibration. Results show that transferability and spatial consistency of parameters increase when adding more basins and spatial pattern observations. Key Points: Clear improvements in simulated spatial patterns can be achieved with very limited tradeoff with discharge performanceMulti‐basin and spatial pattern‐based calibration improve parameter realism and transferability to ungauged basins [ABSTRACT FROM AUTHOR]