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In a study from 2008, Larivière and colleagues showed, for the field of natural sciences and engineering, that the median age of cited references is increasing over time. This result was considered counterintuitive: with the advent of electronic search engines, online journal issues and open access publications, one could have expected that cited literature is becoming younger. That study has motivated us to take a closer look at the changes in the age distribution of references that have been cited in water resources journals since 1965. Not only could we confirm the findings of Larivière and colleagues. We were also able to show that the aging is mainly happening in the oldest 10-25% of an average reference list. This is consistent with our analysis of top-cited papers in the field of water resources. Rankings based on total citations since 1965 consistently show the dominance of old literature, including text books and research papers in equal shares. For most top-cited old-timers, citations are still growing exponentially. There is strong evidence that most citations are attracted by publications that introduced methods which meanwhile belong to the standard toolset of researchers and practitioners in the field of water resources. Although we think that this trend should not be overinterpreted as a sign of stagnancy, there might be cause for concern regarding how authors select their references. We question the increasing citation of textbook knowledge as it holds the risk that reference lists become overcrowded, and that the readability of papers deteriorates. [ABSTRACT FROM AUTHOR]

Groundwater (GW) is commonly conceptualized as causally linked to streamflow (SF). However, confirming where and how it occurs is challenging given the expense of experimental field monitoring. Therefore, hydrological modeling and water management often rely on expert knowledge to draw causality between SF and GW. This paper investigates the potential of convergent cross‐mapping (CCM) to identify causal interactions between SF and GW head. Widely used in ecology, CCM is a nonparametric method to identify causality in nonlinear dynamic systems. To apply CCM between variables the only required inputs are time‐series data (stream gauge and bore), so it may be an attractive alternative or complement to expensive field‐based studies of causality. Three upland catchments across different hydrogeologic settings and climatic conditions in Victoria, Australia, are adopted as case studies. The outputs of the method seem to largely agree with a priori perceptual understanding of the study areas and offered additional insights about hydrological processes. For instance, it suggested weaker SF‐GW interactions during and after the Millennium Drought than in the previous wet periods. However, we show that CCM limitations around seasonality, data sampling frequency, and long‐term trends could impact the variability and significance of causal links. Hence, care must be taken while physically interpreting the causal links suggested by CCM. Overall, this study shows that CCM can provide valuable causal information from common hydrological time‐series, which is relevant to a wide range of applications, but it should be used and interpreted with care and future research is needed. Plain Language Summary: It is common in hydrology to assume that the water below the ground (in aquifers) interacts with the rivers. However, it is challenging to identify where and how it occurs with the available data and financial resources. Therefore, we often use computer models that represent these interactions according to the knowledge of experts. This paper investigates the potential of convergent cross‐mapping (CCM), a method that is widely used in ecology, to identify these interactions. This method only requires time‐series data (e.g., streamflow and groundwater level data) and represents an attractive alternative or complement to expensive field‐based studies. The results of the analysis appear to agree with an initial understanding of the aquifer‐river interactions in three study areas in Victoria, Australia, and offered additional insights. For instance, it suggests weaker interactions during and after the Millennium Drought than in the previous wet periods. However, variability and significance of the causal links inferred by CCM can be due to some limitations of the method. Hence, care must be taken while physically interpreting the results. Overall, CCM can unlock valuable information from common data, which is relevant to hydrology, but it should be used and interpreted with care and future research is needed. Key Points: Convergent cross‐mapping (CCM) is a nonparametric method to identify causality in nonlinear dynamic systems that is widely used in ecologyCCM results suggest heterogeneous causal links that are largely consistent with perceptual understanding of processesCCM seems widely applicable in hydrology, but also has limitations and thus should be used and interpreted with care [ABSTRACT FROM AUTHOR]

Hydraulic connections between a river and an adjacent aquifer are controlled by the river resistance and aquifer diffusivity. In this paper, we derive a spectral solution linking the power spectrum of river stage fluctuations to that of the hydraulic head of a confined aquifer by means of a physical scaling factor. The physical scaling factor represents an algebraic expression of the river resistance and aquifer diffusivity and is included in an exact spectral solution derived herein. Statistical measures of the aquifer diffusivity and river resistance are provided by fitting the solution versus observed groundwater hydraulic head obtained at several distances and/or frequencies. At a study site in the middle reach of the Yangtze River and downstream of the Three Gorges Dam in China, we find systematic damping of the hydraulic head variations with distance from the river, which follows a fractal pattern driven by the river stage. In general, the estimated parameters are consistent with results reported in the literature, which supports the validity of the proposed spectral approach, although the paper discusses advantages and limitations due to application conditions. Plain Language Summary: The characterization of hydraulic connections between a river and an adjacent aquifer requires knowledge of two critical parameters: the river resistance and the aquifer diffusivity. In this paper, we derive a spectral solution to link the power spectrum of river stage fluctuations to that of the groundwater hydraulic head in a confined aquifer and show how such solutions can be used to simultaneously assess the two critical parameters. Parameters estimated from the field case located in the middle reach of the Yangtze River and downstream of the Three Gorges Dam in China are consistent with results reported in the literature. Application conditions, advantages, and limitations of this spectral approach are also discussed. Key Points: The power spectrum of the hydraulic head is linked to that of the river stage by a scaling factorRiver resistance and aquifer diffusivity are analyzed in spectral formsTheoretical developments are applied to a field case study of the Yangtze River, China [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]

Many regions around the world are transitioning out of open access to groundwater resources in order to tackle over extraction by irrigated agriculture. However, the state has limited capacities to regulate effectively agricultural groundwater use. This paper evaluates how users and public authorities can co‐manage groundwater extraction by agriculture. Based on Schlager and Ostrom's "bundle of rights" framework, the paper examines how decisions over access and use of groundwater resources are made in France, Spain and California. The three cases share a common strive to involve groundwater users in decisions over how to reduce over extraction of groundwater resources. However, different choices were made regarding the institutional set‐up for user involvement in allocation decisions. The paper presents the diversity of institutional arrangements influencing groundwater allocations in the three cases, and the relative involvement and power of users and public authorities over these institutions. The papers show the different ways in which "comanagement" may be made operational for managing agricultural groundwater use. Key Points: The paper presents institutional mechanisms influencing allocation decisions in agriculture in France, Spain, and CaliforniaAn evolution is observed toward greater oversight over operational rights of accessing and withdrawing groundwaterA system of check‐and‐balances are needed to ensure that all three sustainability pillars (economic, social, environmental) are met [ABSTRACT FROM AUTHOR]

Hydrogeological barriers can significantly impact groundwater model predictions. They are, however, often excluded from, or misrepresented in, groundwater models if their presence is unknown or their properties are poorly constrained. Here we show that sharp barriers can be included in groundwater model inversion, even where their presence is uncertain. We describe an approach utilizing "phantom structures"—randomly located, linear groups of model cells assigned a unique hydraulic conductivity value—to improve identifiability of barriers. Algorithmic parameter estimation using model‐independent parameter estimation code (PEST) is implemented to determine model structures that best match the hydraulic head and groundwater age observation data from a hypothetical aquifer. Our results show that for a series of case studies, this method was successful in inferring the appropriate location and properties of hydrogeological barriers, when that barrier was not aligned with the dominant flow direction. We compare these results to model inversion using traditional pilot points. The phantom structures approach shows promise in identifying hydrogeological structures and in reproducing groundwater flow across a model domain. Our results demonstrate that the geometric properties of geological structures can remain flexible in a model inversion. This is a step toward reducing conceptual model uncertainty where the presence and properties of hydrogeologic barriers are undefined. Plain Language Summary: Understanding the geological characteristics of a region can be very challenging. This is particularly true if the region contains narrow, linear structures known as faults and dykes. However, these structures can be important when it comes to defining the flow of groundwater. Many faults and dykes obstruct groundwater flow, so may inhibit groundwater availability to rivers and ecosystems or to other groundwater users. In this paper, a methodology is introduced that uses commonly collected hydrogeological datasets (known as hydraulic head and groundwater age) to discover the location, shape and physical properties of certain geological structures in the subsurface. The method relies on "inverse approaches", where data observed in the field is compared to a modeled equivalent. This method of incorporating narrow, linear structures in groundwater models results in a better match between field and modeled data when compared to another approach that relies on representing faults and dykes as broader, flatter, smoother geological anomalies. Key Points: A method for including hydrogeological barriers in model inversion is developed using a regularization device we call phantom structuresNarrow, low‐permeability structures such as faults and dykes are included in model inversions with no prior knowledge of their geometriesInverting models with phantom structures provide improved results compared to using pilot points for a wide range of conditions [ABSTRACT FROM AUTHOR]

Groundwater response to climate variations is often pivotal to managing groundwater sustainably. However, this relationship is rarely explicitly examined because of the complexity of surface to subsurface processes and the diverse impacts of multiple drivers, such as groundwater pumping and land use changes. In this paper, we address this challenge by proposing methods to quantify the sensitivity of groundwater level and recharge to temporal climate variability across Australia. Using the HydroSight groundwater hydrograph toolbox we first identify 1,143 out of a total of 4,350 bores as climate‐driven, where historically, head was primarily driven by climate variations. Streamflow elasticity measures are then adapted to groundwater to quantify the long‐term head and recharge sensitivity. We find that the national median sensitivity of head and recharge to precipitation change are 42 and 0.43 mm mm−1, respectively (interquartiles: 20–77 and 0.30–0.55 mm mm−1); both of which are ∼8 times that of potential evapotranspiration. Nationally, the results are spatially correlated, suggestive of large‐scale effects. The responses of head and recharge appear to be primarily related to climate type and hydrogeology. The more arid the climate, the higher the head sensitivity but the lower the recharge sensitivity. Porous media generally show higher head sensitivity than fractured media due to smaller aquifer specific yield, and again contrarily for that of recharge. These findings contribute to understanding the long‐term impact of climate change on groundwater and thus provide valuable insights for sustainable groundwater management. Plain Language Summary: In this study, we assess the response of groundwater to meteorological variations by using long‐term groundwater level records across Australia. We first identify the sites where the groundwater level has been primarily impacted by climate variations alone. The changes in groundwater level and replenishment rate (also called "recharge") at the natural sites are simulated under a range of precipitation and evapotranspiration shifts and their relationships are statistically quantified. Results show that the national median groundwater level changes by 42 mm and the recharge changes by 0.43 mm per 1 mm change in precipitation. The response of groundwater level and recharge are found to be primarily governed by the inherent properties of the sites, such as climate type and hydrogeology. This study provides valuable insights into climate change impacts on groundwater availability and contributes to developing adaptive water management strategies. Key Points: Climate‐dominated groundwater bores throughout Australia are statistically identified (n = 1,143, 26%)Median head and recharge sensitivity to precipitation are 42 and 0.43 mm mm−1Head and recharge sensitivity are primarily controlled by climate type and hydrogeology [ABSTRACT FROM AUTHOR]

Trace metals in the groundwater of coastal sandy aquifers significantly influence the coastal ecosystem, yet the spatiotemporal controls of these metals remain unclear. In this paper, we comprehensively revealed the distribution patterns, key controlling factors, potential ecological risks, and fluxes to the ocean of groundwater trace metals (As, Ba, Cr, Cd, Fe, Mn, Pb, and Zn) in a coastal deep sandy aquifer. The results showed a clear zonation of trace metals in the groundwater in relation to the mixing extent between seawater and terrestrial freshwater. The freshwater zone exhibited a relatively low concentration of trace metals, whereas the freshwater‐seawater transition zone showed a substantial quantity of dissolved Fe, Mn, As, and Ba. Seawater‐groundwater interactions significantly affected the Fe, Mn, As, and Ba concentrations through redox potential and pH gradients. The tide‐driven saline water zone was vulnerable to oceanic environments and anthropogenic activities, resulting in the enrichment of trace metals such as Zn and Cd. Driven by recirculated submarine groundwater discharge (SGD), the concentrations of trace metals in the density‐driven saline circulation zone were found to be higher than those in the surrounding areas. The ecological risk index suggested that the freshwater‐seawater transition zone posted the highest ecological risks. Trace metal fluxes (i.e., Fe, Mn, and As) via SGD significantly contributed to the total input into the sea, which may have potential impacts on the coastal environments. Our study highlighted the importance of seawater‐groundwater interactions on trace element cycling in coastal sandy aquifers. Key Points: The distribution of groundwater trace metals in a coastal deep sandy aquifer with different seasons was investigated, and four zones were identifiedKey controlling factors, ecological risks, and fluxes of trace metals in different zones were evaluatedSeawater‐groundwater interactions aiding trace metal addition/removal insfluenced trace element cycling on a sandy coast [ABSTRACT FROM AUTHOR]

To address groundwater issues, it is often necessary to develop geological and hydrogeological models. Combining geological, geophysical and hydrogeological data available on a site to build such models is often a challenge. This paper presents a methodology to integrate such data within a geologically consistent model with robust error estimation. The methodology combines the Ensemble Smoother with Multiple Data Assimilation (ESMDA) algorithm with a hierarchical geological modeling approach (ArchPy). Geophysical and hydrogeological field data are jointly assimilated in a stochastic ESMDA framework. To speed up the inversion process, forward responses are computed in lower‐dimensional spaces relevant to each physical problem. By doing so, the final models take into account multiple data sources and regional conceptual geological knowledge. This study illustrates the applicability of this novel approach using actual data from the upper Aare Valley, Switzerland. The results of cross‐validation show that the combination of different data types, each sensitive to different spatial dimensions, enhances the quality of the model within a reasonable computing time. The proposed methodology allows the automatic generation of groundwater models with robust uncertainty estimation and could be applied to a wide variety of hydrogeological issues. Plain Language Summary: When dealing with groundwater, it is necessary to develop underground models. However, taking into account all the different data types on a site is time‐consuming, and there is a lack of uncertainty quantification. In this study, we develop an approach that automatically combines different types of data, including boreholes, geophysical data, and hydrogeological measurements. All data are combined using a stochastic algorithm and produce an ensemble of plausible and data‐compatible models. These models can be used, for example, to forecast groundwater availability, pollutant distribution, or the effect of climate change on groundwater. Key Points: A methodology is proposed to assimilate geological, hydrogeological, and geophysical data in consistent stochastic modelsThe methodology combines a hierarchical geological modeling technique with the ensemble smoother with multiple data assimilationThe applicability of the methodology is demonstrated using actual field data from the upper Aare valley aquifer in Switzerland [ABSTRACT FROM AUTHOR]

The article presents the authors' reply to S. Neuman's comments which advocates the need for an adequate hydrogeological characterization of aquifers. It provides a brief summary of their work that was overlooked by Neuman's comment which include a critical reexamination of the field data collected by L.W. Gelhar et al especially those referred to as of medium or low reliability and the addition of new data what were again screened for reliability.

In geostatistics, Gaussian random fields are often used to model heterogeneities of soil or subsurface parameters. To give spatial approximations of these random fields, they are discretized. Then, different techniques of geostatistical inversion are used to condition them on measurement data. Among these techniques, Markov chain Monte Carlo (MCMC) techniques stand out, because they yield asymptotically unbiased conditional realizations. However, standard Markov Chain Monte Carlo (MCMC) methods suffer the curse of dimensionality when refining the discretization. This means that their efficiency decreases rapidly with an increasing number of discretization cells. Several MCMC approaches have been developed such that the MCMC efficiency does not depend on the discretization of the random field. The preconditioned Crank Nicolson Markov Chain Monte Carlo (pCN‐MCMC) and the sequential Gibbs (or block‐Gibbs) sampling are two examples. This paper presents a combination of both approaches with the goal to further reduce the computational costs. Our algorithm, the sequential pCN‐MCMC, will depend on two tuning‐parameters: the correlation parameter β of the pCN approach and the block size κ of the sequential Gibbs approach. The original pCN‐MCMC and the Gibbs sampling algorithm are special cases of our method. We present an algorithm that automatically finds the best tuning‐parameter combination (κ and β) during the burn‐in‐phase of the algorithm, thus choosing the best possible hybrid between the two methods. In our test cases, we achieve a speedup factors of 1–5.5 over pCN and of 1–6.5 over Gibbs. Furthermore, we provide the MATLAB implementation of our method as open‐source code. Key Points: A hybrid MCMC between the sequential Gibbs and the pCN‐MCMC approach is presentedThis hybrid MCMC is more efficient than both special casesWe present an adaptive algorithm to optimize the hyper‐parameters of this hybrid MCMC during burn‐in [ABSTRACT FROM AUTHOR]

Critical zone science seeks to develop mechanistic theories that describe critical zone structure, function, and long-term evolution. One postulate is that hydrogeochemical controls on critical zone evolution can be inferred from solute discharges measured down-gradient of reactive flow paths. These flow paths have variable lengths, interfacial compositions, and residence times, and their mixing is reflected in concentration-discharge (C-Q) relations. Motivation for this special section originates from a U.S. Critical Zone Observatories workshop that was held at the University of New Hampshire, 20-22 July 2015. The workshop focused on resolving mechanistic CZ controls over surface water chemical dynamics across the full range of lithogenic (e.g., nonhydrolyzing and hydrolyzing cations and oxyanions) and bioactive solutes (e.g., organic and inorganic forms of C, N, P, and S), including dissolved and colloidal species that may cooccur for a given element. Papers submitted to this special section on "concentration-discharge relations in the critical zone" include those from authors who attended the workshop, as well as others who responded to the open solicitation. Submissions were invited that utilized information pertaining to internal, integrated catchment function (relations between hydrology, biogeochemistry, and landscape structure) to help illuminate controls on observed C-Q relations. [ABSTRACT FROM AUTHOR]

The paper compares a theory for immiscible displacement based on distinguishing percolating and nonpercolating fluid parts with experimental observations from multistep outflow experiments. The theory was published in 2006 in Physica A, volume 371, pages 209-225; the experiments were published in 1991 in Water Resources Research, volume 27, pages 2113. The present paper focuses on hysteretic phenomena resulting from repeated cycling between drainage and imbibition processes in multistep pressure experiments. Taking into account, the hydraulic differences between percolating and nonpercolating fluid parts provides a physical basis to predict quantitatively the hysteretic phenomena observed in the experiment. While standard hysteretic extensions of the traditional theory are nonlocal in time the theory used in this paper is local in time. Instead of storing the pressure and saturation history, it requires only the current state of the system to reach the same quantitative agreement. [ABSTRACT FROM AUTHOR]

Reliable accounting of agricultural water use is critical for sustainable water management. However, the majority of agricultural water use is not monitored, with limited metering of irrigation despite increasing pressure on both groundwater and surface water resources in many agricultural regions worldwide. Satellite remote sensing has been proposed as a low‐cost and scalable solution to fill widespread gaps in monitoring of irrigation water use in both developed and developing countries, bypassing the technical, socioeconomic, and political challenges that to date have constrained in situ metering. In this paper, we show through a systematic meta‐analysis that the relative accuracy of different satellite‐based irrigation water use monitoring approaches remains poorly understood, with evidence of large uncertainties when water use estimates are validated against in situ irrigation data at both field and regional scales. Subsequently, we demonstrate that water use measurement errors result in large economic welfare losses for farmers and may negatively impact ability of policies to limit acute and nonlinear externalities of irrigation abstraction on both the environment and other water users. Our findings highlight that water resource planners must consider the trade‐offs between accuracy and costs associated with different water use accounting approaches. Remote sensing has an important role to play in supporting improved agricultural water accounting—both independently and in combination with in situ monitoring. However, greater transparency and evidence is needed about underlying uncertainties in satellite‐based models, along with how these measurement errors affect the performance of associated policies to manage different short‐ and long‐term externalities of irrigation water use. Key Points: Satellite remote sensing has been proposed as a low‐cost solution to fill widespread gaps in monitoring of agricultural water use globallyValidation of remote sensing models is limited with large uncertainties in estimates of irrigation water use at plot and regional scalesMeasurement errors create welfare losses for farmers and may constrain efforts to manage hydrologic impacts of irrigation abstractions [ABSTRACT FROM AUTHOR]

Karstified carbonate aquifers are highly heterogeneous systems characterized by multiple recharge, flow, and discharge components. The quantification of the relative contribution of these components, as well as their numerical representation, remains a challenge. This paper identifies three recharge components in the time and frequency domain. While the analysis in the time domain follows traditional approaches, the analysis of the power spectrum allows frequencies associated with specific spectral coefficients and noise types to be distinguished more objectively. The analysis follows the presented hypothesis that the different frequency‐noise components are the result of aquifer heterogeneity transforming the random rainfall input into a sequence of non‐Gaussian signals. The distinct signals are then numerically represented in the context of a semidistributed pipe network model in order to simulate recharge, flow, and discharge of an Irish karst catchment more realistically. By linking the power spectra of the modeled recharge components with the spectra of the spring discharge, the information usually gained by classical performance indicators is significantly widened. The modeled spring discharge is well matched in the time and frequency domain, yet the different recharge dynamics explain the signal of the aquifer outlet in different noise domains across the spectrum. This study demonstrates the conjunctive use of frequency analysis in conceptualization of a hydrological system together with modeling and evaluation. Key Points: Hydrograph analysis was coupled with frequency and noise analysis to identify recharge dynamics in a karst spring discharge time seriesRecharge, flow, and discharge were modeled in a semidistributed pipe network model considering aquifer heterogeneities and noise domainsA new model evaluation approach using noise analysis provided information on the individual contribution of the internal flows [ABSTRACT FROM AUTHOR]

Strong earthquakes can cause different kinds of hydrological responses, and several mechanisms have been suggested to explain them. Verification of these mechanisms, however, is often lacking. Here we test some hypotheses with a laboratory experiment, in particular the hypothesis that dynamic strain mobilizes trapped water in the unsaturated zone. We construct a sand chamber, partially saturated with water, and subject it to "seismic" shaking of controlled energy. Pore pressure in the saturated and unsaturated zones is monitored before and after shaking. We identify three distinct mechanisms: consolidation of sediments in the saturated zone, release of capillary water from the capillary fringe, and mobilization of isolated pore water in the unsaturated zone. Each mechanism may cause pore pressure in the saturated zone to suddenly increase with shaking, and each may offer new insights to understand the source of the extra water and other shallow hydrological responses that appear after earthquakes. Plain Language Summary: Earthquakes interact with water in a variety of interesting ways. For instance, during earthquakes, streamflow and groundwater level may increase, as occurred following the recent earthquake swarm in Puerto Rico. The mechanisms for such changes, however, are still unclear. In our paper, we measure the response of groundwater pressure to seismic shaking to test the hypothesis that earthquakes can cause shallow groundwater to flow toward streams. To accomplish this, we built a tall sand column, filled it with water, and instrumented it with sensors that measure how the pressure of water between sand grains (pore pressure) responds when the chamber is shaken by an impact. We found that "trapped" water in the shallow subsurface, which is held in place by adhesive forces between sand and water, can be released to the water table by seismic shaking, where it can then flow toward a stream. Key Points: We test mechanisms for groundwater response to earthquakes by performing laboratory experimentsWe observe consolidation of sediments, mobilization of pore water, and release of capillary water from the capillary fringeThese mechanisms can help explain coseismic increases in groundwater level and streamflow when there are no other apparent water sources [ABSTRACT FROM AUTHOR]

The exchange of mass between a stream and its hyporheic zone, or ' hyporheic exchange,' is central to many important ecosystem services. In this paper we show that mass transfer across the streambed by linear mechanisms of hyporheic exchange in a gaining or losing stream can be represented by a thin film model in which (a) the mass transfer coefficient is replaced with the average Darcy flux of water downwelling into the sediment and (b) the driving force for mass transfer is ' flipped' from normal to the surface (concentration difference across a boundary layer) to parallel to the surface (concentration difference across downwelling and upwelling zones). Our analysis is consistent with previously published analytical, computational, and experimental studies of hyporheic exchange in the presence of stream-groundwater interactions, and links stream network, advection-dispersion, and stochastic descriptions of solute fate and transport in rivers. [ABSTRACT FROM AUTHOR]

Training image-based geostatistical methods are increasingly popular in groundwater hydrology even if existing algorithms present limitations that often make real-world applications difficult. These limitations include a computational cost that can be prohibitive for high-resolution 3-D applications, the presence of visual artifacts in the model realizations, and a low variability between model realizations due to the limited pool of patterns available in a finite-size training image. In this paper, we address these issues by proposing an iterative patch-based algorithm which adapts a graph cuts methodology that is widely used in computer graphics. Our adapted graph cuts method optimally cuts patches of pixel values borrowed from the training image and assembles them successively, each time accounting for the information of previously stitched patches. The initial simulation result might display artifacts, which are identified as regions of high cost. These artifacts are reduced by iteratively placing new patches in high-cost regions. In contrast to most patch-based algorithms, the proposed scheme can also efficiently address point conditioning. An advantage of the method is that the cut process results in the creation of new patterns that are not present in the training image, thereby increasing pattern variability. To quantify this effect, a new measure of variability is developed, the merging index, quantifies the pattern variability in the realizations with respect to the training image. A series of sensitivity analyses demonstrates the stability of the proposed graph cuts approach, which produces satisfying simulations for a wide range of parameters values. Applications to 2-D and 3-D cases are compared to state-of-the-art multiple-point methods. The results show that the proposed approach obtains significant speedups and increases variability between realizations. Connectivity functions applied to 2-D models transport simulations in 3-D models are used to demonstrate that pattern continuity is preserved. [ABSTRACT FROM AUTHOR]

This paper presents the fundamental theory and laboratory test results on a new device that is deployed in boreholes in fractured rock aquifers to characterize vertical distributions of water and contaminant fluxes, aquifer hydraulic properties, and fracture network properties (e.g., active fracture density and orientation). The device, a fractured rock passive flux meter (FRPFM), consists of an inflatable core assembled with upper and lower packers that isolate the zone of interest from vertical gradients within the borehole. The outer layer of the core consists of an elastic fabric mesh equilibrated with a visible dye which is used to provide visual indications of active fractures and measures of fracture location, orientation, groundwater flux, and the direction of that flux. Beneath the outer layer is a permeable sorbent that is preloaded with known amounts of water soluble tracers which are eluted at rates proportional to groundwater flow. This sorbent also captures target contaminants present in intercepted groundwater. The mass of contaminant sorbed is used to quantify cumulative contaminant flux; whereas, the mass fractions of resident tracers lost are used to provide measures of water flux. In this paper, the FRPFM is bench tested over a range of fracture velocities (2-20 m/day) using a single fracture flow apparatus (fracture aperture = 0.5 mm). Test results show a discoloration in visible dye corresponding to the location of the active fracture. The geometry of the discoloration can be used to discern fracture orientation as well as direction and magnitude of flow in the fracture. Average contaminant fluxes were measured within 16% and water fluxes within 25% of known imposed fluxes. [ABSTRACT FROM AUTHOR]

This paper develops a coupled hydrologic‐economic model that estimates the effects of six tax institutions that theory predicts will lead to equal amounts of aquifer withdrawal. That said, the distributive effects of the tax institutions are expected to differ because each involves different combinations of tax thresholds and side payments (returned tax revenue). The tax policies can lead to groundwater users being worse off than they would be using an unmanaged aquifer. This study explores whether the distributive impacts of specific policies that have equal marginal incentives lead to differences in the behavior of participants in an experiment involving a common pool groundwater resource. The results reveal that each of the tax policies results in approximately the same reduction in resource use but affects participants' earnings and opinions regarding the policies differently. A tax imposed on groundwater use above a threshold and without a side payment is most effective in increasing the net social benefit associated with using the aquifer; participant earnings under that scheme are almost equal to earnings from an unmanaged aquifer (1.04% less), and overall social efficiency is greater (4.34%). Unfortunately, participants tend to prefer an unmanaged aquifer and tax policies with high side‐payments—treatments that led to lower overall social efficiency. The evidence suggests that aquifer management may require a two‐fold approach: (1) a carefully selected threshold that can make water users financially indifferent between a managed and unmanaged aquifer and (2) education to increase the political acceptability of the managed aquifer policy. Key Points: Six aquifer withdrawal taxes result in similar groundwater use but different user earnings and opinionsThe most effective policy is a groundwater use tax with a threshold and without an upfront side paymentGroundwater users prefer an unmanaged aquifer and tax policies with high side‐payments irrespective of overall aquifer use efficiency [ABSTRACT FROM AUTHOR]

Growing water stress has led to emerging interest in protecting fresh and brackish groundwater as a potential supplement to water supplies and raised questions about factors that could affect the future quality of fresh and brackish aquifers. Limited well infrastructure, particularly in regions where elevated salinity has led to limited historical groundwater development, hinders traditional mapping of salinity distributions through groundwater sampling. This paper presents a quantitative salinity mapping approach of the upper 300 m using high‐resolution, regionally comprehensive resistivity models derived from Bayesian inversion of an airborne electromagnetic survey adjacent to the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley of California. Using local water quality observations as an interpretational foundation, a probabilistic approach yields maps of fresh, saline, and brackish groundwater while quantifying joint uncertainty inherited from the geophysical data and interpretational relations. Saline and fresh regions are mapped with relatively high confidence in many locations, while areas of lower confidence, particularly at depth, can be mapped as their most probable salinity category while reflecting the relative uncertainty in the interpretation. These maps identify a stratified salinity structure, where saline water commonly occurs in the surficial aquifer overlying fresher groundwater in the Tulare aquifer, separated by regional confining clay layers. Downgradient of unlined surface water diversions, recharge of imported surface water results in relatively fresh groundwater throughout the depth of investigation. Plain Language Summary: Salinity, a measure of salt concentration, can impact the potential use of groundwater. Salinity can be difficult to map using wells alone, especially where groundwater development has been limited in the past. Dissolved salts are excellent conductors of electricity, and resistivity measurements are commonly used to estimate salinity where wells are not available. Uncertainty in estimating salinity from resistivity data can be introduced into the interpretation by two sources: (1) how well we can estimate salinity from resistivity and (2) how accurately we can measure resistivity. We present a method for mapping salinity that accounts for both sources of uncertainty using regional‐scale, high‐resolution airborne geophysical data, leading to spatially comprehensive 3‐D maps of likely fresh (low salt) and saline (high salt) groundwater. The method is applied in the southwestern San Joaquin Valley of California adjacent to the Lost Hills and Belridge oil fields. Shallow groundwater is shown to have relatively high salinity in much of the study area, and a clay layer protects lower salinity water in the underlying Tulare aquifer. Leaking surface water canals have imported relatively fresh water into the area, resulting in fresher groundwater downgradient of the canals. Key Points: Fresh, brackish, and saline groundwater are mapped using airborne electromagnetic‐derived regional resistivity dataCategorical probability developed from Bayesian inversion and local wells reflect geophysical and interpretational uncertaintySurface water diversions and clay units strongly influence groundwater quality in the southwestern San Joaquin Valley [ABSTRACT FROM AUTHOR]

This paper introduces the Water Resources Research special section on Uncertainty Assessment in Surface and Subsurface Hydrology. Over the past years, hydrological literature has seen a large increase in the number of papers dealing with uncertainty. In this article, we present an overview of the different sources of uncertainty and the different types of problems associated with uncertainty assessment. It is argued here that clarity about which part of the large field of uncertainty research is addressed by a given research activity would already help guide discussions within the hydrological community. We present an introduction to the differences between the more classical frequentist approach to uncertainty and Bayesian approaches and between probabilistic and nonprobabilistic approaches. Bayesian approaches allow for inclusion of more subjective expert knowledge and would be more appropriate where less 'hard' data are available. Any underlying assumptions need to be made very clear to the end user. Finally, a brief classification of the articles of the special section is presented. [ABSTRACT FROM AUTHOR]

Depth‐resolved chemistry samples are critical to a wide range of groundwater investigations. If a well intersects zones of variable concentrations, a pumped sample is a composite of the inflows, which mix in the well. Where discrete concentrations are required, excessive mixing makes samples less useful and potentially misleading. However, installations for depth‐discrete sampling are expensive, particularly for regional studies, so sometimes there is incentive to use existing infrastructure designed for other purposes (e.g., supply wells). This paper shows how the resolution of groundwater chemistry derived from long‐screened and open borehole wells can be improved by measuring and sampling the in‐well vertical flow regimes in ambient (unpumped) and/or pumped conditions. The ambient flow regime, driven by a natural vertical head gradient, is shown to be particularly useful to sample groundwater native to defined inflow zones (head in the zone > head in the well) and avoid zones impacted by the invasion of intraborehole flow (head in the zone < head in the well). Depth‐specific samples are interpreted either as native groundwater from a discrete source, subject only to analytical error, or a mixture from multiple sources that can be deconvolved, incorporating error in both flow and concentration measurements. Depth‐resolved age tracers (chlorofluorocarbons, 14C, and He) in groundwater from three supply wells are verified with samples from a multidepth nest of piezometers. Results show old groundwater at all depths and the simultaneous occurrence of young water at shallower depths in undisturbed dual‐porosity fractured aquifers in the Pilbara region of Western Australia. Key Points: Sampling ambient vertical flows can provide more insightful data than sampling pumped flowsAmbient flows can be sampled without purging or pumping the wellIn‐well samples are either from a discrete source or the mixture that can be deconvolved [ABSTRACT FROM AUTHOR]

The aim of this paper is to improve semiseasonal forecast of groundwater availability in response to climate variables, surface water availability, groundwater level variations, and human water management using a two‐step data‐driven modeling approach. First, we implement an ensemble of artificial neural networks (ANNs) for the 300 wells across the High Plains aquifer (USA). The modeling framework includes a method to choose the most relevant input variables and time lags; an assessment of the effect of exogenous variables on the predictive capabilities of models; and the estimation of the forecast skill based on the Nash‐Sutcliffe efficiency (NSE) index, the normalized root mean square error, and the coefficient of determination (R2). Then, for the ANNs with low‐ accuracy, a MultiModel Combination (MuMoC) based on a hybrid of ANN and an instance‐based learning method is applied. MuMoC uses forecasts from neighboring wells to improve the accuracy of ANNs. An exhaustive‐search optimization algorithm is employed to select the best neighboring wells based on the cross correlation and predictive accuracy criteria. The results show high average ANN forecasting skills across the aquifer (average NSE > 0.9). Spatially distributed metrics of performance showed also higher error in areas of strong interaction between hydrometeorological forcings, irrigation intensity, and the aquifer. In those areas, the integration of the spatial information into MuMoC leads to an improvement of the model accuracy (NSE increased by 0.12), with peaks higher than 0.3 when the optimization objectives for selecting the neighbors were maximized.tT Key Points: Artificial neural networks can accurately forecast semiseasonal groundwater level changesMuMoC improved the groundwater well‐level forecasting skill for 1‐ to 4‐month lead times with respect to a single ANN model by 25% in NSEThe implementation of MuMoC is recommended in case of densely gauged areas [ABSTRACT FROM AUTHOR]

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 reequilibration 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. Chlorofluorocarbon‐12 (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 reequilibration of both CFC‐12 and 14C to be accurately determined. Since CFC‐12 reequilibrates more rapidly than 14C, recirculating groundwater had a CFC‐12 concentration that was close to modern, but a 14C activity that was higher than the original groundwater, but less than modern recharge. As 3H does not reequilibrate, 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 reequilibration for the groundwater recirculation end‐member, and spatial variations in the composition of the ambient groundwater end‐member. Key Points: Recirculation of water between the land surface and the aquifer can be difficult to identify using ionic tracersThe use of dissolved gases allows quantification of groundwater recirculation due to gas reequilibration on exposure to the atmosphereInfiltration of mine water discharged to creeks is differentiated from natural creek flow using CFC‐12, 14C, and 3H [ABSTRACT FROM AUTHOR]

Nearly one billion people worldwide receive water through piped networks that are not continually pressurized and operate intermittently. The prevalence and persistence of these Intermittent Water Supplies (IWS) is surprising as this mode of operation induces water contamination and customer equity issues. Shortages of source water, customers' water demand, and leaking pipes are frequently cited as necessitating IWS. We propose a framework for understanding the persistence and operation of IWS. The supply system is represented by an average customer and a spatially averaged leakage rate. With this macroscopic hydraulic model, we relate customer demand satisfaction, source water availability, customer demand, and leakage. While this approach ignores the complexities of network topology, we find that the model approximates real systems well (calibrating to four intermittent reference networks achieved R2>0.87). The calibrated model is robust to moderate changes in demand and leakage (maintaining R2>0.81). Using the model, we show that the tipping point between satisfied demand and unsatisfied demand is a local optimum for utilities, which may explain the persistence of IWS. Beyond this point, the volume received by customers does not increase, but utilities must supply more water to the network. The generality of the proposed model enables its use when regulating and upgrading IWS. We demonstrate the latter by critiquing a performance‐based contract that was intended to improve an intermittent supply in India. Demand satisfaction has profound implications for hydraulics and human welfare. We propose the degree of demand satisfaction as a metric for evaluating IWS and for tracking the United Nations Sustainable Development Goal 6.1. Plain Language Summary: While most people get drinking water through underground water pipes, in some areas these pipes only provide water for a few hours each week. Globally, more than one billion people are served by these "intermittent water supply systems". In severely degraded systems, keeping pipes empty most of the time can reduce leakage and conserve source water, but it can also allow mud or sewage to enter through holes or cracks in the pipes, contaminating the water. This paper presents a simple model (an equation) that approximates how intermittent systems behave. The model suggests why intermittent operation is so common and highlights the challenges of improving such systems. The model relates hours of operation to factors such as source water supply, consumer demand, leakage, and if consumer demand is satisfied. The model implies that once consumer demand is satisfied, a system crosses a threshold and behaves differently: leakage, rather than demand, determines most of a system's water requirements. Measuring this threshold could identify systems that leave people thirsty and prioritize such systems for improvements. The model, therefore, provides new tools to support global commitments outlined in the United Nations' Sustainable Development Goal 6.1 and the Human Right to Water. Key Points: Without topology details, our proposed model of intermittent water supplies (IWS) matches closely with more complete network modelsWhile inadvisable, IWS provide utilities traditionally ignored, short‐term benefits (e.g., supply timing will change less due to drought)We propose a new demand satisfaction metric to quantify supply availability and help track Sustainable Development Goal 6.1 in IWS [ABSTRACT FROM AUTHOR]

The hyporheic zone, defined by shallow subsurface pathways through river beds and banks beginning and ending at the river, is an integral and unique component of fluvial systems. It hosts myriad hydrologically controlled processes that are potentially coupled in complex ways. Understanding these processes and the connections between them is critical since these processes are not only important locally but integrate to impact increasingly larger scale biogeochemical functioning of the river corridor up to the river network scale. Thus, the hyporheic zone continues to be a growing research focus for many hydrologists for more than half the history of Water Resources Research. This manuscript partly summarizes the historical development of hyporheic zone hydrologic science as gleaned from papers published in Water Resources Research, from the birth of the concept of the hyporheic zone as a hydrologic black box (sometimes referred to as transient storage zone), to its adolescent years of being torn between occasionally competing research perspectives of interrogating the hyporheic zone from a surface or subsurface view, to its mature emergence as an interdisciplinary research field that employs the wide array of state-of-the-art tools available to the modern hydrologist. The field is vibrant and moving in the right direction of addressing critical fundamental and applied questions with no clear end in sight in its growth. There are exciting opportunities for scientists that are able to tightly link the allied fields of geology, geomorphology, hydrology, geochemistry, and ecology to tackle the many open problems in hyporheic zone science. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear transfer function noise model for time-series modeling of unconfined groundwater hydrographs. The motivation for its development was that existing groundwater time-series models were unable to simulate large recharge events and multiyear droughts. This was because existing methods do not partition rainfall to runoff and do not account for nonlinear soil water drainage. To account for these nonlinear processes, a vertically integrated soil moisture module was added to an existing transfer function noise model. The soil moisture module has a highly flexible structure that allowed 84 different forms to be built. Application of the time-series model requires numerical calibration of parameters for the transfer functions, noise model and, for the nonlinear models, the soil moisture module. This was undertaken using the Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) global calibration scheme. However, reproducible calibration to the global optima was challenging and a number of modifications were required to the transfer function noise model. In trialing the 84 nonlinear models and 2 linear models, each was applied to eleven observation bores within a paired catchment study area in Great Western, Victoria, Australia. In comparison with existing groundwater hydrograph time-series models, the proposed nonlinear time-series model performed significantly better at all observation bores during calibration and evaluation periods. Both the linear and nonlinear models were also used to quantify the impact of revegetation within the paired catchment; however, results were inconclusive, which is likely due to time-series data for the state of the revegetation being unavailable. By analyzing the application of 84 nonlinear models to each bore, an optimal structure for the soil moisture module was identified. It is unlikely, however, that this model structure would be appropriate for all climates and geologies. To encourage further investigations, open-source code for the highly flexible groundwater time-series modeling framework is available and we invite others to develop new models. [ABSTRACT FROM AUTHOR]

This paper contains a new formulation for infiltration inside domains bounded by polygons and its application to problems of steady multiaquifer flow, using the Dupuit-Forchheimer approximation and assuming vertical flow in the separating layers. An alternative formulation is presented for leaky aquifer systems where infiltration or extraction is given. Existing formulations of multiaquifer flow involve a system of equations that must be solved for the heads in the aquifers. These formulations are abstract, and the relation between the parameters in the solution and physical quantities is hidden. The formulation in the paper aims at linking the system of equations to physical quantities; we have done this in two ways. First, we formulate the problem in terms of leakage potentials, related directly to the leakage through the leaky layers. Second, we introduce the concept of 'equilibrated leakage,' leakage that is either the result of infiltration or of some disturbance in the flow pattern, such as that caused by a well. The leakage through the leaky layers tends to some constant value far from a disturbance, e.g., a well, or the boundary of an area of constant infiltration. This concept of equilibrated leakage is useful in practice and helps in understanding the distribution of leakage; we explain this in detail in the paper. The study of problems of steady flow in leaky aquifer systems is inspired by problems of groundwater sustainability, where the overall distribution of flow over long periods of time is important, rather than detailed information. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: High‐dimensional inverse problems are often computationally expensive since a large number of forward model evaluations are usually required. A computationally efficient alternative is to replace in the inversion process the forward model with an accurate but fast‐to‐evaluate surrogate model. However, most existing surrogate methods suffer from the "curse of dimensionality." In this paper, we develop a deep autoregressive neural network‐based surrogate method to efficiently solve such high‐dimensional inverse problems. The autoregressive neural network can efficiently obtain accurate approximations for the time‐dependent outputs of forward models with time‐varying inputs. In addition, a dense convolutional network architecture is employed to transform the surrogate modeling task to an image‐to‐image regression problem by leveraging the robust capability of convolutional networks in image‐like data processing. The curse of dimensionality was tackled though a series of inherent nonlinear projections of the input into low‐dimensional latent spaces. It is shown that the proposed network provides an accurate surrogate of a transport system with high‐dimensional uncertain inputs using relatively limited training data. Reliable inversion results are then obtained with a rather minor computational cost by using the surrogate to replace the forward model in the inversion process. Key Points: A deep neural network surrogate approach is developed for groundwater contaminant transport in highly heterogeneous mediaThe time‐varying process is captured using an autoregressive modelA 686‐dimensional inverse problem of contaminant source identification in heterogeneous media is addressed [ABSTRACT FROM AUTHOR]

In this paper, we develop a reduced generalized multiscale basis method for efficiently solving the parametrized groundwater flow problems in heterogeneous porous media. Recently proposed generalized multiscale finite element (GMsFE) method is one of the accurate and efficient methods to solve the multiscale problems on a coarse grid. However, the GMsFE basis functions usually depend on the random parameters in the parametrized model, which substantially impacts on the computation efficiency when the parametrized equation needs to be solved many times for many instances of parameters. To enhance computation efficiency, we construct reduced generalized multiscale basis functions independent of parameters from the high‐dimensional GMsFE space and generate a reduced‐order multiscale model by projecting the parameterized flow governing equation onto the low‐dimensional reduced GMsFE space. Then, in order to improve the online computation of reduced‐order model, we apply a matrix discrete empirical interpolation method to affinely decompose the nonaffine parametrized systems arising from the discretization of governing equation. Finally, a few numerical experiments are carried out for the parametrized transient flow problems in heterogeneous porous media to illustrate the efficiency and accuracy of the proposed model reduction method. The results show that the proposed reduced generalized multiscale basis method can significantly improve computation efficiency while maintaining comparative accuracy for the groundwater flow problems by selecting a suitable coarse mesh size and an optimal number of reduced GMsFE basis functions at each of coarse nodes. Key Points: A reduced generalized multiscale basis method is developed for solving parametrized transient flow problems with multiscale inputsMethod is designed by incorporating reduced generalized multiscale bases and matrix discrete empirical interpolation into reduction modelThe proposed reduction method significantly enhance computation efficiency while maintaining accuracy for parametrized flow problems [ABSTRACT FROM AUTHOR]

Surrogate strategies are used widely for uncertainty quantification of groundwater models in order to improve computational efficiency. However, their application to dynamic multiphase flow problems is hindered by the curse of dimensionality, the saturation discontinuity due to capillarity effects, and the time dependence of the multi‐output responses. In this paper, we propose a deep convolutional encoder‐decoder neural network methodology to tackle these issues. The surrogate modeling task is transformed to an image‐to‐image regression strategy. This approach extracts high‐level coarse features from the high‐dimensional input permeability images using an encoder and then refines the coarse features to provide the output pressure/saturation images through a decoder. A training strategy combining a regression loss and a segmentation loss is proposed in order to better approximate the discontinuous saturation field. To characterize the high‐dimensional time‐dependent outputs of the dynamic system, time is treated as an additional input to the network that is trained using pairs of input realizations and of the corresponding system outputs at a limited number of time instances. The proposed method is evaluated using a geological carbon storage process‐based multiphase flow model with a 2,500‐dimensional stochastic permeability field. With a relatively small number of training data, the surrogate model is capable of accurately characterizing the spatiotemporal evolution of the pressure and discontinuous CO2 saturation fields and can be used efficiently to compute the statistics of the system responses. Key Points: A surrogate model for uncertainty quantification of dynamic multiphase flows is developed using deep convolutional encoder‐decoder networksA two‐stage network training strategy is proposed to improve the approximation of saturation discontinuityThe method can accurately predict the time‐dependent output fields of a multiphase flow model with a 2,500‐dimensional permeability field [ABSTRACT FROM AUTHOR]

Hillslope hydrological investigations in humid regions to date have focused mostly on runoff generation during events. The few papers that have also examined groundwater recharge processes associated with subsurface stormflow production have found strong linkages between episodes of runoff and recharge to the aquifer. But the range of climate, vegetation, and geological conditions examined thus far has been limited. Here we explore how geologic characteristics, timing of subsurface stormflow, and hydroclimatic conditions relate to the timing of bedrock groundwater recharge at the well‐studied Maimai watershed. We hypothesized that recharge would be determined by subsurface stormflow frequency in this system with high rainfall and little seasonality of the hydrologic response. Unexpectedly, isotopic analysis and noble gas measurements indicated that recharge occurred almost exclusively during winter months despite previous work at Maimai showing subsurface stormflow occurs in all seasons and rainfall‐runoff ratios are high year‐round. A sprinkler and dye experiment conducted directly on open bedrock identified groundwater recharge mechanisms and rates, and a simple empirical recharge model suggests almost 90% of recharge occurred from only 55% of annual precipitation. We found no correlation between the timing and magnitude of groundwater recharge and total precipitation, direct runoff or subsurface stormflow. The catchment effectively converted rainfall to runoff during all seasons, but the unfractured low permeability bedrock (2.3 × 10−8 m/s) required long durations of extended catchment wetness for appreciable recharge to occur—a condition satisfied only during winter months with lower evapotranspiration. These findings suggest the need to better understand the geologic controls of recharge in headwaters. Key Points: Despite minimal seasonality in rainfall, runoff generation, or the rainfall‐runoff ratio, there is strong seasonality in groundwater rechargeExtended periods of high catchment wetness, rather than storm events, were the primary driver of groundwater recharge at the Maimai watershedUnfractured low permeability bedrock and an efficient preferential flow network explain why runoff generation and recharge were uncorrelated [ABSTRACT FROM AUTHOR]

While in catchment and hillslope hydrology a more nuanced approach is now taken to streamflow recession analysis, in the context of major aquifers it is commonly still assumed that the groundwater head recession rate will take exponential form, an idea originally proposed in the 19th Century. However it is shown here that, in early times, the groundwater head recession in a major aquifer should take an almost straight line form with a rate approximately equal to the long-term recharge rate divided by the aquifer storage coefficient. The length of this phase can be estimated from an analytical expression derived in the paper which depends on the aquifer diffusivity, length scale, and the position of the monitoring point. A transitional phase then leads to an exponential phase after some critical time which is independent of the position of the monitoring point. Major aquifers in a state of periodic quasi-steady state are expected to have rates of groundwater flux recession which deviate little from the average rate of groundwater recharge. Where quasi-exponential groundwater declines are observed in nature, their form may be diagnostic of particular types of aquifer properties and/or boundary effects, such as proximity to drainage boundaries, variations in transmissivity with hydraulic head, storage changes due to pumping, nonequilibrium flow at a range of spatial and temporal scales, and variations in specific yield with depth. Recession analysis has applicability to a range of groundwater problems and is powerful way of gaining insight into the hydrologic functioning of an aquifer. [ABSTRACT FROM AUTHOR]

This paper introduces the special section on 'new modeling approaches and novel experimental technologies for improved understanding of process dynamics at aquifer-surface water interfaces.' It is contextualizing the framework for the 27 research papers of the special section by firth identifying research gaps and imminent challenges for ecohydrological research at aquifer-surface water interfaces and then discussing the specific paper contributions on (i) new developments in temperature/heat tracing at GW-SW interfaces, (ii) new methods to capture the temporal and spatial variability of groundwater-surface water exchange, (iii) new approaches in modeling aquifer-river exchange flow, and (iv) new concepts and advanced theory of groundwater-surface water exchange. [ABSTRACT FROM AUTHOR]

The potential for shale gas development and hydraulic fracturing to cause subsurface water contamination has prompted a number of modeling studies to assess the risk. A significant impediment for conducting robust modeling is the lack of comprehensive publicly available information and data about the properties of shale formations, shale wells, the process of hydraulic fracturing, and properties of the hydraulic fractures. We have collated a substantial amount of these data that are relevant for modeling multiphase flow of water and gas in shale gas formations. We summarize these data and their sources in tabulated form. [ABSTRACT FROM AUTHOR]

Abstract: Widely distributed in arid and semiarid regions, phreatophytic roots extend into the saturated zone and extract water directly from groundwater. In this paper, we implemented a vegetation optimality model of root dynamics (VOM‐ROOT) in the Noah land surface model with multiparameterization options (Noah‐MP LSM) to model the extraction of groundwater through phreatophytic roots at a riparian site with a hyperarid climate (with precipitation of 35 mm/yr) in northwestern China. VOM‐ROOT numerically describes the natural optimization of the root profile in response to changes in subsurface water conditions. The coupled Noah‐MP/VOM‐ROOT model substantially improves the simulation of surface energy and water fluxes, particularly during the growing season, compared to the prescribed static root profile in the default Noah‐MP. In the coupled model, more roots are required to grow into the saturated zone to meet transpiration demand when the groundwater level declines over the growing season. The modeling results indicate that at the study site, the modeled annual transpiration is 472 mm, accounting for 92.3% of the total evapotranspiration. Direct root water uptake from the capillary fringe and groundwater, which is supplied by lateral groundwater flow, accounts for approximately 84% of the total transpiration. This study demonstrates the importance of implementing a dynamic root scheme in a land surface model for adequately simulating phreatophytic root water uptake and the associated latent heat flux. [ABSTRACT FROM AUTHOR]

Managed aquifer recharge [MAR) is a promising water management tool toward restoring groundwater balance and securing groundwater ecosystem services (i.e., water for drinking, industrial or irrigation use, control of land subsidence, maintenance of environmental flows to groundwater dependent ecosystems, etc.). Obviously, MAR projects can improve the quality of lives of the people by several ways. Thus, from a social perspective, the benefits of MAR cannot and should not be based only on market revenues or costs. Although the value of groundwater, from a social perspective, has been a subject of socio-economic research, literature on the value of MAR per se is very limited. This paper, focusing on Italy which is a country with extensive utilization of MAR, aims to estimate the economic value of MAR and makes a first step toward filling this gap in the literature. For this purpose, the Contingent Valuation method was implemented to provide a monetary estimate and to explore the factors influencing people's attitude and willingness to pay for MAR. The results show that society holds not only use but also significant nonuse values, which are a part of the total economic value (TEV) of groundwater according to related research efforts. To this end, MAR valuation highlights its social importance for groundwater conservation and provides a solid basis for incorporating its nonmarket benefits into groundwater management policies and assessments. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) geological sequestration plays an important role in mitigating CO2 emissions for climate change. Understanding interactions of the injected CO2 with network fractures and hydrocarbons is key for optimizing and controlling CO2 geological sequestration and evaluating its risks to ground water. However, there is a well-known, difficult process in simulating the dynamic interaction of fracture-matrix, such as dynamic change of matrix porosity, unsaturated processes in rock matrix, and effect of rock mineral properties. In this paper, we develop an explicit model of the fracture-matrix interactions using multilayer bounce-back treatment as a first attempt to simulate CO2 reactive transport in network fractured media through coupling the Dardis's LBM porous model for a new interface treatment. Two kinds of typical fracture networks in porous media are simulated: straight cross network fractures and interleaving network fractures. The reaction rate and porosity distribution are illustrated and well-matched patterns are found. The species concentration distribution and evolution with time steps are also analyzed and compared with different transport properties. The results demonstrate the capability of this model to investigate the complex processes of CO2 geological injection and reactive transport in network fractured media, such as dynamic change of matrix porosity. [ABSTRACT FROM AUTHOR]

Although irrigated agriculture is the primary consumer of global groundwater resources, information on recharge rates and sustainable irrigation is limited. The study objective was to fingerprint irrigation return flow to quantify percolation/recharge and to estimate sustainable irrigation levels. This paper focuses on water quantity; a companion paper addresses water quality. Soil samples from 13 boreholes drilled beneath irrigated agroecosystems in the southern High Plains were analyzed for matric potential and water-extractable Cl and NO3. Unsaturated zone pore water beneath irrigated agroecosystems can be fingerprinted by higher matric potentials (wetter soils, median mp: −40 m) and higher NO3-N (median 71 mg/L) than beneath natural ecosystems (mp −200 m; NO3-N 8.1 mg/L) and by higher Cl (720 mg/L) than beneath rain-fed agroecosystems (8.4 mg/L). The range in percolation/recharge rates beneath irrigated agroecosystems is 18-97 mm/a (median 41 mm/a; 5% of irrigation + precipitation) and occurs primarily in response to extreme precipitation events. Similarity in percolation/recharge rates beneath irrigated and rain-fed (4.8-92 mm/a) agroecosystems was unexpected and is attributed to low irrigation applications (median 300 mm/a) and increased crop yield and evapotranspiration in irrigated areas. Regional water table declines are unsustainably large (≥ 30 m over 10,000 km2) in the north and are much lower in the south. Sustainable irrigation in the south would require reduction of the irrigated area from 23% to 9%. Methods developed for quantifying recharge and sustainable irrigation application rates can be applied to groundwater-fed irrigated areas in semiarid regions globally. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a challenging water resources problem in a developing world city, Chennai, India. The goal is to reconstruct past system behavior and diagnose the causes of a major water crisis. In order to do this, we develop a hydrologic-engineering-economic model to address the complexity of urban water supply arising from consumers' dependence on multiple interconnected sources of water. We integrate different components of the urban water system: water flowing into the reservoir system; diversion and distribution by the public water utility; groundwater flow in the aquifer beneath the city; supply, demand, and prices in the informal tanker-truck-based water market; and consumer behavior. Both the economic and physical impacts of consumers' dependence on multiple sources of water are quantified. The model is calibrated over the period 2002-2006 using a range of hydrologic and socio-economic data. The model's results highlight the inadequacy of the reservoir system and the buffering role played by the urban aquifer and consumers' coping investments during multiyear droughts. [ABSTRACT FROM AUTHOR]

Groundwater quality parameters exhibit considerable spatial variability. Geostatistical methods including the assessment of variograms are usually used to characterize this variability. Copulas offer an interesting opportunity to describe dependence structures for multivariate distributions. Bivariate empirical copulas can be used as an alternative to variograms and covariance functions for the description of the spatial variability. Rank correlations of these copulas express the strength of the dependence independently of the marginal distributions and thus offer an alternative to the variograms. Empirical copulas for four quality parameters, chloride, sulfate, pH, and nitrate, obtained from a large-scale groundwater quality measurement network in Baden-Württemberg (Germany) are calculated. They indicate that the spatial dependence structure of the investigated parameters is not Gaussian. Two theoretical copula-based models are presented in this paper: a Gaussian and a non-Gaussian. Bootstrap-based statistical tests using stochastic simulation of the multivariate distributions are used to investigate the appropriateness of the models. According to the test results the Gaussian copula is rejected for most of the parameters while the non-Gaussian alternative is not rejected in most cases. [ABSTRACT FROM AUTHOR]

Despite increasing computational resources many high-dimensional applications are impractical for model inversions. In this paper, two methods are presented that are promising for high-dimensional model inversion. The methods draw on proper orthogonal decomposition (POD) and yield reduced models that describe a truncated behavior of the original model. We utilize POD differently for the two methods, which differ in efficiency and implementation. The first method (RIGM) applies a POD to an existing partial differential equation; the second method (RISM) applies it to an autoregressive formulation of a discrete model. Both methods were applied to several synthetic cases and a real-world case with synthetic measurements and by comparing them to classic inverse methodologies (i.e., the method of finite differences and the adjoint method). The two POD methods appeared to be computationally robust and more efficient for a wide range of prior estimates. Moreover, the implementation of an adjoint for the RISM method is easy. [ABSTRACT FROM AUTHOR]

During the last decade one has witnessed an increasing interest in assessing health risks caused by exposure to contaminants present in the soil, air, and water. A key component of any exposure study is a reliable model for the space-time distribution of pollutants. This paper compares the performances of multi-Gaussian and indicator kriging for modeling probabilistically the spatial distribution of arsenic concentrations in groundwater of southeast Michigan, accounting for arsenic data collected at private residential wells and the hydrogeochemistry of the area. The arsenic data set, which was provided by the Michigan Department of Environmental Quality (MDEQ), includes measurements collected between 1993 and 2002 at 8212 different wells. Factorial kriging was used to filter the short-range spatial variability in arsenic concentration, leading to a significant increase (17-65%) in the proportion of variance explained by secondary information, such as type of unconsolidated deposits and proximity to Marshall Sandstone subcrop. Cross validation of well data shows that accounting for this regional background does not improve the local prediction of arsenic, which reveals the presence of unexplained sources of variability and the importance of modeling the uncertainty attached to these predictions. Slightly more precise models of uncertainty were obtained using indicator kriging. Well data collected in 2004 were compared to the prediction model and best results were found for soft indicator kriging which has a mean absolute error of 5.6 μg/L. Although this error is large with respect to the USEPA standard of 10 μg/L, it is smaller than the average difference (12.53 μg/L) between data collected at the same well and day, as reported in the MDEQ data set. Thus the uncertainty attached to the sampled values themselves, which arises from laboratory errors and lack of information regarding the sample origin, contributes to the poor accuracy of the geostatistical predictions in southeast Michigan. [ABSTRACT FROM AUTHOR]

Numerical groundwater flow models often have a very high number of model cells (greater than a million). Such models are computationally very demanding, which is disadvantageous for inverse modeling. This paper describes a low-dimensional formulation for groundwater flow that reduces the computational burden necessary for inverse modeling. The formulation is a projection of the original groundwater flow equation on a set of orthogonal patterns (i.e., a Galerkin projection). The patterns (empirical orthogonal functions) are computed by a decomposition of the covariance matrix over an ensemble of model solutions. Those solutions represent the behavior of the model as a result of model impulses and the influence of a chosen set of parameter values. For an interchangeable set of parameter values the patterns yield a low-dimensional model, as the number of patterns is often small. An advantage of this model is that the adjoint is easily available and most accurate for inverse modeling. For several synthetical cases the low-dimensional model was able to find the global minimum efficiently, and the result was comparable to that of the original model. For several cases our model even converged where the original model failed. Our results demonstrate that the proposed procedure results in a 60% time reduction to solve the groundwater flow inverse problem. Greater efficiencies can be expected in practice for large-scale models with a large number of grid cells that are used to compute transient simulations. [ABSTRACT FROM AUTHOR]

A predominant cause of dispersion in groundwater is advective mixing due to variability in seepage rates. Hydraulic conductivity variations have been extensively researched as a cause of this seepage variability. In this paper the effect of variations in surface recharge to a shallow surficial aquifer is investigated as an important additional effect. An analytical formulation has been developed that relates aquifer parameters and the statistics of recharge variability to increases in the dispersivity. This is accomplished by solving Fourier transforms of the small perturbation forms of the groundwater flow equations. Two field studies are presented in this paper to determine the statistics of recharge variability for input to the analytical formulation. A time series of water levels at a continuous groundwater recorder is used to investigate the temporal statistics of hydraulic head caused by recharge, and a series of infiltrometer measurements are used to define the spatial variability in the recharge parameters. With these field statistics representing head fluctuations due to recharge, the analytical formulation can be used to compute the dispersivity without an explicit representation of the recharge boundary. Results from a series of numerical experiments are used to define the limits of this analytical formulation and to provide some comparison. A sophisticated model has been developed using a particle-tracking algorithm (modified to account for temporal variations) to estimate groundwater dispersion. Dispersivity increases of 9 percent are indicated by the analytical formulation for the aquifer at the field site. A comparison with numerical model results indicates that the analytical results are reasonable for shallow surficial aquifers in which two-dimensional flow can be assumed. [ABSTRACT FROM AUTHOR]

Interaction between surface water and groundwater depends on the position of a lake within the regional flow system. The approach in this paper is to nest a local-scale two-dimensional (2-D) lake aquifer model within a 1-D regional aquifer model to examine the effect of the regional setting on surface water-groundwater interaction. This extends previous steady state flow modeling, which is presented in earlier publications. The results indicate that the type of regional setting and position of the lake within that setting impose constraints on the near field flow geometry. Only nine of 39 previously identified flow regimes are possible in the regional flow system considered. Flow-through lakes are dominant and can occur anywhere within the regional flow. Recharge and discharge lakes are more likely to occur near the groundwater divide where regional hydraulic gradients are flattest and can be counteracted by local forcing in and near the lake. [ABSTRACT FROM AUTHOR]

The fractional advection-dispersion equation replaces the second spatial derivative in the usual advection-dispersion equation with a fractional derivative in the spatial variable. It was first applied to tracer tests in underground aquifers, and later to tracer tests in rivers. An alternative model replaces the first time derivative with a fractional derivative in time. Previous work has shown that both models provide a reasonable fit to breakthrough curves in rivers, which has led to a controversy regarding the physically appropriate fractional model. This paper shows that the relevant space-fractional model is mathematically equivalent to the corresponding time-fractional model, thus resolving the controversy. [ABSTRACT FROM AUTHOR]

The management of large-scale water resource systems with surface and groundwater resources requires considering stream-aquifer interactions. Optimization models applied to large-scale systems have either employed deterministic optimization (with perfect foreknowledge of future inflows, which hinders their applicability to real-life operations) or stochastic programming (in which stream-aquifer interaction is often neglected due to the computational burden associated with these methods). In this paper, stream-aquifer interaction is integrated in a stochastic programming framework by combining the Stochastic Dual Dynamic Programming (SDDP) optimization algorithm with the Embedded Multireservoir Model (EMM). The resulting extension of the SDDP algorithm, named Combined Surface-Groundwater SDDP (CSG-SDDP), is able to properly represent the stream-aquifer interaction within stochastic optimization models of large-scale surface-groundwater resource systems. The algorithm is applied to build a hydroeconomic model for the Jucar River Basin (Spain), in which stream-aquifer interactions are essential to the characterization of water resources. Besides the uncertainties regarding the economic characterization of the demand functions, the results show that the economic efficiency of the operating policies under the current system can be improved by better management of groundwater and surface resources. [ABSTRACT FROM AUTHOR]