Heat carried by ground water serves as a tracer to identify surface water infiltration, flow through fractures, and flow patterns in ground water basins. Temperature measurements can be analyzed for recharge and discharge rates, the effects of surface warming, interchange with surface water, hydraulic conductivity of streambed sediments, and basin-scale permeability. Temperature data are also used in formal solutions of the inverse problem to estimate ground water flow and hydraulic conductivity. The fundamentals of using heat as a ground water tracer were published in the 1960s, but recent work has significantly expanded the application to a variety of hydrogeological settings. In recent work, temperature is used to delineate flows in the hyporheic zone, estimate submarine ground water discharge and depth to the salt-water interface, and in parameter estimation with coupled ground water and heat-flow models. While short reviews of selected work on heat as a ground water tracer can be found in a number of research papers, there is no critical synthesis of the larger body of work found in the hydrogeological literature. The purpose of this review paper is to fill that void and to show that ground water temperature data and associated analytical tools are currently underused and have not yet realized their full potential.
Abstract Concentrations of naturally occurring arsenic in ground water vary regionally due to a combination of climate and geology. Although slightly less than half of 30,000 arsenic analyses of ground water in the United States were 1 μg/L, about 10% exceeded 10 μg/L. At a broad regional scale, arsenic concentrations exceeding 10 μg/L appear to be more frequently observed in the western United States than in the eastern half. Arsenic concentrations in ground water of the Appalachian Highlands and the Atlantic Plain generally are very low ( 1 μg/L). Concentrations are somewhat greater in the Interior Plains and the Rocky Mountain System. Investigations of ground water in New England, Michigan, Minnesota, South Dakota, Oklahoma, and Wisconsin within the last decade suggest that arsenic concentrations exceeding 10 μg/L are more widespread and common than previously recognized. Arsenic release from iron oxide appears to be the most common cause of widespread arsenic concentrations exceeding 10 μg/L in ground water. This can occur in response to different geochemical conditions, including release of arsenic to ground water through reaction of iron oxide with either natural or anthropogenic (i.e., petroleum products) organic carbon. Iron oxide also can release arsenic to alkaline ground water, such as that found in some felsic volcanic rocks and alkaline aquifers of the western United States. Sulfide minerals are both a source and sink for arsenic. Geothermal water and high evaporation rates also are associated with arsenic concentrations 10g/L in ground and surface water, particularly in the west.
Ground water exchange affects the ecology of surface water by sustaining stream base flow and moderating water-level fluctuations of ground water-fed lakes. It also provides stable-temperature habitats and supplies nutrients and inorganic ions. Ground water input of nutrients can even determine the trophic status of lakes and the distribution of macrophytes. In streams the mixing of ground water and surface water in shallow channel and bankside sediments creates a unique environment called the hyporheic zone, an important component of the lotic ecosystem. Localized areas of high ground water discharge in streams provide thermal refugia for fish. Ground water also provides moisture to riparian vegetation, which in turn supplies organic matter to streams and enhances bank resistance to erosion. As hydrologists and ecologists interact to understand the impact of ground water on aquatic ecology, a new research field called "ecohydrology" is emerging.
Abstract Management of near‐channel ground water and surface water to maintain stream health and flood plain ecological function requires hydrogeologists to refocus their conceptual models of water exchange between the aquifer and stream. The high hydraulic conductivity fluvial plain directs ground water flow down‐plain where it exchanges with the stream channel creating gaining, losing, flow‐through, and parallel‐flow reaches. The resulting complex flow system requires consideration when profiles representing ground water flowpaths are constructed. In addition to interaction at the scale of the fluvial plain, exchange of ground water and surface water within and immediately adjacent to the stream channel creates hyporheic zones. The physical and bio‐geochemical extent of these zones depends on the head distribution and ground water flow directions, stream hydraulics, and channel bed conditions, and magnitudes and distributions of hydrogeologic parameters. Simulated conceptualizations of flow dynamics caused by slight increases in hydraulic potentials at the surface water‐stream bed interface indicate stream‐ground water mixing could occur to a depth of 1.7 m below the channel. Rescaling of traditional hydrogeologic approaches to include the fluvial plain and channel scale will result in opportunities to expand hydrogeologic research and participate in interdisciplinary research teams attempting to decipher and manage fluvial systems.
Streambed temperature mapping, hydraulic testing using minipiezometers, and geochemical analyses of interstitial water of the streambed were used to delineate the pattern of ground water discharge in a sandy streambed and to develop a flux-based conceptual model for ground water/surface water interactions. A new and simple empirical method was used to relate fluxes obtained from minipiezometer data to streambed temperatures. The relationship allowed flux to be calculated at locations where only streambed temperature measurements were made. Slug testing and potentiomanometer measurements at 34 piezometers indicated ground water discharge ranged from 0.03 to 446 L/m2/day (and possibly as high as 7060 L/m2/day) along a 60 m long by 11 to 14 m wide reach of river. Complex but similar plan-view patterns of flux were calculated for both summer and winter using hundreds of streambed temperatures measured on a 1 by 2 m grid. The reach was dominated by ground water discharge and 5% to 7% of the area accounted for approximately 20% to 24% of the total discharge. < 12% of the total area consisted of recharge zones or no-discharge zones. A conceptual model for ground water/surface water interactions consisting of five different behaviors was developed based on the magnitude and direction of flux across the surface of the streambed. The behaviors include short-circuit discharge (e.g., high-flow springs), high discharge (e.g., preferential flowpaths), low to moderate discharge, no discharge (e.g., horizontal hyporheic or ground water flow), and recharge. Geological variations at depth played a key role in determining which type of flow behavior occurred in the streambed.
Elevated concentrations of sodium (Na+) and chloride (Cl-) in surface and ground water are common in the United States and other countries, and can serve as indicators of, or may constitute, a water quality problem. We have characterized the most prevalent natural and anthropogenic sources of Na+ and Cl- in ground water, primarily in Illinois, and explored techniques that could be used to identify their source. We considered seven potential sources that included agricultural chemicals, septic effluent, animal waste, municipal landfill leachate, sea water, basin brines, and road deicers. The halides Cl-, bromide (Br), and iodide (I) were useful indicators of the sources of Na+-Cl- contamination. Iodide enrichment (relative to Cl-) was greatest in precipitation, followed by uncontaminated soil water and ground water, and landfill leachate. The mass ratios of the halides among themselves, with total nitrogen (N), and with Na+ provided diagnostic methods for graphically distinguishing among sources of Na+ and Cl- in contaminated water. Cl/Br ratios relative to Cl- revealed a clear, although overlapping, separation of sample groups. Samples of landfill leachate and ground water known to be contaminated by leachate were enriched in I and Br; this provided an excellent fingerprint for identifying leachate contamination. In addition, total N, when plotted against Cl/Br ratios, successfully separated water contaminated by road salt from water contaminated by other sources.
The importance of considering ground water and surface water as a single resource has become increasingly evident. Issues related to water supply, water quality, and degradation of aquatic environments are reported on frequently. The interaction of ground water and surface water has been shown to be a significant concern in many of these issues. Contaminated aquifers that discharge to streams can result in long-term contamination of surface water; conversely, streams can be a major source of contamination to aquifers. Surface water commonly is hydraulically connected to ground water, but the interactions are difficult to observe and measure. The purpose of this report is to present our current understanding of these processes and activities as well as limitations in our knowledge and ability to characterize them.
For additional information, contact: National Water-Quality Assessment ProgramU.S. Geological Survey413 National Center12201 Sunrise Valley DriveReston, Virginia 20192https://water.usgs.gov/nawqa/ This report is one of a series of publications, The Quality of Our Nation's Waters, that describe major findings of the NAWQA Program on water-quality issues of regional and national concern. This report presents evaluations of pesticides in streams and ground water based on findings for the first decadal cycle of NAWQA. 'Pesticides in the Nation's Streams and Ground Water, 1992-2001' greatly expands the analysis of pesticides presented in 'Nutrients and Pesticides,' which was the first report in the series and was based on early results from 1992 to 1995. Other reports in this series cover additional water-quality constituents of concern, such as volatile organic compounds and trace elements, as well as physical and chemical effects on aquatic ecosystems. Each report builds toward a more comprehensive understanding of regional and national water resources. The information in this series is intended primarily for those interested or involved in resource management, conservation, regulation, and policymaking at regional and national levels. In addition, the information might interest those at a local level who wish to know more about the general quality of streams and ground water in areas near where they live and how that quality compares with other areas across the Nation.
Water is a critical resource for data centers and an efficient means of cooling. However, meeting the growing water demand of data centers requires substantial peak water withdrawals, which many communities in the United States cannot supply, especially during the hottest days of the year. This largely overlooked water capacity constraint is emerging as a bottleneck for data centers and can force operators to rely on less efficient dry cooling, further stressing the power grid during summer peaks. In this paper, we focus on the direct water withdrawal of U.S. data centers for cooling and examine their impacts on public water systems. Our analysis indicates that, if the 2024 water use intensity persists, U.S. data centers could collectively require 697-1,451 million gallons per day (MGD) of new water capacity through 2030, comparable to New York City's average daily supply of roughly 1,000 MGD. Under an optimistic scenario with a compound annual water use intensity reduction by 10%, the water capacity demand decreases to 227-604 MGD, although high-growth IT loads could still require enough capacity to hypothetically supply about half of New York City for most of the year. The total
OVERVIEW OF MICROBIOLOGY. History, Geology, and Microbiology. Microorganisms Present in the Ground-Water Environment. Bacterial Growth. Bacterial Metabolism. Bacterial Genetics. Microbial Ecology of Ground-Water Systems. MICROBIAL PROCESSES IN PRISTINE GROUND-WATER SYSTEMS. Abundance and Distribution of Bacteria in the Subsurface. Microbiological Sampling of Subsurface Environments. Biogeochemical Cycling in Ground-Water Systems. Oxidation-Reduction Processes in Ground-Water Systems. MICROBIAL PROCESSES IN CONTAMINATED GROUND-WATER SYSTEMS. Microbial Acclimation to Ground-Water Contamination. Biodegradation and Bioremediation of Petroleum Hydrocarbons in Ground-Water Systems. Biodegradation and Bioremediation of Halogenated Organic Compounds in Ground-Water Systems. References. Index.
Sustainable water resource management in transboundary river basins is challenged by fragmented data, limited real-time access, and the complexity of integrating diverse information sources. This paper presents WaterCopilot-an AI-driven virtual assistant developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research for the Limpopo River Basin (LRB) to bridge these gaps through a unified, interactive platform. Built on Retrieval-Augmented Generation (RAG) and tool-calling architectures, WaterCopilot integrates static policy documents and real-time hydrological data via two custom plugins: the iwmi-doc-plugin, which enables semantic search over indexed documents using Azure AI Search, and the iwmi-api-plugin, which queries live databases to deliver dynamic insights such as environmental-flow alerts, rainfall trends, reservoir levels, water accounting, and irrigation data. The system features guided multilingual interactions (English, Portuguese, French), transparent source referencing, automated calculations, and visualization capabilities. Evaluated using the RAGAS framework, WaterCopilot achieves an overall score of 0.8043, with
There can be many competing and contradictory explanations for a single model prediction, making it difficult to select which one to use. Current explanation evaluation frameworks measure quality by comparing against ideal "ground-truth" explanations, or by verifying model sensitivity to important inputs. We outline the limitations of these approaches, and propose three desirable principles to ground the future development of explanation evaluation strategies for local feature importance explanations. We propose a ground-truth Agnostic eXplanation Evaluation framework (AXE) for evaluating and comparing model explanations that satisfies these principles. Unlike prior approaches, AXE does not require access to ideal ground-truth explanations for comparison, or rely on model sensitivity - providing an independent measure of explanation quality. We verify AXE by comparing with baselines, and show how it can be used to detect explanation fairwashing. Our code is available at https://github.com/KaiRawal/Evaluating-Model-Explanations-without-Ground-Truth.
Glycerol acts as a natural cryoprotectant by depressing the temperature of ice nucleation and slowing down the dynamics of water mixtures. In this work we characterize dynamics -- diffusion, viscosity, and hydrogen-bond dynamics -- as well as density anomaly and structure of water mixtures with 1\% to 50\% w/w glycerol at low temperatures via molecular dynamics simulations using all-atom and coarse-grained models. Simulations reveal distinct violations of the Stokes-Einsten relation in the low temperature regime for water and glycerol. Deviations are positive for water at all concentrations, and positive for glycerol in very dilute solutions but turning negative in concentrated ones. The all-atom and coarse-grained models reveal an unexpected crossover in the dynamics of the 1% and 10 % w/w glycerol at the lowest simulated temperatures. This crossover manifests in the diffusion coefficients of water and glycerol, as well as in the viscosity and lifetime of hydrogen-bonds in water. We interpret that the crossover originates on the opposing dependence with glycerol concentration of the two factors controlling the solution's slow-down: the increase in tetrahedrally coordinated water a
It remains to be ascertained whether sub-Neptune exoplanets primarily possess hydrogen-rich atmospheres or whether a population of H$_2$O-rich "water worlds" lurks in their midst. Addressing this question requires improved modeling of water-rich exoplanetary atmospheres, both to predict and interpret spectroscopic observations and to serve as upper boundary conditions on interior structure calculations. Here we present new models of hydrogen-helium-water atmospheres with water abundances ranging from solar to 100% water vapor. We improve upon previous models of high water content atmospheres by incorporating updated prescriptions for water self-broadening and a non-ideal gas equation of state. Our model grid (https://umd.box.com/v/water-worlds) includes temperature-pressure profiles in radiative-convective equilibrium, along with their associated transmission and thermal emission spectra. We find that our model updates primarily act at high pressures, significantly impacting bottom-of-atmosphere temperatures, with implications for the accuracy of interior structure calculations. Upper atmosphere conditions and spectroscopic observables are less impacted by our model updates, and we
This paper studies the problem of optimal placement of water quality (WQ) sensors in water distribution networks (WDNs), with a focus on chlorine transport, decay, and reaction models. Such models are traditionally used as suitable proxies for WQ. The literature on this topic is inveterate, but has a key limitation: it utilizes simplified single-species decay and reaction models that do not capture WQ transients for nonlinear, multi-species interactions. This results in sensor placements (SP) that do not account for nonlinear WQ dynamics. Furthermore, as WQ simulations are parameterized by hydraulic profiles and demand patterns, the placement of sensors are often hydraulics-dependent. This study produces a greedy algorithm that addresses the two aforementioned limitations. The algorithm is grounded in nonlinear dynamic systems and observability theory, and yields SPs that are submodular and robust to hydraulic changes. Case studies on benchmark water networks are provided. The key findings provide practical recommendations for WDN operators.
Accurate water consumption forecasting is a crucial tool for water utilities and policymakers, as it helps ensure a reliable supply, optimize operations, and support infrastructure planning. Urban Water Distribution Networks (WDNs) are divided into District Metered Areas (DMAs), where water flow is monitored to efficiently manage resources. This work focuses on short-term forecasting of DMA consumption using deep learning and aims to address two key challenging issues. First, forecasting based solely on a DMA's historical data may lack broader context and provide limited insights. Second, DMAs may experience sensor malfunctions providing incorrect data, or some DMAs may not be monitored at all due to computational costs, complicating accurate forecasting. We propose a novel method that first identifies DMAs with correlated consumption patterns and then uses these patterns, along with the DMA's local data, as input to a deep learning model for forecasting. In a real-world study with data from five DMAs, we show that: i) the deep learning model outperforms a classical statistical model; ii) accurate forecasting can be carried out using only correlated DMAs' consumption patterns; and
The ground‐water component of stream discharge may be determined from the chemical characteristics of the stream water. A chemical mass‐balance is used to relate total, direct, and ground‐water runoff. To solve the mass‐balance equation, it is necessary to estimate the chemical composition of the ground‐water and direct‐runoff components. The solute concentration of ground water is determined from total runoff during baseflow; the chemical characteristics of direct‐runoff are estimated from samples of total runoff collected from selected locations in a basin during peak discharge periods. In three small watersheds in Nova Scotia ground‐water runoff constituted from 32 to 42% of peak discharge for the period of analysis.
Accurately predicting water table dynamics is vital for sustaining groundwater resources that support ecological functions and anthropogenic activities. This study evaluates a statistical model (BigVAR) that handles three major flexibilities: (a) prediction under a sparsity assumption in coefficients, (b) consideration of a time series autoregression framework, and (c) allowance for lags in both dependent and independent variables for estimating water table depth using daily hydroclimatic data from the USDA Forest Service Santee Experimental Forest (SC) and a site in NC. Data from 2006--2019 (SC) and 1988--2008 (NC) were used, with key predictors including soil and air temperature, precipitation, wind, and radiation. For WS80, RMSE during the dormant season was 10.09 cm, with a daily testing phase RMSE of 14.94 cm. The model achieved an R^2 of 0.93 for 2019 (a dry year) and 0.96 for 2016 (a wet year). Solar radiation, rainfall, and wind direction were among the most influential variables. This predictive model aids in managing wetland hydrology and supports decision-making for forest managers and hydrologists.
The need to assess the effects of variability in climate, biota, geology, and human activities on water availability and flow requires the development of models that couple two or more components of the hydrologic cycle. An integrated hydrologic model called GSFLOW (Ground-water and Surface-water FLOW) was developed to simulate coupled ground-water and surface-water resources. The new model is based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) and the U.S. Geological Survey Modular Ground-Water Flow Model (MODFLOW). Additional model components were developed, and existing components were modified, to facilitate integration of the models. Methods were developed to route flow among the PRMS Hydrologic Response Units (HRUs) and between the HRUs and the MODFLOW finite-difference cells. This report describes the organization, concepts, design, and mathematical formulation of all GSFLOW model components. An important aspect of the integrated model design is its ability to conserve water mass and to provide comprehensive water budgets for a location of interest. This report includes descriptions of how water budgets are calculated for the integrated model and for individual model components. GSFLOW provides a robust modeling system for simulating flow through the hydrologic cycle, while allowing for future enhancements to incorporate other simulation techniques.
In this work, we investigate non-classical wavetrain formations, and particularly dispersive shock waves (DSWs), or undular bores, in systems exhibiting non-convex dispersion. Our prototypical model, which arises in shallow water wave theory, is the extended Korteweg-de Vries (eKdV) equation. The higher-order dispersive and nonlinear terms of the latter, lead to resonance between dispersive radiation and solitary waves, and notably, the individual waves comprising DSWs, due to non-convex dispersion. This resonance manifests as a resonant wavetrain propagating ahead of the dispersive shock wave. We present a succinct overview of the fundamental principles and characteristics of DSWs and explore analytical methods for their analysis. Wherever applicable, we demonstrate these concepts and techniques using both the classical KdV equation and its higher-order eKdV counterpart. We extend the application of the dispersive shock fitting method and the equal amplitude approximation to investigate radiating DSWs governed by the eKdV equation. We also introduce Whitham shock solutions for the regime of traveling DSWs of the eKdV model. Theoretical predictions are subsequently validated agains