Groundwater sustains global agriculture but faces significant pressure from overexploitation, threatening long-term water security. Achieving a balance between agricultural productivity and sustainable groundwater use requires decision-support tools that can integrate hydrologic and economic information and be adapted to different farm and aquifer conditions. This study develops an accessible farm-level hydro-economic model that links groundwater dynamics with economic outcomes to evaluate irrigation strategies under regulatory and physical constraints. The model estimates land value over time while incorporating uncertain precipitation, irrigation practices, and regulatory limits. This research presents a novel application of Conditional Value-at-Risk to assess economic risk of groundwater irrigation by focusing on the tail of the probability curve, emphasizing potential extreme adverse outcomes rather than average performance. Applied to a representative High Plains Aquifer site, the model shows that more pumping does not guarantee greater profitability, as diminishing returns and aquifer depletion can undermine long-term benefits. Instead, irrigation strategies aligned with site-specific aquifer properties and regulatory thresholds improve both economic performance and sustainability. This scalable approach provides a useful framework to inform irrigation policy, support farmer decision-making, and promote sustainable groundwater under growing uncertainty.

Groundwater overexploitation can reduce flows in connected rivers through streamflow depletion, which threatens ecosystems and downstream users who often rely on these flows for their economic wellbeing. Quantifying groundwater-surface water interactions and their economic trade-offs remains challenging for sustainable water management. This study integrates analytical groundwater and streamflow depletion methods with a farm-level hydro-economic model to evaluate the hydrologic and economic effects of irrigation groundwater pumping illustrated using example applications in confined and unconfined aquifers. The model separates the effect on land value of aquifer storage, streamflow depletion, and direct surface water use, allowing a clearer understanding of how each water source affects economic outcomes. Results from the simulated aquifers show that confined aquifers experience faster and larger streamflow depletion, while unconfined systems exhibit slower and smaller depletion. Distance to the stream and pumping rates are key determinants of depletion, shaping both its timing and magnitude, and they also have distinct effects on land values. The marginal economic value of streamflow depletion is consistently low or negative, suggesting that the water gained through depletion contributes minimally to overall economic returns. These findings highlight the importance of identifying water source contributions, well placement, and regulatory constraints when designing irrigation strategies. Through integrated marginal value and risk analyses, this study offers practical insights for policymakers and water managers to design irrigation strategies that balance economic returns with long-term water resource sustainability.

The Giant Mine (1948-1999) generated 16 Mt of Au-bearing mill tailings (2800 mg kg(-1)) originating from a mixture of flotation tailings (84.8 wt%), calcine residues (14.4 wt.%), and arsenic trioxide roaster waste (0.8 wt.%). A water treatment system for high As mine dewatering effluent has operated since the end of mine operations, with the intermediate storage area being the Northwest Tailings Containment Area (NW-TCA). The tailings porewater contains elevated concentrations of dissolved As, Sb, Zn, and other metals. A multi-year water balance supported by an examination of unsaturated and saturated flow conditions and based on isotope and geochemical analysis was conducted to understand the NW-TCA hydrological system. Hydraulic gradients indicate persistent downward flow in the south end of NW-TCA. Water balance calculations indicate an average of 384,000 m(3) y(-1) of water from the NW-TCA entered the groundwater system during the study period (2017-2022). Stable water isotope and water chemistry measurements indicate porewater in areas of high-water table is influenced by mine dewatering effluent. Isotope mass balance indicates 60% of the mine dewatering effluent, which contains high concentrations of As, is sourced from water cycled through the NW-TCA. The impact of the mine dewatering effluent is minimal in areas with a deep vadose zone, containing lower concentrations of As. Hydrological simulations indicate groundwater flow rates into the deep groundwater flow system from the NW-TCA would be modest in the absence of the mine dewater pond because the system is near net evaporative in the absence of mine dewatering effluent.

Climate change is increasingly impacting water availability. National-scale hydrologic models simulate streamflow resulting from many important processes, but often without processes such as human water use and management activities. This work explores and tests methods to account for such omitted processes using one national-scale hydrologic model. Two bias correction methods, Flow Duration Curve (FDC) and Auto-Regressive Integrated Moving Average (ARIMA), are tested on streamflow simulated by the US Geological Survey National Hydrologic Model (NHM-PRMS), which omits irrigation pumping. A semi-arid agricultural case study is used. FDC and ARIMA perform better for correcting low and high flows, respectively. A hybrid method performs well at both low and high flows; typical Nash-Sutcliffe values increased from <-1.00 to about 0.75. Results suggest methods with which national-scale hydrologic models can be bias-corrected for omitted processes to improve regional streamflow estimates. Utility of these correction methods in simulation of future projections is discussed.

AbstractReductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream‐aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision‐making process. Key priorities include (a) linking streamflow depletion to decision‐relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision‐making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision‐support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water‐connected disciplines, professions, governments, organizations, and communities.

Both natural processes and human activities alter streamflow conditions, which can significantly affect streambank erosion and stability, leading to consequences such as sedimentation of reservoirs, contamination of streams, loss of productive land, and damage to infrastructure. Hydrological conditions, which are often controlled by water management decisions and infrastructure (e.g., reservoirs and dams), are a major factor affecting streambank erosion and stability. Extensive research has explored the relationships between hydrology, water management, and streambank stability. However, limited studies directly address the impacts of water management decisions, particularly reservoir operations, on the driving mechanisms of streambank stability such as changes in pore water pressure, pressure differentials between the surface and subsurface, and gravitational forces versus shear stress. This study builds upon these existing concepts by integrating them into a model that accounts for both the effects of water management and inherent hydrologic conditions on streambank stability.The module estimates streambank stability using a factor of safety approach, with hydrologic conditions derived from an established integrated hydrologic model, HydroGeoSphere, coupled with the surface water operations model, OASIS. This module is validated and then demonstrated using simulations from the Lower Republican River Basin in Kansas, United States. Results indicate that several water management decisions, such as groundwater pumping and timing of reservoir releases, may negatively affect streambank stability by changing pore water pressure, the weight of the bank material, and the pressure differential between the surface and the subsurface. Given that most of the rivers and streams of the world are regulated by reservoir operations, this work demonstrates that water management practices need to be considered in simulations of streambank stability.

Study region: The Western Cape (WC), South Africa. Study focus: The WC has become increasingly dependent on groundwater in recent years due to repeated droughts. A framework to monitor the regional groundwater levels is urgently required to sustainably manage the WC's water resources, since the region has inconsistent or unavailable monitoring data. Therefore, this study aims to understand how Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data can be used to monitor groundwater storage variations (AGWS) in the WC. In -situ AGWS time -series from twelve aquifers in the WC were compared to GRACE and GLDAS data. New hydrological insights for the region: GRACE terrestrial water storage anomalies (ATWS) showed moderate positive correlation (r = 0.69) with in -situ AGWS from the Adelaide Subgroup Aquifer (ASA), an unconfined aquifer with large areal extent and large AGWS. The Table Mountain Group Upper Aquifer Unit (TMG UAU) and Cape Flats Aquifer (CFA) also showed significant positive correlations with GLDAS AGWS of 0.83 and 0.73, respectively. Our results suggest that AGWS in the ASA can be monitored using GRACE ATWS, while GLDAS AGWS data can be used to monitor AGWS in the unconfined TMG UAU and CFA. GRACE and GLDAS data may be suitable to monitor groundwater availability in other water- and data -scarce regions of Africa.

Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater-irrigated region in the state of Kansas, USA, where high-quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically-based Water Table Fluctuation method (WTFM); (2) the demand-based SALUS crop model; (3) estimates based on satellite-derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic- and demand-based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application.

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

Groundwater and surface water, including such engineered surface water bodies as irrigation canals and drainage ditches, are connected. As such, changes to the management of these surface water bodies will affect interconnected groundwater systems as well. In the Lower Republican River Basin in Kansas, United States, a regional irrigation district has converted several irrigation canals to buried pipe to reduce water lost to evapotranspiration and groundwater recharge, increasing the delivery efficiency of its system. The objective of this work was to investigate the change in local groundwater levels due to this conversion. Seven existing wells in the vicinity of converted or soon-to-be converted irrigation canals were equipped with pressure transducers, and hourly water-level measurements were collected over several years. Average water levels decreased in all wells post-conversion compared to measurements taken between 1970 and 2001. The water levels did not decrease equally, and in several wells, the water-level variance also changed from pre- to post-conversion. It is hypothesized that the observed changes are controlled by many factors, including those related to canal conversion (proximity to the converted canal and time since canal conversion), proximity to other surface water features such as the main stem of the canal and reservoir, and subsurface characteristics that influence the rate of infiltration from precipitation events. This research highlights the interconnectedness of surface and subsurface water resources and how water management decisions need to consider how these interactions may change to support sustainable water use.

The carbon dioxide (CO2) fluxes from headwater streams are not well quantified and could be a source of significant carbon, particularly in systems underlain by carbonate lithology. Also, the sensitivity of carbonate systems to changes in temperature will make these fluxes even more significant as climate changes. This study quantifies small-scale CO2 efflux and estimates annual CO2 emission from a headwater stream at the Konza Prairie Long-Term Ecological Research Site and Biological Station (Konza), in a complex terrain of horizontal, alternating limestones and shales with small-scale karst features. CO2 effluxes ranged from 2.2 to 214 g CO2 m(-2) day(-1) (mean: 20.9 CO2 m(-2) day(-1)). Downstream of point groundwater discharge sources, CO2 efflux decreased, over 2 m, to 3-40% of the point-source flux, while delta C-13-CO2 increased, ranging from -9.8 % to -23.2 % V-PDB. The delta C-13-CO2 increase was not strictly proportional to the CO2 flux but related to the origin of vadose zone CO2. The high spatial and temporal variability of CO2 efflux from this headwater stream informs those doing similar measurements and those working on upscaling stream data, and that local variability should be assessed to estimate the impact of headwater stream CO2 efflux on the global carbon cycle.

Baseflow, the groundwater contribution to streamflow, sustains surface water between precipitation events and is an important indicator of groundwater availability. Although many site-specific studies have been completed, there are few studies of long-term Canada-wide baseflow trends. In this work, we detected monthly baseflow trends across Canada and related them to changes to climatic predictors (precipitation, temperature, and ante-cedent wetness) using streamflow data from 1275 hydrometer stations from 1989 to 2019. Lyne and Hollick's one-parameter digital filter is used to obtain a baseflow time series and monotonic trends are identified using the Mann-Kendall Trend Test. Historical baseflow is related to climate parameters by means of Generalised Additive Models for Location, Scale and Shape (GAMLSS) statistical analysis. Results based on trend analysis detected no significant trends for most stations (85.7% of all stations and months). However, notable increasing trends were observed across most of southern Canada during the winter and spring months (October-April). Conversely, negative trends were detected from June to September in Alberta and British Columbia and in southern Northwest Territories. Model selection identified antecedent wetness most often as a climate predictor over the same period as trend analysis. Our results highlight that warmer temperatures and increased snow cover across much of Canada have contributed to increased baseflow likely from shifts in snow melt timing and volumes. During warmer months (June-August), results indicate that increases in temperature were related to decreased baseflow, likely through increased evapotranspiration. Many trends in baseflow were not related to any climate predictors. Furthermore, non-reference basins were twice as likely to have no climate predictor, indicating that anthropogenic activities may be driving changes in baseflow. The results of this work can inform water resources management to identify the direction of change in groundwater availability across Canada and regions where mitigation may be necessary.

Agricultural practices in intensively managed landscapes are thought to be shifting hydro-bio-geochemical behavior from transformation to transport dominated systems. Here we explore the impacts of a best management practice known as tile-outlet-terraces (TOT). Tiles at this site are a set of perforated vertical pipes that can receive direct surface water, soil water and groundwater inputs that are connected to horizontal pipes that transport water to a receiving pond. Terraces are constructed, horizontal areas created to divide sloping terrains to reduce slope steepness and erosion, and in so doing they redirect surface water toward standpipes and promote soil and groundwater discharge as a result bisecting local flowpaths. While the impact of tiles on hydrologic behavior has been well studied, the combined impact of TOTs has not been well quantified. To address this knowledge gap, we focus on the response of TOT discharge and biogeochemical behavior across three adjacent agroecosystems in Kansas over three growing seasons (2016–2018). TOT discharge was measured every minute at each location and discharge during storm events was collected and analyzed for dissolved and total nutrients as well as major anion and cation chemistry. Additionally, suction cup lysimeters were installed at the ridges and depression of the terraces to capture soil water solute chemistry prior to storm events. Recession curve analysis revealed that tile inlet density was not directly related to the proportion of quickflow, mixing models showed that antecedent conditions played a critical role in the degree of connectivity of event water to the tiles, and concentration discharge behavior showed the dominant behavior for all constituents was chemostatic across all tile densities. Interestingly, these findings suggest that while TOTs shift the hydrology of agroecosystems away from natural conditions, the storm event size and antecedent conditions can still dominate the hydrologic and biogeochemical response to storm events.