A large imbalance between recharge and water withdrawal has caused vital regions of the High Plains Aquifer (HPA) to experience significant declines in storage. A new predevelopment map coupled with a synthesis of annual water levels demonstrates that aquifer storage has declined by approximately 410 km(3) since the 1930s, a 15% larger decline than previous estimates. If current rates of decline continue, much of the Southern High Plains and parts of the Central High Plains will have insufficient water for irrigation within the next 20 to 30 years, whereas most of the Northern High Plains will experience little change in storage. In the western parts of the Central and northern part of the Southern High Plains, saturated thickness has locally declined by more than 50%, and is currently declining at rates of 10% to 20% of initial thickness per decade. The most agriculturally productive portions of the High Plains will not support irrigated production within a matter of decades without significant changes in management.

Sustainable management of agricultural water resources requires improved understanding of irrigation patterns in space and time. We produced annual, high‐resolution (30 m) irrigation maps for 1999–2016 by combining all available Landsat satellite imagery with climate and soil covariables in Google Earth Engine. Random forest classification had accuracies from 92 to 100% and generally agreed with county statistics (r2 = 0.88–0.96). Two novel indices that integrate plant greenness and moisture information show promise for improving satellite classification of irrigation. We found considerable interannual variability in irrigation location and extent, including a near doubling between 2002 and 2016. Statistical modeling suggested that precipitation and commodity price influenced irrigated extent through time. High prices incentivized expansion to increase crop yield and profit, but dry years required greater irrigation intensity, thus reducing area in this supply‐limited region. Data sets produced with this approach can improve water sustainability by providing consistent, spatially explicit tracking of irrigation dynamics over time.

Irrigation’s effects on precipitation during an exceptionally dry summer (June–August 2012) in the United States were quantified by incorporating a novel dynamic irrigation scheme into the Weather Research and Forecasting (WRF) Model. The scheme is designed to represent a typical application strategy for farmlands across the conterminous United States (CONUS) and a satellite-derived irrigation map was incorporated into the WRF-Noah-Mosaic module to realistically trigger the irrigation. Results show that this new irrigation approach can dynamically generate irrigation water amounts that are in close agreement with the actual irrigation water amounts across the high plains (HP), where the prescribed scheme best matches real-world irrigation practices. Surface energy and water budgets have been substantially altered by irrigation, leading to modified large-scale atmospheric circulations. In the studied dry summer, irrigation was found to strengthen the dominant interior high pressure system over the southern and central United States and deepen the trough over the upper Midwest. For the HP and central United States, the rainfall amount is slightly reduced over irrigated areas, likely as a result of a reduction in both local convection and large-scale moisture convergence resulting from interactions and feedbacks between the land surface and atmosphere. In areas downwind of heavily irrigated regions, precipitation is enhanced, resulting in a 20%–100% reduction in the dry biases (relative to the observations) simulated over a large portion of the downwind areas without irrigation in the model. The introduction of irrigation reduces the overall mean biases and root-mean-square errors in the simulated daily precipitation over the CONUS.

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Linking fecal indicator bacteria concentrations in large mixed-use watersheds back to diffuse human sources, such as septic systems, has met limited success. In this study, 64 rivers that drain 84% of Michigan's Lower Peninsula were sampled under baseflow conditions for Escherichia coli, Bacteroides thetaiotaomicron (a human source-tracking marker), landscape characteristics, and geochemical and hydrologic variables. E. coli and B. thetaiotaomicron were routinely detected in sampled rivers and an E. coli reference level was defined (1.4 log 10 most probable number·100 mL −1). Using classification and regression tree analysis and demographic estimates of wastewater treatments per watershed, septic systems seem to be the primary driver of fecal bacteria levels. In particular, watersheds with more than 1,621 septic systems exhibited significantly higher concentrations of B. thetaiotaomicron. This information is vital for evaluating water quality and health implications, determining the impacts of septic systems on watersheds, and improving management decisions for locating, constructing, and maintaining on-site wastewater treatment systems.Escherichia coli | Bacteroides thetaiotaomicron | baseflow | reference conditions | septic system W ater quality degradation influenced by diffuse sources at large watershed scales has been difficult to describe. Human modifications of natural landscapes can permanently alter hydrologic cycles and affect water quality (1, 2). Deforestation (3) and increased impervious surface area (4) have been linked with decreased infiltration and thus increased surface runoff. Overland flows concentrate pollutants and rapidly transport them down gradient where they eventually enter surface water systems and affect water quality (5, 6). A number of models have been developed to calculate overland and surface water flows (7,8) and nutrient/chemical transport (9), but few studies have focused on microbial movement from land to water, particularly nontraditional fecal indicator bacteria that can be used to track human sources of pollution.Microbial contamination poses one of the greatest health risks to swimming areas, drinking water intakes, and fishing/shellfish harvesting zones where human exposures are highest (10-12). These highly visible areas often receive more attention than sources of contamination because identifying the origin of pollution in complex watersheds requires costly comprehensive investigation of environmental and hydrologic conditions across temporal and spatial scales (13). Grayson et al. (14) suggest using a "snapshot" approach that captures water quality characteristics at a single point in time across broad areas to provide information frequently missed during routine monitoring. Compared with long-term comprehensive investigations, the snapshot approach reduces the number of samples, cost, and personnel required to examine pollution sources.Escherichia coli concentrations are commonly used to describe the relative human health risk during water quality monitoring in li...

In modern agriculture, the interplay between complex physical, agricultural, and socioeconomic water use drivers must be fully understood to successfully manage water supplies on extended timescales. This is particularly evident across large portions of the High Plains Aquifer where groundwater levels have declined at unsustainable rates despite improvements in both the efficiency of water use and water productivity in agricultural practices. Improved technology and land use practices have not mitigated groundwater level declines, thus water management strategies must adapt accordingly or risk further resource loss. In this study, we analyze the water-energy-food nexus over the High Plains Aquifer as a framework to isolate the major drivers that have shaped the history, and will direct the future, of water use in modern agriculture. Based on this analysis, we conclude that future water management strategies can benefit from: (1) prioritizing farmer profit to encourage decision-making that aligns with strategic objectives, (2) management of water as both an input into the water-energy-food nexus and a key incentive for farmers, (3) adaptive frameworks that allow for short-term objectives within long-term goals, (4) innovative strategies that fit within restrictive political frameworks, (5) reduced production risks to aid farmer decision-making, and (6) increasing the political desire to conserve valuable water resources. This research sets the foundation to address water management as a function of complex decision-making trends linked to the water-energy-food nexus. Water management strategy recommendations are made based on the objective of balancing farmer profit and conserving water resources to ensure future agricultural production.

Irrigation enhances agricultural yields and stabilizes farmer incomes, but overexploitation has depleted groundwater resources around the globe. Strategies to address this sustainability challenge differ widely. Socio-ecological systems research suggests that management of common pool resources like groundwater would benefit from localized approaches that combine self-organization along with active monitoring. In 2012, the US state of Kansas established a Local Enhanced Management Area (LEMA) program, empowering farmers to work with local and state officials to develop five-year, enforceable groundwater conservation programs. Here, we assessed the efficacy of the first LEMA implemented from 2013 to 2017 using a causal impact methodology based on Bayesian structural time series that is new to agrohydrology. Compared to control scenarios, we found that the LEMA reduced water use by 31% over the five-year period, with early indications of stabilizing groundwater levels. Three main conservation strategies can lead to reduced water use: (1) reducing irrigated area, (2) reducing irrigation amount applied to existing crops through improved efficiency, and/or (3) switching to crops that require less water. To partition water savings among these strategies, we combined satellite-derived irrigated areas and crop type maps with well records. We found that farmers were able to largely maintain irrigated area and achieved the majority of pumping reductions (72%) from improvements in irrigation efficiency, followed by expansion of crops with lower water demand (19%). The results of this analysis demonstrate that conservation programs that are irrigatordriven with regulatory oversight can provide a path toward sustainability in stressed aquifers.

River ecosystems are driven by linked physical, chemical, and biological subsystems, which operate over different temporal and spatial domains. This complexity increases uncertainty in ecological forecasts, and impedes preparation for the ecological consequences of climate change. We describe a recently developed ''multi-modeling'' system for ecological forecasting in a 7600 km 2 watershed in the North American Great Lakes Basin. Using a series of linked land cover, climate, hydrologic, hydraulic, thermal, loading, and biological response models, we examined how changes in both land cover and climate may interact to shape the habitat suitability of river segments for common sport fishes and alter patterns of biological integrity. In scenariobased modeling, both climate and land use change altered multiple ecosystem properties. Because water temperature has a controlling influence on species distributions, sport fishes were overall more sensitive to climate change than to land cover change. However, community-based biological integrity metrics were more sensitive to land use change than climate change; as were nutrient export rates. We discuss the implications of this result for regional preparations for climate change adaptation, and the extent to which the result may be constrained by our modeling methodology.