High Plains Aquifer Research Articles

Recommendations for Better Collaborative Groundwater Monitoring for the US High Plains Aquifer

Groundwater is a critical resource for the Great Plains region of the United States, providing drinking water for over 2 million people. However, the High Plains Aquifer (HPA) is under significant threat from over-extraction—defined as the excessive withdrawal of groundwater beyond its natural replenishment rate. This overuse jeopardizes not only water availability but also equitable access and allocation. Effective groundwater monitoring is essential to track trends in water availability, assess the impacts of extraction, and develop strategies to ensure long-term sustainability. Without comprehensive monitoring, it is difficult to address key issues like contamination, depletion, and groundwater quality degradation. While several state-level frameworks exist to enhance groundwater monitoring, they operate independently, leading to gaps in data sharing and collaboration, especially for a transboundary resource like the HPA. The Environmental Protection Agency (EPA) and U.S. Geological Survey (USGS) are well-positioned to play a more central role in this process. The EPA, with its mandate to protect water quality, and the USGS, with its expertise in nationwide data collection, are critical to supporting a collaborative and comprehensive groundwater monitoring system. By facilitating the integration of state-level efforts, these federal agencies can help ensure that groundwater monitoring is both consistent and accurate, enabling effective decision-making at regional and national levels. This policy memo provides a detailed analysis of current state-level efforts, highlights the role of the EPA and USGS in addressing governance challenges, and proposes a transboundary governance mechanism to enhance collaborative groundwater monitoring. The intended audience includes policymakers at the EPA and USGS, as well as water resource managers who are key to implementing these changes.

The LTAR Grazing Land Common Experiment at Platte River High Plains Aquifer.

The Long-Term Agroecosystem Research (LTAR) network of the United States Department of Agriculture (USDA) consists presently of 18 sites within the contiguous United States that are managed by the Agricultural Research Service (ARS) and its partners. The LTAR network focuses on developing national strategies for more efficient, resilient, and profitable agricultural production systems, improved environmental quality, and enhanced rural prosperity. The Platte River High Plains Aquifer (PRHPA) LTAR site is managed jointly by the University of Nebraska-Lincoln (UNL) and USDA-ARS and is one of the LTAR sites that conduct research on both integrated cropping and grazing systems. The PRHPA region encompasses multiple land resource areas and diverse agricultural production systems. The PRHPA sites, predominantly located in eastern Nebraska, are designated as an integrated system focused specifically on the region's dominant production practices of row crop (corn and soybean), managed pastures, and beef cattle production. Here, we focus on C3 cool-season smooth bromegrass (Bromus inermis Leyss.) pasture grazing systems under prevailing and alternative management practices for the region. The sites evaluate continuous and rotational grazing with and without pasture fertilization (prevailing practices). In an additional treatment, cattle are supplemented with dry distillers grains plus solubles, while manure supplies fertilization (alternative practice). Main measurements at the site evaluate plant and animal productivity, forage quality, greenhouse gas fluxes, and soil physical, chemical, and biological properties. This paper describes the regional characteristics of the PRHPA site, ongoing LTAR research related to pasture and livestock production, stakeholder engagement, and future research plans.

The capitalization of property rights to groundwater

AbstractThere is limited empirical evidence on the value of formal property rights to natural resources when they are not transferable, and there is regulatory uncertainty about enforcement. This paper takes a hedonic approach to understanding how three core features of groundwater property rights—access, allocation, and seniority—are capitalized into agricultural land values in the High Plains Aquifer region of Kansas. We find that groundwater access rights confer an average land value premium of 71%, or $1445/acre in 2019 dollars. Water rights having larger allocations and more seniority are more highly valued in the land market. The seniority effect is small but is consistent with more junior rights facing greater regulatory risk of curtailment. Taken together, these results suggest that the land market capitalizes constraints to groundwater pumping provided by groundwater property rights. We use our empirical estimates to quantify the distributional costs of modifying existing patterns of pumping, a common challenge of groundwater management organizations seeking to improve the sustainability of extraction.

PyCHAMP: A crop-hydrological-agent modeling platform for groundwater management

The Crop-Hydrological-Agent Modeling Platform (PyCHAMP) is a Python-based open-source package designed for modeling agro-hydrological systems. The modular design, incorporating aquifer, crop field, groundwater well, finance, and behavior components, enables users to simulate and analyze the interactions between human and natural systems, considering both environmental and socio-economic factors. This study demonstrates PyCHAMP's capabilities by simulating the dynamics in the Sheridan 6 Local Enhanced Management Area, a groundwater conservation program in the High Plains Aquifer in Kansas. We highlight how a model, empowered by PyCHAMP, accurately captures human-water dynamics, including groundwater level, water withdrawal, and the fraction of cropland dedicated to each crop. We also show how farmer behavior, and its representation, drives system outcomes more strongly than environmental conditions. The results indicate PyCHAMP's potential as a useful tool for human-water research and sustainable groundwater management, offering prospects for future integration with detailed sub-models and systematic evaluation of model structural uncertainty.

Pipeline emergency preparedness in Nebraska: Identifying interagency preparedness gaps and proposing solutions.

In Nebraska, there are over 28,000 miles of pipelines that carry various materials, which could impact human health and the natural environment in the event of a leak or spill. Nebraska is heavily reliant on its expansive groundwater supply from the large High Plains aquifer system as well as smaller secondary aquifers. Eighty-eight percent of Nebraska's population utilizes groundwater for personal use, and the state's agricultural sector depends on it for irrigation and livestock care. The ongoing challenges facing the implementation of the proposed Keystone XL pipeline system inspired re-searchers to examine the current state of pipeline emergency preparedness in Nebraska. To do this, a pipeline emergency preparedness workshop was held in November 2021 in Norfolk, Nebraska. Conference participants in-cluded county- and regional-level leadership, local public health departments, tribal representatives, and other organizations. Pipeline emergency responders and other stakeholders were invited to listen to plenary presenta-tions about inland oil spill responses and the current state of Nebraska pipelines and to participate in a facilitated discussion identifying pipeline response challenges and potential solutions. Through a facilitated discussion process, participants identified six general response challenge categories and 24 potential solutions. From those 24 solutions, three were selected as easily implementable solutions-increased joint/coordinated planning, increased pipeline emergency exercising, and increased pipeline emergency train-ing/education. Implementing this work will assist in reducing health risks associated with potential spills.

Groundwater quality vs. groundwater quantity. Combining information on irrigator concerns with past water use and cropping behavior.

The effectiveness of groundwater in fulfilling crop water deficits depends on its quality and quantity. This paper examines the relationship between irrigators’ stated concerns over groundwater quality and groundwater quantity and their past water use and cropping decisions. Information on irrigator concerns over groundwater quality and quantity is obtained from 626 survey responses of agricultural producers in the Kansas portion of the High Plains Aquifer. We combine 20 years of field-level water use and cropping data with each of the 626 survey responses. We find that irrigators indicating elevated concern over either groundwater quality or groundwater quantity correlates with less total water use, fewer total irrigated acres, and fewer acres of irrigated corn. Additionally, concerns over groundwater quantity generally correlate with a greater reduction in water use along multiple water use margins compared to equal concerns over groundwater quality.

The U.S. Midwest and High Plains Aquifer-fed croplands are previously unrealized hotspots of extreme evaporative demand exposure

Total evaporative demand or atmospheric thirst is a primary determinant of agroecosystems’ water use and an indispensable input to scientifically based irrigation design and management. However, despite its extensive use to represent agricultural environments, it has not been assessed for its extreme behavior. Prolonged exposure to extreme evaporative demand conditions a.k.a thirstwaves can be especially stressful for agricultural output, water use, and management, but remain uninvestigated owing to lack of meaningful metrics for quantifying and reporting ‘extreme thirst exposure’. In this letter, I present spatial (county-level) and temporal (1981–2021) changes in exposure to extreme thirst during the agricultural growing season across the conterminous U.S. (CONUS). Using a fully physical metric of evaporative demand, i.e., standardized short crop reference evapotranspiration (ETo), I define two novel measures: cumulative extreme thirst exposure (thirstcum) and average extreme thirst anomaly (thirstanom) to represent the seasonal-level severity of thirstwaves. Both metrics showed significant spatiotemporal variation with long-term averages of 12 mm (thirstcum) and 0.66 mm d−1 (thirstanom) for CONUS. Distinct spatial patterns were revealed for extreme thirst exposure that had little in common with those observed for total ETo. Spatially, hotspots of high extreme thirst exposure were co-located with the Midwest and High Plains aquifer regions, that account for 64% of total acreage and 28% of irrigated acreage nationally, respectively. Critical for food and water security, these regions have experienced the highest extreme thirst exposure nationally, hence necessitating reevaluation of regional disparities in water stress. While thirstcum and thirstanom have increased by 5.6 mm and 0.21 mm d−1 on an average in CONUS, worsening of extreme thirst exposure is especially concerning for the High Plains aquifer region (12.6 mm and 0.54 mm d−1, respectively). The emergence of previously unrealized hotspots in regions critical for water security uncover potential pitfalls for planning and adaptation that may result from overlooking extreme measures of evaporative demand.

Spatial Variation in Transit Time Distributions of Groundwater Discharge to a Stream Overlying the Northern High Plains Aquifer, Nebraska, USA

AbstractGroundwater transit time distributions (TTDs) describe the spectrum of flow‐weighted apparent ages of groundwater from aquifer recharge to discharge. Regional‐scale TTDs in stream baseflow are often estimated from numerical models with limited calibration from groundwater sampling and suggest much younger groundwater discharge than has been observed by discrete age‐dating techniques. We investigate both local and regional‐scale groundwater TTDs in the Upper Middle Loup watershed (5,440 km2) overlying the High Plains Aquifer in the Nebraska Sand Hills, USA. We determined flow‐weighted apparent ages of groundwater discharging through the streambed at 88 discrete points along a 99 km groundwater‐dominated stream segment using 3H, noble gases, 14C, and groundwater flux measurements at the point‐scale (<7.6 cm diameter). Points were organized in transects across the stream width (3–10 points per transect) and transects were clustered in five sampling areas (10–610 m in stream length) located at increasing distances along the stream. Groundwater apparent ages ranged from 0 to 8,200 years and the mean groundwater transit time along the 99 km stream is >3,000 years. TTDs from upstream sampling areas were best fit by distributions with a narrow range of apparent ages, but when older groundwater from downstream sampling areas is included, the regional TTD is scale dependent and the distribution is better described by a gamma model (α ≈ 0.4) which accommodates large fractions of millennial‐aged groundwater. Observations indicate: (a) TTDs can exhibit spatial variability within a watershed and (b) watersheds can discharge larger fractions of old groundwater (>1,000 years) than commonly assumed.

Simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

Impacts of irrigation on a precipitation event during GRAINEX in the High Plains Aquifer Region

Land use land cover change, including irrigation, impacts weather and climate. In this paper a precipitation event that occurred on the morning of 23 July 2018 during the Great Plains Irrigation Experiment (GRAINEX) is investigated. Six Weather and Research Forecasting (WRF) model-based experiments were conducted, which involved the increase or decrease of soil moisture by 5 % and up to 15 % over the irrigated croplands. These changes approximated soil moisture content in response to different levels of irrigation applications. An additional experiment, where irrigated land use was changed to grassland, was conducted to capture pre-irrigation land use and its impacts. It was found that regardless of strength of irrigation, precipitation decreased. In addition, the model did not produce precipitation over non-irrigated land use. When grassland replaced irrigated agriculture, increases in precipitation were estimated. With increased irrigation, latent heat flux increased compared to the control simulation and decreased when irrigation decreased. On the other hand, sensible heat flux was decreased compared to control when irrigation increased. The planetary boundary layer over irrigated land use was shallower than over non-irrigated land use while over grassland it was higher than irrigated but lower than non-irrigated land use. The changes in precipitation, the surface energy balance, and the planetary boundary layer served as a reminder of irrigation's complex effects on the atmosphere. Additional analysis of other precipitation events during GRAINEX would be helpful to better understand the effects of irrigation.

Evaluating long-term water storage trends in small catchments and aquifers from a joint inversion of 20 years of GRACE/GRACE-FO mission data

SUMMARY More than 20 yr of measurement data of the gravity missions GRACE (Gravity Recovery And Climate Experiment) and GRACE-FO (GRACE-Follow-On) allow detailed investigations of long-term trends in continental terrestrial water storage (TWS). However, the spatial resolution of conventional GRACE/GRACE-FO data products is limited to a few hundred kilometres which restrains from investigating hydrological trends at smaller spatial scales. In this study GRACE and GRACE-FO data have been used to calculate TWS trends with maximized spatial resolution. Conventionally, GRACE/GRACE-FO is presented as a series of either unconstrained gravity fields post-processed with spatial low pass filters or constrained inversions commonly known as Mascon products. This paper demonstrates that both approaches to suppress spatially correlated noise are mathematically equivalent. Moreover, we demonstrate that readily inverting all available sensor data from GRACE/GRACE-FO for a single TWS trend map, together with annual variations and a mean gravity field, provides additional spatial detail not accessible from the standard products. The variable trade-off between spatial and temporal resolution as a unique feature of satellite gravimetry allows for gravity products that are tailored towards specific geophysical applications. We show additional signal content in terms of long-term water storage trends for four dedicated examples (Lake Victoria, Northwest India, Bugachany Reservoir and High Plains Aquifer) for which external information from other remote sensing instruments corroborates the enhanced spatial resolution of the new mean-field trend product.

A New Highly Parameterized Linear Inversion of Water Table Change and Groundwater Depletion Rate Tested With the High Plains Aquifer, U.S.A.

AbstractUnderstanding groundwater resource dynamics is limited by the sparsity of observations of water levels, pumping rates, and hydraulic properties relative to their spatiotemporal heterogeneity. To address some of this complexity, we proposed a new highly parameterized linear inverse method to quantify water table change and groundwater depletion rate in unconfined aquifers that does not require initial or boundary conditions. The method requires linearization, and we tested the performance of six proposed water table functions with three coordinate systems with synthetic models, finding that water table functions by the dimensionless method achieve the lowest errors. Our inverted water table changes and depletion rates remained stable and accurate with head measurement error of 5%. However, inversions became less accurate when head observations contained large temporal gaps. Next, we applied the inversion for water table changes and depletion rates in the Texas High Plains Aquifer (HPA) and the HPA during 2000–2015. To address sparse water levels and uncertain hydraulic conductivity measurements, two modifications were made to improve data constraints for inversion: (a) calculating winter‐time water levels for wells with >1 head observation by linear interpolation and (b) using hydraulic conductivity geostatistical realizations. The inverted water table change and depletion rate expected mean values and uncertainties were reasonable compared to the known pumping records of the Texas HPA. With relatively minor data curation, the new inverse method can quantify spatiotemporally continuous water table change, depletion rates, and their uncertainty for heterogeneous aquifers with temporally sparse and noisy water level observations.

Temporal and Spatial Pattern Change in Evapotranspiration Over the High Plains: The Impact of and Guide on Extensive Groundwater‐Fed Irrigation

AbstractAquifer depletion due to extensive and intensive irrigation in the High Plains has threatened the environmental sustainability of the region. The change of crop evapotranspiration (ET), the major form of agriculture water consumption, presents a critical signature of hydrologic cycle change. This study evaluates the relative contributions of climate and groundwater‐fed irrigation to ET temporal and spatial pattern change over the High Plains Aquifer, one of the most severely depleted aquifers in the US. We developed a framework to extend the Budyko hypothesis to assess the impact of catchment storage change on long‐term ET. It is found that irrigation from groundwater pumping contributes more than half of the increase in ET (74.1 mm) from the period of 1940–1975 to 1976–2010, despite an increase of precipitation (35.0 mm) in the region. ET seasonal variance is decreased by the decline in precipitation variability (at −20.7 mm) and increase in irrigation (at +14.2 mm). As expected, irrigation decreases ET coefficient of variability (i.e., the ratio of standard deviation to mean). Spatially, we find that the human‐induced ET heterogeneity post‐1975 superimposes over the natural east‐to‐west gradient (in precipitation and ET) of this region. A correlation between the statistics (mean vs. coefficient of variation) on ET and crop yield provides promising signatures for understanding the coupled natural and human system of High Plains agriculture. Guides are discussed regarding how to handle the tradeoffs between agricultural development and natural resource sustainability under climate variability in the High Plains and other regions with similar conditions.

Machine learning algorithms improve MODIS GPP estimates in United States croplands

Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) network, can allow for the study of broader trends in crop productivity and sustainability.Methods: In this study, gross primary productivity (GPP) estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) for three LTAR cropland sites were integrated for use in a machine learning modeling effort. They are Kellogg Biological Station (KBS, 2 towers and 20 site-years), Upper Mississippi River Basin (UMRB - Rosemount, 1 tower and 12 site-years), and Platte River High Plains Aquifer (PRHPA, 3 towers and 52 site-years). All sites were planted to maize (Zea mays L.) and soybean (Glycine max L.). The MODIS GPP product was initially compared to in-situ measurements from Eddy Covariance (EC) instruments at each site and then to all sites combined. Next, machine learning algorithms were used to create refined GPP estimates using air temperature, precipitation, crop type (maize or soybean), agroecosystem, and the MODIS GPP product as inputs. The AutoML program in the h2o package tested a variety of individual and combined algorithms, including Gradient Boosting Machines (GBM), eXtreme Gradient Boosting Models (XGBoost), and Stacked Ensemble.Results and discussion: The coefficient of determination (r2) of the raw comparison (MODIS GPP to EC GPP) was 0.38, prior to machine learning model incorporation. The optimal model for simulating GPP across all sites was a Stacked Ensemble type with a validated r2 value of 0.87, RMSE of 2.62 units, and MAE of 1.59. The machine learning methodology was able to successfully simulate GPP across three agroecosystems and two crops.

Are we saving water? Simple methods for assessing the effectiveness of groundwater conservation measures

Substantial storage reductions by irrigation pumping in many of the world’s major aquifers jeopardize future food production. As a result, new conservation measures are being utilized to reduce pumping and extend aquifer lifespans. The key question is how effective are these practices in attaining true water conservation (i.e., water use reduction) for a given area? Relationships between pumping and precipitation help provide an answer, as precipitation explains most of the variation in annual irrigation water use for aquifers in semi-arid to sub-humid climates when surface water supplies are limited. Our objective is to utilize correlations between radar precipitation and irrigation groundwater use at a range of spatial scales to assess the effectiveness of conservation approaches in the High Plains aquifer in the central USA. Linear regressions between pumping and precipitation for a conservation area established in 2013 in northwest Kansas indicate that water use and water use per irrigated area were over 27 % less and 25 % less, respectively, during 2013–2021 compared to the same climatic conditions during 2005–2012. Similar regressions found over a 38 % reduction and 23 % reduction in irrigation water use and use per irrigated area, respectively, during 2018–2021 compared to the same conditions during 2005–2017 in a west-central Kansas county with conservation areas. A decrease in irrigated area accounted for most of the difference between these reductions. Higher R2 values after conservation area establishment imply that irrigation tracks precipitation better due to use of soil moisture sensors and other measures as part of increased irrigation efficiency and enhanced water management. The precipitation and water use relationships, which are statistically significant for a wide range of spatial scales, have great potential for assessing the effectiveness of conservation practices in areas with high-quality water use and precipitation data.

Changes in groundwater irrigation withdrawals due to climate change in Kansas

Warming temperatures increase the evapotranspiration demand of crops, leading to an increase in irrigation and exacerbating water scarcity. Previous research relies on models of irrigation water requirements to understand the potential impacts of climate change, but these models have significant uncertainty and ignore the risk-averse behavior of irrigators. Here we develop regression models to estimate how changes in vapor pressure deficit and precipitation affect groundwater withdrawals for corn, soybeans, and wheat using well-level data from the Kansas portion of the High Plains Aquifer. Withdrawals are expected to increase for all three crops, with the largest increase for soybeans. Even after accounting for the CO2 improvements in transpiration efficiency, we find that total withdrawals are expected to increase by 5.9% (7.6%) by mid-century under RCP 4.5 (8.5). The increase in withdrawals is expected to accelerate the decline in aquifer water levels and is therefore important to consider when projecting future aquifer conditions.

Quantifying seasonal, depression focused recharge in the context of public supply well vulnerability

AbstractDepression focused recharge (DFR) may be a hydrologically important process that impacts the vulnerability of public supply wells, specifically related to pathogenic contaminants. The nature of DFR in glacial moraine environments, such as those located in northern latitudes within North America and Europe, is less well established than in other regions such as the Prairie Pothole Region (Northern United States, Western Canada) and the High Plains Aquifer (Central United States). The objectives of this study were to quantify seasonal infiltration flux beneath a topographically‐closed depression within 50 m of a public supply well and to interpret the impact of this DFR process on well vulnerability. Field instruments including groundwater monitoring wells, pressure transducers, soil moisture sensors and temperature sensors were installed in vertical clusters to capture the dynamics of infiltration, drainage and recharge within the depression feature. Continuous weather data were recorded by a meteorological station at the site. Transient infiltration was quantified during two contrasting hydrological events. The first event (~2 days) was an intense rainfall (>50 mm) on a melting snowpack during the fall season when the soils were unfrozen. The second was a longer (35 day) period during the spring freshet when the surficial soils were initially frozen and subject to diurnal freezing and thawing and occasional precipitation events. The water table fluctuation method augmented by Darcy flux contributions, in addition to numerical modelling using the HYDRUS‐1D model, were used to quantify recharge rates beneath the depression. Numerical DFR estimates and analytical results differed by ±8%. Results indicate that recharge rates on the order of the annual regional average can occur beneath localized features in response to extreme events associated with snowmelt and intense rainfall. Such events may represent a microbial threat to groundwater quality if public supply wells are located nearby.

The Economic Cost of Groundwater Depletion in the High Plains Aquifer

Next article No AccessThe Economic Cost of Groundwater Depletion in the High Plains AquiferGabriela Perez-Quesada, Nathan Paul Hendricks, and David R StewardGabriela Perez-Quesada Search for more articles by this author , Nathan Paul Hendricks Search for more articles by this author , and David R Steward Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Journal of the Association of Environmental and Resource Economists Just Accepted Published for the Association of Environmental and Resource Economists Article DOIhttps://doi.org/10.1086/726156 HistoryAccepted May 22, 2023 © 2023 Association of Environmental and Resource Economists. All Rights reserved.PDF download Crossref reports no articles citing this article.

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

AbstractThe High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km3/year in 1985 to 18.2 km3/year in 2015, while irrigated croplands increased from 71,928 km2 in 1985 to 78,464 km2 in 2015 in the entire HPA. The hydroclimatic time‐series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time‐series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.

Temperature, Precipitation, and Agro-Hydro-Meteorological Indicator Based Scenarios for Decision Making in Ogallala Aquifer Region

The Ogallala Aquifer is one of the most productive agricultural regions and is referred to as the “breadbasket of the world”. It covers approximately 225,000 square miles beneath the Great Plains region spanning the states of Texas, New Mexico, Oklahoma, Kansas, Nebraska, South Dakota, Wyoming, and Colorado. The aquifer is a major water source for the region, with its use exceeding recharge. Previous studies have documented climate changes and their impacts in the region. However, this is the first study to document temperature and precipitation changes over the entire Ogallala region from 35 General Circulation Models participating in Phase 5 of the Climate Model Intercomparison Project (CMIP5). The main study objectives were (1) to provide estimates of present and future climate change scenarios for the High Plains Aquifer, (2) to translate the temperature and precipitation changes to agro-ecosystem indicator changes for Kansas using scenario funnels, and (3) to make recommendations for water resource and ecosystem managers to enable effective planning for the future availability of ecosystem services. The temperature change ranged from −4 °C to 8 °C, while the precipitation changes were between −50% to +50% over the region. This study improves the understanding of climate change on water resources and agro-ecosystems. This knowledge can be used to evaluate similar resources where the replenishment rate is slow.