Republican River Basin Research Articles

Monitoring Changes in Groundwater Resources Due to Increased Surface Water Delivery Efficiencies in the Lower Republican River Basin

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.

Remote sensing of field-scale irrigation withdrawals in the central Ogallala aquifer region

For agricultural areas facing water scarcity, sustainable water use policy relies on irrigation information that is timely and at a high resolution, but existing publicly available water use data are often insufficient for monitoring compliance or understanding the influence of policy on individual farmer decisions. This study attempts to fill this data gap by using remote sensing to map annual irrigation quantity at the field-scale within the central Ogallala aquifer region of the United States. We compiled in situ annual irrigation volume data at the field scale in the Republican River Basin of Colorado for 2015–2018 and at the Public Land Survey System (PLSS) section scale in western Kansas for 2000–2016, which served as reference data in random forest models that relied on Landsat-based actual evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop) along with maps of irrigated area, Landsat spectral indices, climate, soils, and derived hydrologic variables. The models explained 87% of the variability in irrigation volume in Colorado and 75% in Kansas, but accuracy declined when transferring the models in spatial cross-validation (Colorado R2 =0.81; Kansas R2 =0.51) and temporal cross-validation (Colorado R2 =0.82; Kansas R2 =0.68). Predicted annual totals of irrigation volume in western Kansas had a mean absolute error of 11.9%, which was slightly higher than the average annual change of 11%. Use of predicted irrigation maps also lead to an underestimated effect size for a water use restriction policy in Kansas. These results indicate that field- and section-scale irrigation can be mapped with reasonable accuracy within a region and time period that has adequate sample data, but that methods may need to be improved for applying the models more broadly in areas that lack extensive in situ irrigation data to support further research on water use and aid in structuring policy.

Impacts ofBlock‐RateEnergy Pricing on Groundwater Demand in Irrigated Agriculture

In many regions of the world, energy costs associated with extraction represent the only explicit price for groundwater use. Therefore, energy pricing policies can significantly influence the use of scarce groundwater resources. This article leverages unique well‐level data on groundwater use, electricity prices, and pumping efficiency from the Republican River Basin of Colorado to estimate producer responses to changes in marginal energy prices. Empirical parameter estimates are used to simulate a change in energy pricing policy from existing decreasing block rate structures to a revenue‐neutral uniform marginal price. The simulation results reveal that, on average, uniform energy pricing leads to an 11% decrease in groundwater use than would occur under a decreasing block rate pricing regime. However, a transition to uniform energy pricing diminishes short‐run producer welfare. More broadly, the results illustrate how energy pricing has important implications for groundwater management and informs a more comprehensive understanding of how priced inputs influence the use of unpriced natural resources.

An Integrated Assessment Model for Valuing Water Quality Changes in the U.S.

The US Environmental Protection Agency (EPA) often requires expertise from environmental assessors, hydrologists, economists, and others to analyze the benefits of regional and national policy decisions related to changes in water quality. This led EPA to develop two models to form an Integrated Assessment Model (IAM): HAWQS is a web-based water quantity and quality modeling systems and BenSPLASH is a modeling platform for quantifying the economic benefits of changes in water quality. This paper discusses the development of the component models and applies HAWQS and BenSPLASH to a case study in the Republican River Basin.

Simulating the Effects of Reservoir Management Strategies on Fluvial Erosion

Although sediment is one of the most common causes of stream impairment in the United States, soil erosion is not integrated into many surface water management models. In this work, a module is developed to estimate fluvial erosion within an existing surface water optimization model. This model is applied to the Lower Republican River Basin in Kansas to demonstrate the effects of climate scenarios and water management strategies on water shortages and sediment loads. Results indicate water shortage varies most under different water management strategies, whereas fluvial erosion varies most under different climate scenarios. Fluvial erosion results are highly sensitive to streambank parameters, demonstrating the importance of measuring these parameters and quantifying their uncertainty. This novel modeling approach provides a computationally efficient method of estimating both water shortages and sediment load within one framework and demonstrates the benefit of considering water shortages and fluvial erosion when making water management decisions.

Streamflow Depletion Investigations in the Republican River Basin: Colorado, Nebraska, and Kansas

Water is a critical resource in the Great Plains. This study examines the changes in long-term mean annual streamflow in the Republican River basin. In the past decades this basin, shared by three states, Colorado, Nebraska, and Kansas, displayed decreased streamflow volumes as the river enters Kansas across the Nebraska-Kansas border compared to values preceding the 1950s. A recent lawsuit filed by Kansas challenges water appropriations in Nebraska. More than half of the source area for this water, however, lies outside of Nebraska. Today a higher percentage of the annual flow is generated within Nebraska (i.e., 75% of the observed mean annual streamflow at the NE-KS border) than before the 1950s (i.e., 66% of the observed mean annual streamflow) indicating annual streamflow has decreased more dramatically outside of Nebraska than within the state in the past fifty years.

Effect of Hydrogeologic and Climatic Variability on Performance of a Groundwater Market

AbstractIncentive‐based policies, such as the cap‐and‐trade system, have been shown to be useful in the context of groundwater management. This study compares the performance of a groundwater market with water quotas when assumptions of perfect information are violated due to climate change and hydrogeologic heterogeneity and explores how changes in future climate affect market performance. A subbasin of the Republican River Basin, overlying the Ogallala aquifer in the High Plains of the United States, is used as a case study. Building on a previously developed model, a multiagent system model simulating a groundwater market is developed where self‐interested agents can trade water use permits to maximize individual benefits subject to irrigation and land constraints. This economic model is coupled with a calibrated physically based groundwater model for the study region that allows for an evaluation of streamflow depletion impacts, which has been the focus of management efforts in the basin. Results show that trading of permits between farmers results in increased economic benefits and, in some cases, reduced environmental violations. However, the benefits of a groundwater market are distributed unequally resulting in “winners” and “losers” across the system. Future changes in climate are shown to significantly influence farmers willingness to pay for groundwater and thus increase the variation in groundwater price and pumping. These findings emphasize the importance of addressing hydroclimatologic variability and change in the design of groundwater markets.

Private Actions and Preferences for Coordinated Groundwater Conservation in Colorado's Republican River Basin

AbstractConservation of groundwater resources is critical for maintaining the future productivity of irrigated land in the Ogallala Aquifer Region and beyond. This research explores motivations and behavior related to groundwater conservation among agricultural producers in the Colorado portion of the Republican River Basin, which is part of the Ogallala Aquifer. The empirical modeling uses data from a recently conducted survey to analyze how a common set of producer, farm, and resource characteristics influence groundwater values, concern for future groundwater availability, private conservation actions, and support for coordinated conservation efforts. We find two factors, producer age and land owner status, are consistently correlated with the key conservation‐related outcomes we evaluate. More generally, the results suggest considerable similarities in the characteristics that drive private conservation actions and support for coordinated conservation. This knowledge could be used to better target and incentivize future groundwater conservation efforts in the region. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

Climate change implications for irrigation and groundwater in the Republican River Basin, USA

This study investigates the influence of climate change on groundwater availability, and thereby, irrigation across political boundaries within the US High Plains aquifer. A regression model is developed to predict changes in irrigation according to predicted changes in precipitation and temperature from a downscaled dataset of 32 general circulation models (GCMs). Precipitation recharge changes are calculated with precipitation-recharge curves developed for prognostic representations of precipitation across the Nebraska-Colorado-Kansas area and within the Republican River Basin focal landscape. Irrigation-recharge changes are scaled with changes in irrigation. The groundwater responses to climate forcings are then simulated under new pumping and recharge rates using a MODFLOW groundwater flow model. Results show that groundwater pumping and recharge both will increase and that the effects of groundwater pumping will overshadow those from natural fluctuations. Groundwater levels will decline more in areas with irrigation-driven decreasing trends in the baseline. The methodologies and predictions of this study can inform long-term water planning and the design of management strategies that help avoid and resolve water-related conflicts, enabling irrigation sustainability.

Identifying the Driving Factors of Water Quality in a Sub-Watershed of the Republican River Basin, Kansas USA.

Studies have shown that the agricultural expansion and land use changes in the Midwest of the U.S. are major drivers for increased nonpoint source pollution throughout the regional river systems. In this study, we empirically examined the relationship of planted area and production of three dominant crops with nitrate flux in the Republican River, Kansas, a sub-watershed of Mississippi River Basin. Our results show that land use in the region could not explain the observed changes in nitrate flux in the river. Instead, after including explanatory variables such as precipitation, growing degree days, and well water irrigation in the regression model we found that irrigation and spring precipitation could explain >85% of the variability in nitrate flux from 2000 to 2014. This suggests that changes in crop acreage and production alone cannot explain variability in nitrate flux. Future agricultural policy for the region should focus on controlling both the timing and amount of fertilizer applied to the field to reduce the potential leaching of excess fertilizer through spring time runoff and/or over-irrigation into nearby river systems.

The Heterogeneous Impacts of Groundwater Management Policies in the Republican River Basin of Colorado

AbstractGroundwater is a critical input to agricultural production across the globe. Current groundwater pumping rates frequently exceed recharge, often by a substantial amount, leading to groundwater depletion and potential declines in agricultural profits over time. As a result, many regions reliant on irrigated agriculture have proposed policies to manage groundwater use. Even when gains from aquifer management exist, there is little information about how policies affect individual producers sharing the resource. In this paper, we investigate the variability of groundwater management policy impacts across heterogeneous agricultural producers. To measure these impacts, we develop a hydroeconomic model that captures the important role of well capacity, productivity of water, and weather uncertainty. We use the model to simulate the impacts of groundwater management policies on producers in the High Plains aquifer of eastern Colorado and compare outcomes to a no‐policy baseline. The management policies considered include a pumping fee, a quantity restriction, and an irrigated acreage fee. We find that well capacity and soil type affect policy impacts but in ways that can qualitatively differ across policy type. Model results have important implications for the distributional impacts and political acceptability of groundwater management policies.

On the role of individuals in models of coupled human and natural systems: Lessons from a case study in the Republican River Basin

In models of coupled human and natural systems (CHANS), the role of individuals and human behavior is often overlooked as data are scarce and assumptions hard to verify. To assess this role, we couple an agent-based model simulating farmers' behavior and a groundwater model and apply the models to the case of groundwater-fed irrigation in a river basin in the High Plains Aquifer region. Results show the crucial role of human behavior in driving the interactions between these coupled systems. Conversely, individuals are impacted by the systems’ dynamics in different ways depending on physical, economic and social characteristics. The findings provide implications for local policy making and education and demonstrate that assumptions on human behavior could be treated as an additional source of uncertainty. This work suggests that modeling individuals and human behavior can be an important step to simulate and understand the dynamics of CHANS in a holistic way.

Incorporating Surface Water Operations in an Integrated Hydrologic Model: Model Development and Application to the Lower Republican River Basin, United States

AbstractFew river systems remain unaltered by engineered water management structures. Yet research investigating the interdependence between natural and engineered components of a hydrologic system...

Defining Sustainability in Nebraska’s Republican River Basin

This symposium presents an opportunity to discuss agricultural sustainability. But we have little practical understanding of what agricultural sustainability really means. This is a common problem with sustainability efforts. This Article provides one example of this problem. But it also provides a story of how an effort at defining sustainability served as a catalyst for a group of stakeholders that wanted to make improvements in water management. Understood in this way, sustainability discussions can serve to overcome historic barriers to progress that so often arise with resource management problems, especially in the agricultural sector.

Effects of nonlinear model response on allocation of streamflow depletion: exemplified by the case of Beaver Creek, USA

Anomalies found when apportioning responsibility for streamflow depletion are examined. The anomalies arise when responsibility is assigned to the two states that contribute to depletion of Beaver Creek in the Republican River Basin in the United States. The apportioning procedure for this basin presumes that the sum of streamflow depletions, computed by comparing simulation model runs with and without groundwater pumping from individual states, approximates the streamflow depletion when both states are pumping. In the case study presented here, this presumed superposition fails dramatically. The stream drying and aquifer-storage depletion, as represented in the simulation model used for allocation, are examined in detail to understand the hydrologic and numerical basis for the severe nonlinear response. Users of apportioning procedures that rely on superposition should be aware of the presence and likely magnitude of nonlinear responses in modeling tools.

Model reduction for combined surface water/groundwater management formulations

A methodology for clustering stresses on a groundwater system based on similarity of hydrologic response produced by the stress is presented. The method is relevant to the computationally efficient calculation of response matrixes for use in groundwater management and other applications. The procedure is presented for the case in which the impact of pumping withdrawals on streamflow is of interest. The method uses cluster analysis on multiple, transient responses and a simplified response matrix for the modeled system. It is demonstrated on a field scale hypothetical management problem applied to a portion of the Republican River basin in the High Plains Aquifer of the United States with a multi-decadal planning horizon that maximizes well withdrawal while requiring that minimum streamflows be maintained. For this case, the clustering approach both reduces the computational requirement and helps to produce response coefficients with meaningful precision. The effectiveness of the model reduction is tested by comparing the optimal solutions produced by a full scale formulation and two reduced size formulations.

Optimizing Water Management for Irrigation Under Climate Uncertainty: Evaluating Operational and Structural Alternatives in the Lower Republican River Basin, Kansas, USA

Structural and operational management methods are used to meet water demands in watersheds around the world. Most river systems are affected by reservoirs, dams, or other engineering structures, and decisions regarding their construction and operation are made in advance of knowing what water demands will be. Numerical models are used to predict future water needs and evaluate the effectiveness of water management strategies. It is important to consider a variety of management methods and future environmental conditions to ensure future demands can be met. In this work, a coupled surface water operations and hydrologic model of the Lower Republican River Basin in portions of Nebraska and Kansas, USA is used to evaluate the ability of several water management strategies, including structural and operational, to meet future demands of a water-stressed agricultural basin under a variety of future climate scenarios. Simulations indicate recent administrative and operational changes to the distribution of water between Nebraska and Kansas have significantly decreased water shortages for irrigation districts in Kansas and will continue to do so. Simulations also indicate that structural alternative of reservoir expansion is most effective at minimizing shortages to demands under a repeat of historical climate conditions. However, an operational alternative of increasing water supplies for Kansas' exclusive use, such as those historically purchased under the Warren Act (US Code 43 Section 523–524), is most effective at minimizing shortages to demands under a hotter and drier climate, demonstrating how optimal water management strategies can vary significantly depending upon climate scenario.

Global sensitivity analysis for large-scale socio-hydrological models using Hadoop

A multi-agent system (MAS) model is coupled with a physically-based groundwater model to understand the declining water table in the heavily irrigated Republican River basin. Each agent in the MAS model is associated with five behavioral parameters, and we estimate their influences on the coupled models using Global Sensitivity Analysis (GSA). This paper utilizes Hadoop-based Cloud Computing techniques and Polynomial Chaos Expansion (PCE) based variance decomposition approach for the improvement of GSA with large-scale socio-hydrological models. With the techniques, running 1000 scenarios of the coupled models can be completed within two hours with Hadoop clusters, a substantial improvement over the 42 days required to run these scenarios sequentially on a desktop machine. Based on the model results, GSA is conducted with the surrogate model derived from using PCE to measure the impacts of the spatio-temporal variations of the behavioral parameters on crop profits and the water table, identifying influential parameters.

Data-driven methods to improve baseflow prediction of a regional groundwater model

Physically‐based models of groundwater flow are powerful tools for water resources assessment under varying hydrologic, climate and human development conditions. One of the most important topics of investigation is how these conditions will affect the discharge of groundwater to rivers and streams (i.e. baseflow). Groundwater flow models are based upon discretized solution of mass balance equations, and contain important hydrogeological parameters that vary in space and cannot be measured. Common practice is to use least squares regression to estimate parameters and to infer prediction and associated uncertainty. Nevertheless, the unavoidable uncertainty associated with physically‐based groundwater models often results in both aleatoric and epistemic model calibration errors, thus violating a key assumption for regression-based parameter estimation and uncertainty quantification. We present a complementary data-driven modeling and uncertainty quantification (DDM-UQ) framework to improve predictive accuracy of physically‐based groundwater models and to provide more robust prediction intervals. First, we develop data-driven models (DDMs) based on statistical learning techniques to correct the bias of the calibrated groundwater model. Second, we characterize the aleatoric component of groundwater model residual using both parametric and non-parametric distribution estimation methods. We test the complementary data-driven framework on a real-world case study of the Republican River Basin, where a regional groundwater flow model was developed to assess the impact of groundwater pumping for irrigation. Compared to using only the flow model, DDM-UQ provides more accurate monthly baseflow predictions. In addition, DDM-UQ yields prediction intervals with coverage probability consistent with validation data. The DDM-UQ framework is computationally efficient and is expected to be applicable to many geoscience models for which model structural error is not negligible.

Strategic Planning for Drought Mitigation under Climate Change

AbstractDroughts continue to be a major natural hazard, and mounting evidence of global warming confronts society with a pressing question: Will climate change aggravate the risk of drought at the local scale? Are current infrastructures sufficient to mitigate the damage of future drought, or is in-advance infrastructure expansion needed for future drought preparedness? To address these questions, this study presents a decision-support framework based on a coupled simulation and stochastic optimization model through a case study area, the Frenchman Creek basin (FCB), part of the Republican River basin. A complex watershed simulation model is established and converted into a statistical surrogate model for computational feasibility. Decisions for drought preparedness include traditional short-term tactical measures (e.g., facility operation) and long-term or in-advance strategic measures, which require capital investment. A scenario-based, three-stage stochastic optimization model assesses the roles of str...