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Long-term analysis of groundwater depletion in the High Plains Aquifer: historical, predictive, and solutions

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dc.contributor.authorNozari, Soheil, author
dc.contributor.authorBailey, Ryan, advisor
dc.contributor.authorNiemann, Jeffrey, committee member
dc.contributor.authorRonayne, Michael, committee member
dc.contributor.authorSuter, Jordan, committee member
dc.date.accessioned2024-05-27T10:32:44Z
dc.date.available2025-05-20
dc.date.issued2024
dc.description.abstractSemi-arid agricultural regions worldwide are heavily dependent on groundwater storage in a handful of large and over-exploited aquifers, such as the High Plains Aquifer (HPA) in the U.S. High Plains Region. The HPA, one of the world's largest freshwater aquifers, serves as the primary source of irrigation water in the High Plains Region. The socioeconomic development in the High Plains Region has come at the expense of significant groundwater depletion in the HPA. The ongoing depletion of the HPA poses risks to livelihoods of rural communities, local ecosystems, and national food security. Addressing this issue necessitates the formulation of groundwater management policies that aim to reduce groundwater extraction, while minimizing associated economic costs over a multi-generational timeframe, all in the context of climate change. To inform the formulation of effective policies, it is crucial to develop a suite of decision support tools that empower local managers and planners to assess the outcomes of various groundwater management policies amidst climate change. The primary goal of this dissertation is to enhance the capacity to project the future of groundwater systems in semi-arid agricultural areas, particularly within the High Plains Region, as a coupled human-natural system, under various groundwater management schemes in the face of climate change. To achieve this goal, a number of tools were developed that incorporate a spectrum of modeling approaches, from the increasingly popular data-driven models to the state-of-the-art hydro-economic models. First, a data-driven modeling framework was developed and tested that is fast to employ and yet provides reliable long-term groundwater level (GWL) forecasts as a function of climatic and anthropogenic factors. The modeling framework utilizes the random forests (RF) technique in combination with ordinary kriging and was tested for the HPA in Finney County, southwest Kansas. The introduction of groundwater withdrawal potential as a new surrogate for pumping intensity empowers the RF model to capture decline in groundwater depletion rate as the system progresses towards aquifer depletion and/or as a result of well retirement policies. The RF model was applied over the period from 2017 to 2099 using 20 downscaled global climate models (GCMs) for two representative concentration pathways (RCPs), RCP4.5 and RCP8.5. The findings indicate that, under status quo management and average climate conditions, the aquifer will no longer be able to sustain irrigated agriculture in most of the county by 2060. Additionally, the difference in climate scenarios will likely shift the aquifer's depletion time frame by up to 15 years in most of the study area. The long-term combined impact of well retirement plans and climate conditions on groundwater depletion trends imply well retirement policies do not lead to sustained groundwater savings. In the next step, an agent-based hydro-economic model (ABM-MODFLOW) was developed for a portion of the HPA in eastern Colorado and northwest Kansas, with the aim of addressing the current limitations of hydro-economic models. Through interdisciplinary collaboration, each component of the ABM-MODFLOW was particularly designed to meet specific research objectives. Planting and irrigation decisions were simulated in the ABM-MODFLOW using a detailed representation of real-world farmers. Additionally, well capacity was incorporated as a constraint on irrigation duration. A subsequent thorough validation of the ABM-MODFLOW was conducted to establish its credibility. The validation results indicate satisfactory performance in reproducing historical data and trends. They also reveal the ABM-MODFLOW's superiority over the standalone groundwater model in simulating the groundwater system. The historical simulation outcomes also underscore the impact of soil type on agents' profitability, especially for those with limited irrigation capacities. Overall, the highest profits are earned by agents with high irrigation capacities and fine soils, while the lowest are achieved by those with low irrigation capacities and coarse soils. Lastly, the ABM-MODFLOW was employed to project the coevolution of human activities, crops, and the groundwater system amidst climate change, both with and without policy interventions. The ABM-MODFLOW simulations involved 32 climate scenarios from 16 downscaled GCMs for two RCPs, RCP4.5 and RCP8.5. Additionally, three groundwater management policy instruments were explored: irrigated land retirement, irrigation well retirement, and authorized pump rate reduction. The simulation outcomes reveal that the groundwater depletion rate decreases over time, primarily due to rising summer temperatures from climate change that limit corn production, a water-intensive crop, in the region. Moreover, these rising temperatures hamper the economic benefits of policies, since the early conserved groundwater is predominantly used for winter wheat irrigation in the later years, a crop with substantially lower irrigation value than corn.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierNozari_colostate_0053A_18179.pdf
dc.identifier.urihttps://hdl.handle.net/10217/238455
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2020-
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.accessEmbargo expires: 05/20/2025.
dc.subjectgroundwater management
dc.subjecthydro-economic models
dc.subjectmachine learning
dc.subjectHigh Plains Aquifer
dc.subjectgroundwater depletion
dc.subjectirrigated agriculture
dc.titleLong-term analysis of groundwater depletion in the High Plains Aquifer: historical, predictive, and solutions
dc.typeText
dcterms.embargo.expires2025-05-20
dcterms.embargo.terms2025-05-20
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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