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Modeling Field-level Irrigation Demands with Changing Weather and Crop Choices

Posted on:2016-09-09Degree:M.SType:Thesis
University:University of KansasCandidate:Mardan Doost, BabakFull Text:PDF
GTID:2473390017478299Subject:Engineering
Abstract/Summary:
The Kansas economy and way of life depend on groundwater reservoirs, specifically the High Plains Aquifer. However, long-term economic stability of the state will be jeopardized by unsustainable water withdraws. Modeling water demand is vital to developing sustainable water use policies that will be robust to water scarcity and climatic fluctuations. Additionally, developing a reliable water demand prediction model is a precursor for an integrated sustainable water resource management plan. The presented water budget model is capable of estimate daily water demand over space and time under predicted climate and land-use change. The model-predicted irrigation demand was developed based on crop-specific evapotranspiration, weather data, and with 2007 State-Wide Land Use and Land Cover data. In addition, two coupled sub-models have been developed: 1) a global climate change sub-model, and 2) a feasible pumping rate sub-model, which considers the spatial dynamics of the saturated thickness of the High Plains Aquifer.;The water budget model was calibrated to 1217 fields with reported water use extracted from the Kansas Water Right System (WRIS). In the 4544 water groups, predicted water use matched historic reported water use with a slope of 0.79 and r2 value of 0.55.;The decadal-averaged monthly output of 21 global climate change models (Intergovernmental Panel on Climate Change AB1 scenario) was examined for south west Kansas. It was shown that the growthing season decreases by 20, 25, 30 days for sorghum, soybean, and winter wheat, respectively. Also, it was shown that evapotranspiration from soybean and sorghum fields will increase by .5 and 1.5 mm per day in peak time, whereas it will decrease by 1.5 mm less water for winter wheat per day in peak time between 2090 and 2100.
Keywords/Search Tags:Water, Demand, Model
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