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Abstract (from ScienceDirect): Study region Middle Section of the Rio Grande Basin (MRG), U.S. Study focus Long-term tradeoffs of technologically possible land and water management interventions were analyzed to adapt irrigated agriculture to growing water scarcity in a desert environment under a projected warm-dry future. Nineteen different intervention scenarios were investigated to evaluate potential watershed-scale agricultural water savings and associated water budget impacts in the MRG. The interventions are based on (i) management innovations of growers in implementing deficit irrigation and changing cropping patterns using existing crops, (ii) changing cropping patterns by introducing new alternative drought-...
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Abstract (from Water): This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable Artificial Intelligence (XAI) models for data imputations and numerical or categorical hydroclimatic predictions from nonlinearly combined multidimensional predictors. The AI models considered in this paper involve Extreme Gradient Boosting, Light Gradient Boosting, Categorical Boosting, Extremely Randomized Trees, and Random Forest. These AI models can transform into XAI models when they are coupled with the explanatory methods such as the Shapley additive explanations and local interpretable model-agnostic explanations. The review highlights that the IAI models are capable of unveiling the rationale...
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We present a comprehensive analysis of water availability under plausible future climate conditions in a heavily irrigated agricultural watershed located in the middle section of the Rio Grande Basin in the United States Desert Southwest. Future managed streamflow scenarios (through year 2099) were selected from among 97 scenarios developed based on downscaled, bias-corrected global climate model outputs to evaluate future inflows to the principal surface water storage reservoirs, possible future reservoir releases, and groundwater pumping to sustain irrigated agriculture. The streamflow projections describe a wide range of dry and wet conditions compared to the average historical flows in the river, indicating...
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We review over twenty years of publications on Soil and Water Assessment Tool (SWAT) applications in arid/semi-arid irrigated agricultural watersheds. Our review reveals strict dominance of the model's use for better understanding water quantity aspects of water management. While this is to be expected given the reality of water scarcity and associated challenges for agricultural production systems in arid/semi-arid regions, the capabilities of SWAT to model water quality have been underutilized. The main modeling challenges are lack of observational data, poor data quality, concerns about simulation accuracy, and technical limitations of the model despite numerous advancements in the last two decades. To deal with...
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