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Alfalfa is one of the most cultivated crops in the US, and is being used as livestock feed for the dairy, beef, and horse industries. About nine percent of that is grown in California, yet there is an increasing concern about the large amounts of irrigation water required to attain maximum yield. We introduce a conceptual framework to assist in the design and management of subsurface drip irrigation systems for alfalfa that maximize yield, while minimizing deep percolation water losses to groundwater. Our approach combines the strengths of numerical modeling using HYDRUS-2D with nonlinear optimization using AMALGAM and Pareto front analysis. The HYDRUS-2D model is used to simulate spatial and temporal distributions of soil moisture content, root water uptake, and deep drainage in response to drip-line installation depth and distance, emitter discharge, irrigation duration and frequency. This model is coupled with the AMALGAM optimization algorithm to explore tradeoffs between water application, irrigation system parameters, and crop transpiration (T a), to evaluate best management practices for subsurface drip irrigation systems in alfalfa. Through analysis of various examples, we provide a framework that seeks optimal design and management practices for different root distribution and soil textures. © 2012 .
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