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University of Arizona (2021)

Analyzing Full and Deficit Irrigation Systems for Industrial Crops Using the WINDS Model and Remote Sensing Technology

Maqsood, Hadiqa

Titre : Analyzing Full and Deficit Irrigation Systems for Industrial Crops Using the WINDS Model and Remote Sensing Technology

Auteur : Maqsood, Hadiqa

Université de soutenance : University of Arizona

Grade : Doctor of Philosophy (PhD) 2021

Résumépartiel
Currently, the agriculture sector accounts for about 70% of the global water withdrawals and with increasing urbanization and climate change, there will be a much higher strain on the water resources in the future. If the situation remains unaltered, reports from Food and Agriculture Organization (FAO) predict that by 2050, there could be a 50% increase in food demand and a 40% decrease in the water supply. Adopting water conservation alternatives will help sustain agriculture and the population. To do so, accurate computational tools, such as soil water balance and crop growth models, are needed to provide guidance in irrigation management decisions. The WINDS (Water-use, Irrigation, Nitrogen, Drainage, and Salinity) model is a soil water balance simulation model that divides the soil profile into layers and calculates crop evapotranspiration (ETc) with the FAO56 dual crop coefficient method. In this research, the assumption was that the WINDS model can accurately simulate the ETc and soil moisture contents in soil layers. A foundational purpose of the research was to provide a comprehensive document describing the theory and algorithms used in WINDS. Data from a carefully monitored irrigation experiment conducted in 2007 in Maricopa, Arizona, were then used to calibrate and validate the WINDS model for cotton. Further, the project used the WINDS model to evaluate a guar deficit irrigation experiment conducted in 2018 and 2020 in Clovis, NM. The WINDS model is a daily time-step model that uses tipping bucket algorithms during infiltration events and the Richards’ equation between infiltration events. If the hypothesis is true, then it has a unique ability to accurately model soil moisture content in layers. Input data includes weather data used in FAO-56 dual crop coefficient calculations, soil characteristics, and crop evapotranspiration parameters. In this study, it was validated by comparing simulations with neutron probe water content readings in soil layers collected during the growing season. The WINDS model can simulate surface and subsurface irrigation methods on multiple soil types. One of the features of the model is the ability to assess input data and fill gaps for an infrequent dataset. This research effort was part of the Sustainable Bioeconomy for Arid Regions (SBAR) project. The SBAR project aims to evaluate and improve bioeconomic system for two industrial crops using models, field experiments, advanced computational tools, and outreach. From the project, work on the guar crop for one of the sites has been done.

Mots clés : calibration evapotranspiration modeling soil moisture content

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Page publiée le 19 janvier 2022