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Use of Close-Canopy Remote Sensing Tools Mountable on Ground-Based Platforms to Support Irrigation Water Management in Water-Limited Settings
Abstract
Precise irrigation water management is desired in settings with limited water to improve water use efficiency and optimize the yields. Producers require simple tools for irrigation scheduling. Therefore, this research extended the understanding of use of both stationary and mobile platforms mounted with thermal infrared sensors (thermal infrared thermometers (IRTs) and thermal camera) to quantify water use (i.e., crop evapotranspiration, ETc) and identify water stress (i.e., crop water stress index, CWSI) in in West Central Nebraska. First chapter (Chapter 1) focused on utilizing one-time-of-day Tr to estimate daily maize ETc while using two source energy balance (TSEB) under varied water stress in maize. Knowing daily ETc is important when estimating daily soil water depletion with a soil water balance (SWB) to schedule irrigation. The study proposed use of different scaling methods including time scaling one-time-of-day Tr and its computed instantaneous ETc to obtain daily ETc estimates. However, Tr time scaling method outperformed the rest of used methods in comparison to SWB ETc. Second chapter (Chapter 2) evaluated the sensitivity of different crop water stress (CWSI) approaches with respect to soil water dynamics (i.e., percentage soil water depletion) determined by neutron soil moisture measurements. The differences in sensitivity to soil water depletion were exhibited under various water stress levels, as well as differences in stress magnitudes among CWSI approaches under same treatments. Third chapter (Chapter 3) evaluated different Artificial Intelligence algorithms coupled with sensor data from weather and soil moisture measurements in predicting CWSI and ETc. Best models were then suggested to be incorporated into a closed-loop irrigation decision support system which could be employed to automate irrigation scheduling. Overall, conducted research provided more insights of how close-canopy remote sensing tools can be utilized when coupled with soil moisture sensing and Artificial Intelligence algorithms. To provide quality information which can aid in proper management of irrigation water to help in water savings, reduced pumping costs and conservation of limited water resources.
Subject Area
Water Resources Management
Recommended Citation
Katimbo, Abia, "Use of Close-Canopy Remote Sensing Tools Mountable on Ground-Based Platforms to Support Irrigation Water Management in Water-Limited Settings" (2022). ETD collection for University of Nebraska-Lincoln. AAI29068902.
https://digitalcommons.unl.edu/dissertations/AAI29068902