Project Number: 2020-13660-008-00-D
Project Type: In-House Appropriated
Start Date: Jan 16, 2017
End Date: Jan 15, 2022
The long-term objectives of this project are to develop decision support tools and sensing and computing technologies to support improved crop water use efficiency for irrigated agriculture in arid lands. Objective 1: Develop and integrate models, tools, and strategies to optimize water and nutrient use efficiencies under sufficient, reduced, and variable-rate irrigation strategies in arid environments. Subobjective 1A: Quantify cotton physiological development, fiber yield, fiber quality, and water use responses to variable irrigation rate and timing. Subobjective 1B: Develop end-user irrigation scheduling models for cotton and other crops. Subobjective 1C: Develop nitrogen fertilizer scheduling strategies and tools for cotton. Objective 2: Use remote and proximal sensing at regional and field scales for crop and water management and use proximal sensing for high throughput phenotyping for heat and drought tolerant cultivars. Subobjective 2A: Develop and evaluate airborne and satellite-based remote sensing methods to estimate crop evapotranspiration, ETc, at irrigation district scale. Subobjective 2B: Develop and evaluate airborne and drone-based remote sensing methods to estimate crop evapotranspiration, ETc, at field scale. Subobjective 2C: Develop and evaluate ground-based proximal sensing methods that identify crop heat and drought stress at field scale. Objective 3: Develop and evaluate crop simulation models as tools to synthesize “big” data from agricultural field studies and analyze alternative strategies for crop and water management. Subobjective 3A: Evaluate and improve Cotton2K and DSSAT-CSM models for simulation of cotton physiology, water use, and nutrient use in response to water and nutrient deficit. Subobjective 3B: Develop crop simulation modeling methodologies to analyze potential water savings and production impacts of variable-rate and deficit irrigation practices. Subobjective 3C: Develop methodologies to guide crop simulation and irrigation scheduling models using “big data” from remote and proximal sensing and crop and soil mapping equipment. Objective 4: Develop concepts, technologies, and software tools for the hydraulic analysis of surface irrigation systems. Subobjective 4A: Develop software for the hydraulic analysis of irrigation systems. Subobjective 4B: Model irrigation-induced soil erosion. Subobjective 4C: Develop field technologies for improved surface irrigation management.
Objective 1 Goal 1A: Conduct cotton field experiments using a new VRI system on a lateral move overhead sprinkler to deliver precise irrigation treatments to cotton. Goal 1B: Develop improved irrigation scheduling models and software that account for spatial water application and crop water use in irrigation management and provide guayule growers with new irrigation scheduling tools. Goal 1C: Develop improved N management scheduling models and software that will help optimize the N fertilizer application rate guidelines for cotton under lateral move overhead sprinkler and subsurface drip irrigation. Objective 2 Goal 2A: Reduce ETc estimation uncertainty and bias at irrigation district scales by integrating sensing technologies with weather-based approaches. Goal 2B: Develop a field-scale decision support system for mapping ETc using drone platforms. Goal 2C: Demonstrate that field-based high-throughput plant phenotyping with proximal sensors could be an effective approach for crop breeding. Objective 3 Goal 3A: Conduct evaluations of the Cotton2K and DSSAT-CSM cotton simulation models and identify options for model improvement. Goal 3B: Conduct simulation analyses to assess effects of variable-rate irrigation management practices on crop production and water use. Goal 3C: Develop mathematical approaches for integrating remote and proximal sensing data with irrigation scheduling models and crop simulation models. Objective 4 Goal 4A: Enhance the functionality of the WinSRFR software package by improving the design procedures to account for flow-depth dependent infiltration, developing procedures for furrow systems with return flow, and developing procedures for predicting the transverse distribution of infiltrated water in a furrow cross section based on soil textural properties. Goal 4B: Development and testing of a process-based model of sediment transport coupled to surface irrigation flow. Goal 4C: Develop a process for evaluating the field-level seasonal performance of an irrigation system and developing field technologies for acquiring irrigation evaluation data reliably and inexpensively.