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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #372089

Research Project: Precipitation and Irrigation Management to Optimize Profits from Crop Production

Location: Soil and Water Management Research

Title: BAITSSS model: An opportunity to integrate remote sensing and energy balance modeling for in-season crop water management

item DHUNGEL, RAMESH - Kansas State University
item AIKEN, ROBERT - Kansas State University
item LIN, XIAOMAO - Kansas State University
item Colaizzi, Paul
item Baumhardt, Roland - Louis
item O'BRIEN, DAN - Kansas State University
item Brauer, David

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 5/10/2020
Publication Date: 12/1/2021
Citation: Dhungel, R., Aiken, R., Lin, X., Colaizzi, P.D., Baumhardt, R.L., O'Brien, D., Brauer, D.K. 2021. BAITSSS model: An opportunity to integrate remote sensing and energy balance modeling for in-season crop water management. Proceedings of the 6th Decennial National Irrigation Symposium, ASABE, December 6-10, 2021, San Diego, California. Paper No. 20-065. p. 1-14.

Interpretive Summary: Irrigated crops use over half of the freshwater supplies in the United States and contribute over 40% of the food and fiber supply. Water used for irrigating crops can be conserved by careful management and knowledge of how much water a given crop actually requires. However, crop water requirements are affected by complex interactions of the weather, crop varieties, and farming practices. Therefore, complex models are required to calculate crop water requirements. Scientists from Kansas State University and USDA-ARS in Bushland, Texas, developed and tested a new computer model to calculate crop water requirements. They showed the model can accurately predict crop water use and demonstrated that it can be used by groundwater management districts to meet regulatory mandates that govern pumping from irrigation wells. The model can also aid farmers in scheduling irrigations, resulting in reduced water and energy use, increased crop yields, and increased farm profits.

Technical Abstract: Recent advances in hardware, firmware, and sensors support near-autonomous variable rate irrigation control systems. A novel energy balance application that calculates the soil water balance of the root zone for irrigated crops may be useful for real-time irrigation scheduling. The Backward-Averaged Iterative Two-Source Surface temperature and energy balance Solution (BAITSSS) model utilizes remotely sensed soil-canopy reflectance, available gridded soils data, and weather information to directly solve the two-layer energy balance for soil and canopy sources. BAITSSS can simulate a user-defined spatial and temporal resolution that depends on available input data. We tested model performance against field lysimeters and eddy covariance systems in an irrigated cropland regime, subject to local and regional advection, and at 30 m spatial and hourly temporal resolution. Model application to water management districts has been evaluated against multi-year annual pumping records for regulated water rights. In this paper, we review previous BAITSSS model testing and describe its future application to in-season irrigation scheduling at the field scale.