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ARS Home » Pacific West Area » Maricopa, Arizona » U.S. Arid Land Agricultural Research Center » Water Management and Conservation Research » Research » Publications at this Location » Publication #408221

Research Project: Improving Water Management for Arid Irrigated Agroecosystems

Location: Water Management and Conservation Research

Title: Winds model simulation of guayule irrigation

Author
item KATTERMAN, MATTHEW - University Of Arizona
item WALLER, PETER - University Of Arizona
item ELDIN ELSHIKHA, DIAA - University Of Arizona
item Wall, Gerard - Gary
item Hunsaker, Douglas - Doug
item LOEFFLER, REID - University Of Arizona
item OGDEN, KIM - University Of Arizona

Submitted to: Water
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/5/2023
Publication Date: 10/7/2023
Citation: Katterman, M., Waller, P., Eldin Elshikha, D., Wall, G.W., Hunsaker, D.J., Loeffler, R.S., Ogden, K. 2023. Winds model simulation of guayule irrigation . Water. 15. Article 3500. https://doi.org/10.3390/w15193500.
DOI: https://doi.org/10.3390/w15193500

Interpretive Summary: Current drought conditions in the semi-arid desert Southwest U.S. affect the allocation of available water supplies used in irrigated agricultural. Expected reallocation of water supplies to non-agriculture users in the region would reduce irrigation water supply and could adversely affect crop production. These constraints will require more efficient use of the available irrigation water in the agricultural sector. Reliable modeling tools can help improve irrigation management for achieving crop production and efficient water use. The WINDS (Water-use, Irrigation, Nitrogen, Drainage, and Salinity) simulation model was recently introduced to provide irrigation support for major crops grown in the U.S. Southwest. In this research, ARS scientists at Maricopa, Arizona, evaluated the WINDS model for an important desert shrub, guayule, which is the primary source of natural rubber in the U.S. Results showed the model accurately predicted soil moisture in the guayule root depth, which was measured in a two-year guayule field experiment. In addition, the model accounted for actual crop water use, which is needed for optimizing irrigation scheduling. The findings imply that the WINDS model could provide valuable irrigation decision support for irrigation management of guayule with a limited water supply. The research will be of interest to the US Rubber Industry, including Tire Manufacturers, irrigation consultants, water district water managers, and other research investigators of guayule.

Technical Abstract: The WINDS (Water-Use, Irrigation, Nitrogen, Drainage, and Salinity) model currently evaluates irrigation experiments and will potentially provide decision support for irrigated-crop management in the U.S. Southwest. The model uses a daily time-step soil water balance (SWB) to simulate the dynamics of water content in the soil profile and evapotranspiration. The model employs a tipping bucket approach during infiltration events and Richards’ equation between infiltration events. This research calibrated the WINDS model to simulate water content in seven soil layers and evapotranspiration for a two-season guayule crop utilizing furrow irrigation at the Maricopa Agricultural Center (MAC) in Maricopa, AZ, from 2018 - 2020. The simulation required development of an innovative two-season basal crop coefficient (Kcb) curve. The segmented curve includes first and second season development, midseason, late season and end-season growth stages. The second year Kcb curve resumed after a semi-dormant state during the first winter. The midseason Kcb values were slightly higher during the midseason of year two (Kcb = 1.23) in comparison to year one (Kcb = 1.14). This research also developed a two-season root growth curve and a two-season root activity and root depth table in order to accurately simulate soil moisture depletion rates in layers over the two-year growth cycle. The WINDS model accurately simulated soil moisture content in soil layers with calibrated crop coefficient, soil, and root parameters.