Advanced on-farm technical support for optimum irrigation management with limited water

1Improving Water and Energy Management for Small and Mid-Size FarmsThis project will facilitate on-farm use of an advanced decision support system to facilitateoptimal irrigation management for farms with limited water. The decision support system hasrecently been deployed for a USDA funded on-farm trial in a region in which sustainableground water management is especially critical. Regional farms are required to reduce groundwater pumping substantially and that will reduce the availability of irrigation water by about30% for many farms. That is precisely the kind of management challenge the decision supportsystem was designed for.This proposed project will be conducted in conjunction with the CIG on-farm trials and it willdo two things. It will utilize satellite imagery to significantly enhance the effectiveness of thesystem and it will establish on-farm technical support for calibrating and using the system inorder to facilitate adoption and use by smaller farms with limited in-house technical staff.Optimal management of limited water requires modeling biophysical and economicrelationships to determine water allocation strategies that maximize net farm income (Troutet el. 2019). Such modeling is at the heart of the decision support system. To be fully effectivethat modeling requires locally specific calibration of key parameters that characterize soilscrops irrigation systems and management practices. But the process of calibration requiressome degree of technical expertise. While large well-capitalized farms can generally providethat expertise smaller farms often cannot. The SBIR Phase I project developed prototypesoftware for auto-calibration of the DSS that minimizes the technical expertise requiredmaking the decision support system readily accessible for smaller farms.The analytical tools in the DSS model the disposition and fate of applied water for alternativelevels of water use and irrigation timing. The auto-calibration procedure involves adaptivefeedback using field data in an iterative search to determine key model parameter values. Thecriterion for successful calibration is the ability to accurately project root zone soil moistureand crop water use on a field-wide basis weeks or months into the future.A primary goal of this Phase II project will utilize remote sensing imagery to significantlyenhance the effectiveness of the auto-calibration system and minimize the on-farm costs ofusing the decision support system. A second primary goal will be development of on-farmtechnical support materials that will enable farms with limited in-house technical expertiseto calibrate and utilize the decision support system for the specific circumstances of theirindividual farms and fields. The technical support will include two components: (i) tutorialsand on-line technical assistance for farm staff and (ii) training for local commercial farmadvisory services to provide on-farm assistance with setup and calibration of the DSS andinterpretation of analytical outputs generated by the DSS.The project director is Marshall English President Irrigation for the Future.