Precision Agriculture and Irrigation: Current U.S. Perspectives

Self Cite

Collection PerspectiveHIGHLIGHTS  ASABE and ISAE convened the Global Water Security Conference for Agriculture and Natural Resources in Hyderabad, India, in 2018.  Recommendations represent collective contribution of attendees and presenters in seven key priorities.  Continuation of a narrow focus on technical aspects will likely prevent the success of technical solutions.  Scientists and engineers should work together across all disciplines and boundaries to ensure global water security.

Section: Key Priority 4: Optimize Irrigation Efficiency and Increase mentioning

confidence: 89%

Perspectives on Global Water Security

Harmel¹,

Chaubey²,

Ale³

et al. 2020

Self Cite

“…The relationships between soil water status, crop canopy temperature and crop water stress were studied by Clark and Hiler (1973), Ehrler (1973), and by Jackson et al (1981) at the USDA-ARS Water Laboratory in Tempe, Arizona, and elsewhere in the 1970s and 1980s, as summarized by Jackson (1982). The understanding that crop water stress is related to soil water status is age old, which is why irrigation has been part of human endeavor for several thousand years (Evett et al, 2020), but the relationships between soil water status, plant water stress as indicated by leaf and stem water potentials, and crop leaf and canopy temperatures were not well explored prior to the development in the 1960s of portable, infrared thermometers (IRTs) with bandpass filters in the 8 to 13 m range (Fuchs and Tanner, 1966). Jackson (1982) summarized earlier research, including that done at the USDA-ARS Water Laboratory prior to 1982.…”

Section: Canopy and Leaf Temperature Sensingmentioning

confidence: 99%

Theory and Development of a VRI Decision Support System: The USDA-ARS ISSCADA Approach

Evett¹,

O’Shaughnessy²,

Andrade³

et al. 2020

Self Cite

HighlightsMulti-faceted research efforts converged to an automated irrigation decision support system (DSS).Low-cost, solar-powered, wireless plant abiotic and biotic stress sensors were developed to aid the DSS.Low-cost, accurate TDR soil water sensors and a wireless node and gateway system were developed for the DSS.Sensor systems and research-based algorithms were integrated into an automated irrigation DSS and control system.Abstract. Variable-rate irrigation (VRI) is now possible with every new center pivot irrigation system sold, either using sector (speed) control or both sector and zone (radial along the pipeline) control. However, decision support systems able to generate a prescription for spatially varying irrigation based on crop water need have lagged far behind VRI equipment. Irrigation based on crop water need has been shown to increase both crop water productivity and nutrient use efficiency, meaning that an effective VRI decision support system (DSS) could improve profitability while conserving resources. In this article, we report separately on a VRI DSS using sensor-based plant and soil water feedback as implemented in four U.S. states. This article describes the genesis and development of the Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system, of the integral plant and soil sensors, and of its wireless sensor network subsystems, as well as the role of multi-location research efforts and cooperative research and development agreements in the development of the needed plant and soil sensors and the ISSCADA and wireless sensor network systems. Keywords: Crop water productivity, Decision support system, Product development, Sensors, Variable-rate irrigation, VRI.

“…Irrigation system improvements that increase irrigation uniformity may provide less benefit with DI than with full irrigation because with DI even the areas that receive the most water may not exceed the soil water deficit. Variable-rate irrigation (VRI) systems (Evans et al, 2013) may improve NI with DI by tailoring the water application to the soil storage capacity and measured plant water stress and concentrating the limited water supply and other inputs on portions of the field that have greater yield potential (Evett et al, 2020. Water supply system improvements that increase flexibility of application timing allow irrigation to be strategically applied during critical growth stages and may increase the curvilinearity of the WPF and thus the yield with DI.…”

Section: Practices That May Improve Yields Under Deficit Irrigationmentioning

confidence: 99%

Deficit Irrigation Strategies for the Western U.S.

Trout¹,

Howell²,

English³

et al. 2020

HighlightsDeficit irrigation may maximize net income when irrigation water supplies are limited or expensive.Water production functions are used with economic parameters to maximize net income with deficit irrigation.Net income may be insensitive to the amount of deficit irrigation if production costs are appropriate for anticipated yield.Deficit irrigation increases risk.Abstract. Competition for, regulation of, and depletion of water supplies in the western U.S. has resulted in reduced water available for irrigating crops. When the water supply is expensive or inadequate to meet full crop water requirements, deficit irrigation (DI) may maximize net income (NI) by reducing use of expensive water or irrigating more land with limited irrigation supplies. Managed DI entails rational planning and strategic water allocation to maximize NI when water supplies are constrained. Biophysical and economic relationships were used to develop NI models for DI and determine water allocation strategies that maximize NI under three types of water supply constraints. The analyses determined that potential benefits of DI are greatest when water is expensive, irrigation efficiency is low, the water supply is flexible, and rainfed production is not economically viable. When production costs are appropriate for anticipated yields, NI is less sensitive to DI planning decisions. Deficit irrigation will become more important as irrigation water supplies continue to decline in the future. Net income analysis can assist growers in making rational DI decisions. Keywords: Deficit irrigation, Economic analysis, Irrigation management, Net income, Optimization, Water productivity.