Location: Agricultural Systems ResearchTitle: Irrigation scheduling based on wireless sensors output and soil-water characteristic curve in two soils
Submitted to: Sensors
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/26/2020
Publication Date: 2/29/2020
Citation: Jabro, J.D., Stevens, W.B., Iversen, W.M., Allen, B.L., Sainju, U.M. 2020. Irrigation scheduling based on wireless sensors output and soil-water characteristic curve in two soils. Sensors. 20(5):1336. https://doi.org/10.3390/s20051336.
Interpretive Summary: Irrigation scheduling methods based on smart soil moisture sensors are needed to optimize crop production, enhance water use efficiency, minimize water loss, and reduce adverse environmental impacts. Watermark soil moisture sensors often use to provide continuous real-time measurements of water potential at various depths in the soil profile that can be used for irrigation scheduling. Scientists at the ARS in Sidney Montana evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Watermark sensors can be used to effectively monitor soil water potential in the crop root zone and determine efficient irrigation events by simply setting two matric potential thresholds using soil water characteristic curve data. Each irrigation event can be initiated at the matric potential of soil water depletion level of 50% of plant available water capacity for sandy loam and clay loam soils. Wireless automated WM sensors can help producers and irrigators monitor real-time soil moisture content in the root zone and determine irrigation planning remotely. This technology can provide convenient and reliable ways for continuously monitoring soil moisture conditions in the plant root zone without regular visits to the field and manually downloading data from the loggers. This new irrigation management practice may enhance water use efficiency, sustain productivity, and increase net economic return while maintaining environmental quality.
Technical Abstract: Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground waters quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents at field capacity and permanent wilting point were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam and 35% and 17% for a clay loam, respectively. The field capacity level which occurs immediately after an irrigation event was considered the upper point of soil moisture content and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam and clay loam soils, respectively. Soil WM sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the WM wireless system is reliable, convenient and can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field.