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1 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. (Special issue: Soil Moisture Sensors for Irrigation Management) [doi: https://doi.org/10.3390/s20051336]
Irrigation Scheduling ; Soil water characteristics ; Soil water content ; Soil water potential ; Wilting point ; Water availability ; Sandy loam soils ; Clay loam soils ; Monitoring ; Rain ; Sensors / USA / North Dakota / Montana
(Location: IWMI HQ Call no: e-copy only Record No: H049690)
(1.53 MB) (1.53 MB)
Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water 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, where 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 points, 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 shortly 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. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system 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
2 Dirwai, T. L.; Senzanje, A.; Mabhaudhi, Tafadzwanashe. 2022. Development and validation of a model for soil wetting geometry under moistube irrigation. Scientific Reports, 12:2737. [doi: https://doi.org/10.1038/s41598-022-06763-x]
Irrigation methods ; Subsurface irrigation ; Wetting front ; Geometry ; Models ; Soil hydraulic properties ; Soil water content ; Soil water movement ; Sandy soils ; Clay loam soils ; Silty soils / South Africa / KwaZulu-Natal
(Location: IWMI HQ Call no: e-copy only Record No: H050970)
(2.13 MB) (2.13 MB)
We developed an empirical soil wetting geometry model for silty clay loam and coarse sand soils under a semi-permeable porous wall line source Moistube Irrigation (MTI) lateral irrigation. The model was developed to simulate vertical and lateral soil water movement using the Buckingham pi (p) theorem. This study was premised on a hypothesis that soil hydraulic properties influence soil water movement under MTI. Two independent, but similar experiments, were conducted to calibrate and validate the model using MTI lateral placed at a depth of 0.2 m below the soil surface in a soil bin with a continuous water supply (150 kPa). Soil water content was measured every 5 min for 100 h using MPS-2 sensors. Model calibration showed that soil texture influenced water movement (p< 0.05) and showed a good ft for wetted widths and depths for both soils (nRMSE = 0.5–10%; NSE = 0.50; and d-index = 0.50. The percentage bias (PBIAS) statistic revealed that the models’ under-estimated wetted depth after 24 h by 21.9% and 3.9% for silty clay loam and sandy soil, respectively. Sensitivity analysis revealed agreeable models’ performance values. This implies the model’s applicability for estimating wetted distances for an MTI lateral placed at 0.2 m and MTI operating pressure of 150 kPa. We concluded that the models are prescriptive and should be used to estimate wetting geometries for conditions under which they were developed. Further experimentation under varying scenarios for which MTI would be used, including feld conditions, is needed to further validate the model and establish robustness. MTI wetting geometry informs placement depth for optimal irrigation water usage.
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