Simulation-Based Schemes to Determine Economical Irrigation Depths Considering Volumetric Water Price and Weather Forecasts

AbstractExacerbating water and food insecurity in drylands urge the more efficient use of water in irrigation through volumetric water pricing. The optimum irrigation depths can be determined using a combination of numerical simulation, water costs, and weather forecasts. In this context, we evaluated the effectiveness of three simulation-based schemes to determine irrigation depths that maximize net income during each irrigation interval using the WASH_2D model, which simulates water flow and solute transport through the plant–soil–atmosphere system. Those schemes were three-point (Scheme A) and two-point (Scheme B) schemes, which were used to optimize irrigation depth using three or two simulated cumulative transpiration at different irrigation depths, respectively, considering volumetric water price and weather forecasts; and a refilling scheme (Scheme C), which was used to determine irrigation depth required to return the simulated volumetric water content in the root zone to the field capacity. Those schemes were compared with the typical tensiometer-based automated irrigation scheme (Scheme D) by carrying out a field experiment in a sandy field of the Arid Land Research Center, Tottori University, Japan, using a major crop, sweet potatoes, in 2021. Compared with Scheme D, Schemes A, B, and C achieved 28%, 7%, and 21% higher net income due to applying 26%, 6%, and 17% less water and producing 21%, 5%, and 16% more biomass, respectively. The total simulated net income of Schemes A and B matched those of the measured schemes. Both simulated volumetric water content and actual evapotranspiration were in fair agreement with observed values. Regarding the accuracy of weather forecast, both daily reference evapotranspiration and rainfall forecasts were overestimated, with relative RMS error (RMSE) of 0.81 and 0.77 compared with observed values. In conclusion, both the two- and three-point schemes, which combined simulation, weather forecasts, and water prices, demonstrated significant benefits for farmers in terms of net income and water use compared with the use of basic types and costly automated irrigation systems.