Assessing regional crop irrigation requirements and streamflow availability for irrigation development in Saginaw Bay, Michigan

Abstract

Spatial and temporal variability of soil, crop, and climate significantly affects the estimates of regional irrigation requirements. This paper incorporates soil association data and multiple-station, multiple-year climate data into four simulation models, CERES-MAIZE, SOYGRO, BEANGRO, and YIELD to account for the spatial and temporal variability of the input parameters in estimating the evapotranspiration rates and irrigation requirements of corn, drybean, soybean, and sugarbeet production in the Saginaw Bay basin, Michigan. The Thiessen method was used to delineate the spatial coverage of the weather stations in the study watershed. The results of the simulated crop irrigation requirements at the soil association level were multiplied by the weights of each soil association area to derive regional irrigation requirements. The availability of streamflow at different exceedence probabilities was evaluated to determine the maximum irrigation area the stream is able to sustain without causing water quality degradation. Through a case study of the Saginaw Bay irrigation development, this paper demonstrates that the spatial and temporal variability of soil, crop, and climate can be well represented in the simulation models to provide more realistic simulation results in support of irrigation decision making.