Simulation of Grain Yield, Seasonal Evapotranspiration, Global Warming Potential and Yield Gap Analysis of Wheat Under Varied Water and Nitrogen Management Practices Using InfoCrop Model

Abstract

Spatial heterogeneity of a river basin increases the predicting uncertainty of streamflow using hydrological models, and for such river basins calibration and prediction become a challenge. For a large and low flow–producing river basin like the Pennar basin of India, single-site calibration may ignore spatial heterogeneity, which leads to the use of a multiple-site calibration approach. The present study used Soil and Water Assessment Tool (SWAT) model to develop a real-world numerical model for predicting streamflow in a large, low runoff–producing river basin and evaluated the performance of the model under single-site and multiple-site calibration approaches. Under multiple-site approach, the large basin was divided into smaller subbasins, and the calibrated parameters were sequentially applied to the entire basin, and so local conditions were incorporated very effectively into the calibration process. The results demonstrated the superiority of a multiple-site calibration over a single-site calibration approach in predicting streamflow. The overall improvement of model performance in predicting streamflow using multiple-site approach over single-site approach reached as high as 133% during calibration and 140% during validation, as observed at the basin outlet (Chennur station). It was also observed that, within the basin, precipitation contributed only 15.8% to surface runoff, 2.6% to total aquifer recharge, and 69.3% to evapotranspiration. Uncertainty analysis indicated that more than 64% of the observed streamflow was bracketed by a 95% prediction uncertainty (PPU) band under the multiple-site approach. Thus, the multiple-site calibration approach demonstrated its ability to improve model performance by capturing the heterogeneity of a low runoff–producing basin like Pennar.