Prediction of nitrate accumulation and leaching beneath groundwater irrigated corn fields in the Upper Platte basin under a future climate scenario

摘要

Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize the adverse impacts of agricultural activities on groundwater quality. To evaluate the direct effects of climate change on the transport and accumulation of nitrale-N, we developed an integrated modeling framework combining climatic change, nitrate-N infiltration in the unsaturated zone, and groundwater level fluctuations. The study was based on a center-pivot irrigated corn field at the Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge (GR) and actual evapotranspiration (ETa) rates were predicted via an inverse vadose zone modeling approach by using climatic data generated by the Weather Research and Forecasting (WRF) climate model under the RCP 8.5 scenario, which was downscaled from the global CCSM4 model to a resolution of 24 km by 24 km. A groundwater flow model was first calibrated on the basis of historical groundwater table measurements and then applied to predict the future groundwater table in 2057-2060. Finally, the predicted future GR rate, ETa rate, and groundwater level, together with future precipitation data from the WRF climate model, were used in a three-dimensional (3D) model to predict nitrate-N concentrations in tire subsurface (saturated and unsaturated parts) from 2057 to 2060. The future GR was predicted to decrease in the study area, as compared with the average GR data from the literature. Correspondingly, the groundwater level was predicted to decrease (30 to 60 cm) over the 5 years of simulation in the future. The nitrate-N mass in the simulation domain was predicted to increase but at a slower rate than in the past. Sensitivity analysis indicated that the accumulation of nitrate-N is sensitive to groundwater table elevation changes and irrigation rates. (C) 2019 Elsevier B.V. All rights reserved.