Long-term numerical modeling of nitrate leaching into groundwater under surface drip irrigation of corn

Proper management of fertigation is necessary to deal with the harmful impacts of fertilizers. This research aimed to investigate the nitrate leaching rate into groundwater in different fertigation management under the climate change impact in drip irrigation of corn. For this purpose, HYDRUS-2D was calibrated by performing field experiments. Plant water requirement and rainfall were projected until 2050 using LARS-WG6 under the RCP85 scenario. Then, nitrate leaching up to groundwater at the depth of 5 m was simulated in the growing season of corn and the like until 2050 in three fertigation scenarios, including S1 (three regional fertigation splits with irrigation efficiency of 85%), S2 (weekly fertigation with irrigation efficiency of 85%), and S3 (optimum fertigation with irrigation efficiency of 100%). Finally, the annual nitrate leaching rate to groundwater and leached amount were compared in the studied scenarios. The results demonstrated that nitrate penetrated to the depth of 117 and 105 cm at the end of the first year in S1 and S2 scenarios, respectively. In these scenarios, nitrate will reach groundwater in 2031, but nitrate concentrations will not be the same. In the S3 scenario, the nitrate will reach a depth of 180 cm by 2050. Total leached nitrate to groundwater up to 2050 will be 1740, 1200, and zero kg/ha in S1, S2, and S3 scenarios, respectively. Based on the approach of this study, the vulnerability of groundwater to nitrate contamination in different agricultural areas can be evaluated, and appropriate strategies with minimum environmental impacts of fertilizer abuse can be selected accordingly.

Future climate projections using the LARS-WG6 downscaling model over Upper Indus Basin, Pakistan

This study investigates the projections of precipitation and temperature at the local scale in the Upper Indus Basin (UIB) in Pakistan using six Regional Climate Models (RCMs) from CORDEX under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). For twenty-four stations spread across the study area, the Long Ashton Research Station Weather Generator, version six (LARS-WG6), was used to downscale the daily data from the six different RCMs for maximum temperature (T_max), minimum temperature (T_min), and precipitation (pr) at a spatial resolution of 0.44°. Investigations were made to predict changes in mean annual values of T_max, T_min, and precipitation during two future periods, i.e., the mid-century (2041-2070) and end-century (2071-2100). The model results from statistical and graphical comparison validated that the LARS-WG6 can simulate the temperature and the precipitation in the UIB. Each of the six RCMs and their ensemble revealed a continuously increased temperature projection in the basin; nevertheless, there is variation in projected magnitude across RCMs and between RCPs. The rise in average T_max and T_min was more significant under RCP 8.5 than RCP 4.5, possibly due to unmitigated greenhouse gas emissions (GHGs). The precipitation projections follow the non-uniform trend, i.e., not all RCMs agree on whether the precipitation will increase or decrease in the basin, and no orderly variations were detected during any future periods under any RCP. However, an overall increase in precipitation is projected by the ensemble of RCMs.