This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basi...This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basin (West Africa). Original and bias corrected climate data from the regional climate model REMO were used as input for the Max Planck Institute for Meteorology-Hydrology Model (MPI-HM) to simulate river discharge, runoff, soil moisture and evapotranspiration. The results during the historical period (1971-2000) show that using the bias corrected input yields a better representation of the mean river flow regimes and the 10th and 90th percentiles of river flow at the outlet of the Upper Senegal Basin (USB). The Nash-Sutcliffe efficiency coefficient is 0.92 using the bias corrected input, which demonstrates the ability of the model in simulating river flow. The percent bias of 3.88% indicates a slight overestimation of the river flow by the model using the corrected input. The evaluation demonstrates the ability of the bias correction and its necessity for the simulation of historical river regimes. As for the potential changes of hydrological variables by the end of 21st century (2071-2100), a general decrease of river discharge, runoff, actual evapotranspiration, soil moisture is found under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in all simulations. The decrease is higher under RCP8.5 with uncorrected data in the northern basin. However, there are some localized increases in some parts of the basin (e.g. Guinean Highlands). The projected climate change signal of these above variables has the same spatial pattern and tendency for the uncorrected and bias corrected data although the magnitude of the corrected signal is somewhat lower than that uncorrected. Furthermore, the available water resources are projected to substantially decrease by more than -50% in the majority of the basin (especially in driest and hottest northern basin with RCP8.5 scenario) for all data, except the Guinean highlands where no change is projected. The comparison of simulations driven with uncorrected and bias corrected input reveals that the bias correction does not substantially change the signal of future changes of hydrological variables for both scenarios over the USB even though there are differences in magnitude and deviations in some parts of the basin.展开更多
Motivated by the potential flood outburst of Lake Gojal in the ungauged highly glacierized （27%） upper Hunza River Basin （HRB） in Pakistan that was dammed by a massive landslide on 4 January 2010, we attempt to an...Motivated by the potential flood outburst of Lake Gojal in the ungauged highly glacierized （27%） upper Hunza River Basin （HRB） in Pakistan that was dammed by a massive landslide on 4 January 2010, we attempt to analyze the characteristics of water inflow to the lake employing remote sensing data, two hydrological models, and sparsely observed data. One of the models （Model I） is a monthly degree-day model, while another （Model II） is the variable infiltration capacity （VIC） model. The mixture of glacier runoff output from Model I and runoff over unglacierized areas calculated by Model II has a similar seasonal variation pattern as that estimated from data recorded at a downstream station. This suggests that glacier runoff is the main source （87%） of runoff inflow into the lake. A sensitivity analysis suggests that the water inflow to the lake is highly sensitive to an increase in air temperature. Runoff in May is predicted to sharply increase by 15% to more than two-fold if the air temperature increases by 1 to 7 ℃, but it is predicted to increase only from 9% to 34% if the precipitation increases by 10% to 40%. The results suggested that the water inflow into Lake Gojal will not sharply rise even if there is heavy rain, and it needs to be in caution if the air temperature sharply increases. Analysis on long-term air temperature record indicates that the water inflow into the lake in May 2010 was probably less than average owing to the relatively low air temperature. Consequently, the flood outburst did not occur before the completion of the spillway on 29 May 2010.展开更多
文摘This study assesses the potential impacts of climate change on water resources and the effect of statistical bias correction on the projected climate change signal in hydrological variables over the Upper Senegal Basin (West Africa). Original and bias corrected climate data from the regional climate model REMO were used as input for the Max Planck Institute for Meteorology-Hydrology Model (MPI-HM) to simulate river discharge, runoff, soil moisture and evapotranspiration. The results during the historical period (1971-2000) show that using the bias corrected input yields a better representation of the mean river flow regimes and the 10th and 90th percentiles of river flow at the outlet of the Upper Senegal Basin (USB). The Nash-Sutcliffe efficiency coefficient is 0.92 using the bias corrected input, which demonstrates the ability of the model in simulating river flow. The percent bias of 3.88% indicates a slight overestimation of the river flow by the model using the corrected input. The evaluation demonstrates the ability of the bias correction and its necessity for the simulation of historical river regimes. As for the potential changes of hydrological variables by the end of 21st century (2071-2100), a general decrease of river discharge, runoff, actual evapotranspiration, soil moisture is found under two Representative Concentration Pathways (RCP4.5 and RCP8.5) in all simulations. The decrease is higher under RCP8.5 with uncorrected data in the northern basin. However, there are some localized increases in some parts of the basin (e.g. Guinean Highlands). The projected climate change signal of these above variables has the same spatial pattern and tendency for the uncorrected and bias corrected data although the magnitude of the corrected signal is somewhat lower than that uncorrected. Furthermore, the available water resources are projected to substantially decrease by more than -50% in the majority of the basin (especially in driest and hottest northern basin with RCP8.5 scenario) for all data, except the Guinean highlands where no change is projected. The comparison of simulations driven with uncorrected and bias corrected input reveals that the bias correction does not substantially change the signal of future changes of hydrological variables for both scenarios over the USB even though there are differences in magnitude and deviations in some parts of the basin.
基金supported by the Global Change Research Program of China (No. 2010CB951404)the National Natural Science Foundation of China (Nos. 41030638,41121001)
文摘Motivated by the potential flood outburst of Lake Gojal in the ungauged highly glacierized （27%） upper Hunza River Basin （HRB） in Pakistan that was dammed by a massive landslide on 4 January 2010, we attempt to analyze the characteristics of water inflow to the lake employing remote sensing data, two hydrological models, and sparsely observed data. One of the models （Model I） is a monthly degree-day model, while another （Model II） is the variable infiltration capacity （VIC） model. The mixture of glacier runoff output from Model I and runoff over unglacierized areas calculated by Model II has a similar seasonal variation pattern as that estimated from data recorded at a downstream station. This suggests that glacier runoff is the main source （87%） of runoff inflow into the lake. A sensitivity analysis suggests that the water inflow to the lake is highly sensitive to an increase in air temperature. Runoff in May is predicted to sharply increase by 15% to more than two-fold if the air temperature increases by 1 to 7 ℃, but it is predicted to increase only from 9% to 34% if the precipitation increases by 10% to 40%. The results suggested that the water inflow into Lake Gojal will not sharply rise even if there is heavy rain, and it needs to be in caution if the air temperature sharply increases. Analysis on long-term air temperature record indicates that the water inflow into the lake in May 2010 was probably less than average owing to the relatively low air temperature. Consequently, the flood outburst did not occur before the completion of the spillway on 29 May 2010.
