Abstract:The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region.
Abstract:The Soil and Water Assessment Tool (SWAT) model combined with a temperature index and elevation band algorithm was applied to the Hunza watershed, where snow and glacier-melt are the major contributor to river flow. This study's uniqueness is its use of a snow melt algorithm (temperature index with elevation bands) combined with the SWAT, applied to evaluate the performance of the SWAT model in the highly snow and glacier covered watershed of the Upper Indus Basin in response to climate change on future streamflow volume at the outlet of the Hunza watershed, and its contribution to the Indus River System in both space and time, despite its limitation; it is not designed to cover the watershed of heterogeneous mountains. The model was calibrated for the years 1998-2004 and validated for the years 2008-2010. The model performance is evaluated using the four recommended statistical coefficients with uncertainty analysis (p-factor and r-factor). Simulations generated good calibration and validation results for the daily flow gauge. The model efficiency was evaluated, and a strong relationship was observed between the simulated and observed flows. The model results give a coefficient of determination (R 2 ) of 0.82 and a Nash-Sutcliffe Efficiency index (NS) of 0.80 for the daily flow with values of p-factor (79%) and r-factor (76%). The SWAT model was also used to evaluate climate change impact on hydrological regimes, the target watershed with three GCMs (General Circulation Model) of the IPCC fifth report for 2030-2059 and 2070-2099, using 1980-2010 as the control period. Overall, temperature (1.39 • C to 6.58 • C) and precipitation (31%) indicated increased variability at the end of the century with increasing river flow (5%-10%); in particular, the analysis showed smaller absolute changes in the hydrology of the study area towards the end of the century. The results revealed that the calibrated model was more sensitive towards temperature and precipitation, snow-melt parameters and Curve Number (CN2). The SWAT results also provided reliable information for the daily runoff from the sub-basin watersheds responding to changing climatic conditions. SWAT can thus be used to devise effective strategies for future sustainable water management in the region, while combating vulnerabilities against floods and water storage in downstream water reservoirs such as the Diamer-Basha dam.
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