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Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China
The assessment of water resource responses to climate change is required in water resource planning and management, protecting environmental quality, and managing watersheds. This study modeled surface runoff and baseflow responses to variations in precipitation (0%, ±10%, and ±20%) and temperature (0 °C, ±1 °C, and ±2 °C) in 25 types of scenarios in the Lanhe Watershed (1140 km2), which possesses the typical hydrological and meteorological characteristics of the Loess Plateau in China. The study is based on the Soil and Water Assessment Tool (SWAT), which was calibrated and validated using the coefficient of determination (R2), Nash-Suttcliffe (Ens), and Percent bias (PBIAS), using the observed streamflow of Shangjingyou Station, a unique gauging station in the study area. The model was calibrated with daily streamflow, from 1967 to 1996, and then validated from 1997 to 2011. R2, Ens, and PBIAS were 0.95 and 0.84, 0.78 and 0.72, and 0.6% and −9.1% in annual and monthly calibration periods, 0.90 and 0.78, 0.74 and 0.67, and 22.1% and 18.8% in annual and monthly validation periods, and the overall performance ratings was “satisfactory”. The assessment indicates that surface runoff is likely to be more affected than baseflow when altering temperatures and precipitation, and the noticeable changes of surface and baseflow are from June to September and October to November, respectively. Results also indicate that surface runoff and baseflow are very sensitive to the projected reduction in temperature, rather than to an increase of temperature, while precipitation is a constant. In turn, when the temperature is a constant, the surface runoff is sensitive to the projected increase in precipitation and the baseflow is sensitive to the decrease in precipitation.
Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China
The assessment of water resource responses to climate change is required in water resource planning and management, protecting environmental quality, and managing watersheds. This study modeled surface runoff and baseflow responses to variations in precipitation (0%, ±10%, and ±20%) and temperature (0 °C, ±1 °C, and ±2 °C) in 25 types of scenarios in the Lanhe Watershed (1140 km2), which possesses the typical hydrological and meteorological characteristics of the Loess Plateau in China. The study is based on the Soil and Water Assessment Tool (SWAT), which was calibrated and validated using the coefficient of determination (R2), Nash-Suttcliffe (Ens), and Percent bias (PBIAS), using the observed streamflow of Shangjingyou Station, a unique gauging station in the study area. The model was calibrated with daily streamflow, from 1967 to 1996, and then validated from 1997 to 2011. R2, Ens, and PBIAS were 0.95 and 0.84, 0.78 and 0.72, and 0.6% and −9.1% in annual and monthly calibration periods, 0.90 and 0.78, 0.74 and 0.67, and 22.1% and 18.8% in annual and monthly validation periods, and the overall performance ratings was “satisfactory”. The assessment indicates that surface runoff is likely to be more affected than baseflow when altering temperatures and precipitation, and the noticeable changes of surface and baseflow are from June to September and October to November, respectively. Results also indicate that surface runoff and baseflow are very sensitive to the projected reduction in temperature, rather than to an increase of temperature, while precipitation is a constant. In turn, when the temperature is a constant, the surface runoff is sensitive to the projected increase in precipitation and the baseflow is sensitive to the decrease in precipitation.
Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China
Hua Jin (author) / Qiao Zhu (author) / Xuehua Zhao (author) / Yongbo Zhang (author)
2016
Article (Journal)
Electronic Resource
Unknown
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