摘要
Estimating the impact of mountain landscape on hydrology or water balance is essential for the sus- tainable development strategies of water resources. Specifically, understanding how the change of each landscape influences hydrological components will greatly improve the predictability of hydrological responses to mountain landscape changes and thus can help the government make sounder decisions. In the paper, we used the VIC （Variable Infiltration Capacity） model to conduct hydrological modeling in the upper Heihe River watershed, along with a frozen-soil module and a glacier melting module to improve the simulation. The improved model performed satisfactorily. We concluded that there are differences in the runoff generation of mountain landscape both in space and time. About 50% of the total runoff at the catchment outlet were generated in mid-mountain zone （2,900-4,000 m asl）, and water was mainly consumed in low mountain region （1,700-2,900 m asl） because of the higher requirements of trees and grasses. The runoff coefficient was 0.37 in the upper Heihe River watershed. Barren landscape produced the largest runoff yields （52.46% of the total runoff） in the upper Heihe River watershed, fol- lowed by grassland （34.15%）, shrub （9.02%）, glacier （3.57%）, and forest （0.49%）. In order to simulate the impact of landscape change on hydrological components, three landscape change scenarios were designed in the study. Scenario 1, 2 and 3 were to convert all shady slope landscapes at 2,000-3,300 m, 2,000-3,700 m, and 2,000-4,000 m asl respectively to forest lands, with forest coverage rate increased to 12.4%, 28.5% and 42.0%, respectively. The runoff at the catchment outlet correspondingly declined by 3.5%, 13.1% and 24.2% under the three scenarios. The forest landscape is very important in water conservation as it reduced the flood peak and increased the base flow. The mountains as ＂water towers＂ play important roles in water resources generation and the impact of mountain landscapes on hydrology is significant.
Estimating the impact of mountain landscape on hydrology or water balance is essential for the sus- tainable development strategies of water resources. Specifically, understanding how the change of each landscape influences hydrological components will greatly improve the predictability of hydrological responses to mountain landscape changes and thus can help the government make sounder decisions. In the paper, we used the VIC （Variable Infiltration Capacity） model to conduct hydrological modeling in the upper Heihe River watershed, along with a frozen-soil module and a glacier melting module to improve the simulation. The improved model performed satisfactorily. We concluded that there are differences in the runoff generation of mountain landscape both in space and time. About 50% of the total runoff at the catchment outlet were generated in mid-mountain zone （2,900-4,000 m asl）, and water was mainly consumed in low mountain region （1,700-2,900 m asl） because of the higher requirements of trees and grasses. The runoff coefficient was 0.37 in the upper Heihe River watershed. Barren landscape produced the largest runoff yields （52.46% of the total runoff） in the upper Heihe River watershed, fol- lowed by grassland （34.15%）, shrub （9.02%）, glacier （3.57%）, and forest （0.49%）. In order to simulate the impact of landscape change on hydrological components, three landscape change scenarios were designed in the study. Scenario 1, 2 and 3 were to convert all shady slope landscapes at 2,000-3,300 m, 2,000-3,700 m, and 2,000-4,000 m asl respectively to forest lands, with forest coverage rate increased to 12.4%, 28.5% and 42.0%, respectively. The runoff at the catchment outlet correspondingly declined by 3.5%, 13.1% and 24.2% under the three scenarios. The forest landscape is very important in water conservation as it reduced the flood peak and increased the base flow. The mountains as ＂water towers＂ play important roles in water resources generation and the impact of mountain landscapes on hydrology is significant.
基金
funded by the National Natural Science Foundation of China (41130638)
the key innovation project of the Chinese Academy of Sciences (KZCX2-YW-QN310)
the National Science and Technology Support Program (2013BAB05B03)
