中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin

文献类型:SCI/SSCI论文

作者Zhang F. Y.; Ahmad, S.; Zhang, H. Q.; Zhao, X.; Feng, X. W.; Li, L. H.; Xu, XL; Li, J; Li, J; Xu, XL
发表日期2016
关键词Streamflow Cumulative temperature Snowmelt Infiltration Kaidu River basin System dynamics surface backscatter response trmm precipitation radar forecast lead time climate-change united-states river-basin modeling approach water-resources soil-moisture tarim river
英文摘要Snowmelt and water infiltration are two important processes of the hydrological cycle in alpine basins where snowmelt water is a main contributor of streamflow. In insufficiently gauged basins, hydrologic modeling is a useful approach to understand the runoff formation process and to simulate streamflow. In this study, an existing hydrologic model based on the principles of system dynamics was modified by using the effective cumulative temperature (>0 degrees C) to calculate snowmelt rate, and the soil temperature to adjust the influence of the soil's physical state on water infiltration. This modified model was used to simulate streamflows in the Kaidu River basin from 1982 to 2002, including normal, high, and low flows categorized by the Z index. Sensitivity analyses, visual inspection, and statistical measures were employed to evaluate the capability of the model to simulate various components of the streamflow. Results showed that the modified model was robust, and able to simulate the three categories of flows well. The model's ability to reproduce streamflow in low-flow and normal-flow years was better than that in high-flow years. The model was also able to simulate the baseflow. Further, its ability to simulate spring-peak flow was much better than its ability to simulate the summer-peak flow. This study could provide useful information for water managers in determining water allocations as well as in managing water resources.
出处Stochastic Environmental Research and Risk Assessment
30
1
59-75
收录类别SCI
语种英语
ISSN号1436-3240
源URL[http://ir.igsnrr.ac.cn/handle/311030/43929]  
专题生态系统网络观测与模拟院重点实验室_生态网络实验室
推荐引用方式
GB/T 7714
Zhang F. Y.,Ahmad, S.,Zhang, H. Q.,et al. Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin. 2016.

入库方式: OAI收割

来源:地理科学与资源研究所

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