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DOI | DOI10.1088/1748-9326/abe784 |
Improving cold-region streamflow estimation by winter precipitation adjustment using passive microwave snow remote sensing datasets | |
D Kang; K Lee; E J Kim | |
2021-04-08 | |
发表期刊 | Environmental Research Letters |
出版年 | 2021/04/08 |
英文摘要 | Winter precipitation estimations and spatially sparse snow observations are key challenges when predicting snowmelt-driven floods. An improvement in streamflow prediction is achieved in a snowmelt-dominant basin, i.e. the Red River Basin (RRB), by adjusting the amounts of snowfall through satellite-borne passive microwave observations of snow water equivalent (SWE). A snowfall forcing dataset is scaled to minimize the difference between simulated and observed SWE over the RRB. Advanced microwave scanning radiometer-E (AMSR-E) SWE products serve as the observed SWE to obtain the solution to the linear equation between the AMSR-E and the baseline (no snowfall-forcing adjustment) SWE to yield a multiplication factor (Mfactor). In the headwaters of the RRB in the United States, a Nash–Sutcliffe efficiency (NSE) of 0.74 is obtained against observed streamflow, with Mfactor-adjusted streamflow during the snowmelt seasons (January to April). The baseline streamflow simulation without Mfactor exhibits an NSE of 0.38 owing to an underestimated SWE. |
领域 | 气候变化 |
URL | 查看原文 |
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文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/321957 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | D Kang,K Lee,E J Kim. Improving cold-region streamflow estimation by winter precipitation adjustment using passive microwave snow remote sensing datasets[J]. Environmental Research Letters,2021. |
APA | D Kang,K Lee,&E J Kim.(2021).Improving cold-region streamflow estimation by winter precipitation adjustment using passive microwave snow remote sensing datasets.Environmental Research Letters. |
MLA | D Kang,et al."Improving cold-region streamflow estimation by winter precipitation adjustment using passive microwave snow remote sensing datasets".Environmental Research Letters (2021). |
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