Journal article 407 views
Investigating the critical influencing factors of snowmelt runoff and development of a mid-long term snowmelt runoff forecasting
,
Shanshan Bao,
Yangzong Cidan,
Yingying Liu,
Changhai Li,
Meichu Yao
Journal of Geographical Sciences, Volume: 33, Issue: 6, Pages: 1313 - 1333
Swansea University Author:
Yunqing Xuan
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1007/s11442-023-2131-9
Abstract
Snowmelt runoff is a vital source of fresh water in cold regions. Accurate snowmelt runoff forecasting is crucial in supporting the integrated management of water resources in these regions. However, the performances of such forecasts are often very low as they involve many meteorological factors an...
| Published in: | Journal of Geographical Sciences |
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| ISSN: | 1009-637X 1861-9568 |
| Published: |
Springer Science and Business Media LLC
2023
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63775 |
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| Abstract: |
Snowmelt runoff is a vital source of fresh water in cold regions. Accurate snowmelt runoff forecasting is crucial in supporting the integrated management of water resources in these regions. However, the performances of such forecasts are often very low as they involve many meteorological factors and complex physical processes. Aiming to improve the understanding of these influencing factors on snowmelt runoff forecast, this study investigated the time lag of various meteorological factors before identifying the key factor in snowmelt processes. The results show that solar radiation, followed by temperature, are the two critical influencing factors with time lags being 0 and 2 days, respectively. This study further quantifies the effect of the two factors in terms of their contribution rate using a set of empirical equations developed. Their contribution rates as to yearly snowmelt runoff are found to be 56% and 44%, respectively. A mid-long term snowmelt forecasting model is developed using machine learning techniques and the identified most critical influencing factor with the biggest contribution rate. It is shown that forecasting based on Supporting Vector Regression (SVR) method can meet the requirements of forecast standards. |
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| Keywords: |
Snowmelt runoff, mid-long term forecast, SVR, cold regions |
| College: |
Faculty of Science and Engineering |
| Issue: |
6 |
| Start Page: |
1313 |
| End Page: |
1333 |