Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China

Yangzong Cidan, Hongyan Li (), Yunqing Xuan, Hong Sun and Fang You
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Yangzong Cidan: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Jiefang Street No. 2519, Changchun 130021, China
Hongyan Li: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Jiefang Street No. 2519, Changchun 130021, China
Yunqing Xuan: Department of Civil Engineering, Swansea University Bay Campus, Swansea SA1 8EN, UK
Hong Sun: Hydrological and Water Resources Administration of Jilin Province, Changchun 130028, China
Fang You: Hydrological and Water Resources Administration of Jilin Province, Changchun 130028, China

Sustainability, 2022, vol. 14, issue 17, 1-13

Abstract: The Second Songhua River Basin is located at the northern edge of the East Asian monsoon region in China. The river basin has a large interannual rainfall-runoff variation often associated with frequent droughts and floods. Therefore, the mid-long-term runoff prediction is of great significance. According to a review of the national and international literature, there are few studies on sunspots in the prediction of medium- and long-term runoff. In this study, sunspots are selected as the influencing factors of runoff based on the mechanism of astronomical factors; sensitivity analysis was used to identify the time delay of sunspots’ influence on runoff and determine the prediction factor (relative number of sunspots in January and March). The BP (backpropagation) network is used to identify the correlation between prediction factors and prediction items (monthly average inflow rate of the Fengman Reservoir and the Baishan Reservoir in the flood season), and then the prediction model is constructed. According to the test results of historical data and the actual forecast results, the forecast is working well, and the accuracy of qualitative forecasting is high.

Keywords: medium-long-term runoff forecast; sunspots; BP (backpropagation) network; sensitivity analysis; Second Songhua River Basin (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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