Facebook Instagram Twitter RSS Feed PodBean Back to top on side

A system-theory-based model for monthly river runoff forecasting: model cali-bration and optimization

In: Journal of Hydrology and Hydromechanics, vol. 62, no. 1
Jianhua Wu - Hui Qian - Peiyue Li - Yanxun Song
Detaily:
Rok, strany: 2014, 82 - 88
Kľúčové slová:
System theory; River runoff; Weight function; Frequency analysis; Uncertainty.
URL originálneho zdroja: http://www.ih.savba.sk/jhh
O článku:
River runoff is not only a crucial part of the global water cycle, but it is also an important source for hydropower and an essential element of water balance. This study presents a system-theory-based model for river runoff fore-casting taking the Hailiutu River as a case study. The forecasting model, designed for the Hailiutu watershed, was calibrated and verified by long-term precipitation observation data and groundwater exploitation data from the study area. Additionally, frequency analysis, taken as an optimization technique, was applied to improve prediction accuracy. Following model optimization, the overall relative prediction errors are below 10%. The system-theory-based prediction model is applicable to river runoff forecasting, and following optimization by frequency analysis, the prediction error is acceptable.
Ako citovať:
ISO 690:
Wu, J., Qian, H., Li, P., Song, Y. 2014. A system-theory-based model for monthly river runoff forecasting: model cali-bration and optimization. In Journal of Hydrology and Hydromechanics, vol. 62, no.1, pp. 82-88. 0042-790X (until 2019) .

APA:
Wu, J., Qian, H., Li, P., Song, Y. (2014). A system-theory-based model for monthly river runoff forecasting: model cali-bration and optimization. Journal of Hydrology and Hydromechanics, 62(1), 82-88. 0042-790X (until 2019) .