Research on Annual Runoff Forecast of Shaanxi Section of Hanjiang River Based on Multi-model

Shuni He, Na Wei, Linshun Cao, Zhi Zhang, Shaofei Zhang, Feng Yang, Yating Gao

2021

Abstract

Because of its strong non-stationary and nonlinear characteristics, the runoff series bring serious challenges to the accurate and reasonable prediction of runoff. In the past, the research direction of runoff prediction is mainly the improvement of a single model or mixed model prediction, which often ignores the model’s applicability to the actual situation. From the perspective of multiple models, based on the runoff series data of Yangxian Station in Shaanxi Section of Han River, this paper adopts the ARIMA model, the MGF model, the Grey dynamic model and the DenseNet model to forecast the annual runoff of Yangxian Station. The prediction results are compared and analyzed to select the model most suitable for Yangxian Station among the four models. The results show that the DenseNet model is the most suitable for the runoff prediction activities of the selected watershed. Through the applicability analysis of runoff prediction model, a scientific and reliable runoff prediction can be obtained, which provides a scientific basis for water resources management and allocation, water resources development and utilization.

Paper Citation

in Harvard Style

He S., Wei N., Cao L., Zhang Z., Zhang S., Yang F. and Gao Y. (2021). Research on Annual Runoff Forecast of Shaanxi Section of Hanjiang River Based on Multi-model. In Proceedings of the 7th International Conference on Water Resource and Environment - Volume 1: WRE, ISBN 978-989-758-560-9, pages 377-388

in Bibtex Style

@conference{wre21,
author={Shuni He and Na Wei and Linshun Cao and Zhi Zhang and Shaofei Zhang and Feng Yang and Yating Gao},
title={Research on Annual Runoff Forecast of Shaanxi Section of Hanjiang River Based on Multi-model},
booktitle={Proceedings of the 7th International Conference on Water Resource and Environment - Volume 1: WRE,},
year={2021},
pages={377-388},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={978-989-758-560-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Water Resource and Environment - Volume 1: WRE,
TI - Research on Annual Runoff Forecast of Shaanxi Section of Hanjiang River Based on Multi-model
SN - 978-989-758-560-9
AU - He S.
AU - Wei N.
AU - Cao L.
AU - Zhang Z.
AU - Zhang S.
AU - Yang F.
AU - Gao Y.
PY - 2021
SP - 377
EP - 388
DO -