Flood forecasting study of PanShiTou Reservoir based on three water sources Xin'an River model
DOI:
https://doi.org/10.54097/8b87kd02Keywords:
Three Water Sources Xin'an River Model, PanShiTou Reservoir, Flood Forecasting.Abstract
This paper mainly takes PanShiTou Reservoir as the research object, adopts the three water sources Xin'anjiang model to forecast and analyze the two floods of 850704 and 860520, and selects the rainfall data of six rainfall stations for these two floods, and adopts the three water sources Xin'anjiang model to carry out evapotranspiration calculations, flow production calculations, sub-source calculations, and confluence calculations to derive the predicted value of the flood, and then compare the predicted value with the actual value, and then analyze the error analysis of this study. Comparing the predicted values with the actual values and comparing the error analysis of this study, it is concluded that the prediction level of these two floods is C. This study provides an effective technical means for the flood prediction of reservoirs and provides essential support for the operation and management of reservoirs.
Downloads
References
Situ Z, Wang Q, Teng S, et al. Improving urban flood prediction using LSTM-DeepLabv3+ and Bayesian optimization with spatiotemporal feature fusion [J]. Journal of Hydrology, 2024, 630.
Dandan S, Weimin B, Peng N. A robust real-time flood forecasting method based on error estimation for reservoirs [J]. AQUA — Water Infrastructure, Ecosystems and Society, 2022, 71 (4).
Wang Y, Zhong A P, Zhu F, et al. A modified Xin'anjiang model and its application for considering the regulatory and storage effects of small-scale water storage structures [J]. Journal of Hydrology, 2024, 630.
Tun T Z, Minjiao L. Influence of Data Length on the Determination of Data Adjustment Parameters in Conceptual Hydrological Modeling: A Case Study Using the Xinanjiang Model [J]. Water, 2022, 14 (19).
Shuaihong Z, Zhijia L, Cheng Y, et al. A New Runoff Routing Scheme for Xin’anjiang Model and Its Routing Parameters Estimation Based on Geographical Information [J]. Water, 2020, 12 (12).
Pidal M I, Martín H A J, Alonso-Muñoyerro M J, et al. Real-Time Data and Flood Forecasting in Tagus Basin. A Case Study: Rosarito and El Burguillo Reservoirs from 8th to 12th March, 2018 [J]. Water, 2020, 12 (4).
Chenkai C, Jianqun W, Zhijia L, et al. A New Hybrid Framework for Error Correction and Uncertainty Analysis of Precipitation Forecasts with Combined Postprocessors [J]. Water, 2022, 14 (19).
Hortal P A A, Zawadzki I, Yau K M. A Heuristic Approach for Precipitation Data Assimilation. Effect of forecast errors and assimilation of NCEP Stage IV precipitation analyses A Heuristic Approach for Precipitation Data Assimilation. Effect of forecast errors and assimilation of NCEP Stage IV precipitation analyses [J]. Monthly Weather Review, 2020, 148 (4).
Ali F, Achraf H, Guillaume F, et al. A novel statistical model for flood prediction in the Eel River watershed, New Brunswick, Canada [J]. Water Science, 2023, 37 (1).
Yizhi W, Jia L, Chuanzhe L, et al. A data‐driven approach for flood prediction using grid‐based meteorological data [J]. Hydrological Processes, 2023, 37 (3).
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







