Impact of Digital River Channel Classification on Flood Forecasting of Small and Medium Sized Watershed Based on Liuxihe Model

QIN Jian-ming, CHEN Yang-bo, WANG Huan-yu, ZHANG Jia-yang, LI Ming-liang

Journal of Changjiang River Scientific Research Institute ›› 2018, Vol. 35 ›› Issue (12) : 57-63.

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Journal of Changjiang River Scientific Research Institute ›› 2018, Vol. 35 ›› Issue (12) : 57-63. DOI: 10.11988/ckyyb.20170435
FLOOD PREVENTION AND DISASTER REDUCTION

Impact of Digital River Channel Classification on Flood Forecasting of Small and Medium Sized Watershed Based on Liuxihe Model

  • QIN Jian-ming1, CHEN Yang-bo1, WANG Huan-yu1, ZHANG Jia-yang1, LI Ming-liang2
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Abstract

The aim of this study is to explore the applicability of Liuxihe model in forecasting flood of small and medium sized watershed and the impact of DEM-based digital river channel delineation and classification on flood forecasting result. A Liuxihe model for flood forecasting in the Longhua river watershed is established, with model parameters optimized by using Particle Swarm Optimization (PSO) algorithm. Moreover, the effect of digital river channel classification on flood forecasting is discussed. Results show that higher order of digital river channel would result in higher peak flow of flood, earlier peak flow, larger runoff coefficient, and simulation result closer to factual values. Three-order of river system, rather than one order, is more appropriate when adopting the Liuxihe model for the flood forecast of small and medium sized watershed. As parameters in the Liuxihe model are optimized by PSO algorithm, only one observed flood event is required for parameter optimization in practical application, hence improving the performance of the model effectively. Validated by 50 flood events, the Liuxihe model with three orders of river system for flood forecasting of Longhua river watershed is proved feasible in real-time flood forecasting for the Longhua river watershed

Key words

flood forecasting / small and medium sized watershed / distributed hydrological model / Liuxihe model / digital river channel

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QIN Jian-ming, CHEN Yang-bo, WANG Huan-yu, ZHANG Jia-yang, LI Ming-liang. Impact of Digital River Channel Classification on Flood Forecasting of Small and Medium Sized Watershed Based on Liuxihe Model[J]. Journal of Changjiang River Scientific Research Institute. 2018, 35(12): 57-63 https://doi.org/10.11988/ckyyb.20170435

References

[1] ABBOTT M B, BATHURST J C, CUNGE J A, et al. An Introduction to the European Hydrological System-System Hydrologique Europeen, ‘SHE’, 2: Structure of a Physically-based Distributed Modeling System [J] . Journal of Hydrology, 1986, 87(1):61-77.
[2] VIEUX B E, VIEUX J E. 2002, VfloTM: A Real-time Distributed Hydrologic Model[C] ∥Proceedings of the 2nd Federal Interagency Hydrologic Modeling Conference, Las Vegas, Nevada. July 28-August 1, 2002:1-12.
[3] 李 兰. 有物理基础的LILAN分布式水文模型[M] .北京:科学出版社,2013.
[4] 雷晓辉, 廖卫红, 蒋云钟, 等. 分布式水文模型EasyDHM(Ⅰ):理论方法[J] . 水利学报, 2010,41(7):786-794.
[5] 陈洋波.流溪河模型[M] . 北京:科学出版社,2009.
[6] 陈洋波,任启伟,徐会军,等.流溪河模型I:原理与方法[J] .中山大学学报(自然科学版), 2010,49(1):107-112.
[7] 陈洋波,任启伟,徐会军,等.流溪河模型II:参数确定[J] .中山大学学报(自然科学版), 2010, 49(2):105-112.
[8] O’CALLAGHAN J, MARK D M. The Extraction of Drainage Networks from Digital Elevation Data [J] . Computer Vision, Graphics,and Image Processing, 1984, 28(3):323-344.
[9] STRAHLER A N. Quantitative Analysis of Watershed Geomorphology [J] .Transactions of the American Geophysical Union, 1957, 35(6):913-920.
[10] CHEN Yang-bo, LI Ji, XU Hui-jun. Improving Flood Forecasting Capability of Physically Based Distributed Hydrological Model by Parameter Optimization [J] . Hydrology & Earth System Sciences, 2017, 20(1):1279-1294.
[11] 陈洋波,徐会军,李 计.流域洪水预报分布式模型参数自动优选[J] .中山大学学报(自然科学版),2017,56(3):15-23.
[12] 黄家宝,董礼明,陈洋波,等.基于流溪河模型的乐昌峡水库入库洪水预报模型研究[J] .水利水电技术,2017, 48 (4) :1-7.
[13] 陈洋波,覃建明,王幻宇,等.基于流溪河模型的中小河流洪水预报方法[J] .水利水电技术,2017, 48(7):12-19.
[14] CHEN Yang-bo, LI Ji, WANG Huan-yu, et al. Large-watershed Flood Forecasting with High-resolution Distributed Hydrological Model [J] . Hydrology & Earth System Sciences, 2017, 20(1):735-749.
[15] LI Ji, CHEN Yang-bo, WANG Huan-yu, et al. Extending Flood Forecasting Lead Time in a Large Watershed by Coupling WRF QPF with a Distributed Hydrological Model [J] . Hydrology & Earth System Sciences, 2017, 21(2):735-749.
[16] 熊立华, 郭生练. 基于DEM的数字河网生成方法的探讨[J] . 长江科学院院报, 2003, 20(4):14-17.
[17] 王正勇, 杨胜梅, 马 琨,等. 基于空间信息技术的六股河流域河网水系提取[J] . 长江科学院院报, 2016, 33(11):63-67.
[18] WANG Z M, BATELAAN O, DE SMEDT F.A Distributed Model for Water and Energy Transfer Between Soil, Plants and Atmosphere (WetSpa) [J] . Physics and Chemistry of the Earth,1996, 21(3):189-193.
[19] ARYAL M, PARIS J F. A Physioempirical Model to Predict the Soil Moisture Characteristic from Particle-size Distribution and Bulk Density Data[J] . Soil Science Society of America Journal, 1981,45(6):1023-1030.
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