Establishing a rainfall threshold for flash flood warnings in China's mountainous areas based on a distributed hydrological model

被引:90
|
作者
Miao, Qinghua [1 ]
Yang, Dawen [1 ]
Yang, Hanbo [1 ]
Li, Zhe [2 ,3 ]
机构
[1] Tsinghua Univ, Dept Hydraul Engn, Stare Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
[3] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China
关键词
Flash flood warning; Distributed hydrological model; Ungauged catchments; Rainfall threshold; Binary classification; UNGAUGED LOCATIONS; FORECAST SYSTEM; UNITED-STATES; PART II; SOIL; GUIDANCE; RIVER; PRECIPITATION; PARAMETERS; BASINS;
D O I
10.1016/j.jhydrol.2016.04.054
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Flash flooding is one of the most common natural hazards in China, particularly in mountainous areas, and usually causes heavy damage and casualties. However, the forecasting of flash flooding in mountainous regions remains challenging because of the short response time and limited monitoring capacity. This paper aims to establish a strategy for flash flood warnings in mountainous ungauged catchments across humid, semi-humid and semi-arid regions of China. First, we implement a geomorphology-based hydrological model (GBHM) in four mountainous catchments with drainage areas that ranges from 493 to 1601 km(2). The results show that the GBHM can simulate flash floods appropriately in these four study catchments. We propose a method to determine the rainfall threshold for flood warning by using frequency analysis and binary classification based on long-term GBHM simulations that are forced by historical rainfall data to create a practically easy and straightforward approach for flash flood forecasting in ungauged mountainous catchments with drainage areas from tens to hundreds of square kilometers. The results show that the rainfall threshold value decreases significantly with increasing antecedent soil moisture in humid regions, while this value decreases slightly with increasing soil moisture in semi humid and semi-arid regions. We also find that accumulative rainfall over a certain time span (or rainfall over a long time span) is an appropriate threshold for flash flood warnings in humid regions because the runoff is dominated by excess saturation. However, the rainfall intensity (or rainfall over a short time span) is more suitable in semi-humid and semi-arid regions because excess infiltration dominates the runoff in these regions. We conduct a comprehensive evaluation of the rainfall threshold and find that the proposed method produces reasonably accurate flash flood warnings in the study catchments. An evaluation of the performance at uncalibrated interior points in the four gauged catchments provides results that are indicative of the expected performance at ungauged locations. We also find that insufficient historical data lengths (13 years with a 5-year flood return period in this study) may introduce uncertainty in the estimation of the flood/rainfall threshold because of the small number of flood events that are used in binary classification. A data sample that contains enough flood events (10 events suggested in the present study) that exceed the threshold value is necessary to obtain acceptable results from binary classification. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:371 / 386
页数:16
相关论文
共 50 条
  • [31] Hydrological evaluation of hourly merged satellite-station precipitation product in the mountainous basin of China using a distributed hydrological model
    Zhu, Dehua
    Wang, Gaoxu
    Ren, Qiwei
    Ilyas, Abro M.
    METEOROLOGICAL APPLICATIONS, 2020, 27 (02)
  • [32] Impact of radar-rainfall error structure on estimated flood magnitude across scales: An investigation based on a parsimonious distributed hydrological model
    Cunha, Luciana K.
    Mandapaka, Pradeep V.
    Krajewski, Witold F.
    Mantilla, Ricardo
    Bradley, Allen A.
    WATER RESOURCES RESEARCH, 2012, 48
  • [33] Coupling between weather radar rainfall data and a distributed hydrological model for real-time flood forecasting
    Zhijia, Li
    Wenzhong, Ge
    Jintao, Liu
    Kun, Zhao
    Hydrological Sciences Journal, 2004, 49 (06) : 945 - 958
  • [34] Coupling between weather radar rainfall data and a distributed hydrological model for real-time flood forecasting
    Li, ZJ
    Ge, WZ
    Liu, JT
    Zhao, K
    HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2004, 49 (06): : 945 - 958
  • [35] An agent-based model to simulate human responses to flash flood warnings for improving evacuation performance
    Zhang, Ruikang
    Liu, Dedi
    Du, Erhu
    Xiong, Lihua
    Chen, Jie
    Chen, Hua
    JOURNAL OF HYDROLOGY, 2024, 628
  • [36] DESIGN AND APPLICATION OF FLOOD CONTROL MONITORING AND WARNING SYSTEM BASED ON DISTRIBUTED HYDROLOGICAL MODEL
    Yao, Chenchen
    Tang, Junlong
    Liu, Jinhua
    Zhang, Leilei
    FRESENIUS ENVIRONMENTAL BULLETIN, 2021, 30 (06): : 5808 - 5815
  • [37] Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China
    Haigen Zhao
    Shengtian Yang
    Zhiwei Wang
    Xu Zhou
    Ya Luo
    Linna Wu
    Journal of Geographical Sciences, 2015, 25 : 177 - 195
  • [38] Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China
    Zhao Haigen
    Yang Shengtian
    Wang Zhiwei
    Zhou Xu
    Luo Ya
    Wu Linna
    JOURNAL OF GEOGRAPHICAL SCIENCES, 2015, 25 (02) : 177 - 195
  • [39] Flash flood in the mountainous region of Rio de Janeiro state (Brazil) in 2011: part I—calibration watershed through hydrological SMAP model
    Marianna Rodrigues Gullo Cavalcante
    Priscila da Cunha Luz Barcellos
    Marcio Cataldi
    Natural Hazards, 2020, 102 : 1117 - 1134
  • [40] A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
    Li, Ji
    Yuan, Daoxian
    Zhang, Fuxi
    Liu, Jiao
    Ma, Mingguo
    GEOSCIENTIFIC MODEL DEVELOPMENT, 2022, 15 (17) : 6581 - 6600