Flood frequency prediction for data limited catchments in the Czech Republic using a stochastic rainfall model and TOPMODEL

被引:92
|
作者
Blazkova, S [1 ]
Beven, K [1 ]
机构
[1] UNIV LANCASTER,CTR RES ENVIRONM SYST & STAT,IEBS,LANCASTER LA1 4YQ,ENGLAND
关键词
D O I
10.1016/S0022-1694(96)03238-6
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A continuing problem in hydrology is the estimation of peak discharges for design purposes on catchments with only limited available data. A promising and elegant approach to this problem is the derived hood frequency curve pioneered by Eagleson (1972, Water Resour. Res., 8(4): 878-898). A number of studies using this approach have been published over the last 20 years but only a few have compared the predicted curves with observations. One exception used a simple stochastic rainfall model to drive a version of TOPMODEL (Beven, 1987, Earth Surf. Processes Landforms, 12: 69-82). The present study describes a new version of the stochastic rainfall simulator previously used with TOPMODEL and its application on three small catchments (1.87, 4.75 and 25.81 km(2)) in the Jizera Mountains in the Czech Republic. The rainfall model differentiates between high and low intensity events. The resulting rainfall statistics were checked by comparisons with measured data. The flood frequency curves predicted by the combined model were constrained by the regional estimates or a measured series for short return periods and used to predict longer return period flood magnitudes. Only one TOPMODEL parameter has to be adjusted-an effective average transmissivity. For the two smaller catchments also a rainfall parameter has to be adjusted depending on the size of the catchment, It is shown that the random sequence of rainstorms can have a significant effect on the predicted 100 year return period event, even for 1000 year simulations and without allowing for uncertainty in the rainfall model parameters.
引用
收藏
页码:256 / 278
页数:23
相关论文
共 50 条
  • [41] Analysis of the effect of rainfall and streamflow data quality and catchment dynamics on streamflow prediction using the rainfall-runoff model IHACRES
    Ctr. for Rsrc. and Environ. Studies, Australian National University, Canberra, ACT, Australia
    不详
    Environ Software, 1-3 (193-202):
  • [42] RETRACTED: Prediction of High-Frequency Economic Data Based on Stochastic Fluctuation Model (Retracted Article)
    Zhang, Xiaoyang
    Qi, Tianxiang
    Kim, Dong-Joo
    SECURITY AND COMMUNICATION NETWORKS, 2022, 2022
  • [43] Enhancing transparency in data-driven urban pluvial flood prediction using an explainable CNN model
    Gao, Weizhi
    Liao, Yaoxing
    Chen, Yuhong
    Lai, Chengguang
    He, Sijing
    Wang, Zhaoli
    JOURNAL OF HYDROLOGY, 2024, 645
  • [44] FLOOD SUSCEPTIBILITY ANALYSIS USING FREELY AVAILABLE DATA, GIS, AND FREQUENCY RATIO MODEL FOR NAGPUR, INDIA
    Gaurkhede, N. T.
    Adane, V. S.
    APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2023, 21 (03): : 2341 - 2361
  • [45] Neuro-Fuzzy Model for Quantified Rainfall Prediction Using Data Mining and Soft Computing Approaches
    Vathsala, H.
    Koolagudi, Shashidhar G.
    IETE JOURNAL OF RESEARCH, 2023, 69 (06) : 3357 - 3367
  • [46] Distributed parameter hydrology model (ANSWERS) applied to a range of catchment scales using rainfall simulator data II: application to spatially uniform catchments
    Connolly, R.D.
    Silburn, D.M.
    Journal of Hydrology, 1995, 172 (1-4):
  • [47] Frequency, Damping, and Flutter Prediction from Aircraft Flight Data Using Autoregressive Model
    Sudha, U. P., V
    Deodhare, Girish S.
    Venkatraman, Kartik
    JOURNAL OF AIRCRAFT, 2018, 55 (06): : 2179 - 2190
  • [48] Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data
    Liu, Wenting
    Gui, Zhaozhong
    Jiang, Guilin
    Tang, Lihua
    Zhou, Lichun
    Leng, Wan
    Zhang, Xulong
    Liu, Yujiang
    WEB AND BIG DATA, PT II, APWEB-WAIM 2023, 2024, 14332 : 74 - 88
  • [49] Regional flood frequency analysis using data-driven models (M5, random forest, and ANFIS) and a multivariate regression method in ungauged catchments
    Esmaeili-Gisavandani, Hassan
    Zarei, Heidar
    Fadaei Tehrani, Mohammad Reza
    APPLIED WATER SCIENCE, 2023, 13 (06)
  • [50] Short-term traffic flow prediction using seasonal ARIMA model with limited input data
    S. Vasantha Kumar
    Lelitha Vanajakshi
    European Transport Research Review, 2015, 7