A multi-model approach for long-term runoff modeling using rainfall forecasts

被引：15
|
作者：
Evsukoff, Alexandre G. [1 ]
Cataldi, Marcio [2 ,3 ]
de Lima, Beatriz S. L. P. [1 ]
机构：
[1] Univ Fed Rio de Janeiro, COPPE, BR-21941972 Rio De Janeiro, RJ, Brazil
[2] Univ Fed Fluminense, Dept Engn Agr & Meio Ambiente, Niteroi, RJ, Brazil
[3] ONS, Rio De Janeiro, RJ, Brazil
来源：
EXPERT SYSTEMS WITH APPLICATIONS | 2012年 / 39卷 / 05期
关键词：
Rainfall-runoff model; Catchments; Runoff; Recurrent fuzzy system; Data mining; NEURAL-NETWORKS; GENETIC ALGORITHM; FUZZY; PREDICTION; SCHEME; RIVER; FEEDFORWARD; SYSTEM;
D O I：
10.1016/j.eswa.2011.10.023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This work presents the development of a rainfall-runoff model for the lguacu River basin in the south of Brazil. The model was developed to support the operational planning of hydroelectric power plants and is intended to compute natural flow predictions based on meteorological rain forecasts. A recurrent fuzzy system model was employed, with parameters estimated by a genetic algorithm using observed rainfall as input. This work presents the recurrent fuzzy model within a multi-model approach, where the input data are furnished as an envelope, resulting in a prediction envelope that has demonstrated the ability to produce robust results. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：4938 / 4946
页数：9
相关论文
共 50 条
  • [1] Long-Term Runoff Modeling Using Rainfall Forecasts with Application to the Iguaçu River Basin
    Alexandre Gonçalves Evsukoff
    Beatriz S. L. P. de Lima
    Nelson F. F. Ebecken
    [J]. Water Resources Management, 2011, 25 : 963 - 985
  • [2] Long-Term Runoff Modeling Using Rainfall Forecasts with Application to the Igua‡u River Basin
    Evsukoff, Alexandre Goncalves
    de Lima, Beatriz S. L. P.
    Ebecken, Nelson F. F.
    [J]. WATER RESOURCES MANAGEMENT, 2011, 25 (03) : 963 - 985
  • [3] Enhancing Low-Flow Forecasts: A Multi-Model Approach for Rainfall-Runoff Models
    Andraos, Cynthia
    [J]. HYDROLOGY, 2024, 11 (03)
  • [4] The multi-model approach to rainfall-runoff modelling
    Wyatt, Adam M.
    Franks, Stewart W.
    [J]. PREDICTIONS IN UNGAUGED BASINS: PROMISE AND PROGRESS, 2006, 303 : 134 - +
  • [5] Improvement of Long-Term Run-Off Forecasts Approach Using a Multi-model Based on Wavelet Analysis
    Wang, Xue
    Zhou, Jianzhong
    Deng, Juan
    Guo, Jun
    [J]. APPLIED INFORMATICS AND COMMUNICATION, PT 5, 2011, 228 : 522 - 528
  • [6] Improvement of long-term run-off forecasts approach using a multi-model based on wavelet analysis
    Wang, Xue
    Zhou, Jianzhong
    Deng, Juan
    Guo, Jun
    [J]. 2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL V, 2010, : 323 - 326
  • [7] A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox
    Mojtaba Sadegh
    Amir AghaKouchak
    Alejandro Flores
    Iman Mallakpour
    Mohammad Reza Nikoo
    [J]. Water Resources Management, 2019, 33 : 3011 - 3024
  • [8] A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox
    Sadegh, Mojtaba
    AghaKouchak, Amir
    Flores, Alejandro
    Mallakpour, Iman
    Nikoo, Mohammad Reza
    [J]. WATER RESOURCES MANAGEMENT, 2019, 33 (09) : 3011 - 3024
  • [9] Skill of monthly rainfall forecasts over India using multi-model ensemble schemes
    Kar, Sarat C.
    Acharya, Nachiketa
    Mohanty, U. C.
    Kulkarni, Makarand A.
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2012, 32 (08) : 1271 - 1286
  • [10] Multi-Model Integration for Long-Term Time Series Prediction
    Huang, Zifang
    Shyu, Mei-Ling
    Tien, James M.
    [J]. 2012 IEEE 13TH INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION (IRI), 2012, : 116 - 123
12345