A Window-based tool for design flood estimation using Monte Carlo Simulation Technique

Ataur Rahman, Sk Mazharul Islam

    Research output: Chapter in Book / Conference PaperConference Paper

    Abstract

    ![CDATA[In recent years, there have been notable researches in Australia on a more holistic approach of design flood estimation known as the Joint Probability Approach/Monte Carlo Simulation technique. The principal strength of the Monte Carlo Simulation Technique is that this can consider the probabilistic nature of the major input variables and their correlations to the runoff routing model in a systematic manner. This paper presents a window-based tool that can be used to obtain derived flood frequency curves using the Monte Carlo Simulation Technique, which was developed in the Cooperative Research Centre for Catchment Hydrology. The tool consists of three main modules: rainfall analysis, loss analysis and simulation of streamflow hydrograph. The paper describes the operational procedure of the tool such as necessary inputs, methods of analysis, and interpretation of results. This new tool will make the application of the Monte Carlo Simulation Technique much easier. It is expected that this tool will have a wider application in the professional community for advanced hydrological modelling and research. This tool, at present, is applicable to only small catchments of up to about 200km².]]
    Original languageEnglish
    Title of host publicationProceedings of the 29th Hydrology and Water Resources Symposium: Water Capital, 20-23 February 2005, Rydges Lakeside, Canberra
    PublisherEngineers Australia
    Number of pages5
    ISBN (Print)0858258439
    Publication statusPublished - 2005
    EventHydrology and Water Resources Symposium -
    Duration: 19 Nov 2012 → …

    Conference

    ConferenceHydrology and Water Resources Symposium
    Period19/11/12 → …

    Keywords

    • flood forecasting
    • computer programs
    • hydrologic models
    • joint probability approach
    • Monte Carlo method
    • Australia

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