Flood prediction using parameters calibrated on limited discharge data and uncertain rainfall scenarios
نویسندگان
چکیده
منابع مشابه
Urban flood prediction in real-time from weather radar and rainfall data using artificial neural networks
This paper describes the application of Artificial Neural Networks (ANNs) as Data Driven Models (DDMs) to predict urban flooding in real-time based on weather radar and/or raingauge rainfall data. A 123manhole combined sewer sub-network from Keighley, West Yorkshire, UK is used to demonstrate the methodology. An ANN is configured for prediction of flooding at manholes based on rainfall input. I...
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Corresponding Author: Soo See Chai Department of Software Engineering and Computing, Faculty of Computer Science and Information Technology, University of Malaysia Sarawak (UNIMAS), 94300, Kota Samarahan, Sarawak, Malaysia Email: [email protected] Abstract: Rainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility...
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متن کاملFlood Hydrograph Simulation with Uncertainty in Rainfall - Runoff Parameters
Flood hydrograph simulation is affected by uncertainty in Rainfall – Runoff )RR( parameters. Uncertainty of RR parameters in Gharasoo catchment, part of the great Karkheh river basin, is evaluated by Monte–Carlo (MC) approach. A conceptual-distributed model, called ModClark, was used for basin simulation, in which the basin’s hydrograph was determined using the superposition of runoff generated...
متن کاملFlood Hydrograph Simulation with Uncertainty in Rainfall - Runoff Parameters
Flood hydrograph simulation is affected by uncertainty in Rainfall – Runoff )RR( parameters. Uncertainty of RR parameters in Gharasoo catchment, part of the great Karkheh river basin, is evaluated by Monte–Carlo (MC) approach. A conceptual-distributed model, called ModClark, was used for basin simulation, in which the basin’s hydrograph was determined using the superposition of runoff generated...
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ژورنال
عنوان ژورنال: Hydrological Sciences Journal
سال: 2020
ISSN: 0262-6667,2150-3435
DOI: 10.1080/02626667.2020.1747619