Estimation of River High Flow Discharges Using Friction-Slope Method and Hybrid Models

Accurately estimating river water flow during floods is crucial to water resource management, dam reservoir operation, and flood mitigation strategies. Although hydrological models for flood prediction have improved, they still face constraints and make inaccurate forecasts. Hydraulic models face un...

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Veröffentlicht in:Water resources management 2024-02, Vol.38 (3), p.1099-1123
Hauptverfasser: Shirazi, Fatemeh, Zahiri, Abdolreza, Piri, Jamshid, Dehghani, Amir Ahmad
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container_issue 3
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creator Shirazi, Fatemeh
Zahiri, Abdolreza
Piri, Jamshid
Dehghani, Amir Ahmad
description Accurately estimating river water flow during floods is crucial to water resource management, dam reservoir operation, and flood mitigation strategies. Although hydrological models for flood prediction have improved, they still face constraints and make inaccurate forecasts. Hydraulic models face uncertainties related to riverbed Manning roughness coefficient and energy slope. This study employs a novel Friction-Slope (α parameter) method to estimate flood discharge. Investigation focuses on three alluvial rivers in Golestan, Iran. The computation method uses the Manning formula and accounts for river energy slope and riverbed Manning roughness coefficient. The α parameter is calculated using easy-to-access river cross-section variables: flow depth, area, and hydraulic radius. SVR-PSO, SVR-GWO, and SVR-RSM hybrid methods are used to achieve this. Calculated river flow discharges are compared to measured data. Statistical evaluation criteria like R 2 , MAE, RMSE, and conformity index determined the hybrid models' optimal structures. The SVR-RSM model had the highest accuracy during testing, with an R 2 value of 0.97, MAE of 0.22, RMSE of 1.66, and d of 0.99. Once the α parameter was determined using the RSM-SVR model, river flow discharges were calculated and compared to observed values. The testing phase produced the most accurate results, with R 2  = 0.88, MAE = 0.15, RMSE = 0.41, and d = 0.98.
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The SVR-RSM model had the highest accuracy during testing, with an R 2 value of 0.97, MAE of 0.22, RMSE of 1.66, and d of 0.99. Once the α parameter was determined using the RSM-SVR model, river flow discharges were calculated and compared to observed values. 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subjects Alluvial rivers
Atmospheric Sciences
Civil Engineering
Computation
Constraint modelling
Discharge
Earth and Environmental Science
Earth Sciences
energy
Environment
Estimation
face
flood control
Flood discharge
Flood forecasting
Flood management
Flood predictions
Floods
Friction
Geotechnical Engineering & Applied Earth Sciences
High flow
hybrids
Hydraulic models
Hydraulic radius
Hydrogeology
Hydrologic models
Hydrology/Water Resources
Iran
Mitigation
Parameters
prediction
Reservoir operation
Resource management
River beds
River flow
River water
Riverbeds
Rivers
Roughness
Roughness coefficient
Slope
stream channels
Stream flow
Water depth
Water flow
Water resources
Water resources management
title Estimation of River High Flow Discharges Using Friction-Slope Method and Hybrid Models
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