Research on Combination Forecast Mode of Conceptual Hydrological Model

The calibration and selection of conceptual hydrological model parameters is an important but complex task in runoff forecasting. In order to solve the calibration of conceptual hydrological model parameters, a multi-objective cultural self-adaptive electromagnetism-like mechanism algorithm (MOCSEM)...

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Veröffentlicht in:Water resources management 2016-10, Vol.30 (13), p.4483-4499
Hauptverfasser: Dai, Minglong, Zhou, Jianzhong, Liao, Xiang
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container_title Water resources management
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creator Dai, Minglong
Zhou, Jianzhong
Liao, Xiang
description The calibration and selection of conceptual hydrological model parameters is an important but complex task in runoff forecasting. In order to solve the calibration of conceptual hydrological model parameters, a multi-objective cultural self-adaptive electromagnetism-like mechanism algorithm (MOCSEM) is proposed in this paper. The multi-objective parameter calibration method of runoff forecasting avoids the “averaging effect” and considers both large and small runoffs hydrological features. In this paper, the self-identifying parameter combination forecasting method (SPCFM), a universality combination forecast model, is developed innovatively to improve forecasting precision by using the extreme parameters of Pareto optimal solutions. Finally, MOCSEM is combined with SPCFM to calibrate the parameters of forecasting model and forecast runoff of Leaf River. The results indicate that the proposed methods improve forecast accuracy and provide an effective approach to runoff forecast.
doi_str_mv 10.1007/s11269-016-1401-z
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subjects Algorithms
Atmospheric Sciences
Calibration
Civil Engineering
Earth and Environmental Science
Earth Sciences
Electromagnetism
Environment
Forecasting
Freshwater
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrologic cycle
Hydrologic models
Hydrologic sciences
Hydrology
Hydrology models
Hydrology/Water Resources
Mathematical models
Methods
Multiple objective
Optimization
Parameters
Pareto optimum
Precipitation
Rain
Runoff
Runoff forecasting
Studies
Tasks
Water resources
Water resources management
Watersheds
title Research on Combination Forecast Mode of Conceptual Hydrological Model
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