Sensitivity Analysis and Automatic Calibration of a Rainfall-Runoff Model Using Multi-objectives

被引:0
|
作者
Sun, Fan [1 ]
Liu, Yang [1 ]
机构
[1] Heriot Watt Univ, Sch Management & Language, Edinburgh EH14 4AS, Midlothian, Scotland
关键词
Sensitivity Analysis; Optimisation; Multi-objective Optimisation; Calibration and Validation; MULTIOBJECTIVE GENETIC ALGORITHM; GLOBAL OPTIMIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The practical experience with sensitivity analysis suggests that no single-objective function is adequate to measure the ways in which the model fails to match the important characteristics of the observed data. In order to successfully measure parameter sensitivity of a numerical model, multiple criteria should be considered. Sensitivity analysis of a rainfall-runoff model is performed using the local sensitivity method (Morris method) and multiple objective analysis. Formulation of SA strategy for the MIKE/NAM rainfall-runoff model is outline. The SA is given as a set of Pareto ranks from a multi-objective viewpoint. The Nondominated Sorting Differential Evolution (NSDE) was used to calibrate the rainfall-runoff model. The method has been applied for calibration of a test catchment and compared on validation data. The simulations show that the NSDE method possesses the ability to finding the optimal Pareto front.
引用
收藏
页码:90 / +
页数:2
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