Multi-objective Calibration with Predictive Uncertainty Analysis for Conceptual Hydrological Models

CHEN Jiong-feng; ZHANG Wan-chang; WU Bo

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Multi-objective Calibration with Predictive Uncertainty Analysis for Conceptual Hydrological Models

- Multi-objective Calibration with Predictive Uncertainty Analysis for Conceptual Hydrological Models
- Bulletin of Soiland Water Conservation Vol. 27, Issue 3, Pages: 107-112(2008)
- 作者机构：
  
  1. 南京大学国际地球系统科学研究所,江苏,南京,210093
  2. 南京大学地理与海洋科学学院,江苏,南京,210093
  3. 中国科学院大气物理所东亚区域气候—环境重点实验室全球变化东亚区域研究中心,北京,100029
- 作者简介：
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- Published：2008
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CHEN Jiong-feng, ZHANG Wan-chang, WU Bo. Multi-objective Calibration with Predictive Uncertainty Analysis for Conceptual Hydrological Models[J]. Bulletin of Soiland Water Conservation, 2008, 27(3): 107-112.
DOI：

CHEN Jiong-feng, ZHANG Wan-chang, WU Bo. Multi-objective Calibration with Predictive Uncertainty Analysis for Conceptual Hydrological Models[J]. Bulletin of Soiland Water Conservation, 2008, 27(3): 107-112. DOI：

摘要

参数识别是水文模型应用的前提

在参数识别的同时需要充分考虑模型自身及参数的不确定性。引入了一种具有较强全局与局部搜索能力的多目标优化算法(MOCOM—UA)

探讨了该算法在多目标基础上融合遗传算法和单纯形法两类算法不同搜索机制的模型优化方案

并以汉江上游江口流域新安江模型降水—径流模拟实践为例

将MOCOM—UA算法应用于新安江模型的参数识别

得到了4目标函数情形下的Pareto参数空间和模型的预测范围

并根据该算法模拟计算的结果

初步分析了参数和模型的不确定性。

Abstract

Parameter determination is the prerequisite for the simulation of rainfall and runoff in a hydrological model.Model and parameter uncertainty should be considered during that procedure.This paper started with an introduction of the theory on the multi-objective complex evolution(MOCOM-UA) algorithm of excellent global and local optimization capability for dealing with the complex problem of hydrological model calibration.Based on the Xin'anjiang model

different searching mechanisms between the multi-objective approach based method and genetic and simplex algorithm were respectively discussed by rainfall-runoff simulations for the Baohe watershed in the upper reaches of the Hanjiang River basin.With the application of the multi-objective genetic algorithm coupled with the simplex method as an optimal solution

the Pareto space of parameters and the prediction extent of the model were calculated and analyzed under four objective function conditions.The uncertainties of the model and its parameters were preliminarily investigated.

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