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引用本文:HapuarachchiH.A.P.,李致家,王寿辉.SCE-UA方法在新安江模型参数优化中的应用(英文).湖泊科学,2001,13(4):304-314. DOI:10.18307/20010404
Hapuarachchi H. A. P.,LI Zhijia,WANG Shouhui.Application of SCE-UA Method for Calibrating the Xinanjiang Watershed Model. J. Lake Sci.2001,13(4):304-314. DOI:10.18307/20010404
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SCE-UA方法在新安江模型参数优化中的应用(英文)
HapuarachchiH.A.P., 李致家, 王寿辉
河海大学水文水资源学院, 南京 210008
摘要:
以前在使用新安江模型时人们遇到的最大困难可归因于缺乏有效的参数全局优化的数学方法.事实上对于一个缺乏经验的人来说,模型参数的人工试错计算的过程是一个相当不容易的过程,并且耗时颇多.为此,近些年来研究者们正在探索把概念性水文模型中的专家经验与自动优化计算相结合的方法或者数学优化中的全局优化方法,如SEC UA方法.本文首先简述新安江模型,而后采用3个大小和气候条件各不相同的流域对SCE UA算法就在新安江模型计算的参数优化进行了研究.研究结果表明,SCE UA算法用来进行新安江模型的参数优化所取得的效果是好的.从率定和检验的结果来看,SCE UA算法可以使得率定的新安江模型的参数达到全局最优并且从概念上也合理.
关键词:  新安江模型  概念性模型  模型率定  全局优化  基因算法
DOI:10.18307/20010404
分类号:
基金项目:
Application of SCE-UA Method for Calibrating the Xinanjiang Watershed Model
Hapuarachchi H. A. P., LI Zhijia, WANG Shouhui
College of Water Resources and Environment, Hohai University, Nanjing 210098, P. R. China
Abstract:
The difficulties involved in manually calibrating the Xinanjiang watershed model have in the past been partly attributable to the lack of robust optimization tools. In fact manual calibration process can be a rather frustrating and time-consuming exercise for an inexperienced person. Therefore,in recent years researchers are exploring ways to incorporate "expert knowledge" of conceptual watershed models into the automatic calibration procedures. This paper presents a brief introduction to the Xinanjiang model and a researdiw Tork on application of SCE-UA method for calibrating Xinanjiang watershed model using hydrological data of three catchments of different size and dimatic mnditioiis. Results show that the overall performance of SCE-UA method for calibrating the Xinanjiang model is very good. On the basis of the results derived from the calibration and verification stages it seems that SCE-UA is capable of finding a global optimum and (onceptually realistic parameter set for the Xinanjiang model.
Key words:  Xinanjiang model  conceptual watershed models  model calibration  global optimization  shuffle complex evolution method
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