SWMM模型参数全局敏感性分析
|
摘要
为有效评估暴雨管理模型(SWMM)输入参数对水文输出变量的影响程度,识别出敏感参数,为高效率定奠定基础,采用两种全局敏感性分析方法对暴雨管理模型(SWMM)中与降雨产流模拟有关的参数进行全局敏感性分析。基于拉丁超立方法对输入参数进行采样,以某小区为例建立SWMM模型进行模拟,分别采用偏秩相关分析法和互信息法分析参数对输出结果的影响。分析得知:对峰值时间影响最大的参数是管道糙率系数,管道糙率系数和峰值时间呈负相关;对峰值流量影响最大的参数是透水区的糙率系数,透水区糙率系数和峰值时间呈负相关;对总产流量影响最大的参数是管道糙率系数,管道糙率系数和总产流量呈负相关。研究表明偏秩相关分析方法和互信息分析方法都有自己的局限性,将两种方法共同使用,能够精确识别所有敏感参数。
The intentions of this paper were to evaluate the sensitivity of the Storm Water Management Model(SWMM) output to its input parameters and to improve the calibration efficiency of model parameters. Two different methods of global parameter sensitivity analysis were applied in this study,the first one is the partial rank correlation analysis method,the second one is the mutual information analysis method.Partial rank correlation analysis method and mutual information analysis method were used to assess the global sensitivity of the hydrological parameters of storm water management model. The influence of the change of input parameters to its output were analysed by choosing a neighborhood used to build the SWMM model which parameters were sampled by using Latin hypercube sampling method. The results showed that roughness of conduit is the most sensitive parameter to the peak flow,the roughness of conduit shows negative relation with the peak flow.Roughness of pervious area was the most sensitive parameter to the peak time,the roughness of pervious area shows negative relation with the peak time. The roughness of conduit is the most sensitive parameter to the total runoff volume,the roughness of conduit shows negative relation with the total runoff volume.
The intentions of this paper were to evaluate the sensitivity of the Storm Water Management Model(SWMM) output to its input parameters and to improve the calibration efficiency of model parameters. Two different methods of global parameter sensitivity analysis were applied in this study,the first one is the partial rank correlation analysis method,the second one is the mutual information analysis method.Partial rank correlation analysis method and mutual information analysis method were used to assess the global sensitivity of the hydrological parameters of storm water management model. The influence of the change of input parameters to its output were analysed by choosing a neighborhood used to build the SWMM model which parameters were sampled by using Latin hypercube sampling method. The results showed that roughness of conduit is the most sensitive parameter to the peak flow,the roughness of conduit shows negative relation with the peak flow.Roughness of pervious area was the most sensitive parameter to the peak time,the roughness of pervious area shows negative relation with the peak time. The roughness of conduit is the most sensitive parameter to the total runoff volume,the roughness of conduit shows negative relation with the total runoff volume.
引文
[1]官奕宏,吕谋,王灿,等.低影响开发技术的雨洪控制效果及水质影响分析——基于SWMM模型[J].中国农村水利水电,2017,411(1):84-87.
[2]朱嘉祺,徐向阳,何爽.基于LH-OAT的SWMM模型参数敏感性分析[J].中国农村水利水电,2014,377(3):21-26.
[3]宋晓猛,张建云,占车生,等.水文模型参数敏感性分析方法评述[J].水利水电科技进展,2015,35(6):105-112.
[4]ZHOU N,PIERRE J W,TRUDNOWSKI D.A stepwise regression method for estimating dominant electromechanical modes[J].IEEE Transactions on power systems.2012,27(2):1 051-1 059.
[5]王海霞,李昱,周惠成,等.基于Sobol’敏感性分析法的水库多目标调度模型求解质量与效率[J].水电能源科学,2016,34(6):43-47.
[6]任启伟,陈洋波,舒晓娟.基于Extend FAST方法的新安江模型参数全局敏感性分析[J].中山大学学报(自然科学版),2010,49(3):127-134.
[7]王浩昌,杜鹏飞,赵冬泉,等.城市降雨径流模型参数全局灵敏度分析[J].中国环境科学,2008,28(8):725-729.
[8]Chen Y,Wen J,Cheng S.Probabilistic load flow method based on nataf transformation and latin hypercube sampling[J].IEEE Transactions on sustainable energy,2013,4(2):294-301.
[9]曹渊,韩峰,王铁良,等.爆炸容器力学安全的敏感度分析方法[J].科技导报,2013,31(3):28-32.
[10]熊剑智.城市雨洪模型参数敏感性分析与率定[D].济南:山东大学,2016.
[11]侯改娟.绿色建筑与小区低影响开发雨水系统模型研究[D].重庆:重庆大学,2014.
[2]朱嘉祺,徐向阳,何爽.基于LH-OAT的SWMM模型参数敏感性分析[J].中国农村水利水电,2014,377(3):21-26.
[3]宋晓猛,张建云,占车生,等.水文模型参数敏感性分析方法评述[J].水利水电科技进展,2015,35(6):105-112.
[4]ZHOU N,PIERRE J W,TRUDNOWSKI D.A stepwise regression method for estimating dominant electromechanical modes[J].IEEE Transactions on power systems.2012,27(2):1 051-1 059.
[5]王海霞,李昱,周惠成,等.基于Sobol’敏感性分析法的水库多目标调度模型求解质量与效率[J].水电能源科学,2016,34(6):43-47.
[6]任启伟,陈洋波,舒晓娟.基于Extend FAST方法的新安江模型参数全局敏感性分析[J].中山大学学报(自然科学版),2010,49(3):127-134.
[7]王浩昌,杜鹏飞,赵冬泉,等.城市降雨径流模型参数全局灵敏度分析[J].中国环境科学,2008,28(8):725-729.
[8]Chen Y,Wen J,Cheng S.Probabilistic load flow method based on nataf transformation and latin hypercube sampling[J].IEEE Transactions on sustainable energy,2013,4(2):294-301.
[9]曹渊,韩峰,王铁良,等.爆炸容器力学安全的敏感度分析方法[J].科技导报,2013,31(3):28-32.
[10]熊剑智.城市雨洪模型参数敏感性分析与率定[D].济南:山东大学,2016.
[11]侯改娟.绿色建筑与小区低影响开发雨水系统模型研究[D].重庆:重庆大学,2014.