|本期目录/Table of Contents|

[1]骆乾坤,吴剑锋*,杨 运,等. 基于DREAM算法的含水层渗透系数空间变异特征识别[J].南京大学学报(自然科学),2016,52(3):448-455.[doi:10.13232/j.cnki.jnju.2016.03.005]
 Luo Qiankun,Wu Jianfeng*,Yang Yun,et al. Identification of the spatial variability of aquifer hydraulic conductivity[J].Journal of Nanjing University(Natural Sciences),2016,52(3):448-455.[doi:10.13232/j.cnki.jnju.2016.03.005]
点击复制

 基于DREAM算法的含水层渗透系数空间变异特征识别()
     

《南京大学学报(自然科学)》[ISSN:0469-5097/CN:32-1169/N]

卷:
52
期数:
2016年第3期
页码:
448-455
栏目:
复杂地下水系统模拟
出版日期:
2016-06-01

文章信息/Info

Title:
 Identification of the spatial variability of aquifer hydraulic conductivity
作者:
 骆乾坤1吴剑锋2*杨 运23吴吉春2马淑芬4
1.合肥工业大学资源与环境工程学院,合肥,230009;
2.表生地球化学教育部重点实验室, 南京大学地球科学与工程学院水科学系,南京,210023;
3.淮河水利委员会,蚌埠,233001;
4.中石油华北油田公司储气库管理处,任丘,062550
Author(s):
 Luo Qiankun1Wu Jianfeng2*Yang Yun23Wu Jichun2Ma Shufen4
1.School of Resources and Environmental Engineering,Hefei University of Technology,Hefei,230009,China;
2.Key Laboratory of Surficial Geochemistry,Ministry of Education,Department of Hydrosciences,School of Earth Sciences and Engineering,Nanjing University,Nanjing,210023,China;
3.Huai River Water Resources Commission, Bengbu,233001,China;
4.Petrochina Huabei Oilfield Company UGS Management Authority,Renqiu,062550,China
关键词:
 渗透系数空间变异特征噪声遗传算法DREAM
Keywords:
 hydraulic conductivityspatial variabilitynoisy genetic algorithmDREAM
分类号:
P641,X523
DOI:
10.13232/j.cnki.jnju.2016.03.005
文献标志码:
A
摘要:
 采用差分进化自适应Metropolis(DREAM)算法对描述含水层渗透系数空间变异特征的参数进行识别.利用直接傅里叶变换方法产生一组空间结构参数下的若干个渗透系数场实现,借鉴噪声遗传算法(NGA)思想,计算该组空间结构参数对应的贝叶斯后验概率值,提高DREAM算法求解的效率.算例求解结果表明,DREAM算法能够有效获得含水层渗透系数空间结构参数的后验分布,并可得到对应的一系列渗透系数场,可为含水层参数空间变异性研究提供新的思路.
Abstract:
 In this study,it adopted the Differential Evolution Adaptive Metropolis(DREAM)algorithm to identify the spatial structure parameters of the spatial variability of aquifer hydraulic conductivity.The direct Fourier transform method is used to generate a certain number of hydraulic conductivity field realizations under a special set of the spatial structure parameters.Furthermore,the idea of Noisy Genetic Algorithm(NGA)is introduced to calculate the Bayesian posterior probability values,and improve the computational efficiency of the DREAM algorithm.Optimization results of the field application shows that the DREAM algorithm can effectively find the posterior distribution of the spatial structure parameters of the aquifer hydraulic conductivity,and a set of hydraulic conductivity field realizations can be obtained.Therefore,it may provide a novel research idea for identification of the spatial variability of aquifer hydraulic conductivity.

参考文献/References:

 [1] 陈 彦,吴吉春.含水层渗透系数空间变异性对地下水数值模拟的影响.水科学进展,2005,16(4):482-487.(Chen Y,Wu J C.Effect of the spatial variability of hydraulic conductivity in aquifer on the numerical simulation of groundwater.Advances in Water Science,2005,16(4):482-487.)
[2] 施小清,吴吉春,袁永生.渗透系数空间变异性研究.水科学进展,2005,16(2):210-215.(Shi X Q,Wu J C,Yuan Y S.Study on the spatial variability of hydraulic conductivity.Advances in Water Science,2005,16(2):210-215.)
[3] 阎婷婷,吴剑锋.渗透系数的空间变异性对污染物运移的影响研究.水科学进展,2006,17(1):29-36.(Yan T T,Wu J F.Impacts of the spatial variation of hydraulic conductivity on the transport fate of contaminant plume.Advances in Water Science,2006,17(1):29-36.)
[4] 陆 乐,吴吉春,王晶晶.多尺度非均质多孔介质中溶质运移的蒙特卡罗模拟.水科学进展,2008,19(3):333-338.(Lu L,Wu J C,Wang J J.Monte Carlo modeling of solute transport in a porous medium with multi­scale heterogeneity.Advances in Water Science,2008,19(3):333-338.)
[5] Hassan A E,Cushman J H,Delleur J W.A Monte Carlo assessment flow and transport perturbation models.Water Resources Research,1998,34(5):1143-1163.
[6] Sudicky E A.A natural gradient experiment on solute transport in a sand aquifer:spatial variability of hydraulic conductivity and its role in the dispersion process.Water Resources Research,1986,22(13):2069-2082.
[7] 孙蓉琳.玄武岩渗透系数尺度效应及顺序指示模拟.博士学位论文.武汉:中国地质大学,2006.(Sun R L.Scale effects and sequential indicator simulation of hydraulic conductivity in basalt.Ph.D.Dissertation.Wuhan:China University of Geosciences,2006.)
[8] 陆 乐,吴吉春,陈景雅.基于贝叶斯方法的水文地质参数识别.水文地质工程地质,2008,5:58-63.(Lu L,Wu J C,Chen J Y.Identification of hydrogeological parameters based on the Bayesian method.Hydrogeology & Engineering Geology,2008,5:58-63.)
[9] 陆 乐,吴吉春.地下水数值模拟不确定性的贝叶斯分析.水利学报,2010,41(3):264-271.(Lu L,Wu J C.Bayesian analysis of uncertainties in groundwater numerical simulation.Journal of Hydraulic Engineering,2010,41(3):264-271.)
[10] Shi X Q,Ye M,Curtis G P,et al.Assessment of parametric uncertainty for groundwater reactive transport modeling.Water Resources Research,2014,50:4416-4439.
[11] 曹飞凤.基于MCMC方法的概念性流域水文模型参数优选及不确定性研究.博士学位论文.浙江:浙江大学,2010.(Cao F F.Study on parameter optimization and uncertainty analysis for conceptual hydrological model based on MCMC method.Ph.D.Dissertation.Zhejiang:Zhejiang University,2010.)
[12] Vrugt J A,ter Braak C J F,Diks C G H,et al.Accelerating markov chain monte carlo simulation by differential evolution with self­adaptive randomized subspace sampling.International Journal of Nonlinear Sciences and Numerical Simulation,2009,10(3):273-290.
[13] Laloy E,Vrugt J A.High­dimensional posterior exploration of hydrologic models using multipletry DREAM(ZS)and high performance computing.Water Resources Research,2012,48(1):W01526.
[14] Gelman A,Rubin D B.Inference from iterative simulation using multiple sequences.Statistical Science,1992,7:457-472.
[15] Robin M L,Gutjahr A L,Sudicky E A,et al.Crosscorrelated random field generation with the direct Fourier transform method.Water Resources Research,1993,29(7):2385-2397.
[16] Harbaugh A W,McDonald M G.Programmer’s documentation for MODFLOW­96,an update to the U.S.Geological Survey modular finite­difference ground­water flow model:U.S.Geological Survey Open­File Report,1996,96-486.
[17] Miller B L.Noise,sampling,and efficient genetic algorithms.Ph.D.Dissertation.Urbana­Champaign:University of Illinois,1997.
[18] Gopalakrishnan G,Minsker B S,Goldberg D E.Optimal sampling in a noisy genetic algorithm for risk­based remediation design.Journal of Hydroinformatics,2003,128:11-25.
[19] Wu J F,Zheng C M,Chien C C,et al.A comparative study of Monte Carlo simple genetic algorithm and noisy genetic algorithm for cost­effective sampling network design under uncertainty.Advances in Water Resources,2006,29:899-911.
[20] 南统超,吴吉春.集合卡尔曼滤波估计水文地质参数的局域化修正.水科学进展,2010,21(5):613-621.(Nan T C,Wu J C.Localization corrections for the estimation of hydrogeological parameters using ensemble Kalman filter.Advances in Water Science,2010,21(5):613-621.)

相似文献/References:

备注/Memo

备注/Memo:
 国家自然科学基金(41372235,41502226),中央高校基本科研业务费专项资金(J2014HGBZ0186)
更新日期/Last Update: 2016-07-02