基于三维随机水文地质结构模型的地下水流数值模拟: 以西辽河平原为例
|
摘要
为了探究水文地质结构对地下水流数值模拟的不确定性,可以运用随机模拟建立地下水位的预测模型。根据转移概率地质统计方法模拟多孔介质岩性分布,利用非线性规划的思路计算岩性与水文地质参数之间的关系,从而建立相对精确的随机水文地质参数场。将不同的水文地质参数场运用到MODFLOW中,得到不同的随机模拟结果。通过比较随机模型和确定模型的末流场拟合情况以及水位动态拟合图,发现确定模型和随机模型具有相似趋势,都能与实测流场拟合较好,但是随机模型更能体现真实的水文地质特征。对随机模型预测10年后的地下水水位做不确定性分析,得到水位平均变幅介于-5～5 m之间,且95%置信度水位变幅的平均上限线约为0.146 m。研究结果为决策者提供科学依据。
To explore the uncertainty of the hydrogeological structure on the groundwater numerical simulation the West Liaohe Plain,the groundwater level was predicted using stochastic simulation. In this paper,lithologic distribution of porous media was simulated by the transition probability geostatistical method,and the relationship between lithology and hydrogeological parameters were determined by nonlinear programming. The many accurate stochastic hydrogeological parameters obtained were fed into MODFLOW,which generated the stochastic simulation. By comparing the fitting of the groundwater terminal flow field and the water level dynamic process of the stochastic and deterministic models,we found that the stochastic and deterministic models have similar trends,and are well-fitted to the measured data. The stochastic model can better reflect the real hydrogeological characteristics. According to the uncertainty analysis of the predicted groundwater level after 10 years,the average amplitude of the water level variation is ±5 m,and the average upper limit of the 95% confidence level is 0.146 m. This provides a scientific basis for decision makers.
To explore the uncertainty of the hydrogeological structure on the groundwater numerical simulation the West Liaohe Plain,the groundwater level was predicted using stochastic simulation. In this paper,lithologic distribution of porous media was simulated by the transition probability geostatistical method,and the relationship between lithology and hydrogeological parameters were determined by nonlinear programming. The many accurate stochastic hydrogeological parameters obtained were fed into MODFLOW,which generated the stochastic simulation. By comparing the fitting of the groundwater terminal flow field and the water level dynamic process of the stochastic and deterministic models,we found that the stochastic and deterministic models have similar trends,and are well-fitted to the measured data. The stochastic model can better reflect the real hydrogeological characteristics. According to the uncertainty analysis of the predicted groundwater level after 10 years,the average amplitude of the water level variation is ±5 m,and the average upper limit of the 95% confidence level is 0.146 m. This provides a scientific basis for decision makers.
引文
[1]DAGAN G.Stochastic modeling of groundwater-flow by unconditional and conditional probabilities.1.conditional simulation and the direct-problem[J].Water Resources Research,1982,18(4):813-833.
[2]LEFEBVRE D.Design and time parameters identification for nonMarkovian Petri net models:application to reliability analysis[J].Journal of Risk and Reliability,2011,225(1):1-17.
[3]刘猛,束龙仓,刘波.地下水数值模拟中的参数随机模拟[J].水利水电科技进展,2005,25(6):25-27.
[4]陈陆望,何建东,施小平,等.松散承压含水层水文地质参数分区及水流场数值模拟[J].现代地质,2015,29(4):967-974.
[5]HASSAN A E,CUSHMAN J H,DELLEUR J W.A Monte Carlo assessment of Eulerian flow and transport perturbation models[J].Water Resources Research,1998,34(5):1143-1163.
[6]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[J].水科学进展,2005,16(4):482-487.
[7]李军,郝天珧,刘建,等.基于不同邻域系统的马尔可夫链模型的储层岩相随机模拟[J].现代地质,2006,20(4):621-627.
[8]吴飞.产生随机数的几种方法及其应用[J].数值计算与计算机应用,2006(1):48-51.
[9]张博,李国秀,程品,等.基于随机理论的地下水环境风险评价[J].水科学进展,2016,27(1):100-106.
[10]靳萍,邵景力,李长青,等.基于T-PROGS的地下水三维数值模拟及应用[J].水文地质工程地质,2009,36(4):21-26.
[11]马雷.非均质多孔介质多尺度模型及其在地下水模拟中的应用[D].合肥:合肥工业大学,2013:6-9.
[12]何芳,吴吉春.基于马尔可夫链的多元指示地质统计模型[J].水文地质工程地质,2003,30(5):28-32.
[13]HE X,KOCH J,SONNENBORG T O,et al.Transition probability-based stochastic geological modeling using airborne geophysical data and borehole data[J].Water Resources Research,2014,50(4):3147-3169.
[14]KOCH J,HE X,JENSEN K H,et al.Challenges in conditioning a stochastic geological model of a heterogeneous glacial aquifer to a comprehensive soft data set[J].Hydrology and Earth System Sciences,2014,18(8):2907-2923.
[15]REFSGAARD J C,AUKEN E,BAMBERG C A,et al.Nitrate reduction in geologically heterogeneous catchments-A framework for assessing the scale of predictive capability of hydrological models[J].Science of the Total Environment,2014,468:1278-1288.
[16]LEE S,CARLE S F,FOGG G E.Geologic heterogeneity and a comparison of two geostatistical models:Sequential Gaussian and transition probability-based geostatistical simulation[J].Advances in Water Resources,2007,30(9):1914-1932.
[17]董英.基于随机水文地质结构的华北平原地下水流模拟研究[D].北京:中国地质大学(北京),2006:50-67.
[18]ANDERMAN E R,HILL M C.Modflow-2000,The U.S.Geological Survey Modular Ground-Water Model-Documentation of the Hydrogeologic-Unit flow(HUF)Package[M].Denver:U.S.Geological Survey,2000.
[19]李杨,唐仲华,方琼.含水层非均质结构的马尔可夫链地质统计方法及应用[J].地质科技情报,2006,25(5):92-96.
[20]李长青,邵景力,靳萍,等.基于条件模拟技术的平原区水文地质结构三维建模研究[J].工程勘察,2009,37(5):45-48,52.
[21]韩忠.基于MODFLOW建立大区域地下水流模型的程序优化与改进[D].北京:中国地质大学(北京),2014.
[22]陈铁.科学数据图显分析软件Tecplot[J].软件世界,1995(6):28.
[23]王建,白世彪,陈晔.Surfer8地理信息制图[M].北京:中国地图出版社,2004:10-200.
[24]郑春苗.地下水污染物迁移模拟[M].北京:高等教育出版社,2009:21-40.
[25]中国地质调查局.水文地质手册[M].2版.北京:地质出版社,2012:69-94.
[26]韩忠,邵景力,崔亚莉,等.基于MODFLOW的地下水流模型前处理优化[J].吉林大学学报(地球科学版),2014,44(4):1290-1296.
[2]LEFEBVRE D.Design and time parameters identification for nonMarkovian Petri net models:application to reliability analysis[J].Journal of Risk and Reliability,2011,225(1):1-17.
[3]刘猛,束龙仓,刘波.地下水数值模拟中的参数随机模拟[J].水利水电科技进展,2005,25(6):25-27.
[4]陈陆望,何建东,施小平,等.松散承压含水层水文地质参数分区及水流场数值模拟[J].现代地质,2015,29(4):967-974.
[5]HASSAN A E,CUSHMAN J H,DELLEUR J W.A Monte Carlo assessment of Eulerian flow and transport perturbation models[J].Water Resources Research,1998,34(5):1143-1163.
[6]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[J].水科学进展,2005,16(4):482-487.
[7]李军,郝天珧,刘建,等.基于不同邻域系统的马尔可夫链模型的储层岩相随机模拟[J].现代地质,2006,20(4):621-627.
[8]吴飞.产生随机数的几种方法及其应用[J].数值计算与计算机应用,2006(1):48-51.
[9]张博,李国秀,程品,等.基于随机理论的地下水环境风险评价[J].水科学进展,2016,27(1):100-106.
[10]靳萍,邵景力,李长青,等.基于T-PROGS的地下水三维数值模拟及应用[J].水文地质工程地质,2009,36(4):21-26.
[11]马雷.非均质多孔介质多尺度模型及其在地下水模拟中的应用[D].合肥:合肥工业大学,2013:6-9.
[12]何芳,吴吉春.基于马尔可夫链的多元指示地质统计模型[J].水文地质工程地质,2003,30(5):28-32.
[13]HE X,KOCH J,SONNENBORG T O,et al.Transition probability-based stochastic geological modeling using airborne geophysical data and borehole data[J].Water Resources Research,2014,50(4):3147-3169.
[14]KOCH J,HE X,JENSEN K H,et al.Challenges in conditioning a stochastic geological model of a heterogeneous glacial aquifer to a comprehensive soft data set[J].Hydrology and Earth System Sciences,2014,18(8):2907-2923.
[15]REFSGAARD J C,AUKEN E,BAMBERG C A,et al.Nitrate reduction in geologically heterogeneous catchments-A framework for assessing the scale of predictive capability of hydrological models[J].Science of the Total Environment,2014,468:1278-1288.
[16]LEE S,CARLE S F,FOGG G E.Geologic heterogeneity and a comparison of two geostatistical models:Sequential Gaussian and transition probability-based geostatistical simulation[J].Advances in Water Resources,2007,30(9):1914-1932.
[17]董英.基于随机水文地质结构的华北平原地下水流模拟研究[D].北京:中国地质大学(北京),2006:50-67.
[18]ANDERMAN E R,HILL M C.Modflow-2000,The U.S.Geological Survey Modular Ground-Water Model-Documentation of the Hydrogeologic-Unit flow(HUF)Package[M].Denver:U.S.Geological Survey,2000.
[19]李杨,唐仲华,方琼.含水层非均质结构的马尔可夫链地质统计方法及应用[J].地质科技情报,2006,25(5):92-96.
[20]李长青,邵景力,靳萍,等.基于条件模拟技术的平原区水文地质结构三维建模研究[J].工程勘察,2009,37(5):45-48,52.
[21]韩忠.基于MODFLOW建立大区域地下水流模型的程序优化与改进[D].北京:中国地质大学(北京),2014.
[22]陈铁.科学数据图显分析软件Tecplot[J].软件世界,1995(6):28.
[23]王建,白世彪,陈晔.Surfer8地理信息制图[M].北京:中国地图出版社,2004:10-200.
[24]郑春苗.地下水污染物迁移模拟[M].北京:高等教育出版社,2009:21-40.
[25]中国地质调查局.水文地质手册[M].2版.北京:地质出版社,2012:69-94.
[26]韩忠,邵景力,崔亚莉,等.基于MODFLOW的地下水流模型前处理优化[J].吉林大学学报(地球科学版),2014,44(4):1290-1296.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |