Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2016WR019141 |
Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error | |
Christensen, N. K.1; Minsley, B. J.2; Christensen, S.1 | |
2017-02-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:2 |
文章类型 | Article |
语种 | 英语 |
国家 | Denmark; USA |
英文摘要 | We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability. |
英文关键词 | groundwater modeling prediction uncertainty geological structural uncertainty AEM data stochastic geological models |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000398568800003 |
WOS关键词 | HYDRAULIC CONDUCTIVITY ; GEOPHYSICAL-DATA ; BOREHOLE DATA ; BAYESIAN-APPROACH ; TEM DATA ; INVERSION ; FLOW ; UNCERTAINTY ; SIMULATION ; TRANSIENT |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/22044 |
专题 | 资源环境科学 |
作者单位 | 1.Aarhus Univ, Dept Geosci, Aarhus, Denmark; 2.US Geol Survey, Crustal Geophys & Geochem Sci Ctr, Box 25046, Denver, CO 80225 USA |
推荐引用方式 GB/T 7714 | Christensen, N. K.,Minsley, B. J.,Christensen, S.. Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error[J]. WATER RESOURCES RESEARCH,2017,53(2). |
APA | Christensen, N. K.,Minsley, B. J.,&Christensen, S..(2017).Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error.WATER RESOURCES RESEARCH,53(2). |
MLA | Christensen, N. K.,et al."Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error".WATER RESOURCES RESEARCH 53.2(2017). |
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