Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2017WR021857 |
Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model | |
Mustafa, Syed Md. Touhidul1; Nossent, Jiri1,2; Ghysels, Gert1; Huysmans, Marijke1 | |
2018-09-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:9页码:6585-6608 |
文章类型 | Article |
语种 | 英语 |
国家 | Belgium |
英文摘要 | We present a general and flexible Bayesian approach using uncertainty multipliers to simultaneously analyze the input and parameter uncertainty of a groundwater flow model with consideration of the heteroscedasticity of the groundwater level error. Groundwater recharge and groundwater abstraction multipliers are introduced to quantify the uncertainty of the spatially distributed input data of the groundwater model in addition to parameter uncertainty. The heteroscedasticity of the groundwater level error is also considered in our Bayesian approach by incorporating a new heteroscedastic error model. The proposed methodology is applied in an overexploited aquifer in Bangladesh where groundwater abstraction and recharge data are highly uncertain. The results of the study confirm that consideration of recharge and abstraction uncertainty through the use of recharge and abstraction multipliers is feasible even in a fully distributed physically based groundwater flow model. Heteroscedasticity is present in the groundwater level error and has an effect on the model predictions and parameter distributions. The input uncertainty affects the model predictions and parameter distributions and it is the dominant source of uncertainty in the groundwater flow prediction. Additionally, the approach described also provides a new way to optimize the spatially distributed recharge and abstraction data along with the parameter values under uncertain input conditions. We conclude that considering model input uncertainty along with parameter uncertainty and heteroscedasticity of the groundwater level error is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds. |
英文关键词 | input uncertainty groundwater flow model fully distributed Bayesian approach heteroscedasticity uncertainty quantification |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000448088100042 |
WOS关键词 | MONTE-CARLO-SIMULATION ; NUMERICAL-MODELS ; CALIBRATION ; EVOLUTION ; AQUIFERS ; YIELD ; BASIN |
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/20836 |
专题 | 资源环境科学 |
作者单位 | 1.Vrije Univ Brussel, Dept Hydrol & Hydraul Engn, Brussels, Belgium; 2.Flemish Govt, Flanders Hydraul Res, Dept Mobil & Publ Works, Antwerp, Belgium |
推荐引用方式 GB/T 7714 | Mustafa, Syed Md. Touhidul,Nossent, Jiri,Ghysels, Gert,et al. Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model[J]. WATER RESOURCES RESEARCH,2018,54(9):6585-6608. |
APA | Mustafa, Syed Md. Touhidul,Nossent, Jiri,Ghysels, Gert,&Huysmans, Marijke.(2018).Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model.WATER RESOURCES RESEARCH,54(9),6585-6608. |
MLA | Mustafa, Syed Md. Touhidul,et al."Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model".WATER RESOURCES RESEARCH 54.9(2018):6585-6608. |
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