One-at-a-time sensitivity analysis of pollutant loadings to subsurface properties for the assessment of soil and groundwater pollution potential

2019 ◽  
Vol 26 (21) ◽  
pp. 21216-21238
Author(s):  
Soonyoung Yu ◽  
Seong-Taek Yun ◽  
Sang-Il Hwang ◽  
Gitak Chae
Keyword(s):  
Sensitivity Analysis ◽  
Groundwater Pollution ◽  
Pollution Potential ◽  
Time Sensitivity

scholarly journals Assessment of Groundwater Pollution Potential of the Datong Basin, Northern China

2010 ◽  
Vol 3 (2) ◽  
Author(s):  
Mamadou SAMAKE ◽  
Zhonghua Tang ◽  
Win Hlaing ◽  
Innocent M’Bue ◽  
Kanyamanda Kasereka
Keyword(s):  
Groundwater Pollution ◽  
Northern China ◽  
Pollution Potential ◽  
Datong Basin

scholarly journals A Simple Time-Varying Sensitivity Analysis (TVSA) for Assessment of Temporal Variability of Hydrological Processes

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2463 ◽  
Author(s):  
Yelena Medina ◽  
Enrique Muñoz
Keyword(s):  
Sensitivity Analysis ◽  
Temporal Variability ◽  
Time Windows ◽  
Computational Cost ◽  
Time Varying ◽  
Moving Window ◽  
Time Sensitivity ◽  
Annual Time ◽  
Low Computational Cost ◽  
High Computational Cost

Time-varying sensitivity analysis (TVSA) allows sensitivity in a moving window to be estimated and the time periods in which the specific components of a model can affect its performance to be identified. However, one of the disadvantages of TVSA is its high computational cost, as it estimates sensitivity in a moving window within an analyzed series, performing a series of repetitive calculations. In this article a function to implement a simple TVSA with a low computational cost using regional sensitivity analysis is presented. As an example of its application, an analysis of hydrological model results in daily, monthly, and annual time windows is carried out. The results show that the model allows the time sensitivity of a model with respect to its parameters to be detected, making it a suitable tool for the assessment of temporal variability of processes in models that include time series analysis. In addition, it is observed that the size of the moving window can influence the estimated sensitivity; therefore, analysis of different time windows is recommended.

scholarly journals Groundwater pollution risk using a modified Latin hypercube sampling

2006 ◽  
Vol 8 (3) ◽  
pp. 223-234 ◽  
Author(s):  
Husam Baalousha
Keyword(s):  
Sensitivity Analysis ◽  
Groundwater Pollution ◽  
Probabilistic Models ◽  
Latin Hypercube Sampling ◽  
Model Parameters ◽  
Latin Hypercube ◽  
Deterministic Models ◽  
Estimation Errors ◽  
Mean Estimation ◽  
Longitudinal Dispersivity

Characterisation of groundwater modelling involves significant uncertainty because of estimation errors of these models and other different sources of uncertainty. Deterministic models do not account for uncertainties in model parameters, and thus lead to doubtful output. The main alternatives for deterministic models are the probabilistic models and perturbation methods such as Monte Carlo Simulation (MCS). Unfortunately, these methods have many drawbacks when applied in risk analysis of groundwater pollution. In this paper, a modified Latin Hypercube Sampling method is presented and used for risk, uncertainty, and sensitivity analysis of groundwater pollution. The obtained results were compared with other sampling methods. Results of the proposed method have shown that it can predict the groundwater contamination risk for all values of probability better than other methods, maintaining the accuracy of mean estimation. Sensitivity analysis results reveal that the contaminant concentration is more sensitive to longitudinal dispersivity than to velocity.

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