DRASTIC framework improvement using Stepwise Weight Assessment Ratio Analysis (SWARA) and combination of Genetic Algorithm and Entropy

Environmental Science and Pollution Research - Hybrid and integrated techniques can be used to investigate intrinsic uncertainties of the overlay and index groundwater vulnerability assessment...     

Parametric uncertainty analysis on hydrodynamic coefficients in groundwater numerical models using Monte Carlo method and RPEM

Groundwater resources are the only source of water in many arid and semi-arid regions. It is important to manage these resources to have a sustainable development. However, there are many factors influencing the accuracy of the results in groundwater modeling. In this research, the uncertainty of two important groundwater model parameters (hydraulic conductivity and specific yield) were considered as the main sources of uncertainty in estimating water level in an unconfined aquifer, in Iran. For this purpose, a simple method called Rosenblueth Point Estimate Method (RPEM) was used to assess groundwater modeling parametric uncertainty, and its performance was compared with Monte Carlo method as a very complicated and time-consuming method. According to calibrated values of hydraulic conductivity and specific yield, several uncertainty intervals were considered to analyze uncertainty. The results showed that the optimum interval for hydraulic conductivity was 40% increase–30% decrease of the calibrated values in both Monte Carlo and RPEM methods. This interval for specific yield was 200% increase–90% decrease of the calibrated values. RPEM showed better performance using the evaluating indices in comparison with Monte Carlo method for both hydraulic conductivity and specific yield with 43% and 17% higher index values, respectively. These results can be used in groundwater management and future prediction of groundwater level.