The current study investigated and compared data generation methods for groundwater modeling. Thesemethods can be divided into two classes; geostatistic and probabilistic. By comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study ...
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The current study investigated and compared data generation methods for groundwater modeling. Thesemethods can be divided into two classes; geostatistic and probabilistic. By comparing geostatistic methods,the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area ina grid (9-cell) format. After observing weak spatial correlation between the data, the probabilistic methodwas then considered. The Monte Carlo technique was used for data generation for the governingdistribution function using the probabilistic method. Finally, the results of the two methods were compared.The ground water model used in this research was PMWIN 5.3 (MODFLOW). This model was used topredict the future state of an aquifer by using the generated data and time series of precipitation. Existinginput data processing, data generation by geostatistic/stochastic methods and representation of modeloutput were performed using ARC/INFO GRID.
