Optimization of Piezometeric wells Number for Groundwater Level Prediction Using Factor Analysis (Case Study: Minab Plain)

The lack of rainfall in arid and semi-arid areas result in the limited availability of surface water resources in these areas, hence water consumption in the agricultural, industrial and drinking industries relies heavily on groundwater. In field surveys, such as sampling from deep wells, determining the critical points for sampling is very important in terms of reducing sample size and saving costs and time. In this paper, the principal component analysis (PCA) and the hierarchical clustering have been used to select the effective wells for measuring the static level of groundwater in the Minab plain in Hormozgan province. For this purpose, 38 piezometric wells were considered and the relative importance of each well was computed using the PCA by allocating the values between 0 and 1. The study showed that by removing the wells with the relative importance less than 0.7, the coefficient of variation of groundwater doesn’t increases significantly compared to the case of using all wells. Based hierarchical cluster analysis, the piezometers were divided well into three clusters, which the 3rd cluster with 12 piezometers is the best representative with the lowest error. Finally, the cluster analysis with the lower error compared to the PCA was used as the criterion of conclusion