Evaluation of ground water monitoring network by principal component analysis

Principal component analysis is a data reduction technique used to identify the important components or factors that explain most of the variance of a system. This technique was extended to evaluating a ground water monitorin g network where the variables are monitoring wells. The objective was to id entify monitoring wells that are important in predicting the dynamic variat ion in potentiometric head at a location. The technique is demonstrated thr ough an application to the monitoring network of the Bangkok area. Principa l component analysis was carried out for all the monitoring wells of the aq uifer, and a ranking scheme based on the frequency of occurrence of a parti cular well as principal well was developed. The decision maker with budget constraints can now opt to monitor principal wells which can adequately cap ture the potentiometric head variation in the aquifer. This was evaluated b y comparing the observed potentiometric head distribution using data from a ll available wells and wells selected using the ranking scheme as a guideli ne.