ABSTRACT
Good water quality is considered as a vital component for sustainable development of a nation. The water quality is being affected by anthropogenic activities, in the form of point and diffuses sources of pollution. Water quality monitoring is the collection of quantitative and representative spatiotemporal information of physical, chemical, and biological characteristics of a water body. The initial water quality monitoring program was started in the early 1960s, with the purpose of describing the state of water quality. The design of water quality monitoring network (WQMN) is a crucial task of the monitoring program, which consists of: determination of the number and spatial distribution of monitoring stations, selection of a sampling frequency, and selection of water quality parameters to be monitored. The Bayesian Maximum Entropy (BME) method of geostatistics proposes integration of water quality monitoring data with model predictions to provide improved estimates of water quality in a cost-effective manner.
