Water Quality Monitoring and Network Design

Abstract

Abstract. In recent years, shortcomings of both the available data on water quality and the existing networks have led designers to focus more critically on the design procedures used. Within this respect, this chapter addresses the prevailing problems associated with water quality monitoring networks and discusses current attempts towards improvement of existing networks. IntroductionIn recent years, problems observed in available water quality data and shortcomings of current monitoring networks have led designers and researchers to focus more critically on the design procedures used. Developed countries have feit the need to assess and redesign their monitoring programs after having run their networks for more than 20 years. Developing countries are still in the process of expanding their rather newly initiated networks; yet they also find it necessary to evaluate what they have accomplished so far and how they should proceed from this point on. In both cases of the developed and the developing countries, the major problem is that there are no universally confirmed guidelines to follow in the assessment and design of water quality monitoring networks. Upon this need, significant amount of research has been initiated to evaluate current design procedures and investigate effective means of irnproving the efficiency ofexisting networks (Ward et al., 1990;Chapman, 1992;Adriaanse et al, 1995;Ward, 1996;Timmerman et al. 1996;Niederlander et al., 1996;Dixon and ChisweIl, 1996).At present, the adequacy of collected water quality data and the performance of existing monitoring networks have been seriously evaluated for two basic reasons. First, an efficient information system is required to satisfy the needs of water quality management plans and to aid in the decision making process. Second, this system has to be realized under the constraints of limited financial resources, sampling and analysis facilities, and manpower.Despite all efforts made on monitoring ofwater quality, the current status of existing networks shows that the accruing benefits are low.

Assessment of Informativeness of Groundwater Monitoring in Developing Regions (Gaza Strip Case Study)

“…Economical and water resources data groups (see Table I frequency), determine whether these give enough, redundant or not enough information (adequate, redundant or shortage of information) about the spatial salinity. The main criteria have been used in such studies are transinformation or joint entropy (e.g., Harmancioglu et al, 1999;Mogheir and Singh, 2002;Mogheir et al, 2003a). The assessment stage can indicate whether or not the existing monitoring networks provide adequate information.…”

“…The framework for evaluating the collected data according to the information needs, which are specified according to the objective and tasks, is outlined. Evaluation of these data is based on the entropy theory which measures the information content and the mutual information in a time series of data (e.g., Husain, 1989;Harmancioglu and Alpaslan, 1992;Yang and Burn, 1994). This framework is applied to the data collected from the: (1) groundwater quality monitoring network (Chloride) and (2) groundwater level monitoring network, in the Gaza Strip.…”

Determination of Optimal Water Quality Monitoring Points in Sewer Systems using Entropy Theory

“…Sanders et al [1], Ward et al [2], Harmancioglu et al [3] and Strobl and Robillard [4] produced an overview of the current network design procedures and developed basic guidelines to be followed in both the design and the redesign of water quality monitoring networks. Their studies treat the network design problem in a comprehensive and systematic framework, starting with objectives of monitoring and elaborating on various technical design features, e.g., selection of sampling sites, sampling frequencies, variables to be monitored, and sampling duration.…”

Application of Artificial Neural Networks for the Prediction of Water Quality Variables in the Nile Delta

“…It is a highly complicated issue since there are several variables to choose from in representing surface water quality (e.g. [1]). Several methods are available.…”

“…The results of these studies have shown that information transfer between water quality variables is pretty poor (e.g. [1]). …”