Surface water quality management for drinking use in El-Beheira Governorate, Egypt

This research was initiated to assess and manage water quality status of fourteen surface drinking water intakes in El-Beheira Governorate, Egypt. The study was conducted on four main branches of water resources in the governorate. Three water quality indices (WQIs) and two multivariate statistical techniques were applied, based on the Egyptian guidelines for the Nile River. Water quality records were collected for two successive years, 2014 and 2015, and were analyzed by descriptive statistics. The results revealed the critical water quality status of the four branches at the fourteen intakes. The multivariate statistical techniques returned the critical water quality conditions to the agricultural drainage and the domestic wastewater discharges. In addition, a new software application was developed to manage WQIs calculation. An urgent water quality monitoring and assessment system should be initiated for the drinking water resources all over Egypt, based on the developed water quality assessment techniques of this study. PRACTITIONER POINTS: Three different WQIs and two different statistics tools were applied. Critical water quality status for the investigated surface drinking water intakes was reported. Agricultural drainage then domestic effluents are the main pollution sources. A new software application was developed to calculate WQIs to support decision makers.

Designing the National Network for Automatic Monitoring of Water Quality Parameters in Greece

Water quality indices that describe the status of water are commonly used in freshwater vulnerability assessment. The design of river water quality monitoring programs has always been a complex process and despite the numerous methodologies employed by experts, there is still no generally accepted, holistic and practical approach to support all the phases and elements related. Here, a Geographical Information System (GIS)-based multicriteria decision analysis approach was adopted so as to contribute to the design of the national network for monitoring of water quality parameters in Greece that will additionally fulfill the urgent needs for an operational, real-time monitoring of the water resources. During this cost-effective and easily applied procedure the high priority areas were defined by taking into consideration the most important conditioning factors that impose pressures on rivers and the special conditions that increase the need for monitoring locally. The areas of increased need for automatic monitoring of water quality parameters are highlighted and the output map is validated. The sites in high priority areas are proposed for the installation of automatic monitoring stations and the installation and maintenance budget is presented. Finally, the proposed network is contrasted with the current automatic monitoring network in Greece.

A cost-effective and efficient framework to determine water quality monitoring network locations

A crucial part in designing a robust water quality monitoring network is the selection of appropriate water quality sampling locations. Due to cost and time constraints, it is essential to identify and select these locations in an accurate and efficient manner. The main contribution of the present article is the development of a practical methodology for allocating critical sampling points in present and future conditions of the non-point sources under a case study of the Khoy watershed in northwest Iran, where financial resources and water quality data are limited. To achieve this purpose, the river mixing length method (RML) was applied to propose potential sampling points. A new non-point source potential pollution score (NPPS) was then proposed by the analytic network process (ANP) to classify the importance of each sampling point prior to selecting the most appropriate locations for a river system. In addition, an integrated cellular automata-Markov chain model (CA-Markov) was applied to simulate future change in non-point sources during the period 2026-2036. Finally, by considering anthropogenic activities through land-use mapping, the hierarchy value, the non-point source potential pollution score values and budget deficiency in the study area, the seven sampling points were identified for the present and the future. It is not expected, however, that the present location of the proposed sampling points will change in the future due to the forthcoming changes in non-point sources. The current study provides important insights into the design of a reliable water quality monitoring network with a high level of assurance under certain changes in non-point sources. Furthermore, the results of this study should be valuable for water quality monitoring agencies looking for a cost-effective approach for selecting sampling locations.

Water quality monitoring strategies - A review and future perspectives

The reliable assessment of water quality through water quality monitoring programs (WQMPs) is crucial in order for decision-makers to understand, interpret and use this information in support of their management activities aiming at protecting the resource. The challenge of water quality monitoring has been widely addressed in the literature since the 1940s. However, there is still no generally accepted, holistic and practical strategy to support all phases of WQMPs. The purpose of this paper is to report on the use cases a watershed manager has to address to plan or optimize a WQMP from the challenge of identifying monitoring objectives; selecting sampling sites and water quality parameters; identifying sampling frequencies; considering logistics and resources to the implementation of actions based on information acquired through the WQMP. An inventory and critique of the information, approaches and tools placed at the disposal of watershed managers was proposed to evaluate how the existing information could be integrated in a holistic, user-friendly and evolvable solution. Given the differences in regulatory requirements, water quality standards, geographical and geological differences, land-use variations, and other site specificities, a one-in-all solution is not possible. However, we advance that an intelligent decision support system (IDSS) based on expert knowledge that integrates existing approaches and past research can guide a watershed manager through the process according to his/her site-specific requirements. It is also necessary to tap into local knowledge and to identify the knowledge needs of all the stakeholders through participative approaches based on geographical information systems and adaptive survey-based questionnaires. We believe that future research should focus on developing such participative approaches and further investigate the benefits of IDSS's that can be updated quickly and make it possible for a watershed manager to obtain a timely, holistic view and support for every aspect of planning and optimizing a WQMP.

Combining multivariate statistics and analysis of variance to redesign a water quality monitoring network

The objective of this paper was to demonstrate how multivariate statistics combined with the analysis of variance could support decision-making during the process of redesigning a water quality monitoring network with highly heterogeneous datasets in terms of time and space. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were selected to optimise the selection of water quality parameters to be monitored as well as the number and location of monitoring stations. Sampling frequency was specifically investigated through the analysis of variance. The data used were obtained between 2007 and 2010 at the Long-term Environmental Research Monitoring and Testing System (OPE) located in the north-eastern part of France in relation with a geological disposal of radioactive waste project. PCA results showed that no substantial reduction among the parameters was possible as strong correlation only exists between electrical conductivity, calcium or bicarbonates. HCA results were geospatially represented for each field campaign and compared to one another in terms of similarities and differences allowing us to group the monitoring stations into 12 categories. This approach enabled us to take into account not only the spatial variability of water quality but also its temporal variability. Finally, the analysis of variances showed that three very different behaviours occurred: parameters with high temporal variability and low spatial variability (e.g. suspended matter), parameters with high spatial variability and average temporal variability (e.g. calcium) and finally parameters with both high temporal and spatial variability (e.g. nitrate).

Coupling geostatistical approaches with PCA and fuzzy optimal model (FOM) for the integrated assessment of sampling locations of water quality monitoring networks (WQMNs)

The assessment of the adequacy of sampling locations is an important aspect in the validation of an effective and efficient water quality monitoring network. Two geostatistical approaches (e.g., kriging and Moran's I) are presented to assess multiple sampling locations. A flexible and comprehensive framework was developed for the selection of multiple sampling locations of multiple variables which was accomplished by coupling geostatistical approaches with principal component analysis (PCA) and fuzzy optimal model (FOM). The FOM was used in the integrated assessment of both multiple principal components and multiple geostatistical approaches. These integrated methods were successfully applied to the assessment of two independent water quality monitoring networks (WQMNs) of Lake Winnipeg, Canada, which respectively included 14 and 30 stations from 2006 to 2010.