Water quality monitoring (WQM) is crucial for managing and protecting riverine ecosystems. There has been a plethora of methods to select the monitoring sites, water quality parameters (WQPs), and monitoring frequencies; however, no standard method or strategy has been accepted for the river systems. Water managers have faced difficulties in adopting appropriate WQM network design methods to their local boundary conditions, monitoring objectives, monitoring costs, and legal regulations. With the elevated cost and time consumption of monitoring, approaches to evaluate and redesign the monitoring networks based on monitoring goal achievements are crucial for water managers. Hence, the overall aim of this thesis is to develop and employ a reliable yet straightforward approach to optimise and quantify the effectiveness of the WQM network in rivers. The objectives are to (i) identify the commonly used methods and the boundary conditions to apply these methods in assessing and designing of WQM networks in rivers; (ii) optimise river WQM network design based on compliance criteria; (iii) optimise river WQM network design based on the trade-offs between information provided by the monitoring network versus the monitoring expenses.
A systematic review of the commonly used design methods and their resulting monitoring setups in Chapter 2 shows that multivariate statistical analysis (MVA) is a promising tool to contract the number of monitoring sites and water quality parameters. Most of the reported studies often overlook small streams and trace pollutants such as heavy metals and organic microcontaminants in the analysis. Data availability and expertise’s judgments seem to affect the selection of design methods rather than river size and the extent of the monitoring networks.
The commonly found statistical methods are applied to the case study of the Freiberger Mulde (FM) river basin in eastern Germany to optimise its current monitoring network. Chapter 3 dedicates to redesign the monitoring network for compliance monitoring purposes. In Chapter 3, 82 non-biological parameters are initially screened and analysed for their violations to the environmental quality standards. The subsequent result suggests that polycyclic aromatic hydrocarbons, heavy metals, and phosphorus have been the abundant stressors that caused more than 50% of the streams in the FM river basin failing to achieve good status. The proposed approach using hierarchical cluster analysis and weighted violation factor from 22 relevant WQPs allows a reduction of 42 monitoring sites from the current 158 sites. The Mann-Kendall trend test recommends an increase in monitoring frequency of the priority substances by 12 times per annual, and a decrease in the number of sampling events for metals and general physicochemical parameters by quarterly. Overall, the results suggest that the authorities of the Saxony region should develop proper management measures targeting heavy metals and organic micropollutants to be able to achieve good WQ status by 2027 at the latest.
In Chapter 4, regularly monitoring parameters with less than 15% of censored data are analysed. A combination of principal component analysis and Pearson’s correlation analysis allows the identification of 14 critical parameters that are responsible for explaining 75.1% of data variability in the FM river basin. Weathering processes, historical mining, wastewater discharges, and seasonality have been the leading causes of water quality variability. Both sampling locations and periods are observed, with the resulting mineral contents vary between locations, and the organic and oxygen content differs depending on the time period that was monitored. The monitoring costs are estimated for one monitoring event and based on laboratory, transportation, and sampling costs. The results show that under the current monitoring-intense conditions, preserving monitoring variables rather than sites seems to be more economical than the opposite practice.
The current study provides and employs two statistical approaches to optimise the WQM network for the FM river basin in eastern Germany. The proposed methods can be of interests to other river basins where the historical data are available, and the monitoring costs become a constraint. The presented research also raises some concerns for future research regarding the applications of statistical methods to optimise WQM networks, which are presented in Chapter 5.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:77797 |
| Date | 03 February 2022 |
| Creators | Nguyen, Thuy Hoang |
| Contributors | Krebs, Peter, Hettiarachchi, Hiroshan, Thinh, Nguyen Xuan, Technische Universität Dresden, United Nations University |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1007/s12665-019-8110-x, 10.3390/w12020420 |
Page generated in 0.0149 seconds