Water distribution systems are vulnerable to intentional, along with accidental, contamination of the water supply. Contamination warning systems (CWS) are strategies to lessen the effects of contamination by delivering early indication of an event. Online quality monitoring, a network of sensors that can assess water quality and alert an operator of contamination, is a critical component of CWS, but utilities are faced with the decision of what locations are optimal for deployment of sensors. A sensor placement algorithm was developed and implemented in a commercial network distribution model (i.e. KYPIPE) to aid small utilities in sensor placement. The developed sensor placement tool was then validated using 12 small distribution system models and multiple contamination scenarios for the placement of one and two sensors. This thesis also addresses the issue that many sensor placement algorithms require calibrated hydraulic/water quality models, but small utilities do not always possess the financial resources or expertise to build calibrated models. Because of such limitations, a simple procedure is proposed to recommend optimal placement of a sensor without the need for a model or complicated algorithm. The procedure uses simple information about the geometry of the system and does not require explicit information about flow dynamics.

Even though the necessity of water quality monitoring systems is increasing, and though mobile watery quality monitoring systems using the combination of automatic measuring devices and autonomous vehicles is becoming available, research on effective deployment of such systems is not studied well. The locations or paths to take the measurement are one of the most important design factors to maximize the performance of water quality monitoring systems, and they needs to be optimized to maximize the monitoring performance. To solve these optimization problems, multi-objective genetic algorithms were proposed and developed. The proposed optimization procedures were applied to hypothetical circular lakes and Lake Pontchartrain in order to obtain optimal monitoring locations, straight monitoring paths, and higher-order monitoring paths under various conditions. Also, the effect of various parameters such as the speed of a monitoring vessel, the weights of possible scenarios, and etc. are investigated. The optimization models found optimal solutions efficiently while reflecting various effects of complex physical settings. The results from the optimizations show that distribution of possible source locations is an important factor that affects optimal solutions greatly. In a closed water body, wind is major forcing that determines hydrodynamics and contaminant transport, and it affects optimal solutions as well. Straight monitoring lines do not perform very well due to their incapability to cover the irregular boundaries of water bodies. Higher-order optimal monitoring paths overcome this difficulty and perform well up to a comparable level of a few stationary monitoring locations even under realistic and transient conditions.

M.Sc. / Water quality management is the effort of the community to control the physical, chemical and biological qualities of water. Water quality is mainly controlled by the activities of the community and the hydrological cycle. Usually an effort is made to control only one of the two causes, namely the activities of the community. The Sasolburg industrial complex is the largest of its kind in the Free State and consists mainly of chemical industries. A large proportion of the effluent is returned to the Vaal River via the Sasol sewerage works while some industries have permission to send their effluent to the Taaibosspruit, east of Sasolburg. The most industries let their storm water flow into the Taaibosspruit The option of the location of a monitoring point should determine whether the collected data is representative of the water quality and whether it is useful to observe trends in the water quality. The reliability of the data on water quality is strongly dependent on inter alia, the frequency of monitoring, which is determined by the availibility of staff and funding. By investigating the present monitoring sytem by Rand Water, the Department of Water Affairs and Forestry and the industries through this study it had to be determined whether the functioning of the monitoring network was optimal.Deficiencies like: unmonitored and unauthorised streams; badly contaminated areas which pollute the storm water and; the absence of retention facilities for contamninated storm water were found. Recommendations like: extra monitoring points; retention facilities for storm water and; biomonitoring for combined streams were made. Of great importance is the recommendation for the establishment of a local water quality management body to control the water quality of the water sources in the region.

One approach to continuously achieve a certain data quality level is to use an integration pipeline that continuously checks and monitors the quality of a data set according to defined metrics. This approach is inspired by Continuous Integration pipelines, that have been introduced in the area of software development and DevOps to perform continuous source code checks. By investigating in possible tools to use and discussing the specific requirements for RDF data sets, an integration pipeline is derived that joins current approaches of the areas of software development and semantic web as well as reuses existing tools. As these tools have not been built explicitly for CI usage, we evaluate their usability and propose possible workarounds and improvements. Furthermore, a real world usage scenario is discussed, outlining the benefit of the usage of such a pipeline.

Mawira Sitima is a thermal spring located in the village Sitima outside of Liwonde,Malawi. The spring is used by many of the local villagers to take baths, play around and wash clothes. Washing using detergents in springs may cause harm to the aquatic ecosystems and worsen the water quality, which might pose a health risk to people swimming in the spring. This study compared physico-chemical properties of Mawira Sitima and the soil and plants around it with standards, guidelines and other studies to assess thewater quality of the spring. The water quality of another hot spring, Mawira Liwonde, was also assessed and compared to Mawira Sitima to investigate the potential for recreationaluse of Mawira Sitima. The findings were then used to produce recommendations for future monitoring of relevant variables in the spring. The results indicate that the current water quality of Mawira Sitima is of no concern for the local health and has all basis to be of recreational use. A monitoring system including electrical conductivity, water temperature, pH, total phosphorous, copper, manganese, and iron was recommended based on correlations and trends. Monitoring of extreme meteorological conditions, such as heavy rainfall or drought, were also recommended. / Mawira Sitima är en varm källa belägen i byn Sitima utanför Liwonde, Malawi. Källan används av lokalbefolkningen för att bada, leka och tvätta kläder. Att tvätta med tvättmedel i källor kan skada de akvatiska ekosystemen och försämra vattenkvaliteten vilket kan leda till hälsorisker för de som använder källan. I denna studie jämfördes fysikaliska och kemiska parametrar i Mawira Sitima, och jorden och plantor runtom den, med standarder, riktlinjer och andra studier för att utvärdera vattenkvaliteten i källan. Vattenkvaliteten i en annan källa, Mawira Liwonde, utvärderades också och jämfördes med Mawira Sitima i syftet att undersöka potenitalen för fritidsbruk av Mawira Sitima. Undersökningsresultaten användes sedan för att föreslå ett framtida övervakningssystem av relevanta variabler i källan. Resultaten i studien visar på god vattenkvalitet i Mawira Sitima och stora möjligheter för fritidsbruk. Övervakningssystemet föreslogs innefatta elektrisk konduktivitet, vattentemperatur, pH, totalfosfor, koppar, mangan och järn baserat på korrelationer och trender. Även extremväder såsom stora mängder regn eller extrem torka rekommenderades ingå i övervakningssytemet

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Water is one of the most important resources in the world. It has direct impact on the daily life ofmankind and sustainable development of society. Water quality affects biological life and has to obeystrict regulations. Traditional water quality assurance methods, used today, involve manual samplingfollowed by laboratory analysis. This process is expensive due to high labour costs for sampling andlaboratory work. Moreover, it lacks real time analysis which is essential to minimise contamination.This thesis aims to find a solution to this problem using IoT sensors and Machine Learning techniquesto detect anomalies in the water quality. The spatial scalability is key requirement when selecting transmissionprotocols, as sensors could be spread around the water network. We consider solutions readilyavailable or soon to be in the market. The key LPWAN technologies studied are: SigFox, LoRaWANand NB-IoT. In general these protocols have many characteristics essential for fresh water monitoring,like long lasting battery life and long range, however, they have many limitations in terms of transmissiondata rates and duty cycles. It is therefore essential to find a solution that would correctly find anomaliesin the water quality but at the same time comply with limited transmission and processing capabilities ofthe node sensors and above mentioned protocols.A trial sensor is already in place in lake M¨alaren and its readings are used for this study. Supervisedmachine learning algorithms such as Logistic Regression, Artificial Neural Network, Decision Tree, OneClass K-NN and Support Vector Machine (SVM) are studied and discussed regarding the data available.SVM is then selected, implemented and optimised to comply with the limitations of IoT. The trade offbetween false anomalies and false normal readings was also discussed. / Vatten ä r en av de viktigaste resurserna i vä rlden. Det har direkt inverkan på mä nsklighetens dagliga liv och samhä llets hå llbara utveckling. Vattenkvaliteten på verkar det biologiska livet och må ste fö lja strikta fö reskrifter. Traditionella metoder fö r vattenkvalitetssä kring, som anvä nds idag, innefattar manuell provtagning fö ljt av laboratorieanalys. Denna process ä r dyr på grund av hö ga arbetskostnader fö r provtagning och laboratoriearbete. Dessutom saknar den realtidsanalys som ä r vä sentlig fö r att minimera‌fö rorening.Avhandlingen syftar till att hitta en lö sning på detta problem med hjä lp av IoT-sensorer och maskinlä rningsteknik fö r att upptä cka avvikelser i vattenkvaliteten. Den spatiala skalbarheten ä r ett viktigt krav vid val av ö verfö ringsprotokoll, eftersom sensorer kan spridas runt vattennä tverket. Vi diskuterar lö sningar som ä r lä ttillgä ngliga eller snart ska vara på marknaden. De viktigaste LPWAN-teknikerna som studerats ä r: SigFox, LoRaWAN och NB-IoT. Generellt har dessa protokoll må nga egenskaper som ä r nö dvä ndiga fö r ö vervakning av fä rskvatten, som lå ng batterilivslä ngd och lå ng rä ckvidd, men de har må nga begrä nsningar vad gä ller ö verfö ringshastighet och arbetscykel. Det ä r dä rfö r viktigt att hitta en lö sning som skulle hitta anomalier vid hö gt sä kerhet men samtidigt ö verensstä mmer med begrä nsade ö verfö ringsoch bearbetningskapaciteter hos sensorerna och de ovan nä mnda protokoll.En fö rsö kssensor finns redan på plats i Lake Mä laren och dess avlä sningar anvä nds fö r dennastudie.Ö vervakade maskininlä rningsalgoritmer, så som Logistic Regression, Artificial Neural Network,Decision Tree, One Class K-NN and Support Vector Machine (SVM) studeras och diskuteras beträ ffande tillgä ngliga data. SVM vä ljs sedan, implementeras och optimeras fö r att uppfylla IoTs begrä nsningarna.Balansen mellan falska avvikelser och falska normala avlä sningar diskuteras också .

The aim of this thesis was to contribute to the development of urban water management in large cities in a development context. This study presents a case study of Indonesian cities and Jakarta in particular and provides a monitoring framework to examine the impact of urban water management services on the environment and public health, as well as some alternative solutions for mitigation. Assessments were made by analysing the water demand of the urban population based on existing regional and international standards. To monitor major freshwater resource quality in Jakarta, remote sensing techniques based on Sentinel-2 MSI were used, while Sentinel-1 SAR was used to monitor land subsidence. The study also analysed urban wastewater management in Jakarta in comparison with other major cities in Indonesia and across the wider region. Water quality monitoring of the Ciliwung River, the longest river in Jakarta, was done to understand the impact of urban sanitation on surface water. The impact of water and wastewater management on public health on the incidence of diarrhoeal diseases among children was assessed using available statistical data. Some data were obtained from the Indonesian Demographic and Health Surveys (DHS) 2017 and the ESA Copernicus Science Hub for Sentinel-1 and Sentinel-2 satellites. Other data were obtained from field monitoring and laboratory analysis of water quality in river and reservoir, and from official reports on current coverage of and recent progress in urban wastewater management. These data and information were used to estimate and validate the field data, for instance those on Chlorophyll-a, provided by the Indonesian Fisheries Centre. Water quality monitoring data were compared with those of Sentinel-2 MSI, upon which correlation/regression analysis was performed. Data from on-site monitoring of land subsidence MONAS were compared with Sentinel-1 SAR data. Multivariate statistical analysis was used to assess the association between diarrhoea disease in children under 5 years of age (U5) and associated factors, for instance access to water sources and basic sanitation facilities, education attainment, breastfeeding practices, and other social factors. Thus, strategic intervention can be derived to reduce the incidence of diarrhoeal disease among children. A framework has been developed to monitor rapid urban development, water services and finally consequences for the environment and public outcomes. To monitor water management in urban settings, on-site water and wastewater quality monitoring, the latest remote sensing technology and statistical analysis should be integrated to measure and observe the outcome of urban water services on the environment and public health.:Declarations Foreword Acknowledgement Abstract Table of contents List of figures List of tables Abbreviations Currency equivalents Units Chapter 1 Introduction 1.1 Background 1.2 Objectives and scope 1.3 Research questions 1.4 Hypothesis of the study 1.5 Factors affecting the study 1.6 Outline of dissertation Chapter 2 Literature review 2.1 Economic development and rapid urbanization in Jakarta 2.2 Consequences of rapid urbanization 2.3 Sustainable urban water management 2.4 Withdrawal, treatment, and distribution of fresh water 2.5 Water quality monitoring 2.5.1 Freshwater quality standard 2.5.2 Drinking water quality standards 2.6 Wastewater treatment systems 2.7 Remote sensing with satellite technology 2.7.1 Interferometry synthetic aperture radar (SAR) 2.7.2 Sentinel-2 MSI 2.8 Multivariate analysis of diarrhoea and other factors Chapter 3 Methodology 3.1 Research framework 3.1.1 Remote sensing and water resources management 3.1.2 River water quality monitoring 3.1.3 Gap analysis of drinking water supply and wastewater treatment services 3.1.4 Association of diarrhoea with water and wastewater management 3.2 Global climate change 3.2.1 Urban development 3.2.2 Geography 3.2.3 Local climate characteristic 3.2.4 Precipitation rate 3.2.5 Population 3.3. Data collection and analysis Chapter 4 Results and discussion 4.1 Water quality monitoring at Jatiluhur reservoir 4.1.1 In-situ water quality monitoring 4.1.2 Pre-processing of Sentinel-2 optical images 4.1.3 Post-processing of Sentinel-2 images 4.1.4 Results of post-processing Sentinel-2 images 4.1.5 NDWI of Sentinel-2 images 4.1.6 Discussion of key findings 4.1.7 Major findings regarding water resource management 4.2 Land-subsidence monitoring with synthetic aperture radar (SAR) 4.2.1 Remote sensing for land subsidence monitoring 4.2.2 Results of remote sensing analysis 4.2.3 Discussion of remote sensing using SAR 4.2.4 Major findings of monitoring land subsidence 4.3 River water quality monitoring 4.3.1 Wastewater management and river water quality 4.3.2 Effluent water quality standards and GoI regulations 4.3.3 Key findings from river water quality monitoring 4.3.4 Pollutant index 4.3.5 Biological water quality parameters 4.3.6 Physical water quality parameters 4.3.7 Chemical water quality parameters 4.3.8 Discussion of river water quality monitoring 4.3.9 Key findings from river water quality monitoring 4.4 Drinking water, wastewater demand analysis, and public health 4.4.1 Coverage of drinking water supply and wastewater treatment capacity 4.4.2 Production, distribution and use of drinking water 4.4.3 Collection and treatment of wastewater 4.4.4 Diarrhoeal diseases 4.4.5 Discussion of water demand analysis and public health 4.4.6 Major findings from the analysis of water demand, wastewater and public health 4.5 Analysis of diarrhoea and associated factors 4.5.1 Introduction to multivariate analysis 4.5.2 Focus of study area 4.5.3 Fixed variable 4.5.4 Dependent variables 4.5.5 Results of multivariate analysis Chapter 5 Conclusion 5.1 New insight on urban water management 5.2 Socio-economic factors 5.3 Implication on further study and development List of References Annexes Disclaimer

published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management

In low-resource contexts, household-level point-of-use water treatment (POUWT) techniques are the final, and sometimes only, barrier against waterborne illnesses, and in these and other water-related applications, health risks can be quantified using one of two methods. Firstly, Escherichia coli (or other indicator organism) counts can be used to monitor water and determine adherence to a health-based limit (i.e. compliance monitoring). Secondly, E. coli can be used to conduct a quantitative microbial risk assessment (QMRA), indicating the level of protection conferred by a given POUWT device by spiking test water with E. coli to ascertain a reduction efficacy relative to that target organism, a process referred to as challenge testing, which is typically carried out in a laboratory context. Although both methods are well established, both have scope for improvement for effective field application in low-resource contexts. Regarding compliance monitoring, I assessed the performance of a new low-cost field kit for E. coli enumeration, which was designed by others. I also assessed the feasibility of re-using some disposable materials, in terms of sterility and mechanical wear. The use of the new low-cost field kit was successful during the fieldwork campaign; however, re-using disposable materials introduced a relatively high occurrence of false positive results during E. coli enumeration. Use of the new low-cost field kit can reduce financial barriers, thus enabling greater water quality testing coverage. Regarding challenge testing, the aim of this study was to adapt current protocols to assess the household performance (as opposed to laboratory performance) of POUWT techniques. I developed a conceptual framework to conduct Field Challenge Tests (FCT’s) on POUWT techniques, using a probiotic health supplement containing E. coli as the challenge organism. I successfully carried out a FCT in Malawi with limited resources, verifying FCT viability. Applications of such FCT’s include quality control practices for manufactured devices, guiding QMRA and recommendations by public health organizations regarding POU device selection, and assessing the impact of user training programmes regarding POUWT techniques. / Graduate