Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Studying wild animals in nature is a complex and tedious task for biologists and ecologists. The rugged terrain in which the animals live and hide makes it for researchers difficult to follow and observe the animals. Technology is used to facilitate studies on animals, usually in the form of radio tracking devices. This thesis discusses the problems and shortfalls surrounding the current technology and looks at various ways of improving it. Expanding tracking collars to capture the needed data, as well as improving the radio links to continuously provide data, are seen as the most important improvements. The proposed solution makes use of a wireless network, through which a tracking collar can have an unbroken connection with the outside world. The study focuses on the radio links themselves and topics including antennas, radio frequency bands and propagation effects of the surroundings. An existing routing protocol to use on top of the physical radio links is discussed. Hardware for all parts of the network is designed, built and tested. Proper ways of capturing data in a power efficient way are stated and recommended. Measurements were taken with the hardware prototypes in a location comparable to where the system will ultimately be used. The results obtained proved the feasibility of such a radio network. Radio coverage simulations were set up to predict the coverage that is to be expected by the chosen radios in the location where the tests were done. The simulation parameters were changed until the simulated results most closely matched the real life measurements. Vegetation caused an extra attenuation of around 20dB in the radio signal. Using the tuned parameters for the simulation a network can be designed and costs calculated before huge investments are made. / AFRIKAANSE OPSOMMING: Om wilde diere in die natuur te bestudeer is vir wetenskaplikes ’n uitdagende onderneming. Die ongerepte natuur waarin die diere bly, maak dit vir die dierkundiges moeilik om die diere op te spoor en te agtervolg. Tegnologie word gewoonlik ingespan in hierdie studies en meestal word radiosporingstoestelle gebruik. Hierdie tesis bespreek die probleme en tekortkominge in die bestaande tegnologie. Verskeie moontlike verbeteringe word bekyk. Radiosporingshalsbande wat uitgebrei word om metings te neem, en verbetering van die radioverbindings met die halsbande is twee van die belangrikste punte waarop verbeter kan word. In die voorgestelde verbeterings word ’n radionetwerk gebruik om op ’n deurlopende basis kontak tussen die halsbande en die buitewêreld te verseker. Die studies lê klem op die radioverbindings en onderwerpe soos antennas en radiofrekwensiebande. Radioseine se voortplantingskenmerke in die betrokke omgewing word bespreek. ’n Bestaande netwerkprotokol om op die radioverbindings te implementeer word ook bepsreek. Apparatuur vir alle dele van die netwerk is ontwerp, gebou en getoets. Metodes van datavaslegging op ’n energiedoeltreffende wyse word beskryf en aanbevelings daarvoor gemaak. Metings is geneem met die prototipe van die apparate in ’n plek wat vergelykbaar is met waar die uiteindelike stelsel gebruik behoort te word. Die resulte wat verkry is, het die nut van die radionetwerk bewys. Simulasies van die radiodekking is opgestel om die verwagte dekkings van die betrokke radios in die veld te bepaal. Die simulasieparameters is geleidelik verander totdat die simulasieresultate met die werklike metings ooreenstem. Plantegroei het ’n ekstra verswakking van ongeveer 20dB in die radiosein veroorsaak. Die vasgestelde parameters kan gebruik word in ’n simulasie vir die ontwerp van ’n grootskaalse netwerk. Resultate verkry vanuit die simulasie kan gebruik word vir kosteberekings voordat grootskaalse beleggings gemaak word.

Data collection is an integral part of hydrologic investigations; yet, hydrologic data collection is costly, particularly in subsurface environments. Consequently, it is critical to target data collection efforts toward prospective data sets that will best address the questions at hand, in the context of the study. Experimental and monitoring network designs that have been carefully planned with a specific objective in mind are likely to yield information-rich data that can address critical questions of concern. Conversely, data collection undertaken without careful planning may yield datasets that contain little information relevant to the questions of concern. This dissertation research develops and presents approaches that can be used to support careful planning of hydrologic experiments and monitoring networks. Specifically, three general types of problems are considered. Under the first problem type, the objective of the hydrologic investigation is to discriminate among rival conceptual models, or among rival predictive groupings. A Bayesian methodology is presented that can be used to rank prospective datasets during the planning phases of a hydrologic investigation. Under the second problem type, the objective is to quantify the impact of existing data on reductions in parameter uncertainty. An inverse modeling approach is presented to quantify the impact of existing data on parameter uncertainty when the hydrogeologic conceptual model is uncertain. The third and final problem type focuses on data collection in a water resource management context, with the specific goal to maximize profits without imposing adverse environmental impacts. A risk-based decision support framework is developed using detailed hydrologic simulation to evaluate probabilistic constraints. This enables direct calculation of the profit gains associated with prospective reductions in system parameter uncertainty, and the possible environmental impacts of unknown bias in the system parameters.

This study explores the applicability of including groundwater recharge and water table variation as additional objective functions in a multi-objective optimization approach to design optimal groundwater monitoring networks. The study was conducted using the Ontario Provincial Groundwater Monitoring Network wells in the Hamilton, Halton, and Credit Valley regions in southern Ontario. The Dual Entropy-Multiobjective Optimization (DEMO) model which has been demonstrated to be sufficiently robust for designing optimum hydrometric networks was used in these analyses. The importance of determining the applicability in using additional design objectives in DEMO, including groundwater recharge and groundwater table seasonal variation, is rooted in the limitations of groundwater data and the time required setting up the models. While recharge allows for the capturing of spatial variability of climate, geomorphology, and geology of the area, the groundwater table series reflect the temporal/seasonal variability. The two set of information are complementary and should provide additional information to the DEMO for optimal network design. Two sources of groundwater recharge data were examined and compared; the recharge provided by the local conservation authorities, calculated using both the Precipitation-Runoff Modeling System (PRMS) and Hydrological Simulation Program--Fortran (HSP--F), and the recharge calculated in situ using only PRMS. The entropy functions are used to identify optimal trade-offs between the maximum possible information content and the minimum shared information between each of the existing and potential monitoring wells. The additional objective functions are used here to quantify the hydrological characteristics of the vadose zone in the aquifer as well as the potential impacts of agricultural, municipal, and industrial uses of groundwater in the area, and thus provide more information for the optimization algorithm to use. Results show that including additional design objectives significantly increases the number of optimal network solutions and provides additional information for potential monitoring well locations. These results suggest that it is worthwhile to include recharge as a design objective if the data is available, and to include groundwater table variation for the design of monitoring wells for shallow groundwater system. / Thesis / Master of Applied Science (MASc)

Air pollution sampling site selection is one of the most important and yet most vexing of the problems faced by those responsible for regional and urban air quality management and for the attainment and maintenance of national ambient air quality standards. Since one cannot hope to monitor air quality at all locations at all times, selection of sites to give a reliable and realistic picture of air quality becomes a major issue and at the same time a difficult task. The location (configuration) and the number of stations may be based on many factors, some of which may depend on limited resources, federal and state regulations and local conditions. The combination of these factors has made air quality surveys more complex; requiring comprehensive planning to ensure that the prescribed objectives can be attained in the shortest possible time and at the least cost. Furthermore, the choice and siting of the measuring network represents a factor of significant economic relevance for policymakers. In view of the fact that equipment, maintenance and operating personnel costs are increasing dramatically, the possibility of optimizing the monitoring design, is most attractive to the directors of air quality management programs. In this work a methodology that is able to design an optimal air quality monitoring network (AQMN) is described. The objective of the optimization is to provide maximum information about the presence and level of atmospheric contaminants in a given area and with a limited budget. A criterion for assessing the allocation of monitoring stations is developed by applying a utility function that can describe the spatial coverage of the network and its ability to detect violations of standards for multiple pollutants. A mathematical model based on the Multiple Cell Approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. This data was used to train artificial neural networks (ANN) that were proven to be able to predict very well the pattern and violation scores at different potential locations. These neural networks were embedded within a mathematical programming model whose objective is to determine the best monitoring locations for a given budget. This resulted in a nonlinear program (NLP). The proposed model is applied to a network of existing refinery stacks and the locations of monitoring stations and their area coverage percentage are obtained.

Air pollution sampling site selection is one of the most important and yet most vexing of the problems faced by those responsible for regional and urban air quality management and for the attainment and maintenance of national ambient air quality standards. Since one cannot hope to monitor air quality at all locations at all times, selection of sites to give a reliable and realistic picture of air quality becomes a major issue and at the same time a difficult task. The location (configuration) and the number of stations may be based on many factors, some of which may depend on limited resources, federal and state regulations and local conditions. The combination of these factors has made air quality surveys more complex; requiring comprehensive planning to ensure that the prescribed objectives can be attained in the shortest possible time and at the least cost. Furthermore, the choice and siting of the measuring network represents a factor of significant economic relevance for policymakers. In view of the fact that equipment, maintenance and operating personnel costs are increasing dramatically, the possibility of optimizing the monitoring design, is most attractive to the directors of air quality management programs. In this work a methodology that is able to design an optimal air quality monitoring network (AQMN) is described. The objective of the optimization is to provide maximum information about the presence and level of atmospheric contaminants in a given area and with a limited budget. A criterion for assessing the allocation of monitoring stations is developed by applying a utility function that can describe the spatial coverage of the network and its ability to detect violations of standards for multiple pollutants. A mathematical model based on the Multiple Cell Approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. This data was used to train artificial neural networks (ANN) that were proven to be able to predict very well the pattern and violation scores at different potential locations. These neural networks were embedded within a mathematical programming model whose objective is to determine the best monitoring locations for a given budget. This resulted in a nonlinear program (NLP). The proposed model is applied to a network of existing refinery stacks and the locations of monitoring stations and their area coverage percentage are obtained.

The subject of this work relates to monitoring of large networks consisting of hundreds of active elements and thousands of users. Study of the subject is situated in the Kolejnet computer network environment, where information system is being used. At the moment, the information system includes basic monitoring of this large network. The goal [of this study] is to architect a system that will allow continuous monitoring of active elements which includes collection of data and logging of important events for immediate and later evaluation of serious circumstances that can arise.

A manutenção da qualidade ambiental está diretamente relacionada ao conhecimento e controle das variáveis que interferem no problema, sejam elas resultantes das ações do homem sobre o ambiente ou de suas transformações naturais. Este conhecimento sobre o meio ambiente pode ser obtido através de monitoramento e, no caso dos corpos d’água, a eficácia do monitoramento depende em especial de um projeto e operação adequados do sistema de informações, que é constituído pela aquisição, manipulação, análise e utilização da informação obtida. No que se refere à aquisição da informação, ainda existem grandes lacunas a serem preenchidas na decisão sobre onde, quando e o que monitorar. Neste trabalho são enfocadas as atividades básicas do projeto da rede de monitoramento, ou seja, a localização das estações, a seleção das variáveis, a freqüência e a duração da amostragem, procurando-se buscar um conjunto de diretrizes de aplicação que seja exeqüível e eficaz para o projeto e manutenção de redes de monitoramento, uma vez que não se dispõe atualmente na literatura, de procedimento geral que vise solucionar este problema. A localização das estações de monitoramento na bacia hidrográfica, denominada de macrolocalização, a determinação de freqüências amostrais e a definição das variáveis a serem monitoradas, são tarefas que fazem parte do projeto da rede de monitoramento da qualidade da água. A rede de monitoramento, por sua vez, é parte do sistema de informações sobre qualidade da água, cujo objetivo é a descrição dos fenômenos físicos, químicos e biológicos relacionados à qualidade do corpo d’água. A eficiência da metodologia discutida neste trabalho é demonstrada e discutida através de estudos de casos. Dentre as contribuições deste trabalho podem-se destacar: (i) a ampliação do trabalho de POMEROY e ORLOB, para a localização de estações de monitoramento baseando-se na área e características de drenagem da bacia hidrográfica; (ii) a adaptação do procedimento de otimização no processo de macrolocalização de SHARP; (iii) a dedução da equação da entropia para análise de múltiplas variáveis; (iv) o desenvolvimento de um aplicativo computacional para a análise e avaliação de desempenho de estações de monitoramento baseado no conceito de entropia; e (v) a proposição de uma metodologia geral de dimensionamento e redimensionamento de redes de monitoramento de qualidade da água . Neste trabalho são descritas, discutidas e aplicadas as metodologias disponíveis para a macrolocalização e as recentemente propostas para o redimensionamento de redes de monitoramento, baseadas no conceito de entropia, objetivando a produção de diretrizes de projeto de redes de monitoramento, especialmente para países em desenvolvimento. Assim sendo, neste trabalho não se faz somente uma análise de métodos disponíveis para o projeto de redes de monitoramento mas também é proposta uma metodologia de dimensionamento e redimensionamento de redes de monitoramento para bacias com poucos dados e para bacias com dados de qualidade da água. Desta forma espera-se contribuir com países em processo de início e organização de seus sistemas de informação ambiental, e também para aqueles com suas redes já em operação, facilitando-se a decisão quanto à destinação de recursos para a adequação da realidade financeira aos objetivos de operação e manutenção destes sistemas. / The maintenance of the environmental quality is directly related to the knowledge and control of the variables affected by the problem, either as a result of the human action on the environment, or due to natural transformations. Knowledge on the environment can be obtained through monitoring. The effectiveness of the monitoring especially depends on the project of the information system and its operation. Data acquisition, manipulation, analysis, as well as the use of the generated information, are all activities that must be prepared by the project. As far as the acquisition of information is concerned, there are research gaps about the decision on where, when and what to monitor. This study will focus on the basic activities of the monitoring network project, that is, the location of the stations, the variable selection and the sampling frequency. The objective is to find out a group of application guidelines that has a practical use and is effective both to the project and maintenance of monitoring networks, since a general procedure to solve this problem is not available in the literature. Water quality monitoring networks are part of the water resources information system, with the objective of describing the physical, chemical and biological phenomena related to the quality of the water body. The efficiency of the methodology discussed in this study is demonstrated and discussed through case studies. The most important contributions of this study are: (i) the expansion of the POMEROY and ORLOB studies to locate monitoring stations based on the watershed area and channel network; (ii) the extended use of the optimization procedure proposed by SHARP to improve the macrolocation process; (iii) the deduction of the entropy equation to analyze the multiple variables; (iv) the software to analyze and to propose a new design for monitoring networks, based on the entropy concept; and (v) the proposal of a general methodology to the water quality monitoring network design and redesign. The processes and methodologies proposed in this study were developed to be applied in developing countries. Usually such countries are in the process of initialization and organization of their environmental information systems, and we hope that this study will be able to bring satisfactory benefits, taking into account that optimization is necessary to bring the costs down and to make the monitoring effort sustainable.

A manutenção da qualidade ambiental está diretamente relacionada ao conhecimento e controle das variáveis que interferem no problema, sejam elas resultantes das ações do homem sobre o ambiente ou de suas transformações naturais. Este conhecimento sobre o meio ambiente pode ser obtido através de monitoramento e, no caso dos corpos d’água, a eficácia do monitoramento depende em especial de um projeto e operação adequados do sistema de informações, que é constituído pela aquisição, manipulação, análise e utilização da informação obtida. No que se refere à aquisição da informação, ainda existem grandes lacunas a serem preenchidas na decisão sobre onde, quando e o que monitorar. Neste trabalho são enfocadas as atividades básicas do projeto da rede de monitoramento, ou seja, a localização das estações, a seleção das variáveis, a freqüência e a duração da amostragem, procurando-se buscar um conjunto de diretrizes de aplicação que seja exeqüível e eficaz para o projeto e manutenção de redes de monitoramento, uma vez que não se dispõe atualmente na literatura, de procedimento geral que vise solucionar este problema. A localização das estações de monitoramento na bacia hidrográfica, denominada de macrolocalização, a determinação de freqüências amostrais e a definição das variáveis a serem monitoradas, são tarefas que fazem parte do projeto da rede de monitoramento da qualidade da água. A rede de monitoramento, por sua vez, é parte do sistema de informações sobre qualidade da água, cujo objetivo é a descrição dos fenômenos físicos, químicos e biológicos relacionados à qualidade do corpo d’água. A eficiência da metodologia discutida neste trabalho é demonstrada e discutida através de estudos de casos. Dentre as contribuições deste trabalho podem-se destacar: (i) a ampliação do trabalho de POMEROY e ORLOB, para a localização de estações de monitoramento baseando-se na área e características de drenagem da bacia hidrográfica; (ii) a adaptação do procedimento de otimização no processo de macrolocalização de SHARP; (iii) a dedução da equação da entropia para análise de múltiplas variáveis; (iv) o desenvolvimento de um aplicativo computacional para a análise e avaliação de desempenho de estações de monitoramento baseado no conceito de entropia; e (v) a proposição de uma metodologia geral de dimensionamento e redimensionamento de redes de monitoramento de qualidade da água . Neste trabalho são descritas, discutidas e aplicadas as metodologias disponíveis para a macrolocalização e as recentemente propostas para o redimensionamento de redes de monitoramento, baseadas no conceito de entropia, objetivando a produção de diretrizes de projeto de redes de monitoramento, especialmente para países em desenvolvimento. Assim sendo, neste trabalho não se faz somente uma análise de métodos disponíveis para o projeto de redes de monitoramento mas também é proposta uma metodologia de dimensionamento e redimensionamento de redes de monitoramento para bacias com poucos dados e para bacias com dados de qualidade da água. Desta forma espera-se contribuir com países em processo de início e organização de seus sistemas de informação ambiental, e também para aqueles com suas redes já em operação, facilitando-se a decisão quanto à destinação de recursos para a adequação da realidade financeira aos objetivos de operação e manutenção destes sistemas. / The maintenance of the environmental quality is directly related to the knowledge and control of the variables affected by the problem, either as a result of the human action on the environment, or due to natural transformations. Knowledge on the environment can be obtained through monitoring. The effectiveness of the monitoring especially depends on the project of the information system and its operation. Data acquisition, manipulation, analysis, as well as the use of the generated information, are all activities that must be prepared by the project. As far as the acquisition of information is concerned, there are research gaps about the decision on where, when and what to monitor. This study will focus on the basic activities of the monitoring network project, that is, the location of the stations, the variable selection and the sampling frequency. The objective is to find out a group of application guidelines that has a practical use and is effective both to the project and maintenance of monitoring networks, since a general procedure to solve this problem is not available in the literature. Water quality monitoring networks are part of the water resources information system, with the objective of describing the physical, chemical and biological phenomena related to the quality of the water body. The efficiency of the methodology discussed in this study is demonstrated and discussed through case studies. The most important contributions of this study are: (i) the expansion of the POMEROY and ORLOB studies to locate monitoring stations based on the watershed area and channel network; (ii) the extended use of the optimization procedure proposed by SHARP to improve the macrolocation process; (iii) the deduction of the entropy equation to analyze the multiple variables; (iv) the software to analyze and to propose a new design for monitoring networks, based on the entropy concept; and (v) the proposal of a general methodology to the water quality monitoring network design and redesign. The processes and methodologies proposed in this study were developed to be applied in developing countries. Usually such countries are in the process of initialization and organization of their environmental information systems, and we hope that this study will be able to bring satisfactory benefits, taking into account that optimization is necessary to bring the costs down and to make the monitoring effort sustainable.

Two of the most important environmental challenges in the 21st century are to protect the quality of fresh water resources and to utilize renewable energy sources to lower greenhouse gas emissions. This study contributes to the solution of the first challenge by providing methodologies for optimal design of real-time water quality monitoring systems and interpretation of data supplied by the monitoring system to identify potential pollution sources in river networks. In this study, the optimal river water quality monitoring network design aspect of the overall monitoring program is addressed by a novel methodology for the analysis of this problem. In this analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. The data collected from these monitoring stations can be used to identify contamination source locations. This study suggests a methodology that utilizes a classification routine which associates the observations on a contaminant spill with one or more of the candidate spill locations in the river network. This approach consists of a training step followed by a sequential elimination of the candidate spill locations which lead to the identification of potential spill locations. In order to contribute the solution of the second environmental challenge, this study suggests utilizing available excess energy in water distribution systems by providing a methodology for optimal design of energy recovery systems. The energy recovery in water distribution systems is possible by using micro hydroelectric turbines to harvest available excess energy inevitably produced to satisfy consumer demands and to maintain adequate pressures. In this study, an optimization approach for the design of energy recovery systems in water distribution networks is proposed. This methodology is based on finding the best locations for micro hydroelectric plants in the network to recover the excess energy. Due to the unsteady nature of flow in water distribution networks, the proposed methodology also determines optimum operation schedules for the micro turbines.