Safe drinking water is a basic need; and risk assessment tools may assist in prioritizing actions to improve water safety. The objective of this research was to determine the appropriateness of current risk assessment approaches for First Nations drinking water systems. Criteria to evaluate risk assessment approaches were developed by combining common elements from literature, key informant interviews, and surveys. The criteria were compared against selected tools for drinking water risk assessment, including tools developed by Australia, Montana, Indian and Northern Affairs, and the University of Guelph. None of the tools, as available, met all of the criteria. Important considerations were found to include the operator, monitoring and recordkeeping, maintenance, technical considerations, emergency response plans, and source water protection. The tools were generally weak in assessing some potential challenges facing small, remote, and First Nations communities; including financial constraints, and taking a holistic view of water. / Note: this thesis was also submitted in hard-copy to Graduate Services

Algae and cyanobacteria occur naturally in source waters and are known to cause extensive problems in the drinking water treatment industry. Cyanobacteria (especially Anabaena sp. and Microcystis sp.) are responsible for many water treatment problems in drinking water treatment works (DWTW) all over the world because of their ability to produce organic compounds like cyanotoxins (e.g. microcystin) and taste and odour compounds (e.g. geosmin) that can have an adverse effect on consumer health and consumer confidence in tap water. Therefore, the monitoring of cyanobacteria in source waters entering DWTW has become an essential part of drinking water treatment management. Managers of DWTW, rely heavily on results of physical, chemical and biological water quality analyses, for their management decisions. But results of water quality analyses can be delayed from 3 hours to a few days depending on a magnitude of factors such as: sampling, distance and accessibility to laboratory, laboratory sample turn-around times, specific methods used in analyses etc. Therefore the use of on-line (in situ) instruments that can supply real-time results by the click of a button has become very popular in the past few years. On-line instruments were developed for analyses like pH, conductivity, nitrate, chlorophyll-a and cyanobacteria concentrations. Although, this real-time (on-line) data has given drinking water treatment managers a better opportunity to make sound management decisions around drinking water treatment options based on the latest possible results, it may still be “too little, too late” once a sudden cyanobacterial bloom of especially Anabaena sp. or Microcystis sp. enters the plant. Therefore the benefit for drinking water treatment management, of changing the focus from real-time results to future predictions of water quality has become apparent. The aims of this study were 1) to review the environmental variables associated with cyanobacterial blooms in the Vaal Dam, as to get background on the input variables that can be used in cyanobacterial-related forecasting models; 2) to apply rule-based Hybrid Evolutionary Algorithms (HEAs) to develop models using a) all applicable laboratory-generated data and b) on-line measureable data only, as input variables in prediction models for harmful algal blooms in the Vaal Dam; 3) to test these models with data that was not used to develop the models (so-called “unseen data”), including on-line (in situ) generated data; and 4) to incorporate selected models into two cyanobacterial incident management protocols which link to the Water Safety Plan (WSP) of a large DWTW (case study : Rand Water). During the current study physical, chemical and biological water quality data from 2000 to 2009, measured in the Vaal Dam and the 20km long canal supplying the Zuikerbosch DWTW of Rand Water, has been used to develop models for the prediction of Anabaena sp., Microcystis sp., the cyanotoxin microcystin and the taste and odour compound geosmin for different prediction or forecasting times in the source water. For the development and first stage of testing the models, 75% of the dataset was used to train the models and the remaining 25% of the dataset was used to test the models. Boot-strapping was used to determine which 75% of the dataset was to be used as the training dataset and which 25% as the testing dataset. Models were also tested with 2 to 3 years of so called “unseen data” (Vaal Dam 2010 – 2012) i.e. data not used at any stage during the model development. Fifty different models were developed for each set of “x input variables = 1 output variable” chosen beforehand. From the 50 models, the best model between the measured data and the predicted data was chosen. Sensitivity analyses were also performed on all input variables to determine the variables that have the largest impact on the result of the output. This study have shown that hybrid evolutionary algorithms can successfully be used to develop relatively accurate forecasting models, which can predict cyanobacterial cell concentrations (particularly Anabaena sp. and Microcystis sp.), as well as the cyanotoxin microcystin concentration in the Vaal Dam, for up to 21 days in advance (depending on the output variable and the model applied). The forecasting models that performed the best were those forecasting 7 days in advance (R2 = 0.86, 0.91 and 0.75 for Anabaena[7], Microcystis[7] and microcystin[7] respectively). Although no optimisation strategies were performed, the models developed during this study were generally more accurate than most models developed by other authors utilising the same concepts and even models optimised by hill climbing and/or differential evolution. It is speculated that including “initial cyanobacteria inoculum” as input variable (which is unique to this study), is most probably the reason for the better performing models. The results show that models developed from on-line (in situ) measureable data only, are almost as good as the models developed by using all possible input variables. The reason is most probably because “initial cyanobacteria inoculum” – the variable towards which the output result showed the greatest sensitivity – is included in these models. Generally models predicting Microcystis sp. in the Vaal Dam were more accurate than models predicting Anabaena sp. concentrations and models with a shorter prediction time (e.g. 7 days in advance) were statistically more accurate than models with longer prediction times (e.g. 14 or 21 days in advance). The multi-barrier approach in risk reduction, as promoted by the concept of water safety plans under the banner of the Blue Drop Certification Program, lends itself to the application of future predictions of water quality variables. In this study, prediction models of Anabaena sp., Microcystis sp. and microcystin concentrations 7 days in advance from the Vaal Dam, as well as geosmin concentration 7 days in advance from the canal were incorporated into the proposed incident management protocols. This was managed by adding an additional “Prediction Monitoring Level” to Rand Waters’ microcystin and taste and odour incident management protocols, to also include future predictions of cyanobacteria (Anabaena sp. and Microcystis sp.), microcystin and geosmin. The novelty of this study was the incorporation of future predictions into the water safety plan of a DWTW which has never been done before. This adds another barrier in the potential exposure of drinking water consumers to harmful and aesthetically unacceptable organic compounds produced by cyanobacteria. / PhD (Botany), North-West University, Potchefstroom Campus, 2015

Algae and cyanobacteria occur naturally in source waters and are known to cause extensive problems in the drinking water treatment industry. Cyanobacteria (especially Anabaena sp. and Microcystis sp.) are responsible for many water treatment problems in drinking water treatment works (DWTW) all over the world because of their ability to produce organic compounds like cyanotoxins (e.g. microcystin) and taste and odour compounds (e.g. geosmin) that can have an adverse effect on consumer health and consumer confidence in tap water. Therefore, the monitoring of cyanobacteria in source waters entering DWTW has become an essential part of drinking water treatment management. Managers of DWTW, rely heavily on results of physical, chemical and biological water quality analyses, for their management decisions. But results of water quality analyses can be delayed from 3 hours to a few days depending on a magnitude of factors such as: sampling, distance and accessibility to laboratory, laboratory sample turn-around times, specific methods used in analyses etc. Therefore the use of on-line (in situ) instruments that can supply real-time results by the click of a button has become very popular in the past few years. On-line instruments were developed for analyses like pH, conductivity, nitrate, chlorophyll-a and cyanobacteria concentrations. Although, this real-time (on-line) data has given drinking water treatment managers a better opportunity to make sound management decisions around drinking water treatment options based on the latest possible results, it may still be “too little, too late” once a sudden cyanobacterial bloom of especially Anabaena sp. or Microcystis sp. enters the plant. Therefore the benefit for drinking water treatment management, of changing the focus from real-time results to future predictions of water quality has become apparent. The aims of this study were 1) to review the environmental variables associated with cyanobacterial blooms in the Vaal Dam, as to get background on the input variables that can be used in cyanobacterial-related forecasting models; 2) to apply rule-based Hybrid Evolutionary Algorithms (HEAs) to develop models using a) all applicable laboratory-generated data and b) on-line measureable data only, as input variables in prediction models for harmful algal blooms in the Vaal Dam; 3) to test these models with data that was not used to develop the models (so-called “unseen data”), including on-line (in situ) generated data; and 4) to incorporate selected models into two cyanobacterial incident management protocols which link to the Water Safety Plan (WSP) of a large DWTW (case study : Rand Water). During the current study physical, chemical and biological water quality data from 2000 to 2009, measured in the Vaal Dam and the 20km long canal supplying the Zuikerbosch DWTW of Rand Water, has been used to develop models for the prediction of Anabaena sp., Microcystis sp., the cyanotoxin microcystin and the taste and odour compound geosmin for different prediction or forecasting times in the source water. For the development and first stage of testing the models, 75% of the dataset was used to train the models and the remaining 25% of the dataset was used to test the models. Boot-strapping was used to determine which 75% of the dataset was to be used as the training dataset and which 25% as the testing dataset. Models were also tested with 2 to 3 years of so called “unseen data” (Vaal Dam 2010 – 2012) i.e. data not used at any stage during the model development. Fifty different models were developed for each set of “x input variables = 1 output variable” chosen beforehand. From the 50 models, the best model between the measured data and the predicted data was chosen. Sensitivity analyses were also performed on all input variables to determine the variables that have the largest impact on the result of the output. This study have shown that hybrid evolutionary algorithms can successfully be used to develop relatively accurate forecasting models, which can predict cyanobacterial cell concentrations (particularly Anabaena sp. and Microcystis sp.), as well as the cyanotoxin microcystin concentration in the Vaal Dam, for up to 21 days in advance (depending on the output variable and the model applied). The forecasting models that performed the best were those forecasting 7 days in advance (R2 = 0.86, 0.91 and 0.75 for Anabaena[7], Microcystis[7] and microcystin[7] respectively). Although no optimisation strategies were performed, the models developed during this study were generally more accurate than most models developed by other authors utilising the same concepts and even models optimised by hill climbing and/or differential evolution. It is speculated that including “initial cyanobacteria inoculum” as input variable (which is unique to this study), is most probably the reason for the better performing models. The results show that models developed from on-line (in situ) measureable data only, are almost as good as the models developed by using all possible input variables. The reason is most probably because “initial cyanobacteria inoculum” – the variable towards which the output result showed the greatest sensitivity – is included in these models. Generally models predicting Microcystis sp. in the Vaal Dam were more accurate than models predicting Anabaena sp. concentrations and models with a shorter prediction time (e.g. 7 days in advance) were statistically more accurate than models with longer prediction times (e.g. 14 or 21 days in advance). The multi-barrier approach in risk reduction, as promoted by the concept of water safety plans under the banner of the Blue Drop Certification Program, lends itself to the application of future predictions of water quality variables. In this study, prediction models of Anabaena sp., Microcystis sp. and microcystin concentrations 7 days in advance from the Vaal Dam, as well as geosmin concentration 7 days in advance from the canal were incorporated into the proposed incident management protocols. This was managed by adding an additional “Prediction Monitoring Level” to Rand Waters’ microcystin and taste and odour incident management protocols, to also include future predictions of cyanobacteria (Anabaena sp. and Microcystis sp.), microcystin and geosmin. The novelty of this study was the incorporation of future predictions into the water safety plan of a DWTW which has never been done before. This adds another barrier in the potential exposure of drinking water consumers to harmful and aesthetically unacceptable organic compounds produced by cyanobacteria. / PhD (Botany), North-West University, Potchefstroom Campus, 2015

A Water Safety Plan for Extreme Events - PSAEE, has the purpose of description the procedures in potentially critical situations due to the occurrence of extreme weather events (droughts and floods). Provides the developing of preventive actions and contingency plan as a way to mitigate the effects of these phenomena. Will be developed in different and complementary steps, aiming anticipation, recognition and risk assessment, identification and monitoring of vulnerable regions and the implementation of a warning network against Floods and Droughts. The present document describes guidelines for structuring a Water Safety Plan for Extreme Events, Floods and Droughts, structured in five (05) steps; 1. Preliminary Steps, 2 Diagnostic System; 3 Operational Monitoring; 4. Management Plans and 5.Validation and Verification. As a case study, the document analyzed the process of implementing the Situation Room of the Water Resources Management Company of Cearà - COGERH , also presenting some suggestion of a Work Plan for the Situation Room, which will serve as a Management Center of Extreme Hydrological Events for the State of CearÃ, Brazil. / Um Plano de SeguranÃa de Ãgua para Eventos Extremos â PSAEE, tem como objetivo a descriÃÃo de procedimentos em situaÃÃes potencialmente criticas devido a ocorrÃncia de eventos climÃticos extremos (Secas e Cheias). Prevà o desenvolvendo de aÃÃes preventivas e plano de contingÃncia como forma de mitigar os efeitos destes fenÃmenos. Serà desenvolvido em etapas distintas e complementares, visando a antecipaÃÃo, reconhecimento e avaliaÃÃo de riscos, a identificaÃÃo e monitoramento de regiÃes vulnerÃveis, a implementaÃÃo de rede de alerta contra Cheias e Secas. O presente trabalho descreve diretrizes para estruturaÃÃo de um Plano de SeguranÃa de Ãgua para Eventos Extremos, Cheias e Secas, estruturado em 05 (cinco) etapas; 1. Etapas Preliminares, 2. DiagnÃstico do Sistema; 3. Monitoramento Operacional; 4. Planos de GestÃo e 5. ValidaÃÃo e VerificaÃÃo. Como estudo de caso, o trabalho analisou o processo de implantaÃÃo da Sala de SituaÃÃo da Companhia de GestÃo dos Recursos HÃdricos do Cearà â COGERH, apresentando, tambÃm, sugestÃo de um Plano de Trabalho para a Sala de SituaÃÃo, a qual servirà de Centro de GestÃo de Eventos Extremos HidrolÃgicos para o Estado do CearÃ, Brasil.

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No. of bitstreams: 5 Dissertação - Rafaela Jacob de Oliveira Braga - 2015.pdf: 1948227 bytes, checksum: c3c87600aa30f0048b56fd72d588d73b (MD5) Dissertação - Rafaela Jacob de Oliveira Braga - 2015 - Planilha Misto.doc: 266752 bytes, checksum: c16374ac18c0b62729ec2e1ee410900a (MD5) Dissertação - Rafaela Jacob de Oliveira Braga - 2015 - Planilha Subterrâneo.doc: 143872 bytes, checksum: 0ad941014880c6e9c08f4f8d4383ecd7 (MD5) Dissertação - Rafaela Jacob de Oliveira Braga - 2015 - Planilha Superficial.doc: 268800 bytes, checksum: c74e02c904962b746dfd07e41437fbc6 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-12-10 / Water supply systems (WSS) for human consumption aim to produce and supply drinking water to the population through the distribution network. However, the need to revise the actuals methodological procedures that maintain the water quantity and water quality in satisfactory levels for domestic consumption has caused the World Health Organization to propose a new methodology called Water Safety Plan (WSP), still incipient at state of Goiás. In this way, this study aims to propose Safety Plan of Water to 21 cities located at the state of Goiás that presenting WSS managed by local governments. The study was divided into two chapters. The first chapter characterized the WSS of this 21 cities in the state of Goiás, including the collect, treatment and distribution of treated water, and identified ways of managing providers of sanitation services. It was observed that 61% of the supply systems provide by surface water supply system (SWSS). Mixed water supply systems (MWSS) and underground water supply system (UWSS) found up to 50% non-specific departments and 50% for the departments, respectively. Regarding the source of supply, it was noted that the worst results for the quality of supply source were assigned by the WSS managed by non-specific sanitary services departments. Only the cities Abadiânia, Corumbá de Goiás, Mineiros, Rio Quente, Trombas, Caldas Novas, Catalão, Panamá and Senador Canedo add fluorine to their treated water. In relation of the reservation and distribution system of treated water, there is the prevalence of elevated tanks. The worst scenarios for the reservation system and treated water distribution were found at the cities Cachoeira de Goiás, Guarinos, Mossâmedes, Nova Roma, Paranaiguara and São Simão. It was concluded that the WSS have diverse scenarios regarding the treatment of the water and the planning monitoring and maintenance of them are deficient. The second chapter identified the elements of risk perceived by the population associated with water resources. They evaluated the dangerous events by qualitative and quantitative techniques applied to goianos WSS managed by the own cities. The WSS were evaluated by collect system component, raw water reservoir and adduction (A); water treatment system (B); reservation system and distribution of treated water (C). The studied cities that have more high and very high risk, considering all components of the systems, are Cachoeira de Goiás, Guarinos, Mossâmedes, Nova Roma, Paranaiguara and São Simão. Regarding the UWSS, it seems that the A system component registered the same percentage to Cachoeira de Goiás and Guarinos. The B and C system components registered 62.5% and 50% at Cachoeira de Goiás and 75% and 78.5 % at Guarinos. The MWSS with the highest percentage of high and very high risks were situated at the cities Santa Rita do Novo Destino and Nova Roma (52.4 % for question A). Mossâmedes and Nova Roma were the cities that had the highest number of high risks and too high risks for the components B and C in MWSS. The cities Paranaiguara and São Simão had UWSS with the highest number of high and very high risk. The WSS at cities in the state of Goiás managed by the own cities feature deficiencies in the safe management of the water distributed to the population. It is necessary to adopt methodologies that addresses all components of the WSS regardless of system type. / Sistemas de abastecimento de água (SAA) para consumo humano tem o objetivo de produzir e fornecer água potável à população por meio de rede de distribuição. Entretanto, a necessidade de rever os procedimentos metodológicos existentes para a manutenção da quantidade e qualidade da água em níveis satisfatórios para o consumo da população fez com que a Organização Mundial de Saúde propusesse uma nova metodologia denominada Plano de Segurança da Água (PSA), ainda incipiente no Estado de Goiás. Nesse sentido, o estudo objetiva propor Plano de Segurança da Água aos 21 municípios do Estado de Goiás que apresentam SAA geridos pelas prefeituras. O estudo foi dividido em dois capítulos. O primeiro capítulo caracterizou os SAA de 21 municípios do Estado de Goiás operados pelas prefeituras, abrangendo a captação, o tratamento e a distribuição da água tratada, além de verificar as formas de gestão dos prestadores dos serviços de saneamento. Observou-se que quanto à gestão dos SAA, predominam-se as autarquias com 61% para sistema de abastecimento de água superficial (SAAS). Já nos sistemas de abastecimento de água misto (SAAS) e sistema de abastecimento de água subterrâneo (SAASU) constataram-se 50% para secretarias não específicas e 50% para os departamentos, respectivamente. Em relação à fonte de abastecimento, nota-se que os piores resultados para a qualidade da fonte de abastecimento são atribuídos aos SAA geridos por secretarias não específicas para os serviços de saneamento. Em relação ao sistema de tratamento de água, os municípios de Abadiânia, Corumbá de Goiás, Mineiros, Rio Quente e Trombas para SAAS e Caldas Novas, Catalão, Panamá e Senador Canedo para SAAM realizam fluoretação independente do método empregado para tratar a água. Quanto ao sistema de reservação e distribuição de água tratada, nota-se o predomínio dos reservatórios elevados. Os piores cenários para o sistema de reservação como de distribuição de água tratada foram encontrados em Cachoeira de Goiás e Guarinos; Mossâmedes e Nova Roma e Paranaiguara e São Simão. Concluiu-se que os SAA apresentam cenários diversificados em relação ao tratamento da água, deficitários quanto ao planejamento de ações de monitoramento e manutenção dos SAA. O segundo capítulo identificou os elementos de risco perceptíveis pela população associados aos recursos hídricos. Foram avaliados os eventos perigosos mediante técnicas quali-quantitativas aplicadas aos SAA goianos geridos pelas prefeituras. Os SAA foram avaliados por componente do sistema em captação, reservatório e adução de água bruta (A); sistema de tratamento de água (B); sistema de reservação e distribuição de água tratada (C). Entre os municípios estudados que possuem maior número de riscos altos e muito altos, considerando todos os componentes dos sistemas, destacam-se: Cachoeira de Goiás, Guarinos, Mossâmedes, Nova Roma, Paranaiguara e São Simão. Em relação ao SAAS, observou que o componente do sistema A registrou o mesmo percentual para Cachoeira de Goiás e Guarinos. Já o B e C registraram 62,5% e 50% para Cachoeira de Goiás e 75% e 78,5% para Guarinos. Os SAAM com o maior percentual de riscos altos e muito altos foram os situados em Santa Rita do Novo Destino e Nova Roma com 52,4% cada para A. Mossâmedes e Nova Roma foram os municípios que apresentaram SAAM com o maior número de riscos altos e muito altos para os componentes B e C. Paranaiguara e São Simão apresentaram SAASU com o maior número de riscos altos e muito altos. A Em SAA goianos geridos pelas prefeituras, notam-se deficiências na gestão segura da água distribuída à população. É necessária a adoção de metodologia que contemple todos os componentes dos SAA, independente da tipologia do sistema.

FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgico / A terceira ediÃÃo dos Guias para a Qualidade de Ãgua PotÃvel da OrganizaÃÃo Mundial de SaÃde â OMS trouxe uma nova visÃo e preocupaÃÃo com a saÃde, cuja finalidade à a garantia da qualidade da Ãgua como instrumento de proteÃÃo à saÃde pÃblica. Para isso, o Plano de SeguranÃa da Ãgua (PSA) foi proposto como ferramenta para assegurar a qualidade da Ãgua proveniente de um sistema de abastecimento de Ãgua a partir de um planejamento integral de avaliaÃÃo dos riscos e gestÃo, envolvendo todas as etapas do sistema de abastecimento, desde a bacia de captaÃÃo atà a sua distribuiÃÃo ao consumidor final. O plano envolve algumas medidas essenciais para garantia da qualidade da Ãgua: a avaliaÃÃo do sistema de abastecimento de Ãgua, o monitoramento operacional eficaz e a sua respectiva gestÃo. O desenvolvimento do plano tambÃm abrange algumas etapas essenciais e, dentre elas, inclui-se a avaliaÃÃo dos fatores de perigo e caracterizaÃÃo dos riscos. Os mÃtodos utilizados no PSA baseiam-se em muitos dos princÃpios e conceitos aplicados em outros sistemas de gestÃo de riscos, como o sistema de barreiras mÃltiplas e a anÃlise de perigo e de pontos crÃticos de controle (APPCC). O presente trabalho traz uma proposta metodolÃgica utilizando ferramentas baseadas na LÃgica Fuzzy e metodologias de AnÃlise MulticritÃrio, com o intuito de auxiliar no processo decisÃrio. Como estudo de caso, foram selecionados os Sistemas de Abastecimento de Ãgua (SAA) que atendem 13 dos 15 municÃpios da RegiÃo Metropolitana de Fortaleza, no Estado do CearÃ. Utilizando a metodologia pode-se concluir que os sistemas estÃo com nÃvel de pertinÃncia mais preponderante, de maneira geral, em uma escala de Risco Baixo, fora o caso especÃfico de apenas um deles, que ficou com maior nÃvel de pertinÃncia para a escala de Risco Moderado. AlÃm de indicar os nÃveis de pertinÃncia do risco em que se encontra cada SAA, a metodologia permitiu ainda classificÃ-los em funÃÃo da escala de risco. Numa escala de risco e em nÃvel relativo, os municÃpios puderam ser classificados em ordem, onde o de mais baixo risco evidenciado foi o municÃpio de Maracanaà e, o Ãltimo, o de Cascavel. Ademais, a metodologia mostrou-se ser uma alternativa para fornecer subsÃdios para avaliaÃÃo dos riscos e tomada de decisÃo em consonÃncia com as diretrizes dos Planos de SeguranÃa da Ãgua. / The third edition of the Guidelines for Drinking Water Quality of the World Health Organization - WHO brought a new vision and concern for health, whose purpose is the guarantee of water quality as a tool for public health protection. For this, the Water Safety Plan (PSA) was proposed as a tool to ensure the quality of water from a water supply system from a comprehensive planning risk assessment and management, involving all stages of system supply, from catchment to distribution to final consumers. The plan involves some key measures to ensure the water quality evaluation system for water supply, operational monitoring and its effective administration thereof. The development plan also covers some essential steps, and among them include the assessment of risk factors and risk characterization. The methods used in the PSA are based on many of the principles and concepts applied in other systems of risk management, as the system of multiple barriers and Hazard Analysis and Critical Control Point (HACCP). This paper presents a methodology using fuzzy logic-based tools and Multicriteria Analysis methodologies in order to assist in decision making. As a case study, we selected the Water Supply Systems (WSS) that serve 13 of the 15 municipalities of the Metropolitan Region of Fortaleza, in CearÃ. Using the methodology can be concluded that systems with a level of relevance with a Low Risk scale are more prevalent, in general, outside the specific case of only one, who took higher level of relevance in the Moderate Risk scale. Besides indicating the relevance of the levels of risk of each WSS, the methodology also allowed us to classify them according to the scale of risk. On a scale of risk and the relative level, the municipalities could be sorted, where the lowest risk was evident to Maracanaà and the last, to Cascavel. Furthermore, the methodology proved to be an alternative to providing subsidies for risk assessment and decision making in line with the guidelines of the Water Safety Plans.