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Article

Risk Management Associated with Surface Sources of Public Water Supply in Urban and Rural Areas in a Developing Country

by
Isabel Francisco de Araújo Reis
1,*,
Hamilton Cristiano Leôncio
2,
Ana Letícia Pilz de Castro
3 and
Aníbal da Fonseca Santiago
4
1
Environmental Engineering Graduate Program, School of Mines, Federal University of Ouro Preto, Ouro Preto 35400-000, Brazil
2
Biological Sciences Program, Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto 35400-000, Brazil
3
Department of Civil Engineering, Federal University of Ouro Preto, Ouro Preto 35400-000, Brazil
4
Department of Environmental Engineering, Federal University of Ouro Preto, Ouro Preto 35400-000, Brazil
*
Author to whom correspondence should be addressed.
Water 2024, 16(19), 2732; https://doi.org/10.3390/w16192732
Submission received: 11 June 2024 / Revised: 18 July 2024 / Accepted: 19 July 2024 / Published: 26 September 2024
(This article belongs to the Section Urban Water Management)
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Abstract

:
This research aimed to apply a risk management methodology to multiple surface water sources in urban and rural areas of a developing country. The applied methodology enabled the identification of hazards, classification, and the prioritization of risks at 21 collection points in the rural area and 9 collection points in the urban area. Both rural and urban areas exhibited common events with a high-risk level, such as human access (100% in urban areas and 90% in rural areas), climatic events, and inadequate collection structures (100% of points in both urban and rural areas). However, rural areas presented specific risks associated with animal husbandry (70% of points with high risk), a lack of monitoring, limited infrastructure (30% of points with high risk), and wildlife, including birds and worms (50% of points with high risk in rural areas and 10% in urban points). On the other hand, urban areas faced challenges related to vandalism and sabotage (high risk in 40% of points). Understanding these similarities and differences permits integrated risk management among the various stakeholders who can contribute to risk management within a watershed.

1. Introduction

Risk management in water supply systems (WSS) is the process of identifying hazards, classifying risks, and proposing control measures, all the way from the water source to the delivery of water to the end consumer. These are important stages in water safety plans (WSP). In this process, the protection of the watershed that contributes to the catchment source is one of the crucial factors in providing an effective water supply and reducing treatment costs. Furthermore, this protection helps to reduce the incidence of waterborne diseases when the treatment process fails [1]. The capability of cutting the costs with unnecessary water treatment technologies makes WSP extremely useful in developing countries where financial resources are scarce [1,2].
The lack of cohesion and the disparate interests of water utility companies and watershed users, as well as the lack of legislation on the matter of risk management, all point to the need for the participation of a multidisciplinary team and the presence of objective guidelines, without which it is difficult to implement the proper risk management of supply sources [3]. In developing countries, in addition to these difficulties, there is also a lack of interest on the part of utility companies in the implementation of WSP, since this requires financial investment and the hiring of a qualified multidisciplinary team, elements not easily found in these countries.
In addition to these challenges, the execution of a WSP requires the assessment of operational and management aspects of the entire river basin besides the catchment point, as the latter reflects land uses throughout the river basin. Therefore, the enforcement of control measures that aim to mitigate risk at the point of capture involves the entire river basin. Consequently, risk management provides enhanced security to end users, for reducing the entry of contaminants into the water source ensures greater safety to the supply system users than the removal of contaminants through treatment processes [4,5].
Furthermore, social, political, economic, or regulatory limitations can pose significant obstacles to the protection of source waters. Some countries, including Brazil, lack the necessary legislation and authority to impose restrictions on land use. Additionally, the cost–benefit analysis of protecting source water is not always clearly identifiable, complicating efforts to persuade governments to implement such initiatives. The results of water treatment phases are more easily measurable than the benefits identified in the improvement of source water [6].
The institutional responsibility for controlling economic activities in the area of influence of the watershed does not lie with the sanitation companies or bodies responsible for the supply system, thus justifying the difficulty in implementing risk management at the source. Therefore, collaboration with other external agents is essential to ensure effective risk management [7]. However, although challenging, the ability to carry out risk management already at the original watershed is an opportunity for developing countries to have access to information on the land use of their river basins, which will serve as an input for identifying hazards in the catchment source as well as for decision making on strategic issues such as the economy and the environment [4].
This study is intended to identify, evaluate, and prioritize existing and potential risks in urban and rural water supply systems of developing countries, using risk assessment and prioritization methods. This allows for the proposal of the better adaptation of raw water quality to the characteristics of treatment processes, resulting in a reduction in operating costs, which is particularly crucial for developing nations. The innovative purpose of this paper is to share practical experience and examples of ‘good practices’ which may be of benefit to professionals and regulators, and particularly those new to WSP development and application. Demonstrating the application of this methodology (its potential and limitations) is relevant, as it can provide guidelines for building risk management strategies in WSS in developing countries.
In addition, it is hoped that the publication of this research will promote the dissemination of a topic that is still incipient in the literature of developing countries. The research can serve as a reference for studies that address this issue in various regions, including rural districts. It should be mentioned that rural areas in developing countries require significant investments to achieve average coverage levels similar to those in developed countries, considering that millions of people still lack access to adequate drinking water. Globally, this study is also relevant in the light of the United Nations’ Sustainable Development Goal (SDG) 6, which aims to produce safe water.

2. Materials and Methods

2.1. Region of Study

The municipality of Mariana is located in the State of Minas Gerais, Brazil, and is supplied by multiple urban and rural supply sources. The population recorded in the last demographic census, of 2022, was 61,387 inhabitants [8]. Figure 1 displays the location map of the city of Mariana.

2.2. Characterization of Polluting Sources

In order to select the hazardous events that could be related to supply sources, it was necessary to identify the main polluting sources and potential hazards that could be associated with watersheds. The main watersheds of the municipality are the Gualaxo do Sul river basin, Gualaxo do Norte river basin, and Carmo river basin. In all, 24 field visits were carried out, describing the structural characteristics of the catchments, such as the struc-tural conditions of the raised dam, the presence of bottom and grid discharge, land uses up-stream of the supply source, and the type of abstracted water treatment carried out. After concluding this evaluation, based on the results of the water quality diagnosis and biblio-graphic research, an analysis was carried out whether or not the 22 hazardous events listed in the river basins were or were not relevant to each catchment point: the leaching of contaminants released in the mining activity, the discharge of domestic wastewaters, vandalism and sabotage, mechanical, electrical, and structural failures and communication difficulties [9,10], erosion with the deposition of soils and sediments, intensive fishing, fish farming and mortality of fish, physical obstacles such as a trash racks obstructed by leaves preventing the flow of water, animal husbandry [10], climatic events (drought and dry spells, forest fires) [9,11], recreational activities, the discharge of hazardous waste in soil and water, wildlife, the existence of sites contaminated by hazardous waste, human access, access to animals including birds and worms, inappropriate intake, inadequate vegetation, silviculture (Forest) [9], the leaching of pesticides and fertilizers from agriculture [9,10,12], algae bloom [9,10,12,13], the leaching of contaminants released in mining activities [13], and the compliance of water quality parameters [14].
The selection of the 22 hazardous events was based on documentary research in articles, books, theses, and dissertations that contained characteristics of the watersheds where the water intake points were located. Additionally, field visits were conducted to better characterize the hazards and hazardous events. A total of 24 visits were made to each intake point between January 2019 and December 2020. Observations from these visits were recorded and systematized in spreadsheets. The ESRI® ArcGis 10.2 software was used to evaluate the region upstream of the intake point. Concurrently, communication with the sanitation company’s sectors was carried out to assess whether the 22 observed events were relevant to the studied intake points. It is noteworthy that communication with the sanitation company was conducted through personal contact with the managers and employees involved in each evaluated stage. The company did not have computerized record systems with complete information.
The eleven events that were considered relevant to the Mariana catchment systems were associated with potential hazards: (1) physical obstacles such as a trash rack obstructed by leaves preventing the draining of water, (2) wildlife including birds and worms, (3) human access, (4) actions of vandalism and sabotage, (5) climatic events (drought and dry spell, forest fires), (6) erosion with the deposition of soils and sediments, (7) animal husbandry, (8) inadequate vegetation, (9) an inappropriate intake, (10) mechanical, electrical, and structural failures and communication difficulties), and (11) the compliance of water quality parameters.
After these procedures, the risk classification and prioritization matrix was applied to the hazardous events. The matrix uses the Probability of Occurrence Scale and a scale of the Severity of Consequences of the hazardous event for the health of the population served, in which the product of the score of these two scales will result in the Risk Classification matrix [9,15]. The Table S1 presents the criteria used in assessing the likelihood of occurrence and the severity of consequences in the risk matrix.
The classified risks were associated with their respective intake point and identified in the Mariana map, where the risks were classified as low (green), moderate (yellow), high (orange), and extreme (red), as recommended by the risk classification matrix. The intake points that presented hazardous events with a high-risk score must be prioritized. Table 1 presents the criteria used in applying the risk classification and prioritization matrix. For each intake point, procedures were established to calculate the occurrence and severity of each hazardous event. These criteria were established through 24 field visits and in accordance with the guidelines of the World Health Organization [15,16].

3. Results and Discussion

3.1. Characterization of Polluting Sources

The geological, morphological, and pedological aspects and climate, vegetation, and erosion potential showed similarities in the characteristics found in the three watersheds evaluated. This equivalence reflected on the land use and influenced the hazardous events identified upstream of the supply sources. The main polluting sources found in the municipality’s watersheds were agriculture, livestock (unconfined livestock), swine, and poultry farming, mining, untreated domestic wastewater, fires, erosion, rural rainwater drainage, urban rainwater drainage, and informal mining.
In farming areas, there may be pesticides, fertilizers, increased turbidity, and changes in color and nutrients. Algal blooms may occur during this activity. In livestock (unconfined livestock), swine, and poultry farming, pathogenic microorganisms and an increase in nutrients, turbidity, and water color may occur [9]. Algal blooms may occur during this activity. In mining, one may find leach substances such as phosphorus and aluminum [17]. Only in the Gualaxo do Sul river basin was informal mining not identified. In untreated domestic wastewater, pathogenic microorganisms, an increase in nutrients [9], and increased turbidity and color may occur. Fires may lead to an increase in calcium, magnesium, potassium, phosphorus, and nitrogen in the water and changes in the pH and dissolved oxygen in the water [18]. In the case of erosion, there may be an increase in the water turbidity. In rural rainwater drainage, pathogenic microorganisms and increased turbidity and water color may occur. In urban rainwater drainage, there may be the occurrence of lead, zinc, and petroleum products from streets and roads which are leached into waterways, increasing the color, turbidity and number of microorganisms from domestic animals in the water [9]. In informal mining, one can find arsenic and mercury associated with mining activity. Other elements such as Ag, Sb, Cu, Pb, and Zn may be found in gold deposits and may be important sources of these elements [19].
When evaluating these polluting sources, it is clear that the control of these activities is not the institutional responsibility of the sanitation company, since controlling economic activities in the area of influence of the watershed is the responsibility of environmental regulatory bodies. Thus, integrating these diverse interests is one of the challenges for implementing control measures in the areas of influence of the catchment point [4,5]. Partnering with these bodies can be an important management path. However, relying on partnerships can cause difficulties in the risk mitigation process.
Catchments without proper structures (dams with precarious raising, the absence of a trash rack or bottom intake discharge) may be associated with changes in turbidity and water flow. The intake points P13, P14, P16, P17, P18, P19, P20, P21, P22, P23, P24, P25, P26, P27, P28, P29, and P30, located in the rural districts of Mariana, did not have proper structures (poor regulation of the dam and the absence of a trash rack or bottom discharge), in addition to having no structures to carry out raw water treatment processes. At the intakes points P13, P14, P17, P18, P19, and P20, the water undergoes a disinfection process, but no clarification process. This result demonstrated that rural sanitation in Brazil is precarious and that only a small number of rural areas are provided with this service, and even so, inadequately [20].
In the district seat (intake points P1, P2, P3, P4, P5, P6, P7, P8, P9, P10, P11, P12, and P15), one can see the presence of four systems with complete cycle water treatment (sample points P1, P2, P3, and P4), and in intake points P5, P6, P7, P8, P9, P10, P11, P12, and P15, the distributed water only goes through a disinfection process, but there are no structures to carry out the water clarification process. Regarding the structural level of the intake points in the district seat, all of them have proper structures when compared to the intake points of rural districts (with the exception of points P8 and P15), presenting dams raised with reinforced concrete, a trash rack, and bottom discharge. This result identified precarious structures for collecting water in rural Brazilian districts [21].

3.2. Application of the Risk Classification Matrix

Figure 2 shows the percentage of risks in urban and rural areas of the municipality of Mariana.
The risk assessment results depicted in Figure 2 indicated that certain hazardous events received the same risk classification in both urban and rural areas. Consequently, 100% of the evaluated intake points in both urban and rural areas were classified as high-risk for climatic events, mechanical, electrical, and structural failures, and physical obstacles such as a trash rack obstructed by leaves preventing the drainage of water. The event “wildlife including birds and worms” presented a low-risk level in 89% of the urban intake points and 52% of the rural intake points. Complementarily, the extreme risk level was identified in 11% of the urban intake points and 48% of the rural intake points.
Regarding the hazardous event “human access”, the results indicated a high-risk level in 56% of the urban intake points and 71% of the rural intake points. However, an extreme risk was observed in 44% of the urban intake points and 24% of the rural intake points. Additionally, for this hazardous event, 5% of the rural district intake points were classified as low-risk. For the hazardous event “vandalism and sabotage”, the results demonstrated that 56% of the urban intake points were classified as low-risk, while 44% were classified as high-risk. In the rural areas, in that same event, 100% of the intake points were classified as low-risk.
In the hazardous events “animal husbandry”, “inappropriate vegetation”, and “compliance with water quality parameters”, a low-risk level was identified in all urban intake points. In rural areas, for the event “animal husbandry”, 33% of the intake points were identified as low-risk and 67% as high-risk. Concerning the events “inappropriate vegetation” and “compliance with water quality parameters”, the risk assessment indicated that 62% of the intake points were classified as low-risk and 38% as high-risk. For the hazardous event “erosion with deposition of soils and sediments”, the results indicated a low risk in 67% of the urban intake points and 86% of the rural intake points. In the same event, a moderate risk was indicated in 33% of the urban intake points and in 14% of the rural intake points. Figure 3a,b depict the 11 hazardous events associated with their risks, using a colorimetric scale, at each of the 30 intake points in Mariana.
In Figure 3a,b, it can be observed that high and extreme risks were identified both in the district seat and in rural districts. However, hazardous events classified as extreme risk (wildlife, human access, and livestock) were identified at fewer intake points (P2, P3, P10, P11, and P12 in Figure 3a,b) compared to rural districts (P13, P16, P17, P18, P20, P21, P22, P23, P24, P25, P26, P27, P28, P29, and P30).
Two factors corroborated the risk classification as extreme (hazardous event) for wildlife and human access at point P3: the circulation of people in the areas upstream of the intake point and the presence of planorbids of the genus Biomphalaria contaminated with Schistosoma mansoni, an etiological agent of schistosomiasis, in the supply source. Identifying hazards such as the presence of planorbids of the Biomphalaria glabrata genus in the catchment area and proposing control measures to mitigate the risk associated with their presence is essential. Schistosoma mansoni affects approximately 200 million people worldwide across approximately 75 countries, with schistosomiasis being endemic in about 49 countries across the Americas, the Antilles, and Africa, including Brazil. In this context, risk management methodologies in these countries can prioritize control measures that will positively impact the water quality. Another criterion considered in the risk classification was the test results of the historical series of E. coli, as this microorganism is considered the most specific indicator of the recent fecal contamination of water [22]. Since the quantifications of E. coli were below the reference values set forth and established by Brazilian legislation, no fecal contamination was detected. However, contaminated planorbids were found in the spring, thus underscoring the importance of conducting risk management at water sources and catchment points, in accordance with the guidelines recommended by the WSP. Even though the test results were below the predetermined limits, a priority risk was identified at that intake point.
Intake points located in rural districts, such as P17, P20, P21, P23, P24, and P26, and point P2 in Figure 3b, responsible for supplying the main district, have been classified as extreme risks (hazardous event: subsistence cattle raising). This classification stems from the presence of animal waste (from cattle and poultry) at the water supply sources and intake points, which can contribute to the spread of pathogenic microorganisms, alterations in the water turbidity, color, and biochemical oxygen demand (BOD), as well as increased concentrations of substances such as nitrogen, phosphorus, organic matter, metals, salts, and sediments [23]. Cryptosporidiosis is an example of a disease that can originate from domestic animals and cattle, highlighting the imperativeness of prioritizing the implementation of control measures at these intake points [9]. An important control measure would be to promote confined animal feeding operations through municipal ordinances that provide financial incentives. The proper management of animal waste under such measures would prevent water source contamination from these wastes [24].
In addition to the presence of animals, another criterion that intensified the risk classification was the absence of historical data series for quantifying E. coli levels. Specifically, at intake points P22, P25, P27, P28, P29, and P30 during hazardous events related to animal husbandry and compliance with water quality parameters (Figure 3b, located in rural districts), there were no historical data series available for monitoring this parameter. For in-take points lacking historical E. coli data series, the maximum risk was attributed to hazardous events such as cattle raising, wildlife interaction, and human access. When insufficient data are available to apply scores on the likelihood of occurrence and the severity of consequences scales, the risk should be considered high until further investigations and data collection provide sufficient grounds for classification [25].
The absence of historical data series also contributed to an increased risk (classified as high for hazardous events such as wildlife and human access) at intake points P21, P23, P24, P26, and P30, as shown in Figure 3a. It can be inferred that in rural areas, the lack of E. coli monitoring was a determining factor in the elevated risk classification. The isolation of the intake points (presence of fences) and access conditions, such as natural challenges related to the terrain relief where intake points are situated, were also significant factors contributing to the high-risk classification for hazardous events related to human access at intake points P4, P5, P6, P7, P8, P9, P14, P17, P19, P27, P28, P29, and P30, as depicted in Figure 3a (intake points located in the district seat and rural areas).
Poor conditions at intake points, including the absence of essential structures like properly regulating dams, trash racks, and bottom discharge systems, as well as a lack of vegetation, were also critical factors in the high classification of hazardous events related to an inadequate intake and vegetation, as shown in Figure 3b. Intake points P2, P8, P13, P14, P15, P17, P18, P19, P20, P24, P25, P28, and P29, which have been operational for more than 20 years and require ongoing maintenance that can cause water flow changes and turbidity, were classified as high-risk.
Older water mains, typically over 20 years old when made of polyvinyl chloride (PVC) and over 35 years old when made from cast iron, are generally more susceptible to maintenance issues compared to newer pipes. The aging of these structures leads to failures, ruptures, and an increased likelihood of scaling. In addition to these vulnerabilities, access to intake points is hindered during maintenance processes, as they often lack direct connections to main roads. This results in delays, requiring travel on foot over long stretches of unpaved roads, lacking signage, and through unmaintained trails, which is especially challenging during night-time maintenance. The mountainous terrain further complicates these efforts. Research has shown that the maintenance of the mains in the Mariana catchment systems may occur weekly due to inadequate installation and protection, leaving them vulnerable to external impacts and necessitating frequent repairs. Communication difficulties also contribute to these challenges. It is crucial to adopt preventive measures such as establishing leak detection schedules to mitigate these issues [26].
The movement of people upstream of the springs, the absence of separation fences, and easy access to catchment areas have significantly influenced the high classification of hazardous events related to vandalism and sabotage at the intake points. These points are located both in the district seat and in rural districts, as depicted in Figure 3a. At the assessed intake points, this hazardous event may be associated with valve breaks and/or the theft of electrical wires from the grid, thereby resulting in a high-risk classification of electrical, mechanical, or structural failures at the intake points, as shown in Figure 3b.
The vandalism and sabotage actions can be associated with physical, chemical, and biological hazards as, in some of these episodes, people can release contaminants into the water, having a harmful effect on human health or causing significant organoleptic changes such as color change, changes in turbidity, and a shortage of water. However, in the structures of Mariana, vandalism is related to issues of intermittence in the water supply system, associated with changes in turbidity, color, and shortages, although the release of contaminants into the water has not been identified [27].
One method of safeguarding water supply systems is to identify vulnerabilities that could present threats [27,28]. Another approach is to investigate potential motivations associated with attacks and identify the locations where such events are most likely to occur. Targeting water supply infrastructure may aim to destabilize political structures, as water scarcity affects numerous individuals, leading to public grievances [28]. This conclusion is applicable in the case of the municipality of Mariana, where the position of the agency manager is closely tied to the municipal executive branch, making sabotage actions potentially aimed at disrupting governance. The research indicates that sabotage incidents peak during election periods.
Prolonged drought, combined with high temperatures and intense winds, are characteristics that influenced the classification of high-risk hazardous climate events such as forest fires, droughts, and dry spells in Figure 3a [29]. Additionally, the presence of conservation units such as the APA (Environmental Protection Area), Seminário Menor, Tripuí Ecological Station, and Itacolomi Park further exacerbates these risks and can contaminate water bodies [30]. Forest fires constitute one of the sources of pollution in the studied watersheds. In 2020, there were 8737 cases of fires in Minas Gerais. Of these, 1155 were registered in August, 3467 cases in September, and 2404 in October. In the Atlantic Forest biome, 17,572 cases of forest fires were recorded. Of these, 4079 were identified in August, 4279 in September, and 2553 in October. There is a large concentration of fires in the months of August, September, and October and it is essential to intensify preventive measures in this period [31]. In Itacolomi State Park, there are areas where forest fires were recorded, and it is important to control these disasters not only in Mariana, but throughout the Atlantic Forest biome, especially in the watersheds studied [32].
Dry spells also influenced the high classification of the hazardous event illustrated in climatic events in Figure 3a, as evidenced by the decreased water flow in the municipality of Mariana during the dry season. To mitigate this issue, water trucks are contracted, despite research stating that the basins in the region currently maintain a comfortable water balance situation, as estimated demands, both current and future, are lower than available water resources. Generally, no water deficits were identified in the region’s basins during periods of scarcity (year 2010 and projections for 2030). Adequate volumes were available to meet human and economic water supply demands. However, this apparent contradiction can be attributed to the fact that users of the municipal water supply system are not metered, and there is no collection of fees for water treatment, leading to wastage that directly impacts water availability [33].
The high rainfall in the region where the intake points are located, coupled with steep slopes and the presence of soils highly susceptible to erosion (haplic cambisols), has rendered intake points P1, P3, P5, P6, P10, and P11 particularly prone to laminar erosion, which typically occurs during the rainy season. This situation influenced their intermediate-risk classification (moderate) in the hazardous event of erosion with soil deposition, as depicted in Figure 3b [34].
The watersheds utilized in the municipality’s water supply system encompass extensive areas of preserved Atlantic forest; however, certain areas are occupied by pastures and deforested lands [34]. Through fieldwork and the Geographic Information System (GIS), pastures and deforested areas have been identified upstream of intake points P17, P19, P20, P21, P24, P25, P27, and P29, highlighting their susceptibility to erosion. Vegetation plays a critical role in mitigating erosive processes that can lead to changes in turbidity, presenting potential hazards associated with inadequate vegetation management at intake points and water sources, thereby influencing their classification as under high risk in this hazardous event [35].
The intake points of the district seat and rural districts of the municipality of Mariana are located in areas with semideciduous forests which go through the leaf fall process annually [29]. Thus, the hazardous event of physical obstacles such as a trash rack obstructed by leaves in Figure 3a can cause a color change in the water. In the study, it was determined that the trash racks at the intake points of the Mariana water supply systems are cleaned daily, with no noticeable changes in the water quality or negative effects on the health of users. Therefore, this contributes to a low-risk classification. Regarding specific parameters such as E. coli, the annual geometric mean, cyanobacterial count, color, turbidity, and pH, the test results were found to be below the maximum allowable values (VMP) at all springs with historical data for evaluation. However, intake points P21, P22, P23, P24, P27, P28, P29, and P30 located in the rural districts lacked historical data for these parameters. Consequently, these intake points were classified as posing an extreme risk in terms of compliance with water quality parameters, as shown in Figure 3b.
Among the contaminants assessed, manganese exceeded the VMP at the P20 spring during the rainy season. The presence of manganese in water may stem from natural or anthropogenic sources. In the Mariana region, the manganese presence has been linked to the rainy season and soils derived from schists, phyllites, and canga (a type of ferricrete). Thus, the presence of manganese in the water may have occurred due to the lithological characteristics of the studied region [25]. There is no evidence of the harmful effects of manganese on human health [15]. However, high concentrations in natural waters can cause organoleptic changes [36]. These characteristics justify the low risk in complying with the water quality parameters in Figure 3b.
The other groups of contaminants evaluated presented test results below the VMP established for raw water, as recommended by GM/MS Ordinance No. 888, dated 4 May 2021, [36]. The intake points P23, P24, P25, and P26 did not present historical series for any of these contaminants evaluated. Thus, these catchment points were classified as extreme-risk in compliance with the water quality parameters during the hazardous event, as shown in Figure 3b. The lack of historical series of water quality data in the rural district WSS is another factor that impacted the risk classification of the water sources studied in the research. As such, the development of this type of methodology serves as a data input for developing countries to prioritize the construction of historical series of water quality data in their WSS.
Developing the risk management methodology in both urban and rural areas was important, as the main challenge for water suppliers is the identification and risk assessment of hazards associated with the water source [37]. Additionally, implementing and expanding the methodology for rural water supply systems ensures the protection and safety of water resources and helps maintain consumer health [38].
The research contributed practical examples of the implementation of the risk classification and prioritization matrix in water sources, as the analysis of hazards and risk assessment is the primary challenge for water suppliers to implement the Water Safety Plan (WSP). Additionally, the creation of these risk matrices aids in the implementation of audits in locations where the WSPs have been implemented, facilitating risk management [37].
The records of identified risks in the research support the evaluations of control measures implemented at collection points in urban and rural areas, as risk management methodologies must be continuously reviewed and updated by water concessionaires. Some hazardous events such as wildlife (including birds and worms), human access, actions of vandalism and sabotage, climatic events (drought and dry spells, forest fires), erosion with the deposition of soils and sediments, animal husbandry, and inappropriate vegetation do not depend solely on the risk management of the water concessionaire. Therefore, collaboration with other external agents is essential to ensure effective risk management. This is achieved through a combination of formal and informal processes, supported by good communication and strong working relationships [6].
The limitations of the research include the lack of historical data at certain catchment points, which impacted the risk classification and suggested the need for alternative approaches for areas with insufficient data. Another limitation of the research is the data collection from the water supply system through personal communication with managers and workers of the supply system. From this perspective, there was a reduction in the reliability of the data when compared to written records. However, this procedure helped involve the team in the application of the risk classification matrix, as risk management methodologies recommend that the execution of their steps should involve managers and operators of the supply system.

4. Conclusions

The identification of hazards, classification, and the prioritization of risks was conducted at 21 collection points in rural areas and 9 collection points in urban areas. Both rural and urban areas exhibited common events with a high-risk level, such as human access (100% in urban areas and 90% in rural areas), climatic events, and inadequate collection structures (100% of points in both urban and rural areas). However, rural areas presented specific risks associated with animal husbandry (70% of points with a high risk), a lack of monitoring, limited infrastructure (30% of points with a high risk), and wildlife, including birds and worms (50% of points with a high risk in rural areas and 10% in urban points). On the other hand, urban areas faced challenges related to vandalism and sabotage (a high risk in 40% of points).
Rural and urban areas share some risks in common, such as the presence of contaminating substances from agriculture, livestock, and industrial activities. However, rural areas presented specific risks associated with animal husbandry, a lack of monitoring, and limited access to water treatment facilities. On the other hand, urban areas had challenges related to the presence of vandalism and sabotage in supply structures. Understanding these similarities and differences was essential for adapting risk management measures according to the characteristics of each region.
The research carried out has brought advances in the risk management of water supplies in urban and rural environments because it was sensitive and effective for identifying, evaluating, and prioritizing risks, incorporating aspects of water quality and the characteristics of river basins. In addition, the research can serve as a basis for decision making and risk mitigation actions in water supply systems, since by identifying hazards and prioritizing risks, it is possible for managers to identify and prioritize important control measures in their supply systems. The study’s limitations include the lack of historical data at certain catchment points, which impacted the risk classification, suggesting the need for alternative approaches for areas with insufficient data.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16192732/s1. Table S1 presents the criteria used in assessing the likelihood of occurrence and the severity of consequences in the risk matrix.

Author Contributions

Conceptualization, I.F.d.A.R., A.L.P.d.C. and A.d.F.S.; methodology, I.F.d.A.R. and H.C.L.; software, H.C.L.; validation, I.F.d.A.R., A.L.P.d.C. and A.d.F.S.; formal analysis, I.F.d.A.R., A.L.P.d.C. and A.d.F.S.; investigation, I.F.d.A.R. and H.C.L.; resources, I.F.d.A.R.; data curation, I.F.d.A.R.; writing—original draft preparation, I.F.d.A.R.; writing—review and editing, I.F.d.A.R. and A.d.F.S.; visualization, A.L.P.d.C. and A.d.F.S.; supervision, A.L.P.d.C. and A.d.F.S.; project administration, A.L.P.d.C.; funding acquisition, A.L.P.d.C. and A.d.F.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Coordination for the Improvement of Higher Education Personnel—Brazil (CAPES)—Financing Code 001, Federal University of Ouro Preto and Postgraduate Program in Environmental Engineering.

Data Availability Statement

The survey data are available at: http://www.repositorio.ufop.br/jspui/handle/123456789/14467.

Acknowledgments

The authors express their gratitude to the Coordination for the Improvement of Higher Education Personnel—Brazil (CAPES)—Financing Code 001, the Federal University of Ouro Preto, and the Postgraduate Program in Environmental Engineering and Autonomous Water and Sewage Service of Mariana.

Conflicts of Interest

The authors declare no conflicts of interest.

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Water 16 02732 g001
Figure 1. Location map of the Municipality of Mariana, inserted in the Ouro Preto microregion, in the State of Minas Gerais, Brazil.
Figure 1. Location map of the Municipality of Mariana, inserted in the Ouro Preto microregion, in the State of Minas Gerais, Brazil.
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Water 16 02732 g002
Figure 2. Percentage of risks in urban and rural areas. L: Low, M: Moderate, H: High, E: Extreme, U: Urban Area, R: Rural Area; (1) physical obstacles such as a trash rack obstructed by leaves preventing the draining of water, (2) wildlife including birds and worms, (3) human access, (4) actions of vandalism and sabotage, (5) climatic events (drought and dry spell, forest fires), (6) erosion with deposition of soils and sediments, (7) animal husbandry, (8) inappropriate vegetation, (9) inappropriate intake, (10) mechanical, electrical, and structural failures and communication difficulties, and (11) compliance of water quality parameters.
Figure 2. Percentage of risks in urban and rural areas. L: Low, M: Moderate, H: High, E: Extreme, U: Urban Area, R: Rural Area; (1) physical obstacles such as a trash rack obstructed by leaves preventing the draining of water, (2) wildlife including birds and worms, (3) human access, (4) actions of vandalism and sabotage, (5) climatic events (drought and dry spell, forest fires), (6) erosion with deposition of soils and sediments, (7) animal husbandry, (8) inappropriate vegetation, (9) inappropriate intake, (10) mechanical, electrical, and structural failures and communication difficulties, and (11) compliance of water quality parameters.
Water 16 02732 g002
Water 16 02732 g003aWater 16 02732 g003b
Figure 3. (a,b) Intake points associated with their risk classification. P1—Belém intake, P2—Serrinha intake, P3—Principal do Seminário intake, P4—Matadouro intake, P5—Efigênia intake, P6—Pantera intake, P7—Maquiné intake, P8—Del Rey intake, P9—Cris-tal intake, P10—Dulico intake, P11—Cartucha intake, P12—Gogô intake, P15—Bicão intake (PIPA), P16—Bandeirantes intake, P21—Coelhos intake, P22—Zeca Barbosa intake, P23—Água Fria intake, P24—Flavinho intake, P25—Arthur intake, P26—Ferreira intake, P13—ETA Padre Viegas intake, P14—Buraco da Onça intake, P17—Adro intake, P18—Barreira intake, P19—Buraco do Juá intake, P20—Tombadouro intake, P27—Águas Claras intake, P28—Patrimônio intake, P29—Serra do Coco intake, and P30—Camargos intake (in-take points of rural districts).
Figure 3. (a,b) Intake points associated with their risk classification. P1—Belém intake, P2—Serrinha intake, P3—Principal do Seminário intake, P4—Matadouro intake, P5—Efigênia intake, P6—Pantera intake, P7—Maquiné intake, P8—Del Rey intake, P9—Cris-tal intake, P10—Dulico intake, P11—Cartucha intake, P12—Gogô intake, P15—Bicão intake (PIPA), P16—Bandeirantes intake, P21—Coelhos intake, P22—Zeca Barbosa intake, P23—Água Fria intake, P24—Flavinho intake, P25—Arthur intake, P26—Ferreira intake, P13—ETA Padre Viegas intake, P14—Buraco da Onça intake, P17—Adro intake, P18—Barreira intake, P19—Buraco do Juá intake, P20—Tombadouro intake, P27—Águas Claras intake, P28—Patrimônio intake, P29—Serra do Coco intake, and P30—Camargos intake (in-take points of rural districts).
Water 16 02732 g003aWater 16 02732 g003b
Table 1. Criteria that were used in applying the risk classification and prioritization matrix. O: Probability of occurrence, S: Severity of consequences, P: Scoring, C: risk classification. L: Low, M: Moderate, H: High, E: Extreme.
Table 1. Criteria that were used in applying the risk classification and prioritization matrix. O: Probability of occurrence, S: Severity of consequences, P: Scoring, C: risk classification. L: Low, M: Moderate, H: High, E: Extreme.
Dangerous EventOccurrence (Periodicity)DangerRisk Assessment
OSPC
1Leaf fallPhysical (color change)212L
2Presence of animals at the capture point and its relationship with results of E. coliMicrobiological (presence of pathogens, for example, Schistosoma mansoni) 155L
5525E
3Protection of the water source and difficult accessMicrobiological (presence of pathogens, for example, Schistosoma mansoni) 5525E
155L
3515H
4Breaking records and/or theft of wires in the electrical networkPhysical (changes in turbidity and color) Microbiological (penetration of pathogens)3515H
155L
5Drought, drought and forest firesChemical (contaminants present in cizas), microbiological (for example, pathogens related to diarrheal diseases, viral hepatitis, diseases caused by vectors)2510M
6Terrain slope, soil characteristics, and rainfallPhysical (turbidity changes)133L
5315M
7Presence of cattle and anseriformes at the capture point and its relationship with results of E.coliMicrobiological (presence of pathogens, for example, Klebsiella sp., Citrobacter sp., Enterobacter sp. E. coli, Salmonella Silva et al. (2014)155L
5525E
8LoggingPhysical (turbidity changes)5315M
133L
9Structural features (adequate level lifting dam, grating, and bottom discharge)Physical (turbidity changes)5315M
133L
10Mechanical, electrical, and structural failures and communication difficultiesPhysical (turbidity changes)4312M
11Historical series not present for these parameters and showed a test result above the VMPPhysical, chemical, and microbiological 155L
5525E
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de Araújo Reis, I.F.; Leôncio, H.C.; de Castro, A.L.P.; da Fonseca Santiago, A. Risk Management Associated with Surface Sources of Public Water Supply in Urban and Rural Areas in a Developing Country. Water 2024, 16, 2732. https://doi.org/10.3390/w16192732

AMA Style

de Araújo Reis IF, Leôncio HC, de Castro ALP, da Fonseca Santiago A. Risk Management Associated with Surface Sources of Public Water Supply in Urban and Rural Areas in a Developing Country. Water. 2024; 16(19):2732. https://doi.org/10.3390/w16192732

Chicago/Turabian Style

de Araújo Reis, Isabel Francisco, Hamilton Cristiano Leôncio, Ana Letícia Pilz de Castro, and Aníbal da Fonseca Santiago. 2024. "Risk Management Associated with Surface Sources of Public Water Supply in Urban and Rural Areas in a Developing Country" Water 16, no. 19: 2732. https://doi.org/10.3390/w16192732

APA Style

de Araújo Reis, I. F., Leôncio, H. C., de Castro, A. L. P., & da Fonseca Santiago, A. (2024). Risk Management Associated with Surface Sources of Public Water Supply in Urban and Rural Areas in a Developing Country. Water, 16(19), 2732. https://doi.org/10.3390/w16192732

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