1 Introduction

Hazard is a phenomenon, an event, or occurrence (Smith 1992; Gunn 1992; Yin 2003; Haase 2012) that has the potential for causing harm to life or damage to property or the environment (Raetzo et al. 2002; Hutton and Haque 2003; ISDR 2010; Balica et al. 2012). Vulnerability refers to the limitation of a community to a hazard and the prevailing condition, including physical, socioeconomic, and political factors that adversely affect its ability to respond to hazards or disastrous events (Kumar 1987; Brouwer et al. 2007; Ginige 2009; Chen et al. 2012). However, the community-based disaster risk refers to the combined susceptibility and vulnerability of the community to potential damage caused by a particular hazard within a specified future time period (Tobin and Montz 1997; Khan 2007; Blaike et al. 1994). Risk is rooted in conditions of physical, socioeconomic, and environmental vulnerability that need to be assessed and managed on a continuous basis (Morrow 1999; Fekete et al. 2010). Disaster risk measures involve the assessment and mapping of hazards, identification of the elements at risk (Morshed and Huda 2002; Bartuska 2007; Menoni et al. 2012), and their vulnerability to a specific hazard, and formulating risk-reducing measures, including risk mapping and hazard prioritization (Van 2005; Fussel and Klein 2006; Tate 2012). Whether a disaster is major or minor, of national or local proportion, it is the people at the community or village level who suffer its adverse effects (Buckle 2001; Trim 2004; Hayles 2010). Especially, developing countries and poor communities are more prone to disasters because of greater vulnerability to hazard and risk than higher-income countries (Bruna and Rota 1990; Sayers et al. 2002; IPCC 2007; Menoni et al. 2012).

Bangladesh is one of the most natural disaster–prone areas in the world. Different types of disasters such as flood, cyclonic storms, tidal surges, droughts, tornadoes, riverbank erosion, and earthquake occur frequently in Bangladesh (ADB 2002; Abarquez and Murshed 2004; Keogh et al. 2011). Matlab municipality, one of the most disaster-prone coastal areas in Bangladesh, is located 90°40′ and 90°45′ east longitude and 23°22′ and 23°19′ north latitude of Dakshin Upazila of Chandpur District in Bangladesh (Fig. 1). Due to recent climate variability, siltation of rivers systems and low-lying flood plain, Matlab suffered several hazards such as flood, riverbank erosion, cyclone, water logging, hail storm, drought, heavy rainfall, and Nor’wester (Haque and Zaman 1993; Morshed and Huda 2002; Ali 2006; Alam and Collins 2010). Most of the time, some of these hazards turn into disasters and cause huge damage and loss of life in Matlab municipality (Rahman and Alam 2003; Pathirage 2008; Kappes et al. 2012). This municipality also is an area of high risk by coastal threats and therefore in need of analysis at a local level with understanding of community resilience, local land-use pattern, and its socioeconomic conditions in order to improve the value of hazard prioritization and risk mapping and suitable adaptation measures (Hewitt 2012). Community-based risk assessments are valuable measures to support the risk evaluation and mitigation process and to find appropriate risk reduction options such as land-use planning, early warning systems, preparedness, awareness-building activities, and suitable adaptation strategies (Bell and Glade 2004; Kunzler et al. 2012). Use of SMUG and FEMA models can be appropriate to prioritize different hazards for mitigation measures. SMUG is a qualitative assessment technique, while FEMA is a quantitative assessment technique. The FEMA model suggests a threshold of maximum 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the qualitative SMUG system. In this context, this study tried to find out the present situation of natural hazards in Matlab municipality, analyze hazards and vulnerability risks to the community, integrate SMUG and FEMA models to prioritize hazards for mitigation measures, and illustrate the local adaptation strategies and mitigation measures.

Fig. 1
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Study area map showing the roads, river, water bodies, canal, etc. and also existence of municipality area in Bangladesh

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2 Methodology and data

For prioritizing the local hazards of the Matlab municipality, intensive field observation and focus group discussion (FGD) were considered in this study. Based on the findings of the FGDs, field visits and discussion with farmers, and review of historical data, some adaptation strategies have been identified and documented. FGDs were dealt with a series of open-ended questions developed based on the research objectives. Each of the FGDs included at least 20 people such as those in municipality administration, local knowledgeable persons, local professionals, school teachers, and representatives of primary stakeholders. The hazard and risk maps were produced by Arc View GIS.

The SMUG model with four indicators seriousness, manageability, urgency, and growth adopted by the Tasmania State Emergency Service (NDO 1991; John 2003) and the FEMA (the United States Federal Emergency Management Agency) uses four criteria in an evaluation and scoring systems of hazards; history, vulnerability, maximum threat, and probability, which models are implemented in this study (Kuban 2010).

2.1 Application of SMUG model approach

The SMUG model is not prescriptive in providing solutions to hazards, and it acts instead as a tool to deliver a simple analysis of several hazards and, importantly, to prioritize hazards (Armenakis and Nirupama 2012). The four indicators (seriousness, manageability, urgency and growth) are generally used for prioritizing the hazards. As example, seriousness is called the numbers of lives lost and potential for injury and the physical, social, and economic consequences of a hazard event. All identified hazards are rated as “high,” “medium,” or “low,” in terms of seriousness, manageability, urgency, and growth. In case of seriousness, high indicates 30 % of damage to people and property, medium 5–30 %, and low <5 %. In case of manageability, high indicates that the management capacity is well in the reduction, readiness, responses, and recovery sectors, medium means that the manageability capacity is well in at least two sectors, and low means that the manageability capacity is not good in any sector. In case of term urgency, high means that something should be done now, medium means something should be done in the near future, low means there is no urgency and action can be deferred. In case of growth, high risk increases from both increase in the probability of an extreme event occurring and an increase in the exposure of the community at a high rate.

2.2 Application of FEMA model approach

The FEMA model uses four criteria in an evaluation and scoring system: history, vulnerability, maximum threat, and probability (Plough and Krimsky 1987; WHO 1999). History refers to a certain type of emergency that has occurred in the past, and it is known that there were sufficient hazardous conditions and vulnerability to cause the event (Haase 2012). Vulnerability attempts to determine the number of people and the value of property that may be vulnerable based on such factors as vulnerable groups (aged, disabled, and children); population densities; location of population groups; location and value of property; and location of vital facilities, e.g., hospitals. Maximum threat is essentially the worst-case scenario; that is, it assumes the most serious event possible and the greatest impact. It is expressed in terms of human casualties and property loss. Secondary events (such as dam failure following an earthquake) also need to be considered. Probability is the likelihood of an event occurring, expressed in terms of chances per year that an event of a specific intensity (or greater) will occur. There is some link between probability and history; however, since some hazards are without historical precedent, an analysis of both history and probability is necessary (FEMA 1997).

Table 1 shows the scoring system on the basis of hazards and their vulnerability states of Matlab municipality. The total score is not as important as how it compares with the total scores for other hazards the jurisdiction faces (Ikeda 1995; Jegillos 1999); by comparing scores, the jurisdiction can determine priorities. An evaluation of low, medium, or high is made for each criterion shown. These categories are weighed according to the responses (simply by assigning “low” 1 point, “medium” 5 points, and “high” 10 points and weighing the totals by multiplying the history score by 2, vulnerability by 5, maximum threat by 10, and probability by 7); thus, a total “score” for the particular hazard is derived. Information placed into the model was obtained by key informants in the study area. Some criteria have been determined as more important than others, and the following weighing has been established: history = — × 2, vulnerability = — × 5, maximum threat = — × 10, and probability = — × 7. Here, the dashes (—) indicates the number of individual points. By multiplying the weight factors associated with the categories by the severity ratings, it calculates subscore for history, vulnerability, maximum threat, and probability for each hazard. Adding the subscores will produce a total score for each hazard. The FEMA model suggests a threshold of 100 points (FEMA 1997). All hazards that total more than 100 points may receive higher priority in emergency preparedness (Table 2). Hazards totaling <100 points, while receiving a lower priority, should still be considered.

Table 1 Criteria-oriented characterization, scoring system, and vulnerability rating of identified hazards in the study area by integrating SMUG and FEMA models
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Table 2 Different criteria of FEMA model, evaluating level of each criterion and their scoring systems and weighting values for prioritizing the hazards in the Matlab municipality, the study area
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3 Findings and discussion

3.1 Hazard analysis and characterization

In this study, several natural hazards and their potential impact, which are the most common causes for damages in Matlab municipality, are considered for analysis and characterization on the basis of a combination of local hazard intensity and vulnerability on observed performance (Table 3). Early and seasonal flood, riverbank erosion, drought, cyclone and Nor’wester, hailstorm, sand carpeting, water logging, etc. are the major hazards of the Matlab municipality area. Early and seasonal floods occur in rainy season. Riverbank erosion is high during the high flood peak. Water logging occurs in rainy season within the embankment area due to poor drainage system. Sand-carpeted environment occurs just after the flood event. Hazards and land use/cover are strongly related to each other. It is important to identify causal processes of land system vulnerability (Handmer 1990; Quarantelli 2002; Dash et al. 2012). The present study reveals that the land-use pattern of the Matlab municipality is broadly classified into four major categories: agricultural land, fallow land, settlement, and water bodies (Fig. 2). Due to dense population and some urban characteristics, about 40 % of the total area of the municipality is occupied for human settlement. Due to the high population growth and low-lying topography, about 49 % of area is under agricultural sector. Water bodies such as ponds occupy an area of about 9 %, and the remaining 2 % area is fallow land. During the rainy season, the whole area is submerged (i.e., seasonal inundation). According to the observation of local people of the municipality, more than 70 % area is inundated during the wet season. Seasonal rains inundate wide areas of lowland, typically from June through to October. This season, mostly farmers have to wait for agricultural practice until the flood water withdraws from the low land. It is observed on the social map of the municipality that the settlement areas have been built densely (Fig. 3). Wetland includes the rivers khal, beel, haor, baor, pond, dighi and other water bodies of the municipality. Dhanagada River flows beside the municipality area. Lots of canals can be found connecting with Dhanagada Rivers. 20–25 % households have their own pond. During rainy season, almost 70 % area of the municipality is inundated; The Matlab municipality has been experiencing water logging for the every year even a little rain causes a serious problem for certain areas. Most of the time during the monsoon, the water level in the river remains higher than the terrain inside the municipal area. This implies that the municipality drainage depends very much on the water levels of the peripheral river systems.

Table 3 Hazard classification, the most vulnerable sectors, and the description of risk level according historical scenarios in the Matlab municipality, the study area
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Fig. 2
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Land-use map of the study area. The land-use map has been prepared with the help of the local community, Google Earth Image of 2011, and the Local Government Engineering Department (LGED) base map

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Fig. 3
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The social map of Matlab municipality. The social map consists of social institutions, roads, rivers, and land use. It has been prepared with the help of the local community and the Local Government Engineering Department (LGED) base map

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3.2 Spatial distribution of risks and vulnerabilities

Spatial distributions of risks and vulnerabilities assessment are important issues for local-level hazard risk planning to implement suitable mitigations measures for a local community (Haque 1995; Sayers et al. 2002; Chen et al. 2012). Prepared hazard risk map contains the risk zones and the resources at risk in Matlab municipality. Hazard risk zone and resources map of Matlab municipality are shown along with the spatial distribution of hazards and the resources that are under at risk. Particularly, the river-side area is under high risk and vulnerabilities from different hazard events (Balica et al. 2012). The present study area is experienced multiple flood hazards in a year (Fig. 4). Catastrophic flood has occurred in 1954, 1955, 1974, 1987, 1988, 1998, 2004, and 2007 in the study area and country as well (Haque 1997; Anderson and Woodrow 1998; Alam 2004). The average duration of flood in the municipality is about 2–3 months. The study area is particularly susceptible to flooding along Dhanagada River and many canals (Fig. 5).

Fig. 4
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Hazard risk zone and resources map of Matlab municipality; this map shows the hazard risk zone, spatial distribution of hazards, and the resources that are at risk. The river-side area is under very high risk zone. Flood risk is not counted here.

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Fig. 5
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Flood risk zone of Matlab municipality; the map shows the flood risk zones, i.e., high, medium, and low risk. The low land area and the river-side area are under high flood risk zone

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The Dhanagada River bisects the northwestern part of the municipality. The farmers depend on the surplus waters for rice cultivation and secondary crops and have devised extensive water management systems to trap and store the water. But in years of extreme flooding, the high waters wash away dikes and distribution structures, destroy crops and livestock, damage homes, places of worship, schools, clinics, roads, and other community infrastructure and cause loss of human life (Haque and Blair 1992). The Matlab municipality is vulnerable to riverbank erosion along the Dhanagada River in the area of north and western side, particularly Baispur, Udumdi, Forazikandi villages, and Kazir bazar and Matlab Ferry Ghat (station). Tropical cyclone that comes from the Bay of Bengal and Nor’wester attacks all over the area damages the crops, destroys infrastructure, and causes of human death (Sultana and Rayhan 2012). The area is also at risk of hail storm, sand carpeting, water logging, pest attack, and heavy rainfall, etc. The cropping calendar of the municipality represents the major cropping pattern of the municipality as Aush, Aman, and Boro. Aush is the pre-monsoon crop that the farmers practice in minor scale, because the pre-monsoon season in the municipality is very vulnerable to local environmental hazards such as early floods.

3.3 Implementation of SMUG and FEMA for hazard prioritization

Implementation of SMUG and FEMA models for hazard prioritization is summarized in this paper. The FEMA model suggests a threshold of 100 points. It is observed that the history got 10 score for flood because the flood occurs every year in the study area. All hazards that total more than 100 points may receive higher priority in emergency preparedness. Hazards totaling less than 100 points, while receiving a lower priority, should still be considered. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system if there are sound numerical data on the hazards. Table 4 describes a broad scenario of hazardous condition and risk status. The table also shows the seriousness of hazards, manageability of the community people both individual and whole, urgency to mitigate the hazards, and growth of the hazards of the municipality. According to Table 5, it is observed that vulnerability low means 1 point, medium 5 points, and high 10 points, determined by SMUG model analysis. As example, in case of flood vulnerability is HMHH that mean total scores for flood vulnerability according to SMUG model is (10 + 5+10 + 10 = 35) and similarly for Pest/rat vulnerability is LHLL (1 + 10 + 1+1 = 13).

Table 4 Hazard analysis and characterization by SMUG model; it describes a broad scenario of hazardous condition and risk status
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Table 5 Hazard prioritization and ranked matrix in Matlab municipality by SMUG hazard analysis indicators and scenarios
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Based on the hazard analysis criteria shown, the following hazards are considered to be of greatest risk to Matlab municipality. If flood occurs every year, then it is ranked high and the following category is used here. This is same for the other hazards. For example, drought does not occur every year. It occurs once in 2 years. So here, the history is medium and the score is 5. These are same in vulnerability, maximum threat, and also probability. Severity ratings are to be applied for four categories as low 1 point, medium 5 points, and high 10 points. Combining Table 1 with Table 2 (in methodology section), the hazard prioritizing by FEMA model is assessed (Tables 6 and 7). According to Table 8, we can see the flood is prioritized rank 1 by evaluating both SMUG and FEMA models. But in case of cyclone and riverbank erosion, FEMA model ranked 2 and 3, respectively. On the other hand, SMUG model ranked in case of cyclone and riverbank erosion 3 and 2, respectively. So, it is very important to identify the hazard prioritizing and their mitigation priority.

Table 6 Hazard prioritization and ranked matrix in Matlab municipality by FEMA hazard analysis indicators and weighted
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Table 7 Hazard prioritization and ranked in Matlab municipality by FEMA hazard analysis indicators
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Table 8 Hazard prioritization in Matlab municipality by comparison between SMUG and FEMA models
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3.4 Existing mitigation strategies and their limitations

Mitigation is the process of lessening the impact of natural hazards before, during, and after a natural hazard. Each hazard requires a specific type of mitigation measure. Every community has some adaptation strategies or measures for disaster risk reduction (Moulton and Roberts 1993; Helm 1996). Different kinds of environmental hazards are the common phenomena of Matlab municipality. The people of the municipality were living with these hazards for long periods. The local people are trying to adapt this vulnerable condition using their traditional coping strategies to survive these hazards. Mitigation strategies in the local communities of Matlab municipality are not sufficient for long-term development. In this study, performed FGD’s participant of Matlab municipality provided their opinions that some modern thoughts including modern communications networks, that would allow them to benefit from warnings transmitted via television, radio and with SMS alerts and systematic coping strategy could be able to mitigate the overall vulnerability, loss and damages which can ensure their steady economic growth for their social development. Authorities in Matlab municipality have also introduced some activities for reducing the disaster risk. Table 9 describes the current mitigations strategies and their limitations against disaster risks in the Matlab municipality. From the field observation and FGD, the community people hope in several implementation strategies. These basic implementation strategies may be meaningful for the local people of the study area to cope with the associated environmental hazards (Kumar and Kunte 2012). Based on the opinion of the local community, the following mitigation options can reduce the hazard vulnerability and people can cope with the hazards. The subsequent mitigation strategies might be meaningful for the local people of the study area to cope with the associated environmental hazards. Cyclone/flood centers have to be constructed, so that during hazardous events, local people can occupy these as their shelters (Sultana and Rayhan 2012). During and after hazard, it is very important to provide people with safe drinking waters, food, and medicine. Vegetation cover should be available around the houses, so that they can protect houses from both flood and cyclones. The inactive tube wells should be prepared as early as possible for safe drinking water for poor people of the community. The local people of Matlab municipality also employ their coping strategies before, during, and after a hazardous event. Table 10 reveals that the local people of Matlab municipality need to implement their adaptation/coping strategies before, during, and after hazards.

Table 9 Existing hazards and disasters mitigation strategies in Matlab municipality and their limitation to these strategies
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Table 10 The local people of Matlab municipality are needed to implement their adaptation/coping strategies before hazards, during hazards, and after hazards
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3.5 Vulnerability and discussion of findings

The study area is particularly susceptible to flooding along Dhanagada River and several canals. The Dhanagada River bisects the northwestern part of the municipality. The farmers depend on the surplus waters for rice cultivation and secondary crops and have devised extensive water management systems to collect and store the water. But in the years of extreme flooding, the high waters can wash away dikes and distribution structures, destroy crops and livestock, damage homes, places of worship, schools, clinics, roads, and other community infrastructure, and cause loss of human lives. The municipality area experienced cyclone and Nor’wester almost every year (Alam et al. 2003). The poor people suffer huge losses because of these events. Every year, cyclone and Nor’wester damages the agricultural crop, houses, utility services, and vegetation cover. The people who live along the riverbank are more vulnerable than those in other part of the area. Riverbank failure occurs when a large mass of bank materials collapses and slips into the stream (SRDI 2002). It is an endemic and recurrent natural hazard in the study area. The Dhanagada River eroded its two sides in the north and west side of the municipality. Along the different canals of the study area are also eroded in rainy season due to heavy rainfall.

Due to the annual inundation, the agricultural lands are now being regularly sand-carpeted. In few cases, pest attack also causes high damage. Apart from these, heavy rainfall causes high damage to the crops. During the cyclone and Nor’wester, trees can be broken down on roads or human settlements. If cyclones such as SIDR occur, about 20–30 % crops may be damaged of the municipality area. River erosion along the riverbank reduces the agricultural land, and sand carpeting decreases the crop production of the area. Sand carpeting is the state of sandy layer at the top soil.

During summer, the agricultural land is affected by drought in the municipality. Uncertainty of rainfall during pre-kharif (March–April) and lack of soil moisture during the dry season reduce crop production. Water logging is also a common phenomenon of the municipality area. The area under the Meghna–Dhanagada Irrigation project is waterlogged in rainy season. The residential area of the municipality is also water logged. Pest/rat attack is a very common hazard in the municipality area. During drought, agricultural production is very little, while these pests and rats also reduce the agricultural production.

If all these hazards occur frequently, the Matlab municipality will be under serious threat. Mitigation is the process of lessening the impact of natural hazards before, during, and after a natural hazard. In these contexts, Matlab municipality needs to implement some immediate mitigation policies for short-term and long-term basis. But the question is that who will do, when, how, and where? For getting answer of these questions, it is definitely need to identify hazard prioritizing and their vulnerability assessment. Table 11 shows the probable mitigation strategies that are needed in Matlab municipality with emergency basis.

Table 11 Emergency basis need to implement some strategies to cope with hazards and their vulnerability in the Matlab municipality area
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4 Recommendations

It is revealed from this study that Matlab municipality is affected by various natural hazards. Suitable adaptation measures are specifically needed to reduce the current risks and prevent future risks to the local community. To reduce the risk and mitigate the disaster vulnerability of Matlab municipality, the following steps are necessary to implement as early as possible.

4.1 Early warning systems

Early warning system is one of the most effective measures for disaster preparedness (Jonathon 1997). Well-functioning of such a system is needed to deliver accurate information dependable and on time. It should also be people centered to empower communities’ preparedness against natural hazards. Currently, local community of the study area uses the outdated old-fashioned warning systems. By raising public awareness and effective early warning dissemination at the community level, loss of lives and properties of community could be reduced.

4.2 Strengthening the active participation of local communities

It is important to strengthen coastal community with active participation by the decision-making and monitoring process at the local level through the acquisition of knowledge and skills about the preparedness of hazard intensity (Sumathipala 2002). The active participation of vulnerable community in decision-making and in the daily life of the community helps to ensure that plans are equitable and effective. Participation can positively impact the health, well-being and safety of the vulnerable residents. Special attention should be given to ensuring that all groups are able to participate, including those with specific needs and/or those who are marginalized and lacking a voice in decision-making.

4.3 The role of modern technology in enhancing indigenous coping mechanisms

Over the years, rural communities have developed mechanisms for coping with seasonal stress and recurring disasters using their traditional institutions and practices. Technological advancement of early warnings must not be used to undermine the traditional knowledge of local communities about disasters. Efforts should be made to facilitate the integration of these two kinds of knowledge, taking the better aspects of the traditional knowledge into the modern system, to enhance community understanding of the causes of disasters and to improve mechanisms for prevention, mitigation, and response. External supporting agencies, government, NGOs, etc., however, usually is not aware of these existing mechanisms. It is therefore important to develop modern technology by integrating indigenous knowledge and supporting agencies.

5 Conclusion

The paper tries to integrate two models for prioritizing the hazards, their vulnerability risks, and mitigation challenges in the community of Matlab municipality in Bangladesh. The municipality is susceptible to different kinds of natural hazards. The people and resources of the municipality are under threat to natural hazards due to its geographic and geologic settings. The SMUG and FEMA models are considered for hazard risk description and hazard prioritization. Vulnerability assessment involves first identifying all the elements which may be at risk from a particular hazard. Local knowledge is used to complete the inventory and appraisal data to specify the elements of risk. Risk is compiled from hazard and vulnerability records and from the record of elements at risk. Some strategy and mitigation measures discussed by the local people and knowledgeable persons are illustrated to help rank the hazards and disasters risks, which would help in reducing the risk and vulnerability of the municipality. In the end, it is a case study that might shed some useful light combining scientific assessment models such as SMUG and FEMA, which could feed evidence-based decision-making processes for mitigation of vulnerable communities.