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Kuala Lumpur, the capital of Malaysia, is exposed to several natural hazards, among which flash floods are most common and frequent. Expanding development and higher intensity of rainfall are the primary causes of flash floods. As the urbanisation is growing, the number of exposed properties, people and business premises are also increasing. This may have a detrimental impact on the socio-economic state of the city. Therefore, the purpose of this chapter is to investigate the frequency and intensity of flash flood occurrences between 2011 and 2016 and to delineate how it is impacting the urban livelihood. For this study, several news reports of flash flood events, previously published and reports were reviewed to elicit information so that the frequency and intensity of flash floods can be analysed for identifying flash flood risk areas. Along with the information from newspapers, Google map was used to identify the spatial locations of flash flood events, thus identifying the risk zones. This study found the City Centre as the most risk prone to flash floods. It was noted that 39% of flash floods occurred in this place. The Damansara-Penchala area comes in the second position with 20% of flash floods occurring in this place. Most of the people of these zones are exposed to flash flood and the affected people suffer from road blocking and heavy traffic jam. This study will help researchers and policymakers to understand the impact of flash floods in the city. This will also help to identify the most flood-prone areas of the city.

Up to now most of the research into flash flood disaster has examined scientific aspects of this natural phenomenon. This paper aims to focus on the flash flood disaster scenario of Uttarakhand, a newly created Himalayan State in India, on the basis of their severity and mechanism so that management efforts can be mounted by the disaster managers.

Besides compiling the hazard‐ and risk‐related work done by the various research institutions and universities the paper attempts to understand the mechanism responsible for this natural hazard.

Uttrakhand is a state highly prone to disasters. Flash floods are disasters that are seasonal in nature and strike during a certain period of the year in certain pockets of the state with high frequency.

The analysis is based on observations made in the entire state.

Awareness amongst the masses regarding the flash flood disaster that is likely to affect them and their life support strategy is a must for bringing forth voluntary adoption of the safety norms.

Armed with the information about the hazards and their spatial distribution, the disaster managers in Uttarakhand may undertake certain preventive and mitigative measures for further strengthening and streamlining the Disaster Management System in the state and pave the way for similar activities in other states of India.

Existing literature on how social learning stemming from flood experience influences management and adaptation to flood-risks, and resilience-building is scant. In this context, the purpose of this study is to map the processes and examine the application of social learning in formulating coping measures and adaptation strategies in Bangladesh's wetland communities.

To bridge this research gap, conceptually, we formulated the Social Learning from Disasters (SLD) Framework to explain the process of social learning from flood experience and the mechanism of its influence on community resilience. Applying a qualitative research approach, the empirical investigation was carried out in the Fenarbak Union of Sunamganj District, Bangladesh. Using a participatory approach and qualitative techniques, the required primary data were procured.

The results of the study yielded three key findings: (1) social learning and memory have often enabled wetland communities to adopt diverse coping and adaptive measures in response to flash floods; (2) social learning-based actions have resulted in reduced flood-risk and enhanced community resilience to flash floods, especially when these actions were supported by both local and external innovations and (3) the aforementioned social learning stemmed primarily from first-hand experience of flash floods, which was shared via various collective learning platforms.

The study followed a participatory methodology and the data were procured from two communities in the union level unit of Bangladesh. Therefore, generalization to apply to the larger context should be made with caution. Also, the study represents a cross-sectional study, and thus understanding of the long-term trend is not possible.

The findings of the study have direct and profound implications for local community-level disaster-risk planning. As there are serious deficiencies in documenting and preserving social learning for community resilience and development planning, this study offers a conceptual framework, along with empirical evidence, for transforming these lessons learned into practical actions for change.

The findings of the study highlight the importance of social learning as a collective effort and provide empirical evidence of innovative adaptations to change. These results are critical to formulating societal strategies for disaster-risk management as well as to enhance community resilience.

Limited efforts have hitherto been made to determine (1) how the actual process of social learning from disaster shocks takes place, and (2) how innovative adaptation strategies lead vulnerable communities to take up social learning-based actions. Our research attempts to fill these knowledge gaps by providing an evidence-based account of community resilience-building responses to flash flood disasters.

The purpose of this study is to provide recommendations for improving the social performance of warnings using mobile services in flash flood prone communities. A warning cannot be considered effective until it is received, understood and responded to by those at risk. This is defined as the social performance of warning communication techniques. Mobile services offer opportunities for improving this, particularly in Bangladesh, but have been underutilised. In this research, characteristics of the warning, mobile services and community are found to influence the social performance.

A framework on the factors affecting the social performance was developed and applied using data collected through interviews at the national and regional level along with focus-group discussions (FGDs) and key informant interviews at the local level in the Sunamganj District, Bangladesh.

The study demonstrated that mobile services are the preferred means of warning communication. Communities strongly preferred voice short messaging service (SMS) and interactive voice response (IVR) because of easier accessibility and understanding of the message. Text-based services [SMS and cell broadcasting service (CBS)] were still found to be acceptable. These should be simple, use symbols and refer to additional sources of information. Further recommendations include mixing push (e.g. SMS and CBS) and pull-based (e.g. IVR) mobile services, utilising local social networks, decentralising the dissemination process and raising awareness.

A limited sample of interviews and FGDs were used.

Concrete recommendations are made for overcoming obstacles related to the effective use of mobiles services.

The suggestions made can contribute to improving the social performance of flood early warning communication.

The conceptualisation of mobile services’ contribution to social performance of flood warning and field-level application.

The main objective of the study is to identify the vulnerable areas for river‐line and flash flood hazard and its mitigation through GIS Database Management System (DBMS) of geo‐hydrometeorological parameters. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.

The Dabka DBMS is constituted of three GIS (Geographic Information System) modules, i.e. geo‐informatics (consists of geomorphology, soils, geology and land use pattern, slope analysis, drainage density and drainage frequency), weather informatics (consists of daily, monthly and annual weather data about temperature, rainfall, humidity and evaporation) and hydro‐informatics (consist of runoff, sediment delivery, and denudation). The geo‐informatics and weather informatics modules carried out by comprehensive field work and GIS mapping than both modules used to carry out hydro‐informatics module. Through the integration and superimposing of spatial data and attribute data with their GIS layers of all these modules prepared Flood Hazard Index (FHI) to identify the level of vulnerability for flood hazards and their socio‐economic and environmental risks.

The results suggest that geo‐environmentally most stressed areas of barren land (i.e. river‐beds, flood plain, denudational hills, sites of debris flow, gullies, landslide prone areas etc.) have extreme vulnerability for flood hazard due to high rate of runoff, sediment load delivery and denudation during rainy season (i.e. respectively 84.56 l/s/km², 78.60 t/km² and 1.21 mm/year) whereas in geo‐environmentally least stressed dense forest areas (i.e. oak, pine and mixed forests) have low vulnerability due to low rate of stream runoff, sediment load delivery and denudation (i.e. respectively 20.67 l/s/km², 19.50 t/km² and 0.20 mm/year). The other frazzled geo‐environment which also found high vulnerable for flood hazard and their risks is agricultural land areas due to high rate of stream runoff, sediment load delivery and denudation rates (i.e. respectively 53.15 l/s/km², 90.00 t/km² and 0.92 mm/year).

For hydro‐informatics module it is quite difficult to monitor water and sediment discharge data from each and every stream of the Himalayan terrain due the steep and rugged topography. It requires strategic planning and trained man power as well as sufficient funds; therefore representative micro‐watershed approach of varied ecosystem followed for a three years (2006‐2008) period.

The study will have great scientific relevance in the field of river‐line flood and flash flood hazard and its socio‐economic and environmental risks prevention and management in Himalaya and other mountainous terrain of the world.

This study generated primary data on hydro‐informatics and weather informatics to integrate with geo‐informatics data for flood hazard assessment and mitigation as constitutes a part of multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.

The purpose of this paper is to address the gaps in knowledge about how people get information in a flood and what they want to know.

A total of 27 people were interviewed from two communities that suffered flooding in the 12 months before the interviews. Slow‐moving flood and flash flood were covered.

The type of disaster determines how people seek information. In slow‐moving flood, people heard from others, tracked it visually and via web‐available river gauge information, and talked to others with more flood experience. Radio was an important confirmation tool in the slow‐moving flood. In flash flood, people first heard from others and then turned to television.

Participants made up a small sample skewed toward regional areas and were selected by snowball/convenience sampling methods. A survey is required to confirm or refute findings.

Word of mouth needs to be tapped into by agencies, and mobile phone networks and social media are critical to this. Radio and television should be more proactively used by emergency agencies and maps should be a feature of all flood communication.

The focus of disaster communication research tends to have been on agency use of communication rather than the individual's use of a range of communication channels. This study encourages agencies to look at how individuals look for information, the channels they use to get information and the type of information they seek.

The rapid and ongoing expansion of urbanised impervious areas could lead to more frequent flood inundation in urban flood-prone regions. Nowadays, urban flood inundation induced by rainstorm is an expensive natural disaster in many countries. In order to reduce the flooding risk, eco-roof systems (or green roof systems) could be considered as an effective mechanism of mitigating flooding disasters through their rainwater retention capability. However, there is still a lack of examining the stormwater management tool. The purpose of this paper is to evaluate the effects on flooding disaster from extensive green roofs.

Based on geographical information system (GIS) simulation, this research presents a frame of assessing eco-roof impacts on urban flash floods. The approach addresses both urban rainfall-runoff and underground hydrologic models for traditional impervious and green roofs. Deakin University’s Geelong Waurn Ponds campus is chosen as a study case. GIS technologies are then utilised to visualise and analyse the effects on flood inundation from surface properties of building roofs.

The results reveal that the eco-roof systems generate varying degrees of mitigation of urban flood inundation with different return period storms.

Although the eco-roof technology is considered as an effective stormwater management tool, it is not commonly adopted and examined in urban floods. This study will bring benefits to urban planners for raising awareness of hazard impacts and to construction technicians for considering disaster mitigation via roof technologies. The approach proposed here could be used for the disaster mitigation in future urban planning.

This study aims to explore the preparedness and the recovery/rebuilding activities or strategies adopted by the respondents during the phases of natural disaster/crisis in Jammu and Kashmir and Assam, India.

The qualitative research design was chosen for the study. The interview method was adopted in the present research. The respondents were selected purposefully from the representatives of tourism organizations/destinations management organizations and emergency organizations, i.e. disaster management and hotels experienced by natural disasters, i.e. flood 2014 in Kashmir valley 2019 in Assam states of India.

Moderate level of preparedness among the tourism organizations, tourism businesses such as hotels leaves implications for them to enhance the disaster or crisis resilient community. The preparedness programs, efficient social media, communications strategies and development of tourist destinations-specific disaster-related crisis management plans were suggested to enhance disaster resilience.

The present study is widely contributing to the theory of the vital concepts of crisis management at tourism destinations. This study suggests the practical implications for and suggestions to the industry practitioners, government agencies and researchers to rebuild the tourist destinations from the disaster/crisis and enhance global resilience.

The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land use‐informatics and climate‐informatics. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.

Land use‐informatics consists of land use mapping and change diction, i.e. decadal changes and annual changes. Climate‐informatics consists of climate change detection through daily, monthly and annual weather data for a period of 25 years.

The exercise revealed that oak and pine forests have decreased, respectively, by 25 percent (4.48 km²) and 3 percent (0.28 km²) thus bringing a decline of 4.76 km² forest in the watershed during 1990 to 2010. But, due to climate change the mixed forest taking place of oak forest in certain pockets and consequently the mixed forest in the catchment increased by 18 percent (2.3 km²) during the same period which reduced the overall loss of forests in the region but its not eco‐friendly as the oak forest. Barren land increased 1.21 km² (56 percent), riverbed increased 0.78 km² (52 percent) and cultivated land increased about 0.63 km² (3 percent) during the period of 1990 to 2010. Out of the total seven classes of the land use land cover, five classes (i.e. Oak, Pine, Mixed, Barren and Riverbed) are being changed dominantly due to climate change factor and anthropogenic factors plays a supporting role whereas only two classes (scrub land and agricultural land) are being changed dominantly by anthropogenic factors and climate change factors plays a supporting role. Expansion of mixed forest land brought out due to upslope shifting of existing forest species due to climate change factor only because upslope areas getting warmer than past with the rate of 9°C‐12°C/two decades. Consequently, the results concluded that the high rate of land use change accelerating several environmental problems such as high runoff, flash flood, river‐line flood and soil erosion during monsoon season and drought during non‐monsoon period. These environmental problems cause great loss to life and property and poses serious threat to the process of development with have far‐reaching economic and social consequences.

This study generated primary data on land use‐informatics and climate‐informatics to integrate each‐other for impact assessment and mitigation through sustainable land use as constitutes a part of a multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.

Floods are considered as one of the most lethal natural disasters having the potential to cause havoc to entire communities. Pakistan is the land of wide topographic and climatic variations which make it vulnerable to floods. The purpose of this paper is to identify flood susceptible zones in the Panjkora Basin using frequency ratio model.

A total of seven parameters or flood conditioning factors were considered, and weights were assigned according to the frequency ratio technique. For the preparation of layers, satellite imageries and digital elevation model data were used. Frequency ratio was calculated using correlation between these parameters and flood. Flood susceptibility index map was divided into five zones through quantile method in ArcMap.

Findings of the study reveal that near half of the area (43%) is located in the very high susceptible zone, while only 20% area is classified as low to very low susceptible.

This paper is entirely based on original research. The approach used in this study has not been applied to the study area before.