This research analyses 'natural' disaster policies for Mexico. The objective is to demonstrate that 'natural' disaster and the policies oriented to prevent them are socially constructed. It adopts a constructionist perspective because it is concerned with the understanding of collective social constructions of meaning and knowledge that are determined by political and social processes. This study focuses on the relation between the discourses of disaster causality, policy problem construction and policy responses in Mexico. The central argument is that in Mexico when disaster is conceived as a 'natural' phenomenon the exposure of vulnerable people to disaster risk is concealed therefore inhibiting the emergence of socially sensitive responses at policy level. Two analytical inter-related frameworks were elaborated. The first framework was set up to examine the discursive construction of floods causality as a policy problem and the second one to unpack the argumentative construction of policy responses. The research chooses the case of Chalco Valley's floods that took place in June 2000 in the State of Mexico, Mexico and the institutional responses deployed before, during and after the floods as the empirical ground on which the central argument is examined. Four different disaster discourses were found at policy level, namely inadvertence by 'ignorance', inadvertence by 'carelessness', accidental and structural. These were shaped by how causal ideas of disaster were assembled and made persuasive. In turn, these four different discourses construct four different floods policy problems and therefore imply four types of policy responses even though important connections were found amongst them. These connections represent relevant policy coalitions upon which policy change can be sought. It was found that people's vulnerability to floods is a component in only one discourse, namely structural causality discourse, and therefore in one group of policy responses. The research approach and the findings suggest areas to improve policy making and research in the disaster field in Mexico. The outcome of the research contributes to a better understanding of the how scientists, policy makers and people affected by disaster assign meanings and beliefs, construct knowledge and use evidence to support and legitimise disaster causality claims in different ways. These epistemological differences have to be acknowledged for improving policy formulation and implementation aimed at reducing disaster risk of vulnerable people.

There is an increasing uptake of Natural Flood Management (NFM) and land use management (LUM) schemes to tackle excessive, rapid runoff in rural catchments. At the local scale, there is a growing knowledge base regarding the impacts of NFM and LUM. However, evidence and understanding of how these local impacts manifest at a larger catchment scale is less well understood. There are many types of model that have been used for investigating NFM and LUM impacts at larger scales ( > 10 km2), ranging from the comparatively simple lumped conceptual approaches to more complex, physically-based, distributed models. How best to represent NFM and LUM impacts in models is ambiguous. This thesis presents research into impact modelling of flood mitigation measures from the hillslope to the catchment scale, using the lumped FEH rainfall-runoff model and a novel physicallybased, distributed model, Juke. A Flood Impact Modelling (FIM) methodology is proposed for rapid impact assessment using the FEH approach; FEH hydrographs are generated for sub-catchments and routed to the outlet. The impact of changes in timing and runoff generation in specific sub-catchments on the downstream hydrograph can be investigated to inform catchment planning. The Juke methodology is designed to make best use of field observations and existing GIS datasets for parameterising the runoff and routing components. Juke uses some of the knowledge embedded in the FEH approach regarding the timing and runoff generation and applies it spatially. Juke is capable of emulating the FEH, but also allows consideration of spatial changes in LUM. Two catchments in the north of England have been instrumented to characterise the rainfall-runoff behaviour and understand what causes the largest flood events, where NFM and LUM have taken place. This knowledge informs the LUM and NFM scenarios explored as well as for model parametrisation. Results from the lumped FEH modelling suggest that the mitigation of flood flow by managing the volume and timing of fast runoff will have the greatest impact on floods caused by short duration, high intensity rainfall events. The Juke modelling also suggests that the impact of NFM and LUM is likely to be minimal ( < 10 % flood peak reduction for 12 % coverage of riparian woodland) and depends on the duration and intensity of rainfall events and the internal synchronisation of the component sub-catchments. The flood peaks for some events ii may increase due to the effects of timing and synchronisation of flows from the landscape elements. The outcomes of this thesis recommends flood managers make field observations to better understand the causes of flooding within a catchment. Schemes using NFM and LUM are likely to be most beneficial for comparatively small catchments ( < 10 km2) that suffer from frequent flooding from short duration, high intensity rainfall.

The need to achieve a greater understanding of the potential for shared learning between scientists, policy-makers and practitioners for Disaster Risk Reduction (DRR) is internationally recognised through the Sendai Framework for DRR. This is complemented by academic calls for interdisciplinarity in addressing disasters along with a growing interest in the concept of social learning as a lens through which to explore processes of collaboration in environmental management. Adopting a social learning approach this research uses a Community of Practice Framework to explore the potential for shared learning between earthquake scientists and humanitarian Non-Governmental Organisations (NGOs) based in the UK and Ireland. The thesis is based on qualitative interviews carried out with earthquake scientists and humanitarian practitioners, as well as individuals working at the interface of the two groups. Additional empirical evidence includes workshop recordings from a particular example of earthquake science-humanitarian collaboration. The analysis defines earthquake science and humanitarian NGOs as separate Communities of Practice (CoPs) and seeks to understand the elements uniting community members around a shared sense of enterprise, as well as gaining insight into the learning practices unique to each group. It highlights the crucial role of legitimacy in driving one's motivation to participate within a specific CoP or engage in cross-community learning. It finds high degrees of difference in community knowledge and culture to be presenting barriers to knowledge exchange. Mapping the multiple ways in which boundary work takes place between the CoPs the thesis finds those engaged in cross-community activities to be experiencing marginalisation, and current attempts to overcoming marginality to be ineffective. Recognising that the inherent challenge of evaluating boundary activities lies at the root of why they tend to be unsupported, the study seeks to adopt a postpositivist approach to evaluation, exploring alternative methods of critiquing boundary work in the short term. Wider political and economic factors are seen to underpin the potential for earthquake scientists and humanitarian practitioners to undertake fruitful collaboration in the long-term. To conclude, the thesis discusses structural implications and recommendations for supporting shared learning and legitimising boundary work between the earthquake science and humanitarian NGO communities.

Qabil Ajmeri (an Urdu poet) once wrote: وقت کرتاهے پرورش برسوں حادثہ ایک دم نہيں ھوتا Translation: Time nurtures for years Accident is never sudden Same is true for disasters; they just don’t happen suddenly. It is our actions (or inaction in certain cases) over the years that turn a hazard into a disaster. Development policies, governance system, disaster management system, poverty, and level of hazard are some of the most important factors that contribute towards disaster vulnerability. Most of the developing countries suffer higher disaster losses (as compared to the developed countries) due to their inability to properly address these factors. Societies need to have better development policies, good governance, efficient disaster management system, and improved livelihoods to minimise disaster vulnerability. Conducted from the positionality (Robinson 2014) of a victim of the earthquake and an important functionary of the post-2005 earthquake reconstruction programme in AJK, this research is an auto-ethnographic study in order to understand how societies become vulnerable to natural disasters and what role post-disaster housing reconstruction can play in addressing this vulnerability. By loosely following Blaikie et al.’s (1994) ‘Pressure and Release’ (PAR) model and Collins’ (2009) “disaster and development approach”, this research attempts to find what factors made people vulnerable to seismic hazard in AJK and turned an otherwise not so big Mw=7.6 earthquake into one of the deadliest environmental disasters in the world. The performance and impact of the post-2005 earthquake housing reconstruction program is evaluated in this study by using the mixed-methods research approach. The study finds that the sustainability of the seismic resistant construction and continuation of the pre-earthquake vulnerability factors are still issues. Till the time issues mentioned in this study are not addressed properly, communities in general and the study area in particular will remain vulnerable to environmental disasters.

The interaction between natural events and technological installations involves complex mechanisms which have the potential to affect simultaneously more critical systems, nullifying the redundancy measures common to industrial safety systems and endangering the integrity of facilities. The concerns related to this kind of events are far from being restricted to a merely economic or industrial nature. On the contrary, due to the sensitivity of most processes performed in industrial plants and the negative consequences of eventual releases of hazardous materials, the impact of simultaneous failures embraces also the environment and population surrounding the installations. The risk is further widened by the trend of climate extremes: both observations over the past century and projections for next decades suggest an increase of the severity of extreme weather events and their frequency, both on local and global scales. The rise of sea water levels together with the exacerbation of extreme winds and precipitations, enlarge the geographic area of risk and rise the likelihood of accidents in regions historically susceptible to natural hazards. The prevention of technological accidents triggered by natural hazards lies unavoidably with the development of efficient theoretical and computational tools for the vulnerability assessment of industrial installations and the identification of effective strategies to tackle the growing risks to which they are subject. In spite of the increasing trend of the risk and the high-impact consequences, the current scientific literature still lacks robust means to tackle these issues effectively. The research presented in this dissertation addresses the critical need for novel theoretical and computational methods tailored for the risk assessment of complex systems threaten by extreme natural events. The specific requirements associated with the modelling of the interaction between external hazards and engineering systems have been determined, resulting in the identification of two main bottlenecks. On the one hand, this kind of analysis has to deal with the difficulty of representing accurately the complexity of technological systems and the mutual influence among their subsystems. On the other, the high degree of uncertainty affecting climate variables (due to their inner aleatory nature and the restricted information generally available), strongly bounds the accuracy and credibility of the results on which risk-informed decisions must be made. In this work, well-known traditional approaches (such as Bayesian Networks, Monte Carlo methods etc.) as well as cutting-edge methods from different sectors of the scientific literature have been adopted and integrated in order to obtain a novel theoretical strategy and computational tool able to overcome the limitations of the current state of the art. The result of the research is a complete tool for risk assessment and decision making support, based on the use of probabilistic graphical models and able to fully represent a wide spectrum of variables types and their uncertainty, to provide the implementation of flexible computational models as well as their computation and uncertainty quantification.

This thesis examines flood preparedness approaches in an East African context. There is growing awareness that the impacts of disasters can be reduced if the communities in hazard-prone areas have knowledge and capacity to effectively respond to a particular hazard. Understanding why only some groups of households are prepared for flood hazards while others are not is crucial, as flood disasters cause significant loss of human lives and livelihoods that impose unbudgeted spending on emergency relief and recovery for government and households. Although much work has been undertaken in US and Europe, little research has been undertaken to understand the actual processes through which flood preparedness occurs in an African context. Particularly lacking is the analysis of the complex relationships between the state and community i.e. the nature of the ties that connect public officials and citizens (embeddedness) and mutually supportive relationships between the state and community (complementarity) in facilitating flood preparedness. This thesis investigates the motivating factors that lead resJdents of Kilosa District, Tanzania, to prepare for flood events. Kilosa District is a relatively poor area with low levels of income and dependence on crop cultivation. Their exposure to flood hazards generates a range of social and economic implications. Using five different approaches namely: stakeholder analyses; exposure analyses; vulnerability analyses; risk perception assessments; and social network analyses, this study investigated the process and drivers of preparation. Data were collected using a multi-method approach including household surveys, semi- structured interviews and focus group discussions. The results reveal that flood preparedness can be enhanced by jointly considering the complexities between the physical factors and societal processes. In Kilosa District, vulnerable households live in locations with high levels of exposure to floods and depend on agriculture for their livelihoods. Collaborative engagement between the government and the community is shown to be essential for effective flood risk planning. Household surveys reveal that flood preparedness is more successful when built on trusting relationships, frequent interaction and active engagement of different actor groups in disaster mitigation activities. Flood emergency response (e.g. evacuation, temporary accommodation) is more successful when built on existing informal networks. Nevertheless, micro- finance operations can affect - both positively and negatively - a household's long- term preparedness. Preparation for floods, which includes activities such as livelihood diversification and improvement in house structures, is a subjective decision affected by individual interpretations of risk, fear of floods and past hazard exposure. Without considering the complex relationships between the state and society, by including actors at all scales,flood risk planning will prove to be expensive and ineffective. Synergistic relations between the government and the residents of Kilosa District proved to be critical in explaining how households access resources for individual or collective flood response. These findings offer a practical means of increasing the likelihood of individuals adapting to flood events. Keywords: Flood disasters, vulnerability, preparedness, social capital, Tanzania, Kilosa District

Research regarding anthropogenic effects on flood inundation and morphological/landscape change in the River Niger is presented in this thesis. Various anthropogenic effects are considered within the case study area. Effects of dam construction were numerically modelled using Dynamic Harmonic Regression (DHR) Model, Geographical Information System (GIS) and Cellular Automaton Evolutionary Slope And River model (CAESAR). CAESAR model was used to simulate different flood scenarios resulting from environmental change (climate and anthropogenic land cover change) on the River Niger. Most pm1s of the Niger River Basin lack spatially distributed hydrological data to facilitate efficient monitoring of anthropogenic effects on the river. The use of parsimonious models such as Dynamic Harmonic Regression models which require few spatially-distributed data are therefore suitable for simulating water stages behaviour/response to anthropogenic effects, in this case, the Kainji and Jebba Dam constructions. DHR routines were used to simulate the dynamics of pre- and post-dam constmction water stages within the River Niger Basin in Nigeria. The DHR model explicitly calculates the uncertainty in the estimated cycles and trends and thereby ensures that the data are not over-interpreted. Seasonal cycles and trend in water stage data across the Niger River Basin within Nigeria before and after Kainji and Jebba dams construction were captured using this model. It has robustly quantified a range of differences in the water stage regimes after the dam construction especially at the immediate downstream gauge station. These differences, however, dissipate further down the downstream catchment towards the Niger Delta.

This study began in the summer of 2007, when parts of the UK experienced exceptionally high rainfall and were devastated by flood water. It is an ethnography of the residents and responders in one flooded village: of the relationships that are formed, the houses that are rebuilt, the personal items that are missed or thrown away, and the places that are lost or compacted. It is also a reflection on the changing role of the researcher as an insider in emergency planning who became entangled in the life of the village. The health and social consequences of flooding, and more specifically the loss of home, a sense of security, space and possessions, have been documented in a number of studies. Some of these consequences have also become the focus of UK government attention. How well people recover from flooding events is seen to have a direct bearing on individual, community and economic wellbeing. A plethora of instruments: checklists, templates and guidance documents have been produced by government planners to effect this recovery. In this study I define these as technologies of recovery within a wider context of emergency planning which has at its core the aim of bringing order to complex and messy times. Technologies of recovery endeavour to place a framework over a complex process where much is uncertain, reactive and dependent on individual and ad hoc social relations. Like many other areas of health and social policy, while such protocols are not necessarily unwelcome, they carry many assumptions. I demonstrate that these are built on official narratives where much has been left unseen or unsaid. The final product is distilled and compromised; blind to the situated practices that remain hidden. Drawing on literature from science and technology studies, human geography and disaster research this study shows how technologies of recovery are transformed in localised practice; enabling actions to happen that are entwined with a community's own existing strength and resilience. The contribution of this thesis is to show, through a case study that makes visible the practices that are often hidden, how localised emergency responders find ways to collaborate with residents. In an informal network they do different with the instruments to co-produce regeneration and survivance within a community.

My thesis analyzes the determinants of the differential impact of natural disasteIS in Latin America and the Caribbean identifying the political, social and economic structures that determine social outcomes of narural disasters. It studies two adaptation tools, one individual (social capital) and one institutional (public spending and humanitarian aid) that could reduce the social impact of natural disasters. At aggregate level (countries) I conduct a time-series cross-section (I'SCS) analysis, between 1960 and 2010, to analyze the impact of social capital. international aid, and public spending on the number of deaths caused by natural disasters. At individual level, I use logistic regression models to predict the probability of becoming poor aft:er the Haitian and Chilean earthquakes in 2010. Findings at aggregated level confirm that higher the levels of social capital. disaster relief aid and public spending lower the number of casualties due to a natural disaster. However, the efficacy of these tools depends on the institutiorul framework of the country. Countries with higher democratization levels public spending is more effective in reducing the death roll after natural disasters. On the contrary, in more autocratic governments humanitarian aid becomes more efficient in reducing the death rate. The individual level results show that the social pamclpation and network ties are fundamental in reducing the impact of the earthquakes on the levels of poverty "With some differences between the countries. Regarding institutional mechanisms. both in Haiti and Chile the previous levels of public spending and aid within societies do help in mitigating the impact of disasters, however, results demonstrate the funding distributed afterwards encounter several limitations.

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