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Climate vulnerability is driven not only by physical changes in the climate, but also by natural and anthropogenic factors such as demographics, economics, landscape and infrastructure that influence the sensitivity of places and populations to climatic changes and their capacity to respond to natural disasters. This WP will:
  • Improve the understanding of vulnerability and resilience of African cities to climate change;
  • Identify and quantify the hazards affected by climate change in different African cities;
  • Identify the vulnerable urban areas more at risk of climate related hazards and analyse the causes and time evolution of their vulnerability;
  • Investigate which elements of the urban system (e.g. people, goods, economy, buildings and infrastructures, open spaces) are particularly at risk;
  • Assess global risk value in each city based on a multi-risk approach allowing for cascade effects and interactions among different natural hazards;
  • Identify natural and social factors that promote or inhibit recovery of African cities after climate related Disasters;
  • Provide methods and suggest guide lines for a multi-risk assessment approach compatible with the UN- ISDR framework;
  • Cooperate closely with and contribute to the research efforts in WP3 and help to define innovative strategies for adaptation (risk mitigation and resilience building).

WP 2 consists of four interrelated tasks:

Task 2.1 Vulnerability of urban structures and lifelines
This WP is focussed on the methods of assessment of vulnerability of urban structures which are crucial for risk management and in general for the resilience of metropolitan areas. Existing research indicates that floods, flash floods, in-town soil movements are the main hazards expected to be enhanced by climate changes in most of the selected cities. Time dependent outcome vulnerability of life-lines (sewer and transportation systems) and very vulnerable informal settlements and adobe houses to these events will be studied. The main objectives include the definition of indexes measuring the vulnerability and the development of an algorithm allowing the assessment of the vulnerability of existing structures and lifelines in the presence of uncertainties due to imperfect knowledge and incomplete data. The poor quality spontaneous buildings of informal settlements, such as adobe structures, are considered one of the most vulnerable types of structures in the presence of natural phenomena such as floods, landslides and heavy rain. Classification of these structures and areal extent of each typology will be made using satellite data and field surveys (in collaboration with Task 2.2). Then, a vulnerability assessment of the main typology to hydro-geological hazards will be carried out as described in Table 1.3.d. This will also lead to proposal of low-cost and large-scale rehabilitation techniques for the different settlement typologies.
An integrated model of hydro-geological management in the urban catchments will be implemented, incorporating the regional and temporal distributions of the rain load, founded on an analysis of the time dependent physical vulnerability of the sewer system. A multi-level decision of flood-control planning approach, based on the assessment of flood-control function, reduction in damages, spatial planning and economy (physical and non-physical measures) will be performed. A flood damage assessment procedure must be consider not only direct urban damages but also storm sewer overflows on water quality of urban rivers and coastal waters, with consequent alterations of the hydrological, physical and chemical characteristics of receiving waters and degradation of ecosystems. The analysis of the relationship between climatic changes and storm sewer overflows (frequency, discharges, water quality) will allow to collect weighty data in order to assess the impact of sewer system on urban ecosystem (link to task 2.2).
About the roadway network the system vulnerability assessment subjected to events induced by climate change is not yet well established. However, this work will tackle this problem for the particular case of rainfall and consequential extreme events like floods and landslides. During and in the aftermath of a flood or landslide, the possibility to access the critical facilities is extremely important. Moreover, specific criteria needs to be established in order to identify a failed road segment/connection. Finally, the reliability of the damaged network can be evaluated based on the network capacity to endure floods and landslides and the estimated traffic flow.

Task 2.2 Vulnerability and adaptation potential associated with urban ecosystems
The objectives are (1) to characterise and analyse, quantify and map important ecosystem services of the urban green infrastructure that increase the resilience of African cities to climate change; (2)to assess the impacts of climate change on urban green structure & its ecosystem services; and (3) to evaluate the prospects for urban green structure as a measure for adapting African cities to climate change.
Current green structure assessment will be carried out using image processing and interpretation techniques (biomass measures such as the NDVI and associated land cover metrics), GIS-based techniques and ground survey work.
Assessment of current ecosystem services includes quantification of the role of the green structure for provisioning functions (associated with urban community assets (food and fuel)) and regulating functions such as the protection of urban neighbourhoods through: flood and storm water retention, mitigation of urban heat islands, soil protection; stabilisation of slopes and storm protection. This analysis will account for long-term resilience and short-term functions, such as the provision of refuges in case of catastrophic events. In each case study, selected urban ecosystem services of particular relevance will be studied. Where possible simple modelling approaches will be applied, which have the capacity to estimate both current and future ecosystem services and will be validated for the study cities (e.g. Pauleit and Duhme 2000, Pauleit et al. 2005, Gill et al., 2007). As Africa often lacks accurate data on past climate related disasters and even when data exists it is hard to interpret correctly. CLUVA researchers will - in agreement with the city Mayor - organise workshops with head of departments and experts appointed by the city council to overcome this situation. Those workshops aim at
  • Identify and help interpreting existing historical data,
  • Describe existing eco-services relevant to the study,
  • Capture the knowledge of local experts when no formal statistical data exists.
In case of major information gaps or if the available information is too old to be used for the research, qualitative approaches will also be used to understand the social dimensions of ecosystem services. For example, analysis of provisioning functions will also include limited ground surveys and application of social survey methods such as interviews and workshops (as mentioned before) to characterise the day to day services that the green structure provides. CLUVA will develop questionnaires that will help to close information gaps and help to better understand the available data. All interviewees will be recruited during the workshops on a fully volunteer basis and the surveys will be conducted in a fully anonymous manner, i.e. in no circumstances personal data will be collected or processed. All results from the questionnaires will be analysed for potential traceability, which will be subsequently removed. The results of the surveys will be kept private and will only be used to fructify the research performed in the CLUVA project. Aggregation and fuzzification mechanisms will be applied if survey results become part of public research documents.
Analysis of the relationship between ecosystem services and the urban green infrastructure. This element will be used to determine the critical components of urban green structures for maximising ecosystem services in the case study areas. Analysis includes investigations in to the way how the provision of services is linked to green structure use and management (linking to Task 2.3).
Establishment of the relationship between the ecosystem services provided by current green structure and patterns of vulnerability and hazards by combining results from stages 1, 2 and 3 with results of vulnerability and hazards obtained through WP 1 in order to determine how areas of high and low functionality compare geographically and an assessment made of the implications for strategy development in the Innovative Strategies WP 3. Assessment of the resilience of urban green structure to climate and urbanisation pressures will draw on previous data, expert judgement and future plans. Results from climate scenario modelling in WP1 will be used to estimate the consequences of heat waves and droughts, as well as floods and excessive rainfall on green infrastructure and its ecosystem services.
Future ecosystem services and potential disbenefits. Validated models from stage 2 and knowledge on practice of green structure use and management will be used to generate future ‘what-if’ scenarios for urban green structure functionality as an input to strategy development in WP3. The Task 2.2 research effort will seek to provide baseline assessments for each of the case study areas but with more detailed assessments being carried out for a subset of areas. The precise locations for detailed assessment will be decided in collaboration with African partners and will depend on the results from earlier deliverables from the CLUVA project.

Task 2.3 Assessing social vulnerability
The objectives of this task are (1) to select social vulnerability indicators based on a review of existing approaches, (2) to develop a framework for an asset vulnerability and adaptation appraisal in order to analyse and compare the vulnerability and adaptation strategies within and between different urban areas; and (3) to conduct in selected case-studies in-depth investigation by means of qualitative and quantitative social science methods in order to (1) apply the previously developed asset based vulnerability and adaptation framework and (2) to be able to contextualise and interpret the associated findings in order to better understand core drivers and possible responses for input into other CLUVA WPs.
The work will include:
A review and evaluation of existing social vulnerability indicators (and indices where relevant) which help to explain adaptation capacity and other aspects of individual and community resilience.
Development of a framework for asset vulnerability and adaptation appraisal. The aim of this framework is to develop a more context-sensitive understanding of people’s social vulnerability and adaptation strategies. This is necessary, as pure “taxonomic” approaches too often fail to fully take into account the multi-dimensionality of social vulnerability. Therefore, an “asset vulnerability and adaptation framework“ is developed. It is based on the work of Moser (2009) and identifies the types of socio-economic vulnerability and groups most affected in four closely inter-related ‘phases’ or ‘stages’ that can occur during urban climate change (long term resilience, anticipation of hazard, coping with immediate impacts and recovery). It will furthermore allow identifying a range of ‘bottom-up’ climate change adaptation strategies that individuals, households and communities have developed. The aim is to develop a context-sensitive concept and respective indicators of social vulnerability—this is what is described by the “situativeness” of vulnerability.
Case studies: Identification of research area and specification of methods –the case-studies areas will be selected in close collaboration with African partners. Local partners and engaged stakeholders will also play a prominent role in vulnerability reduction and adaptation strategies. This will also involve close liaison with other tasks and WPs.

Task 2.4 Multi-risk models
This task copes with complex facets of risk assessment and helps to draw together the work on hazards and vulnerability assessments of WP1 and WP2. Its rationale stems from the concept that multi-risk is not simply the aggregation of single risk analysis, the frequent interaction among different hazards and risk (cascade effects) produces an enhancement of individual risks. A second issue of interest in a multi-risk perspective is the evolution of the concept of vulnerability which now includes physical, societal, economic aspects, dependence on time and interaction among different objects (systemic vulnerability). Risk is considered as a probabilistic parameter, therefore the best approach is by advanced probabilistic methods. Bayesian methods have proven very effective in this context. In this task a Bayesian method will be improved to account for all the above mentioned complexities and applied to the selected test cities. (Durham 2003, Grunthal et al., 2006, Marzocchi and Woo, 2007, Marzocchi et al., 2009).
One of the main difficulties with Bayesian methods is to account for are the so called external environmental inputs, the internal variables describing the evolution of the state of the ecological variables in the hinterland and city considered (environmental variables), the internal economic and industrial variables describing the evolution of the main resources of the system considered (economic variables) and the internal variables describing the state of the population (sociological variables). We will deal with them using models termed “system dynamics models”. These models are deterministic and thus quite different from those used in Bayesian models. They emphasize a different kind of knowledge (qualitative versus probabilistic, feedback versus sequential). Due to the complexity of the problems faced by African cities, all sources of information and knowledge have to be used and an important aim of the project is to aggregate the outcomes of these two modelling methods (Bayesian and System Dynamics). However, System Dynamics models are known to become easily very complex and difficult to understand. To cope with that, we will use an emerging methodology called “Kinetic graphs” which provides equivalent models.
Multi-risk indexes will be produced with both methods for the selected test cities, and the relevance of both for land and urban planning and decision making will be discussed.