Flood vulnerability analysis and assessment are urgently needed to improve urban-risk management and to protect the local population. Our aim was to deliver an adapted approach for an integrated vulnerability assessment for data-scarce areas by combining different disciplinary perspectives with local knowledge.An integrated way of understanding vulnerability is by means of a **social-ecological vulnerability assessment (SEVA)**. SEVA is defined “_as the extent to which environmental degradation and climate change cause negative changes in exposure, susceptibility and in the capacity of the social-ecological system to anticipate, cope with and recover from the hazard_” [^2].
We use the **SEVA concept** as common framework [^1] to assess the different vulnerability components, exposure, sensitivity and adaptive capacity, from an integrated social-ecological perspective. Our integrated SEVA is carried out at different spatial and temporal levels and summarizes the results of the various work packages, in particular the analysis on heavy rainfall hazards (WP 2), on flash flood risk (WP 3) and on the adaptive capacity (WP 4).
Besides the vulnerability assessment for the current situation, we also explore vulnerability for possible future pathways with regard to climate (heavy rainfall) and land cover changes (exposure and sensitivity), as well as measures to decrease flash flood damages (adaptive capacity). Using a [scenario analysis](https://gitlab.pik-potsdam.de/peterh/captainrain/-/wikis/Home/WP%205%20Vulnerability%20assessment%20for%20Amman/Scenario%20Analysis), the effects of changes in heavy rainfall and land use changes, as well as measures to decrease flash flood damages are simulated with hydraulic and [hydrologic models](https://gitlab.pik-potsdam.de/peterh/captainrain/-/wikis/Home/WP-3-Flash-flood-risk-analysis/Hydrological-modelling-using-HEC-HMS) and assessed using vulnerability indicators. The results are incorporated into recommendations for urban planning (Fig.1).
Besides the vulnerability assessment for the current situation, we also explore vulnerability for possible future pathways with regard to climate (heavy rainfall) and land cover changes (exposure and sensitivity), as well as measures to decrease flash flood damages (adaptive capacity). Using a [scenario analysis](https://gitlab.pik-potsdam.de/peterh/captainrain/-/wikis/Home/WP%205%20Vulnerability%20assessment%20for%20Amman/Scenario%20Analysis), the effects of changes in heavy rainfall and land use changes, as well as measures to decrease flash flood damages are simulated with hydraulic and [hydrologic models](https://gitlab.pik-potsdam.de/peterh/captainrain/-/wikis/Home/WP-3-Flash-flood-risk-analysis/Hydrological-modelling-using-HEC-HMS) and assessed using vulnerability indicators. The results are incorporated into recommendations for urban planning (Fig.1).
<br>Fig. 1. _Vulnerability assessment cycle within the Captain Rain project_
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@@ -15,7 +15,7 @@ Our approach is based on the SEVA concept of Thiault et al. 2021[^2] and the gen
### Exposure
Exposure determines the degree to which a subject (inhabitant, building, ecosystem) is exposed to flooding in case of a flash flood event. It is calculated for the different domains using different sets of indicators:
Exposure determines the degree to which a subject (inhabitant, building, ecosystem) is exposed to flooding in case of a flash flood event. It uses a similar approach to the [analysis](WP 3 Flash flood risk analysis/Risk Maps), but takes into account a buffer of 10 m around the flood paths when assessing whether a building/object is exposed or not. It is calculated for the different domains using different sets of indicators:
-**Social Exposure**: Describes the exposure of residents, which is determined based on the proximity of residental buildings to flood prone areas. Classification was based on the simplified risk analysis of DWA-M 119 [^6] using the expected water level (cm) during a flash flood event (Baseline Scenario).
<details><summary>Detailed description</summary>
we classified all residential buildings within the analyzed watershed of Amman according to the simplified risk analysis of DWA-M 119. Using the expected water level (cm) during a flash flood event (Baseline Scenario) classification is as follows: 1 = low (<10cm);2=moderate(10–30cm),3=high(30-50cm)and4=veryhigh(> 50 cm). The final results were transformed to a 2 m raster file.
