- Climate adaptation focuses its efforts on supporting adaptation and building resilience. Building resilience is also an important task for DRR. There is thus a common need to address climatological extremes and to reduce vulnerability and enhance resilience.
- The common interests include the identification, implementation and evaluation of prevention and preparedness measures in the context of extreme events. These have led to an expressed need for a stronger relationship between the DRR and climate adaptation communities, including between their respective service platforms.
b. DRR and CCA services - consideration of risk
CCA : - Integration of climate, environment as well as socio-economic information and data. Interest in assessing and addressing climate-related risks.
DRR: - Integration of climate, environment as well as socio-economic information and data. Interest in assessing and addressing disaster related risks, (broader than just climate risks).
c. Means of delivery
- Available and accessed through a variety of mechanisms, including web-based platforms
d. The nature and scope of the platforms Climate adaptation platforms:
- have different origins and do not yet have a general guiding framework (EEA, 2015)
- tend to focus on providing action-oriented and supportive policy data, information and knowledge (services)
- include socio-economic and other environmental data and information, and tools and resources to support adaptation decision-making.
- addresses changes in extreme climate events,
- focuses its efforts on supporting adaptation and building resilience Platforms on DRR:
- cover the whole policy and implementation cycle of early warning, prevention, preparedness, response and recovery.
- provide opportunities for interested practitioners to share and develop knowledge and experiences on DRR-related issues
- include socio-economic and environmental data and information, and tools and resources to support risk management decision-making.
- focuses its efforts on supporting adaptation and building resilience 4.3.2 Risk Data hub linking DRR and CCA
The RiskData Hub enhance collaborations with climate adaptation platforms. The RiskData hub is focused on sharing data, information and knowledge, which support users on disaster risk management. Even though various DRR platforms have been operating for this purpose only, the common interests have required a stronger interaction at regional and national level with climate change adaptation platforms.
RiskData Hub enhance collaboration within climate adaptation platforms by:
- Identifying incentives (e.g. provide loss and damage assessments as results of extreme events) and resources to enable the appropriate collaboration;
Figure 15. Conceptual approach of the relation DRR and CCA on Risk Data Hub platform
Source: Risk Data Hub, 2017.
- Improving the institutional linkages to better connect these platforms in areas of common interest (identification, implementation and evaluation of prevention and preparedness);
- Exchanging experiences on the collection and structuring of data, information and knowledge;
- Identifying priority areas and improve the links to support collaboration (e.g. integration of response policies, plans and action, and better consideration of the long-term perspective of adaptation in addressing local DRR)
An example: Risk Data Hub contributes to the harmonisation and standardisation of the risk data content, collection and structuring of data considering CCA. It supports the basis for estimating likelihood (from return periods) of extreme events. Socio-economic and environmental exposure and impacts to extreme events are structured based on return periods and are considering climate change scenarios (RCP2.6, RCP4.5, and RCP8.5)3 for base period, near future and end of the century.
This is important when users are expected to switch between different views of the same topic such: as short-term risk management of extreme events versus long-term adaptation to extreme events in a changing climate (Fig. 15).
3 Three emissions scenarios, termed Representative Concentration Pathways (RCP) by the Intergovernmental Panel on Climate Change (IPCC). All scenarios specify radiative forcing relative to pre-industrial conditions.
The RCP8.5 scenario is the most severe, with greenhouse gases continuing to increase through the next century, resulting in radiative forcings of 8.5 W/m2 , CO2 concentrations of 1370 pppm and a temperature anomaly of 4.9 ◦ C by 2100. The RCP4.5 scenario represents a medium future scenario, where greenhouse gases and therefore radiation stabilize by the end of the century with an overshoot at 4.5 W/m2 , 650 ppm CO2, and a temperature anomaly of 2.4 ◦ C. The least severe future scenario is the RCP2.6, which includes a mid-century peak at 3 W/m2 before declining to 2.6 W/m2 , 490 ppm CO2, and a temperature anomaly of 1.5◦ C.( Moss et al., 2010).
5 Conclusions
Key messages on risk web-platforms good practices
There are several platforms (ONRN, PLANAT, HORA) that offered a complete and easy to access information that used the following characteristics:
- the geospatial information presented on the web platform included the relation exposure – hazard. This approach provides a more complete insight to practitioners and policy makers regarding disaster risk assessments in general.
- the across-scale view in disaster risk assessment was included considering administrative units as aggregation stages for risk information. The management of the risk reflects more the policy component and they are linked with administrative directives, organizations and operational skills coordinated at level of administrative entities.
- the disaster risk information is linked across scale to individual assets/exposure data that can be easily integrated with preparedness, resilience and financing schemes (top-down actions) that are linked at property/asset level.
- the hazard assessment included information based on scenarios (return period).
This approach support the probabilistic approach (risk is the probability of the impact/damage) in disaster risk assessment.
- the geospatial information includes mapping on hazard, vulnerability, risk and resilience at local level.
- the cross-discipline approach includes a Multi-Hazard approach. This implies an alignment of methodological approaches and data used for disaster risk assessment across different hazards.
- the geospatial data on hazards and exposure was backed up by loss records of historical events and lessons learnt.
- the level of disaster risk reduction are presented as analysis of the progress made in the implementation of prevention measures (e.g. ONRN platform).
Key messages on risk web-platforms landscape in Europe
- The disaster risk web-platforms in Europe is varied, and the number and scope of such platforms are increasing. There are risk web-platforms that are providing disaster risk information at the national level and for multiple hazards (Austria-HORA, France-ONRN, Slovenia – Atlas Okolja etc.). They are part of governmental institutions, mostly the Environment Ministry.
- At sub-country level the presence of the disaster risk web platforms are linked either with project developments (ex. France – SAMCO project) or are means of assisting decision-makers in the different steps of the adaptation policy cycle. They are primarily linked to the preparation, implementation and evaluation of adaptation strategies and plans. For example the Implementation of flood directive:
• Catalonia Internal Hydrographic Basin, (GIS Viewer) http://aca-web.gencat.cat/recursos/sig/public/VisorPEF.html
• Miño-Sil Hydrographic Basin, (GIS Viewer) http://siams.chminosil.es/snczi/
• Jucar Hydrographic Basin, (GIS Viewer)
http://aps.chj.es/idejucar/?f=RWEB_WEB_ARPSI_F&c=SNCZI_Estudio_cartografico_z onas_inundables
• Ebro Hydrographic Basin, (GIS Viewer) http://iber.chebro.es/sitebro/sitebro.aspx?SNCZI
• Eastern Cantabrico Hydrographic Basin, (GIS Viewer) http://www.uragentzia.euskadi.net/appcont/gisura/
- At transnational level, the web platforms, mainly developed during projects, are focusing on single hazards (e.g. DriDanube, The ALP FFIRS, Enviro Grids for water scarcity. These different platforms have varied histories and have been in place for different lengths of time. They have also policy contexts that are reflected in the scope of services provided. Most of the platforms are directly linked to the implementation of EU adaptation strategies and plans.
The EU research funds have served as an input for developing amongst platforms, for example the FP7 Framework or the Horizon 2020 Framework Programme for Research and Innovation call. A great number of projects have been developed at European level such as Drought Impact Report Inventory – EDII.
Key messages on needs in risk web platform developments
The geospatial representation of the relation exposure - hazard provides a more complete insight to practitioners and policy makers regarding risk assessments. Disaster risk assessment is set on identifying the geographically located causal factors of disasters, including exposure to hazards, vulnerability of people and property, land use and environment. This is important since an inventory based disaster risk assessment linked to individual assets/exposure, can be easily integrated with preparedness, resilience and financing schemes (top-down actions) that are linked at property/asset level. There is though limitations in terms of linking information to assets level where administrative areas or hydrological basin). Therefore, the extraction of exposure data for an individual community or sub-set of communities can be challenging and time-consuming for a practitioner. This is important since an inventory based disaster risk assessment linked to individual assets/exposure, can be easily integrated with preparedness, resilience and financing schemes (top-down actions) that are linked at property/asset level.
- The geospatial representation of the relation exposure - hazard with aggregated totals rarely provide practitioners with the ability to focus on a particular topic of interest such as a demographic attribute (e.g., renter-occupied households), business sector (e.g., manufacturing or retail) or land cover type (e.g., wetlands). Availability and accessibility of attribute information for exposure provide the necessary link to evaluate whether the hazard metrics can predict impacts. This detailed datasets creates the basis for studies relating physical characteristics of the natural hazard events to their various impacts.
- In the case of climate driven hazards, most of the risk web-platforms does not offer hazard assessment information based on scenarios and it is limited to presenting aggregated totals (over an area and over historical period).
- Finally, the risk web-platforms that are based on the underlying hazards and socioeconomic relations (temporal, spatial coincidence etc.) are not designed to allow for regular updates as new hazard modelling is completed or new socioeconomic data are acquired.
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List of figures
Figure 1. Different categories of drought and their development ...14 Figure 2. CDI classification scheme based on three drought impact levels and two vegetation recovery stages (Sepulcre-Canto, et. al., 2012) ...15 Figure 3. Landslide susceptibility assessment at the NUTS 3 aggregation level ...16 Figure 4. Forest fire –number of fires - at the country administrative level ...17 Figure 5. Risk modelling of disaster risk provides quantitative risk metrics that capture the severity and frequency of the loss distribution. For example, an EP curve portrays the probability of exceeding a given level of loss, the area under the curve represents the average annual loss (AAL), return period (RP) is the reciprocal of the exceeding
probability, while Loss RP is the loss for a given return period ...19 Figure 6. Example of the risk matrix approach ...21 Figure 7. Risk Indicator based approach ...21 Figure 8. Drought Exposure, Risk, Vulnerability and Hazard at the NUTS 2 aggregation level ...22 Figure 9. Mapping drought risk, likelihood of impact occurrence (for fifteen specific impact sectors) ...25 Figure 10. Flood Exposure, Risk, Vulnerability and Hazard at the NUTS 2 aggregation level ...26 Figure 11. Map view of the ONRN indicators. As example: a). Number of landslides, b).
Proportion of municipal surface area with high subsidence in 2014 (%), c).Progress of flood prevention plans, d). Mean cost €/ inhabitant in 2013 due to flood damage. ...36 Figure 12. Schema of the Multi-Hazard Risk Data Hub architecture, based on the
Geonode technology stack. The hub will be also integrated with the DRMKC web portal (e.g. for displaying the latest published layers) through the RESTul web services made available by GeoNode. ...38 Figure 13. Infrastructure potential impact (equivalent to tonnes of oil) from landslide susceptibility ...39 Figure 14. Flood (RP 10yr) potential impact on demography; a) – population age < 5 years old; b) population age > 65 years old: c) population age >65 leaving alone; d) population potentially affected by flood ...40 Figure 15. Conceptual approach of the relation DRR and CCA on Risk Data Hub platform ...43
List of tables
Table 1. Drought risk assessment resources ...23 Table 2. Web platforms for risk management considered ...33
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