DISFLOOD - Disaster Information System for Large-Scale Flood Events using Earth Observation | Umweltbundesamt

Background and Goals

The most recent floods in Germany have illustrated the vulnerability of towns and communities and have affected many sectors and areas of activity, including infrastructure, communication, commerce, culture, industry etc. Assessing the characteristics of a flood situation and its negative effects is a prerequisite for effective flood management. However, assessing the geographical extent of flooding is difficult, particularly for large-scale events. For this kind of large-scale events, the information on flooding and its consequences is distributed between a range of institutions in different communities or regions. There is not normally a standardised picture of the entire event. Satellite data now enables the entire geographical situation to be represented. In combination with large-scale data records, e.g. state-wide topographical and socio-economic data, it is possible to provide differentiated variables for characterising a flood risk.

The objective of the project is to use the latest methods in remote reconnaissance, modelling and the incorporation of socio-economic data to develop a flood information system for large river drainage basins in Germany. This will ensure that risks and damage can be assessed more quickly, increase public awareness and support political decision makers. The effects of large-scale flooding are assessed using earth observation. The method used is implemented with a software system in the NaDiNe networking platform.

The flood information system has the following objectives:

•  Provision of flood areas based on satellite data;
•  Derivation of parameters that influence damage (e.g. flooding height);
•  Assessment of direct economic losses;
•  Provision of vulnerability indicators.

The project involves the following activities:

1. Vulnerability and flood risk assessment: Earth observation based identification and characterisation of at-risk locations (hospitals, industrial plants, dykes etc.) and urban and rural population structures; indication of risk areas.

2. Rapid recording of flood areas: Derivation of flood areas from the latest optical and SAR satellite image data; monitoring dynamics of flood events over time.

3. Extrapolation/interpolation of flood areas for the high water level: Cutting of flood area using digital land model in GIS; derivation of hydraulic parameters (e.g. flood depth, flood duration); adaptation of water level based on current or forecast level data and derivation of relevant flood area.

4. Validation of damage assessment and disaggregation: Identification of affected locations, infrastructure and land use types; disaggregation of calculated vulnerability indicators and damage.

The work will be carried out at a macro level. The methods will be developed for the Elbe and for the states of Saxony and Saxony-Anhalt, but could potentially also be applied to other major rivers such as the Rhine and the Danube.

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