A Geospatial Assessment Toolbox for Spatial Allocation of Large-Scale Nature-Based Solutions for Hydrometeorological Risk Reduction
Adam Mubeen (IHE Delft Institute for Water Education, TU Delft - BT/Environmental Biotechnology)
Vishal Balaji Devanand (IHE Delft Institute for Water Education)
Laddaporn Ruangpan (Deltares)
Zoran Vojinovic (IHE Delft Institute for Water Education, University of Exeter)
Arlex Sanchez Torres (IHE Delft Institute for Water Education)
Jasna Plavšić (University of Belgrade)
Natasa Manojlovic (Hamburg University of Technology)
Guido Paliaga (Geographical Information Systems International Group, Genova)
João P. Leitão (Eawag - Swiss Federal Institute of Aquatic Science and Technology)
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Abstract
The compounding effects of hydrometeorological hazards are being driven by climate change. As urban areas expand, this leads to degradation of the surrounding environment and exposes more people to hazards. Growing losses show that conventional approaches to addressing these issues can compound these problems. Over the last few decades, nature-based solutions (NBSs) have become an increasingly popular alternative. These measures, inspired by natural processes, have shown potential for reducing hazards by complementing traditional approaches and providing co-benefits in the form of eco-system services. With the adoption of NBSs becoming a more mainstream approach, there is a need for tools that support the planning and implementation of interventions. Geospatial suitability assessment is a part of this planning process. Existing tools are limited in their application for large-scale measures. This paper intends to improve this by building upon a multi-criteria analysis (MCA)-based approach that incorporates biophysical and land use criteria and conditions for mapping the suitability of large-scale NBSs. The methodology was developed and tested on six sites to assess the suitability of floodplain restoration, retention or detention, afforestation, and forest buffer strips. The resulting suitability maps also show potential for combining two or more measures for greater risk reduction.
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