Cross-Scale Evaluation of Nature-Based Solutions for fluvial flood hazard reduction

Floods are among the most damaging natural hazards worldwide, with impacts expected to intensify due to climate change and increasing exposure in flood-prone regions. Recent large river floods, such as the July 2021 event in the Meuse basin affecting Belgium, Germany, and the Netherlands, have led to new interest in Nature-based Solutions (NBS) to manage floods by using natural processes in river systems. NBS for example, include reforestation and flood plain restoration in downstream areas. However, robust evidence of the effectiveness of NBS across spatial scales, hydroclimatic conditions, and flood magnitudes remains limited, particularly for large river basins and transboundary settings. 

In this study, we evaluate the effectiveness of NBS for fluvial flood hazard reduction, applying the hydrological–hydrodynamic GEB modelling framework. Basin-scale hourly hydrological simulations are dynamically linked to the 2D hydrodynamic model SFINCS, to simulate flood hazard dynamics on a 10m resolution. Next, we include two NBS measures in the model: upstream reforestation and downstream in-channel (floodplain restoration). We schematize these measures into our modeling framework and simulate their effectiveness for lowering flood peaks as individual measures and in combination. Reforestation is implemented within the hydrological model by altering land cover, soil, vegetation, and Manning's roughness parameter in designated upstream zones. Floodplain restoration is represented in the hydrodynamic model by modifying topography and hydraulic parameters along the main river channel in downstream areas.  

We test the NBS across basins with different hydroclimatic conditions and spanning multiple countries. We selected three similarly sized catchments (~30,000 km²) across different Köppen climate zones: the transboundary Meuse basin in Western Europe, the Upper Paraná River basin in Brazil, and the Krishna River sub-basin (Tungabhadra) in India. The model has been validated against satellite-observed flood extents from Copernicus Emergency Management Service products, showing good agreement for the 2021 Meuse flood (Critical Success Index = 0.75). For each of the three basins, we select multiple flood peaks with different timings and magnitudes. Using boundary conditions for these different events as input, flood extents are simulated before and after NBS implementation and evaluated by comparing baseline and intervention scenarios. We evaluate differences by (1) quantifying basin-scale changes in peak discharge, (2) inundation extent, and (3) average water depth. 

The novelty of this research lies in its comparison of NBS across multiple river basins with different climates and geographic settings. By testing the same NBS measures in the Meuse, Upper Paraná, and Krishna basin, this study assesses whether their effects on flood peaks and inundation patterns are consistent across regions and flood events. This provides much-needed evidence on the conditions under which NBS are (or are not) effective in reducing flood hazards in large river systems.