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Natural flood management (NFM), or working with natural processes, is a growing flood risk management method in the UK, Europe and worldwide. However, unlike the current dominant technical flood management, it lacks an established evidence base of flood risk parameters. This lack of evidence base can limit the uptake of NFM as a flood management method. This paper critically evaluates examples of NFM and wider relevant literature in order to identify NFM knowledge gaps and suggest how to overcome these. The UK is used as a microcosm of different environments for diverse examples. The sections include: land cover, land management, landscape interactions and trade-offs, evaluating the wider benefits of NFM and, finally, scaling from plot to catchment. This concludes in a suggested framework for a new approach to NFM research, which encompasses spatial scales, interactions and trade-offs of NFM and consistency of reporting results. Widening the NFM empirical evidence base should be seen as an opportunity for a new approach to flood research through exploring new habitats and new flood resilience methods. [ABSTRACT FROM AUTHOR]

Grasslands vary with diverse forms and functions ranging from monocultures of perennial rye grass to more biodiverse unimproved grasslands which cover around 5% of Europe. Despite the broad diversity of grassland types, within environmental and flood risk models grasslands are frequently represented by a singular set of hydrological and structural parameters which belies their diversity and complexity. This study aimed to determine empirically the extent to which improved versus unimproved grasslands exhibit different hydrological connectivity. Working in SW England at neighbouring field sites with comparable slopes and rainfall regimes, we used unpiloted aerial vehicles to survey a tussocky Molinia caerulea dominated unimproved grassland field (MCUG) field and a Lolium perenne dominated improved grassland (LPIG) field. Using digital photogrammetry workflows applied to the overlapping aerial images, we produced a digital surface model (DSM) at 0.03‐m resolution from which flow pathways were modelled using GIS and compared with 1‐m LiDAR and DSM produced by a global navigation satellite system (GNSS). MCUG had longer, tortuous pathways through the dense tussock network with a drainage density of 2.54 m m−2. This was significantly greater than drainage density in the LPIG (1.82 m m−2). As a result of this study, we rescaled the Manning's n value for MCUG according to photogrammetrically‐derived roughness values. We suggest it should lie between 0.075 and 0.09. Our data shows that MCUG can play an important role in reducing overland flow impacts when compared to LPIG through lower connectivity which can delay run‐off to rivers. [ABSTRACT FROM AUTHOR]