Table 4.
Purpose/summary | Type of NBS (place) | Models to simulate NBS efficiency | Input parameters | References |
---|---|---|---|---|
Modelling the spatial pattern of root reinforcement | Re-introduction of vegetation (New Zealand) | Root Bundle Model | Root distribution data, tree stem diameter at breast height |
Schwarz et al. (2010) Schwarz et al. (2016) Vergani et al. (2014) |
Modelling landslide susceptibility for predicting sustainable forest management in an altered climate | Forest management (Queets watershed within the Olympic Experimental State Forest (OESF)) in western Washington State (U.S.) | Process-based hydrology model (Distributed Hydrology Soil Vegetation Model (DHSVM)) | Historic Meteorological Inputs, DEM (150 m), soil and land cover distribution, projected meteorological inputs from climate change scenarios, Soil and vegetation information (cohesion, unit weight), High resolution DEM (10 m) | Barik et al. (2017) |
Modelling the effects of sand-filled ditches on the hydrological conditions in a fruit farm on a slope (amount of infiltrating water) | Sand-filled drainage ditch (Olszanka, Poland) | FEFLOW | Slope geometry, ditch dimensions, soil parameters, vegetation cover data | Widomski et al. (2010) |
Assessing of the impacts of European forest types on hill slope stabilisation (mountainous area of Lombardy, Italy) | Forest Management | Limit equilibrium model, probabilistic framework (Monte Carlo techniques) | Root density and root mechanical properties | Chiaradia et al. (2016) |
To estimate the function of vineyards on slope stabilisation by modelling the additional strengthening to the soil supported by grapevine roots and their spatial distribution. | Plant roots and vegetations (northeastern part of Oltrepo Pavese, Northern Italy) | Root Bundle Model, Slope stability model | Root distribution and characteristics (diameter, length etc.), soil strength parameters | Cislaghi et al. (2017) |
Evaluate the impact of underlying foundations of birch trees on soil fortification and slant adjustment. | Birch trees | PLAXIS | The rainfall, slope gradient, geotechnical and hydrological parameters and soil thickness | Lotfalian et al. (2019) |
To investigate the capacity of vegetational NBS to reduce the onset and propagation probabilities of tsunamis generated landslides at Stromboli Island, Italy | Trees, forests, and grasslands | FUNWAVE-TVD | Bathymetric, topography | Fornaciai et al. (2019) |
To investigate the different aspects of hydrological and greenery effects on the stabilisation of hillslopes | Hydrological and greenery | SSHV-2D | Bathymetric, topography | Emadi-Tafti and Ataie-Ashtiani (2019) |
To simulate the efficiency of species and assessing its mechanical resistance against shallow landslides. | Vegetation | tRIBS-VEGGIE | Bathymetric, topography | Arnone et al. (2016a) |
To simulate the effectiveness of NBS against shallow landslides. | Forest canopies, leaf area index and plant height, and optimised forest management | BROOK90 | Forest structure, meteorological variables, root density, hydrological parameters and soil permeability | Federer et al. (2003) |