Table 5.
Overview of input hydroclimatic variables used to understand storm surge risk and models used to simulate the efficiency and performance of NBS against storm surges.
| Purpose/summary | Type of NBS (place) | Models to simulate NBS efficiency | Input hydroclimatic indicators | References |
|---|---|---|---|---|
| Quantifying the reduction of wave height and wave energy; | Salt marsh (laboratory) | The rate of wave height decay diminishes with distance into the marsh | Sea level | Hadadpour et al. (2019) |
| Quantifying the reduction in flood/wave velocity; minimising net sediment loss | Salt marsh (Chesapeake Bay; USA) | Relative reduction in flood/wave velocity; net sediment loss; Water level attenuation rates | Vegetation type, density, distribution; water pressure; topography; current profile during storm; wave velocity | Paquier et al. (2017) |
| Quantifying the stability of a marsh | Salt marsh (Alabama, USA) | SWAN | Significant wave height; frequency of occurrence of significant waves | Roland and Douglass (2005) |
| Explore the effect of a mangrove island on waves reaching port, which lies behind the island; explore the effects of eco-engineering and managing mangroves for coastal risk reduction | Mangroves (forests) (Kanika Sands mangrove island, Orissa, India) | SWAN model | Significant wave height; frequency of occurrence of significant waves, distance to port, type of mangrove trees, extent of mangrove forest |
Narayan et al. (2010) Hoque et al. (2020) |
| Quantify the effect of mangroves on storm surge peak water levels; the effect of wind waves and ground slope; | Mangroves (Mathbaria, Bangladesh) | 1D nonlinear, long wave differential equation | Maximum wind speed; water levels | Tanaka (2008) |
| Explore the effects of land cover types on flood extent. | Mangroves (Biscayne Bay, Florida, USA) | Unstructured Eulerian-Lagrangian Circulation (ELCIRC) model | Peak wind speed 227 km/h, maximum storm tide 5.2 m; Coastal mangrove zone 1 to 4 km wide with tree heights of 1 to 20 m, species (Rhizophora mangle, Avicennia germinans) | Xu et al. (2010) |
| Quantify peak water reduction through NBS area | Mangroves (Gulf Coast, Florida, USA) | Coastal and Estuarine Storm Tide (CEST) model | Maximum winds of 195 km/h speed, peak water level 5 m. Dominant species R. mangle, Laguncularia racemosa, A. germinans. Trees 4 to 18 m high, stem diameters 5 to 60 cm. Mangrove width 6 to 30 km; recorded water levels |
Zhang et al. (2012) Liu et al. (2013) |
| Quantifying the reduction of wave loading, flood/wave velocity | Vegetated berms (similar to dunes), Henderson Point, Mississippi, USA | Coupled storm surge and wave model (ADCIRC and SWAN) Hydrodynamic model (XBeach) | Sea levels high water mark elevation records, ground surface elevations (digital terrain model, LIDAR), flood hazard maps, storm return periods, 1:100 flood elevation, future sea level rise, storm locations, winds, pressures; vertical/horizontal wave loading; hydrodynamic force of drag, current velocity. Exposure, aspect and water availability considered for the vegetation on the berms | Web et al. (2018) |
| To model the wind field which drives the storm surge | Any/none (coastal USA) | Sea, Lake, and Overland Surges from Hurricanes model (SLOSH model) | Estimate storm surge heights resulting from historical, hypothetical, or predicted hurricanes by taking into account the atmospheric pressure, size, forward speed, and track data. A set of physics equations which are applied to a specific locale's shoreline, incorporating the unique bay and river configurations, water depths, bridges, roads, levees and other physical features |
Glahn et al. (2009) |
| To quantify the benefits from reef management. | Coral reefs (Global) | Nearshore hydrodynamics reef wave model, nearshore hydrodynamics total water level model, model of wave setup and run-up | Coastal profiles (2 km resolution), global wave climate and sea levels, topo- and bathy-metric data, | Beck et al. (2018) |
| To quantify coastal region resilience and protection offered by three types of NBS. | Reefs, seagrasses, and mangroves (Belize) | Numerical model for wave evolution and storm surge | Present and future scenario for non-storm and storm conditions; sea level rise, coral reef scenarios (live, decreasing, no corals); seagrass scenarios (different drag coefficient); mangrove conditions (presence of mangroves, drag coefficient) | Guannel et al. (2016) |
| To quantify the flow characteristics and sediment trapping capacity of seagrass meadows. | Seagrass meadows (laboratory) | Experimental model of the flow characteristics and sediment trapping capacity | Numerical model with measured shear stress and turbulence of flow, leaf density | Hendricks et al. (2008) |
| To evaluate the effectiveness of coastal wetlands in reducing expected flood damages. | Coastal wetlands, USA | Regression analysis | Wind speed, storm tracks and frequency of 34 major US hurricanes since 1980 | Costanza et al. (2008) |
| To assess future coastal flood risk in the Gulf of Mexico coast, USA. | Wetland restoration Barrier island restoration Oyster reef restoration Beach restoration US Gulf of Mexico coast |
Open-source software ‘CLIMADA’, and its ‘COASTAL’ module | The pressure, wind, rainfall, wind-waves and storm surge were calculated using parametric models. | Reguero et al. (2018) |