Reduced-complexity modeling as a valuable tool for studying the coastal impacts of climate change

Forecasting the coastal response to climate change is a complex problem due to the nonlinear interplays at multiple scales between the different hazards, i.e. flooding and erosion. To handle this challenge, the use of simple and computationally efficient, yet accurate tools is required. The combination of reduced-complexity shoreline modelling and efficient physics-based flood spread models is an appropriate way to project coastal risks under climate scenarios, being a balanced solution regarding computational time and accuracy. We present a methodology comprised by an efficient wave downscaling methodology, the recently developed shoreline evolution model IH-LANS (Alvarez-Cuesta et al., 2021a), flood-spread modeling and an ensemble treatment of climate-related uncertainty as in (Alvarez-Cuesta et al., 2021b) to forecast the evolution of coastal risk. The methodology is applied at a vulnerable low-lying coastal area in Murcia, Spain and it allowed to highlight the coastal hotspots and the definition and evaluation of adaptation measures. This application strengthen the suitability of reduced-complexity modeling to guide decision making in complex coastal settings.

 

Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021a). Modelling long-term shoreline evolution in highly anthropized coastal areas . Part 1 : Model description and validation. Coastal Engineering, 169(July), 103960. https://doi.org/10.1016/j.coastaleng.2021.103960

Alvarez-Cuesta, M., Toimil, A., & Losada, I. J. (2021b). Modelling long-term shoreline evolution in highly anthropized coastal areas . Part 2 : Assessing the response to climate change. Coastal Engineering, 168(July), 103961. https://doi.org/10.1016/j.coastaleng.2021.103961