Spotting areas critical to storm waves and surge impacts on coasts with data scarcity: a case study in Santa Catarina, Brazil

Abstract

The impacts of severe storms on the coastal zone, combined with rapid population growth in this area, has made coastal risk management an urgent need. However, integrated risk assessment can be a challenging task for many locations worldwide, as it normally requires the use of a large amount of data. The Coastal Risk Assessment Framework phase one (CRAF1), is a recently proposed analytical scheme based on empirical models and spatial analysis that combines different indicators to identify storm-induced hotspots. The methodology, however, requires accurate data at the regional scale and was conceived and validated for the European region. In this study, we show that this approach can be applied, with some simplifications, on data-poor areas, allowing the identification of hotspots considering one or multiple hazards. Here, the coastal risk was assessed for erosion and coastal flooding events with return periods of 10 and 50 years on the Santa Catarina Central Coast. The study area is characterized by the occurrence of storminduced impacts that historically cause disruption and damage to local communities.Although the components of risk have been assessed using various methods along this sector, to date, no integrated risk analysis has been presented in probabilistic terms.Predicted scenarios for the Santa Catarina Central Coast suggest that extreme episodes may cause several impacts, exposing urban settlements as well local road systems, especially in the municipalities of Tijucas and Florianópolis. The results show that the CRAF1 is an appropriate approach for a first-level risk analysis, even when implemented with poor data resolution, as it effectively points to some of the most vulnerable stretches detected in the study area.

Identification of coastal natural disasters using official databases to provide support for the coastal management: the case of Santa Catarina, Brazil

“…This result points to the greater exposure of the two locations to meteoceanographic events, with emphasis on the Island (Horn Filho 2006). In the study by Pazini et al (2021), the authors also discussed the very high risk of storm-induced impacts in the same municipalities in the central sector. Furthermore, the greatest morphological changes on beaches usually occur during processes of sudden energy transfer to the system, such as during storm surges.…”

“…In addition, we must consider the meteoceanographic conditions that interact with the coast, such as the intensity, duration, and direction of prevailing winds; the intensity and direction of local marine currents; the intensity and variations of astronomical and meteorological tides; the height, period and direction of the waves; and the proximity to river mouths. Additionally, several researchers highlight human activities as an impacting factor that contributes to changing the dynamics of the coastal area (Castro 2003;Klein et al 2016;Luijendijk et al 2018;Leal et al 2020;Pazini et al 2021).…”

“…The coast trends from south to southwest for approximately 430 km, and contains 922 km of open coast and bay shoreline, with 246 sandy beaches occupying 60% of the shore (Klein et al 2016). In the state, about 1,417,089 (22.7%) of the total 6,248,436 inhabitants are located in these municipalities (IBGE, 2010), where coastal natural disasters are frequently recorded (Klein et al 1999;Horn Filho 2006;Klein et al 2006;Santos 2007;CEPED UFSC 2013;Herrmann 2014;Klein et al 2016;CPRM, 2018;Dalinghaus et al 2018;Muehe 2018;Leal et al 2019;Silveira et al 2019;Leal et al 2020;De Lima et al 2020;Furtado and Bonetti 2021;Pazini et al 2021). The geological, geomorphological, climatic, sedimentary, and oceanographic characteristics of the study area can be found in detail in the study by Klein et al (2016).…”