Climate-Induced Sea Level Rise and Sustainable Coastal Management: The Influence of Existing Policy Frameworks on Risk Perception

2014 ◽  
Vol 7 (6) ◽  
pp. 299-303 ◽  
Author(s):  
Chad J. McGuire
2021 ◽  
Vol 13 (8) ◽  
pp. 1424
Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.


Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence 15 of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal 16 management. This study aims to develop and to validate two different models to predict the 17 sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for plan-18 etary-scale environmental data analysis. The first model is a Bathtub Model based on the uncer-19 tainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and 20 Modeling System software. The validation process performed in the Rio Grande do Sul coastal 21 plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule for-22 mula implemented in GEE and is capable to determine the coastline retreat of a profile through the 23 creation of a simple vector line from topo-bathymetric data. The model shows a very high correla-24 tion (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE 25 platform seems to be an important tool for coastal management. The models developed have been 26 openly shared, enabling the continuous improvement of the code by the scientific community.


Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
João Francisco Gonçalves ◽  
Luiz Magalhães Filho ◽  
Cristina Bernardes

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal man-agement. This study aims to develop and to validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.


Author(s):  
Inti Carro ◽  
Leonardo Seijo ◽  
Gustavo J. Nagy ◽  
Ximena Lagos ◽  
Ofelia Gutiérrez

Purpose This study aims to show a case study of ecosystem-based adaptation (EbA) measures to increase coastal system’s resilience to extreme weather events and sea-level rise (SLR) implemented at Kiyú (Uruguayan coast of the Rio de la Plata river estuary). Design/methodology/approach A participatory process involving the community and institutional stakeholders was carried out to select and prioritise adaptation measures to reduce the erosion of sandy beaches, dunes and bluffs due to extreme wind storm surge and rainfall, SLR and mismanagement practices. The recovery of coastal ecosystems was implemented through soft measures (green infrastructure) such as revegetation with native species, dune regeneration, sustainable drainage systems and the reduction of use pressures. Findings Main achievements of this case study include capacity building of municipal staff and stakeholders, knowledge exchanges with national-level decision makers and scientists and the incorporation of EbA approaches by subnational-level coastal governments. To consolidate EbA, the local government introduced innovations in the coastal management institutional structure. Originality/value The outcomes of the article include, besides the increase in the resilience of social-ecological systems, the strengthening of socio-institutional behaviour, structure and sustainability. This experience provides insights for developing a strategy for both Integrated Coastal Management and climate adaptation at the national scale.


Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2263
Author(s):  
Lida Davar ◽  
Gary Griggs ◽  
Afshin Danehkar ◽  
Abdolrassoul Salmanmahiny ◽  
Hossein Azarnivand ◽  
...  

Sea-level rise (SLR) is known as a central part of the Earth’s response to human-induced global warming and is projected to continue to rise over the twenty-first century and beyond. The importance of coastal areas for both human and natural systems has led researchers to conduct extensive studies on coastal vulnerability to SLR impacts and develop adaptation options to cope with rising sea level. Investigations to date have focused mostly on developed and highly populated coasts, as well as diverse ecosystems including tidal salt marshes and mangroves. As a result, there is less information on vulnerability and adaptation of less-developed and developing coasts to sea-level rise and its associated impacts. Hence, this research aimed at outlining an appropriate coastal management framework to adapt to SLR on the coasts that are in the early stage of development. A coastal area with a low level of development, located in southern Iran along the Gulf of Oman, was selected as a case study. The types of lands exposed to the high-end estimates of SLR by 2100 were identified and used as the primary criteria in determining the practical adaptation approaches for developing coasts. The result of coastal exposure assessment showed that, of five exposed land cover types, bare land, which is potentially considered for development, has the highest percentage of exposure to future sea-level rise. In order to protect the exposed coastal lands from future development and increase adaptive capacity of coastal systems, we developed a Spatial Integrated SLR Adaptive Management Plan Framework (SISAMP) based on an exposure reduction approach. Spatial land management tools and coastal exposure assessment models along with three other key components were integrated into the proposed conceptual framework to reduce coastal vulnerability through minimizing exposure of coastal communities to SLR-induced impacts. This adaptation plan provides a comprehensive approach for sustainable coastal management in a changing climate, particularly on developing coasts.


Author(s):  
Lucas Terres de Lima ◽  
Sandra Fernández-Fernández ◽  
Carlos V. C. Weiss ◽  
Volney Bitencourt ◽  
Cristina Bernardes

This work assesses sea-level rise using three different models created on Free and Open-Source Software for Geographic Information System (FOSS4GIS). Based on regional projections of Special Report on Climate Change and Oceans and Cryosphere (SROCC) of the Intergovernmental Panel on Climate Change (IPCC), the models were applied to a case of study on Rio Grande do Sul coast – Brazil under different sea-level rise scenarios by the end of this century. The End Point Rate for QGIS (EPR4Q), calculates a shoreline projection using End Point Rate method. The Uncertainty Bathtub Model (uBTM), analyses the sea-level rise impact by the uncertainty of sea-level projec-tions and vertical error of the Digital Elevation/Terrain Model (DEM/DTM). The Bruun Rule for Google Earth Engine Model (BRGM) predicts the shoreline position with sea-level rise, using topographic and bathymetric data from Unmanned Aerial Vehicles (UAV) and Coastal Modelling System (SMC – Brazil), respectively. The results indicated a maximum shoreline retreat for 2100 of -502 m and -1727 m using EPR4Q and BRGM, correspondingly. The uBTM using the land-use of Mapbiomas showed a maximum of 44.57 km2 of urban area impacted by the sea-level flood. This research highlights the possibility of performing coastal management analysis in GIS environ-ment using non-commercial software.


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