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Harkunti Pertiwi Rahayu, Richard Haigh, Dilanthi Amaratunga, Benedictus Kombaitan, Devina Khoirunnisa and Vito Pradana
This paper aims to describe an in-depth study that aimed to assess and develop a strategic disaster risk reduction plan to integrate climate change adaptation countermeasures in…
Abstract
Purpose
This paper aims to describe an in-depth study that aimed to assess and develop a strategic disaster risk reduction plan to integrate climate change adaptation countermeasures in Cilincing, a North Jakarta City sub-district.
Design/methodology/approach
The study used a back-casting approach to cover hazard assessment induced by increased susceptibility, as well as vulnerability, both as a baseline study and projected up to 2045 at the micro level. The urban village (Kelurahan) level is the unit of analysis. The capacity analysis is used as baseline data, which is reviewed against the trend of the hazard and vulnerability.
Findings
The results of the study identify short-, medium- and long-term recommendations to integrate disaster risk reduction and climate change adaption. These include capacity building, especially emergency response capabilities, an increase of drainage capacity, improvements to transboundary management and minimising driving forces.
Practical implications
These findings at the micro level are very important to present a more holistic and realistic strategy that can be implemented until 2045, but also provides a basis for up scaling into metropolitan region planning.
Originality/value
This is a unique, micro-scale case study in the Cilincing sub-district of Jakarta that assesses and develops strategic disaster risk countermeasures and a reduction plan that integrates the effects of climate change, thereby addressing future disaster risk in Jakarta.
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José Guilherme Moreira Simões Vieira, Joana Salgueiro, Amadeu Mortágua Velho da Maia Soares, Ulisses Azeiteiro and Fernando Morgado
The development of models that allows the evaluation and prediction of erosion processes is an important tool for the management and planning of coastal systems. Mangrove forests…
Abstract
Purpose
The development of models that allows the evaluation and prediction of erosion processes is an important tool for the management and planning of coastal systems. Mangrove forests systems are under threat by the impacts of erosion, which is also intensified by human activity (and aggravated in the scenarios of global warming and climate change). The purpose of this paper is to develop a model of geographic information systems (GIS) that can be used for any estuary area, but it can also be used for mangroves.
Design/methodology/approach
This paper uses georeferentiation which is defined as a set of parameters that best characterize the mangrove areas: elevation (m); geomorphology; geology; land cover; anthropogenic activities; distance to the coastline (m) and maximum tidal range (m). Three different methods are used to combine the various vulnerability parameters, namely, DRASTIC index, analytical hierarchy process (AHP) and square root of the geometric mean.
Findings
The three approaches presented in this work show different types evaluating vulnerability to erosion, highlighting a stronger overvaluation of the areas presented with a high vulnerability, through the use of DRASTIC index when compared with two other approaches. The use of the AHP shows similarity to the square root of the geometric mean model, but the AHP also presents a higher percentage of vulnerable areas classified as having medium to very high vulnerability. On the other hand, the use of square root of the geometric mean led to a higher percentage of areas classified as having low and very low vulnerability.
Research limitations/implications
These three qualitative models, based on a cognitive approach, using the set of parameters defined in this research, are a good tool for the spatial distribution of erosion in different mangroves in the world.
Originality/value
Global warming and climate change scenarios require adaptation and mitigation options supported by science-based strategies and solutions.
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