Comparing adaptive capacity index across scales: The case of Italy

How can we analyze environmental health resilience and vulnerability? A joint analysis with composite indices applied to the north of France

In environmental health, vulnerability reflecting the cumulative harmful constraints and nuisances to which populations are subjected and resilience defined as the capacity of a territory to cope with health inequalities have been little extensively investigated together with the same importance. Besides the diversity of factors involved, there is no consensual framework to develop composite indices, one recognized methodology to deal with a multifaceted issue. Therefore, this research aims to establish a new transferable approach to assess the spatial heterogeneity of territorial inequalities. This new strategy relies on the simultaneous evaluation of resilience and vulnerability and the joint analysis based on the cross-interpretation of the spatialized composite indices of resilience and vulnerability. A case study was conducted to demonstrate the feasibility of this methodology, using the municipality as a spatial unit of analysis within a region in the north of France. To provide the most holistic description possible of the 3817 studied municipalities, 50 variables related to the economic, environment, policy, health, services and social dimensions were used to develop the composite indices. The vulnerability Index has a median value of 0.151 with an IQR of [0.126-0.180] and the Resilience Index has a median value of 0.341 with an IQR of [0.273-0.401]. The joint analysis was conducted to classify each municipality among four defined typologies: 1687 municipalities (44.2%) belong to the "To monitor" category, 1646 (43.1%) to the "Resilient" category, 329 (8.6%) to the "Have resources" category and 155 (4.1%) to the "Territorial blackspot" category. The methodology herein may be a diagnostic tool to identify and prioritize municipalities that could benefit from the implementation of specifically tailored public health policies.

Assessment of smallholder farmers' adaptive capacity to climate change: Use of a mixed weighting scheme

Weighting scheme definition represents an important step in assessment of adaptive capacity to climate change with indicator approach since it defines the trade-offs among indicators or components and can be source of uncertainty. This study aims to assess smallholder farmers' adaptive capacity to climate change by using a mixed weighting scheme that reflect farmers' perceived importance of adaptive capacity components to inform policy makers. To achieve that objective, the sustainable livelihood framework was adopted and indicator approach was used for the assessment. The mixed weighting scheme were defined by using both equal weights and experts judgement methods during the assessment process. The mixed weighting scheme index is compared to the case where equal weights are applied in the assessment process and an uncertainty analysis was performed on relative standard deviation through a Monte Carlo simulation. Primary Data were collected from 450 farmers in two communities in northern Benin with a structured questionnaire and through focus groups discussion. The results show that smallholder farmers in both communities do not have the same perceived importance of adaptive capacity components. The index scores show that farmers have in majority low adaptive capacity. When weighted product aggregation method is used, there is more uncertainty related to the index computed with the mixed weighting scheme, but it leads to the same characterisation when compared with the index computed with the equal weights. It is recommended that mixed weighting scheme should be preferred for the assessment of adaptive capacity and weighted product aggregation method should be used.

Flood Vulnerability Assessment for Prioritizing and Evaluating Rehabilitation of Ungauged Reservoirs Considering Climate Change

The objective of this research was to apply the flood vulnerability assessment to ungauged reservoirs for prioritizing and evaluating the reservoir rehabilitation according to climate change. The flood vulnerability index (FVI) can quantitatively compare the flood vulnerabilities of the analysis targets and can be used for the relative comparison of hydraulic structures to determine the reinforcement priority. In this study, we proposed a simple FVI that contained exposure and adaptive capacity of the hydraulic structure. We selected ten dam heightening reservoirs in Korea and constructed data for flood vulnerability assessment. The FVI was calculated before and after the dam heightening to analyze the priority and effect of reservoir rehabilitation under climate change. Flood vulnerability indices were estimated for four periods (1995s: 1981–2010, 2025s: 2011–2040, 2055s: 2041–2070, 2085s: 2071–2100) and before/after the dam heightening project. As a result, flood vulnerability indices decreased after the dam heightening project for all reservoirs, and the indices have increasing tendencies in the future. The indices developed in this study can be useful to determine the priority and to evaluate the effect of rehabilitation for hydraulic structures.

Constructing a comprehensive disaster resilience index: The case of Italy

Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans.