An Integrated Multidimensional Resilience Index for urban areas prone to flash floods: Development and validation.

Resilience analysis is critical in developing flash flood risk reduction strategies in the context of global change and sustainable development. The most common method for assessing resilience is index-based. Nevertheless, the resulting indices typically fail to represent resilience's multidimensional character since they frequently disregard all involved dimensions (i.e., social, economic, environmental, physical, institutional, and cultural). Furthermore, regional resilience indices are rarely externally validated in urban areas prone to flash flooding because the required data are limited and flash flooding does not occur concurrently throughout the study region. This research developed and validated a regional Integrated Multidimensional Resilience Index (IMRI) in urban flash flood-prone areas to address the aforementioned knowledge gaps. The Monte Carlo method enabled internal validation of the IMRI following uncertainty and sensitivity analyses. Latent Class Cluster Analysis (LCCA) was used to characterize resilience, leveraging resulting regional spatial patterns. The findings obtained revealed that the most resilient urban areas have greater social and cultural resilience, while the least resilient urban areas should strengthen their social and institutional resilience. Validation results demonstrated a low bias between the IMRI scores and the control statistics derived from the Monte Carlo analysis as well as a higher than 80 % probability of not getting variations in the resilience categories, confirming the robustness of the IMRI. Through LCCA, five distinct regional spatial patterns of resilience were identified. The methodological approach deployed here enabled the identification of the underlying characteristics that determine the urban system's resilience to flash flooding, thereby supporting the formulation of resilience-building strategies for each dimension and urban area under consideration.

How to construct and validate an Integrated Socio-Economic Vulnerability Index: Implementation at regional scale in urban areas prone to flash flooding.

Flash flooding is the natural hazard provoking the largest number of casualties, so adequately characterizing vulnerability is key to improve flood risk analysis and management. Developing composite indices is the most widely used methodology in vulnerability analysis. However, very few studies have so far assessed vulnerability in urban areas prone to flash flooding and the resulting research presents two main drawbacks: i) a fragmented approach is often pursued, i.e. without jointly considering the vulnerability components (exposure, sensitivity and resilience) and the two most influential dimensions in urban environments (social and economic); and ii) vulnerability indices are not usually validated because an ancillary dataset is not generally available and flash flooding events do not happen simultaneously in all urban areas of a particular region. Considering the above gaps, this paper describes the construction of an Integrated Socio-Economic Vulnerability Index (ISEVI) at the regional scale, which considers all vulnerability components and social and economic dimensions. ISEVI was subsequently validated through an uncertainty and sensitivity analysis using the Monte Carlo method. Further, regional spatial patterns of vulnerability were identified implementing a Latent Class Cluster Analysis. Uncertainty analysis reveals the high stability of vulnerability categories of the ISEVI and sensitivity analysis shows that the type and the conservation state of buildings are the vulnerability factors that cause a greater variability in ISEVI scores. The method deployed here may allow specific strategies for vulnerability reduction to be developed based on disaggregating the validated ISEVI into dimensions and components and using the regional spatial patterns characterized.

Laboratory and Field Protocol for Estimating Sheet Erosion Rates from Dendrogeomorphology.

Sheet erosion is among the crucial drivers of soil degradation. Erosion is controlled by environmental factors and human activities, which often lead to severe environmental impacts. The understanding of sheet erosion is, consequently, a worldwide issue with implications for both environment and economies. However, the knowledge on how erosion evolves in space and time is still limited, as well as its effects on the environment. Below, we explain a new dendrogeomorphological protocol for deriving eroded soil thickness (Ex) by acquiring accurate microtopographic data using both terrestrial laser scanning (TLS) and microtopographic profile gauges. Additionally, standard dendrogeomorphic procedures, dependent on anatomical variations in root rings, are utilized to establish the timing of exposure. Both TLS and microtopographic profile gauges are used to obtain ground surface profiles, from which Ex is estimated after the threshold distance (TD) is determined, i.e., the distance between the root and the sediment knickpoint, which allows defining the lowering of the ground surface caused by sheet erosion. For each profile, we measured the height between the topside of the root and a virtual plane tangential to the ground surface. In this way, we intended to avoid small-scale impacts of soil deformation, which may be due to pressures exerted by the root system, or by the arrangement of exposed roots. This may provoke small amounts of soil sedimentation or erosion depending on how they physically affect the surface runoff. We demonstrate that an adequate microtopographic characterization of exposed roots and their associated ground surface is very valuable to obtain accurate erosion rates. This finding could be utilized to develop the best management practices designed to eventually halt or perhaps, at least, lessen soil erosion, so that more sustainable management policies can be put into practice.