Social vulnerability plays a vital role in understanding how various societal characteristics influence communities during extreme events. This study aimed to systematically identify key indicators and methodological approaches used in Social Vulnerability Index (SVI) research by utilizing the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The study specifically addresses gaps in indicator selection and emphasizes incorporating land-related and diverse variables for improved applications across various contexts. Social variables essential for SVI development were collected, and their applications across studies were analyzed. A total of 30,443 articles were identified from multiple databases, with 72 meeting the inclusion criteria after rigorous evaluation. Key aspects such as methodologies, weighting schemes, and primary variables used in SVI computation were outlined. Principal component analysis emerged as the most commonly employed method, though diverse approaches have gained traction in recent years. Significant variability was observed in the variables across studies, with demographic indicators being the most frequently utilized. The identified variables were categorized into 21 domains, comprising 61 indicators. While the findings of this study focus on improving the understanding of SVI development and its diverse applications, they also hold potential for informing sustainable land management and disaster resilience strategies, particularly in tailoring interventions to region-specific vulnerabilities.

Large flood events in recent years in the state of Wisconsin, USA raised a question of whether high precipitation events are on the rise. The objective of the research was to examine temporal and spatial patterns of extreme precipitation in Wisconsin during 1950–2006. The daily precipitation data used in the study were created by researchers at the University of Wisconsin-Madison using spatial interpolation of weather stations data across the state to a grid mesh with a spatial resolution of 8 km. For extreme precipitation indices, we calculated 99th, 95th, 90th, 85th, and 80th percentiles of daily total precipitation (>1 mm) in a year and the number of days per year with daily precipitation exceeding 10 mm, 20 mm, and 50 mm. We also conducted the Mann–Kendall test for trend, examined how geographical heterogeneity varied over time, and built quantile regression models for annual summer precipitation. Main findings include the following: the temporal trend of extreme precipitation varied widely across the state; the highest percentile index showed an increasing trend over the largest area, whereas indices of less extreme precipitation tended to generally decrease; extreme precipitation tended to show more dispersed and skewed spatial patterns than annual total precipitation. Overall, indices related to frequency showed more similar spatial and temporal trends to total precipitation than magnitude indices.

Choi, H.-J.; Cho, S.-J.; Hwang, T.; Nam, J., and Hwang C.S., 2021. Cumulative impact assessment for marine spatial planning: A case study of the Gyeonggi Bay in South Korea. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 360–364. Coconut Creek (Florida), ISSN 0749-0208. Cumulative impact assessment (CIA) techniques for marine spatial planning (MSP) exist in Europe and North America. Effective MSP requires a process for evaluating the effects of human activities on marine ecosystems, that is, a CIA. In Korea, MSP has progressively been developed for waters since the enactment of an MSP law (Act on Marine Spatial Planning and Management) in 2019. This study aims to perform the first CIA for Korea, evaluate its limitations, and assess alternatives for an operational MSP. This study involves an extensive review of the literature, followed by an assessment of the cumulative impact of human activities on the marine ecosystem in Gyeonggi Bay, Korea. Information on the marine ecosystems and influencing activities was collected, and the concept of the activity–pressure–ecosystem relationships adopted. The results reveal high cumulative impact scores along the coast, where human activities are concentrated, with fishing activities accounting for the highest proportion (i.e., 60.3% for gillnet, trap, and stow-net fishing) of the total cumulative impact among the marine activities. The cumulative impact is confirmed to vary by activity depending on whether the weight of the marine ecosystem is applied. This study provides an overview for quantifying the cumulative impacts of marine activities within a spatial context. It also highlights the importance of adequately considering the collection and processing of data before CIA. In addition, the activity–pressure–ecosystem linkage concept must consider the conditions of the study area to improve the accuracy and reliability of CIA. Further, the analysis and mapping techniques for CIA require improvement. This study can be used as a guideline for developing and utilizing the CIA tool in countries and regions planning to adopt MSP.