The identification and classification of flood-prone areas comprise a fundamental step in the Flood Risk Management approach, providing subsidies for land use planning, floodproofing policies, the design of mitigation measures and early warning systems. To address this issue, a frequently used preliminary tool is the flood susceptibility mapping of a region using a range of widely available data. Therefore, the present study introduces an index-based approach able to qualitatively assess flood-prone areas, named Physical Susceptibility to Floods Index (PhySFI), based on a multi-criteria decision-making method and developed in a GIS environment. The methodology presupposes a critical discussion of variables commonly used in other flood indexes, intending to simplify the proposed representation, and emphasizes the role of the user/modeler. PhySFI is composed of just four indicators, based on physical parameters of the assessed environment. This index was developed and first applied in the city of Rio de Janeiro, as part of the Rio de Janeiro Climate Change Adaptation Plan. The validation process was based on a comparative analysis with flood extent and height simulated by the hydrodynamic modeling of four watersheds within the study area, with different urbanization processes for each one. The results indicate that the index is a powerful preliminary tool to assess flood-prone areas in coastal cities.

In view of global climate change, studies on long-term changes in Near-Surface Air Temperature (NSAT) in the Brazil region are highly relevant. Climate warming requires the government to develop various adaptation strategies to these changes in order to maintain marine and terrestrial ecosystems in a stable state. Pearson correlation analysis, with significance assessment of the obtained results, was used to analyze NSAT data from 39 weather stations, along with the ERA5 reanalysis dataset and 33 CMIP6 models, for the different SSP scenarios of greenhouse gas emissions in the Brazil region (10° N–40° S; 75–25° W). The increase in NSAT of the Brazil region for 1964–2023 was 0.4 ± 0.2 °C based on meteorological stations and 0.3 ± 0.1 °C based on the ERA5 reanalysis. NSAT by ERA5 data changed little from 1940 to 1970, after which a relatively rapid increase began at a rate of +0.18 °C/10 years. The increase in NSAT for the period 1940–2023 was 0.66 ± 0.17 °C based on the CMIP6 model ensemble. The CMIP6 models show the increase in the average NSAT across the region of 0.75–1.08 °C from 1994–2023 to 2024–2053. The average NSAT in the region under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios shows an increase of 1.05, 1.89, 2.75, and 3.53 °C by the end of the 21st century, respectively. Moreover, NSAT over land in the study region is increasing faster than over the ocean. According to the CMIP6 ensemble, NSAT over land in the Brazil region increased by an average of 0.6–1.0 °C from 1940–1969 to 1994–2023, while over the ocean near the Brazilian coastline it increased by approximately 0.5 °C. From 1994–2023 to 2070–2099, the projected warming over land is expected to be 1.0–1.4, 1.6–2.6, 2.4–3.8, and 3.2–5.0 °C for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Over the ocean, however, the estimated warming is substantially smaller—from 0.8 to 2.8 °C, depending on the SSP scenario, which may be explained by the stabilizing role of the ocean.