Cassiano Antonio Bortolozo

Landslides induced by subsurface water infiltration represent a growing hazard in rapidly urbanizing regions, particularly where infrastructure is deficient. Leakage from potable water distribution systems can trigger slope instabilities that often remain undetected by conventional rainfall-based early warning systems. This study employs electrical resistivity tomography and three-dimensional resistivity imaging to identify leakage pathways and assess subsurface moisture conditions in a high-risk sector of Recife municipality, Northeastern Brazil. High-resolution 2D and 3D multigrad array surveys were conducted and converted into volumetric soil moisture estimates using empirical relationships. The results reveal a major infiltration zone and several shallow, spatially distributed leaks, with saturation levels frequently exceeding 30–40%, particularly in low-resistance soil layers as corroborated by standard penetration test data. Three-dimensional isosurface visualizations of moisture distribution further delineate critical saturation volumes. These findings highlight the utility of resistivity-based geophysical methods for detecting non-meteorological landslide triggers and support their integration into proactive risk monitoring strategies in vulnerable urban environments.

Campos do Jordão, a city situated in the Mantiqueira Mountains of São Paulo, Brazil, is highly susceptible to mass movements due to its steep topography and high annual precipitation. These hazards have been exacerbated by rapid urban expansion since the 1970s. This study investigates a critical slope sector in the Vila Abernéssia neighborhood, where a historical monastery constructed in the 1940s coexists with more recent infrastructure, including a school built at a lower elevation. In 2002, foundation works for the school triggered a landslide that severely affected both the construction site and the monastery's parking area. Despite subsequent stabilization efforts, signs of ground deformation, such as wall cracking and floor heaving, have persisted. To reconstruct the geomorphological evolution and subsurface conditions of the area, we integrated Electrical Resistivity Tomography (ERT), Frequency-Domain Electromagnetic (FDEM) surveys, geotechnical testing, historical and contemporary photographic records, and qualitative data obtained from local residents. The results reveal that slope instability has been driven by a combination of natural and anthropogenic factors, including heterogeneous landfill deposition, unregulated excavation, and hydrological influences. Two principal types of mass movement were identified: a shallow landslide and long-term soil creep, the latter likely sustained by ongoing loading and infiltration. The main novelty of this study lies in the reconstruction of nearly 90 years of slope evolution in a tropical urban environment through the integrated analysis of geophysical, geotechnical, historical, and community-based data. Rather than focusing on a single triggering event, the study demonstrates how successive anthropogenic interventions progressively modified subsurface conditions, ultimately leading to both rapid failure and long-term creep processes. This multidisciplinary approach enabled a detailed delineation of sliding surface geometries and highlighted how unplanned urbanization on geotechnically fragile terrain contributes to slope failure. The results provide a rare long-term perspective on the cumulative effects of urban occupation on slope stability in tropical environments, offering insights applicable to similar settings across the Global South. The site exemplifies broader patterns of development in Brazilian urban centers and similar contexts across the Global South, where inadequate land-use planning amplifies the risks posed by natural hazards.

Introduction. Landslides occur when slope stability is compromised by natural factors, such as intense rainfall, and human factors, such as irregular occupation. Climate variations have made extreme precipitation events more frequent and severe, increasing the social, economic, and environmental impacts of disasters. Objective. This study evaluates the effectiveness of the Automatic Rainfall Half-Life Cluster System (ARHCS) for monitoring landslides in Jaboatão dos Guararapes comparing its alerts to those issued by National Center for Monitoring and Early Warning of Natural Disasters (Centro Nacional de Monitoramento e Alertas de Desastres Naturais, Cemaden). Methodology. ARHCS uses the concept of rainfall half-life to estimate soil saturation potential and incorporates cluster analysis and data inversion to define alert thresholds. The comparison with Cemaden’s alerts was conducted for the year 2021. Results. The results indicated high compatibility between the systems, with ARHCS demonstrating greater accuracy in issuing alerts for “high” and “very high” risk levels, in addition to a low incidence of alerts without occurrences. Conclusion. These findings suggest that ARHCS can complement the existing alert system, especially in municipalities with limited monitoring infrastructure.

In this study, we present a new methodology for 2D joint inversion, or data fusion, of DC electro-resistivity and Transient Electromagnetic methods. These geophysical techniques have traditionally been used separately, but by combining them, we aim to decrease ambiguities and increase the robustness of the resulting subsurface model. The inversion process was conducted using the classical Occam method with smooth models and synthetic studies were also conducted to understand the limitations and advantages of the method. We also applied the algorithm to data obtained in groundwater exploration in Brazil, and the results showed that the 2D joint inversion is promising in increasing accuracy and reducing ambiguity in subsurface imaging.

In March 2020, an extreme rainfall in Baixada Santista, Brazil, led to a series of landslides affecting more than 2800 people and resulting losses exceeding USD 43 million. This attribution study compared extreme rainfall in two large ensembles of the UK Met Office Hadley Centre HadGEM3-GA6 model that represented the event with and without the effects of anthropogenic climate change. Antecedent rainfall conditions on two different timescales are considered, namely extreme 60-day rainfall (Rx60day) which relates to the soil moisture conditions and extreme 3-day rainfall (Rx3day) which represents landslide triggering heavy rainfall. In the scenario including both natural and human-induced factors the antecedent 60 day rainfall became 74% more likely, while the short-term trigger was 46% more likely. The anthropogenic contribution to changes in rainfall accounted for 20–42% of the total losses and damages. The greatest economic losses occurred in Guarujá (42%), followed by São Vicente (30%) and Santos (28%). Landslides were responsible for 47% of the homes damaged, 85% of the homes destroyed, all reported injuries, and 51% of the deaths associated with heavy rainfall. Changes in land cover and urbanization showed a pronounced increase in urbanized area in Guarujá (107%), São Vicente (61.7%) and Santos (36.9%) and a reduction in farming area. In recent years, the region has experienced an increase in population growth and a rise in the proportion of irregular and/or precarious housing in high-risk areas. Guarujá has the highest number of such dwellings, accounting for 34.8%. Our estimates suggest that extreme precipitation events are having shorter return periods due to climate change and increased urbanization and population growth is exposing more people to these events. These findings are especially important for decision-makers in the context of disaster risk reduction and mitigation and adaptation to climate change.

El aumento de la frecuencia, la intensidad y la duración de los fenómenos extremos es una preocupación mundial y el centro de atención de varios estudios debido a los posibles impactos en la sociedad. A escala regional, estos cambios pueden estar modulados por aspectos regionales como el uso y la cobertura del suelo, la humedad, la concentración de aerosoles y la urbanización, por lo que los análisis regionales son esenciales para comprender los cambios en diferentes climas y condiciones. Así, el presente estudio tuvo como objetivo investigar el comportamiento espacial y las tendencias de los eventos extremos de precipitación y temperatura en la Región Metropolitana del Valle de Paraíba y Litoral Norte. Se analizaron 16 índices de extremos, 6 de precipitación y 10 de temperatura del Expert Team on Climate Change Detection and Indices (ETCCDI). Los resultados mostraron un aumento significativo de los extremos cálidos y una disminución de los extremos fríos, lo que indica un calentamiento en toda la región. Los extremos de precipitación no mostraron tendencias estadísticamente significativas y el promedio de los índices destacó la región central del área de estudio con mayor intensidad de extremos cálidos y secos. O aumento da frequência, intensidade e duração de eventos extremos é uma preocupação global e pauta de diversos estudos devido aos possíveis impactos à sociedade. Em escala regional essas mudanças podem ser moduladas por aspectos regionais como uso e cobertura do solo, umidade, concentração de aerossóis e urbanização, assim, análises regionais são essenciais para entender as mudanças em diferentes climas e condições. Desse modo, o presente estudo buscou investigar o comportamento espacial e tendências dos eventos extremos de precipitação e temperatura na Região Metropolitana do Vale do Paraíba e Litoral Norte (SP). Foram analisados 16 índices para extremos (6 de precipitação e 10 de temperatura) dos índices climáticos definidos por Expert Team on Climate Change Detection and Indices (ETCCDI). Os resultados mostraram aumento significativo nos extremos quentes e diminuição nos extremos frios, indicando um aquecimento em toda região. Os extremos de precipitação não obtiveram tendências estatisticamente significativas e a média dos índices destacaram a região central da área de estudo com maior intensidade de extremos quentes e secos. The increase in frequency, intensity, and duration of extreme events is a global concern and the focus of several studies due to the possible impacts on society. At the regional scale, these changes can be modulated by regional aspects such as land use and land cover, humidity, aerosol concentration, and urbanization, thus regional analyses are essential to understand changes in different climates and conditions. Thus, the present study sought to investigate the spatial behavior and trends of extreme events of precipitation and temperature in the Metropolitan Region of the Paraíba Valley and North Coast. We analyzed 16 indices for extremes, 6 for precipitation and 10 for temperature from the Expert Team on Climate Change Detection and Indices (ETCCDI).. The results showed a significant increase in the warm extremes and decrease in the cold extremes, indicating a warming throughout the region. The precipitation extremes did not show statistically significant trends and the average of the indices highlighted the central region of the study area with higher intensity of hot and dry extremes.

An innovative comparative study among three different global optimization methods (GOMs) to invert time domain electromagnetic data (TDEM), was applied in the 1.5D subsurface resistivity imaging. These stochastic methods allow the incorporation of different kinds of constraints in the objective function, due to the easiness of implementation in their algorithms and their computational efficiency. Nevertheless, global optimization methods, like any other based on swarm intelligence cost much computational time, including problems with a high number of unknown parameters and when the forward modeling involves time-consuming calculations such as Gaver-Stehfest inverse transforms, Hankel transforms, and others. To overcome this difficulty, we developed a parallel pure MPI version of each GOM, allowing the distribution of the computation among several cores of a cluster. The performances of the classic version of particle swarm optimization (PSO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA) using MPI parallelism for solving 1.5D TDEM inverse problems are compared here in a set of synthetic and real data. The principal outcomes show: (1) These GOMs reproduce quite well the distribution of subsurface resistivity either synthetic models or real data, (2) WOA and PSO exhibit better computational performances, converging first than GWO, (3) WOA provided better performance in the final value achieved of the cost function than PSO and GWO, and (4) pure MPI parallelism provided a 17x and 50x speedup in the computation time for both synthetic and real data, respectively. In a better way to classify this comparison, we analyzed the solutions using total variation (TV) and Global smoothness (GS) constraints, to identify smooth and sharp structures. Additionally, we have diminished the computational time execution with the parallel solution (MPI version of each stochastic traditional method) against the sequential processing.

Landslides have a high degree of uncertainty requiring new methods for their analysis, monitoring and forecasting. In Brazil, Cemaden is responsible for actions related to the natural disasters and, recently, has started with partner institutions, a project sponsored by FINEP in order to monitor ten prone-landslides areas situated in different regions of the country. This paper presents the proposal of REDEGEO to implant a laboratory of modeling and geovisualization to study landslide processes in urbanized areas. The laboratory consists of three parts: A) Field surveys to obtain high resolution images from unmanned aerial vehicles and to obtain the internal geometry of outcrops from geophysics methods (Resistivity and Radar Soil Penetration - GPR); B) 3D modeling using the software Geovisionary® which allows the analysis of image and geophysical dataset from different formats considering their volumetric properties; C) Geovisualization and Virtual Reality (VR) where the images obtained in the fieldwork can be observed from a human-machine interface which allows that the researchers have a full immersion in the selected areas. The creation of a laboratory related to the natural disasters, which include geovisualization and VR, stimulates the active participation of the researcher team and creates mechanisms for the participation of technologies developers, managers, civil defense agents and even the population that lives in the risk prone-areas.