Produção acadêmica-PPGPLUR

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Alert scenarios for the Metropolitan Region of Recife-PE based on monitoring of rainfall and soil humidity – a case study
(Brazilian Association for Soil Mechanics and Geotechnical Engineering) Coutinho, Roberto Quental; Morais, Bruno Diego de; Mendes, Rodolfo Moreda; Andrade, Marcio Roberto Magalhães de
In Brazil, landslides are frequent, causing deaths and property damage, and occur under the influence of natural and/or anthropic conditions. Rain acts as the main non-anthropic agent in triggering this phenomenon. Because of this, the prediction of landslides becomes an essential tool for managing high-risk areas. The Metropolitan Region of Recife (MRR) has a large history with numerous cases of mass movements over the years. Currently, research points out improvements in the quality of forecasts by including hydrological information, such as soil moisture, in warning systems. Given the importance of measuring soil moisture in situ, a network of equipment consisting of rain gauges and capacitive moisture sensors was installed in the MRR, to monitor rainfall and soil moisture in an integrated manner. The objective of this article is to understand the hydrological conditions of the soil in two high-risk areas of the MRR, built over the Barreiras Formation to set the foundations for the development of a Landslide Early Warning System (LEWS) that integrates rain and humidity. The data showed that the variation in soil moisture is very dependent on rainfall and presents sudden variations in moisture with increasing hourly rainfall. The data also revealed that the monitored soils remained wet for approximately six months in the year 2022, highlighting the potential for moderate rainfall during this period to trigger landslides.
Antecedent precipitation index to estimate soil moisture and correlate as a triggering process in the occurrence of landslides
(Scientific Research Publishing) Moraes, Marcio Augusto Ernesto de; Mendes Filho, Walter Manoel; Mendes, Rodolfo Moreda; Bortolozo, Cassiano Antonio; Metodiev, Daniel; Andrade, Marcio Roberto Magalhães de; Egas, Harideva Marturano; Mendes, Tatiana Sussel Gonçalves; Pampuch, Luana Albertani
Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process; thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems; hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.
ARHCS (Automatic Rainfall Half-Life Cluster System): A Landslides Early Warning System (LEWS) Using Cluster Analysis and Automatic Threshold Definition
(Scientific Research Publishing) Bortolozo, Cassiano Antonio; Pampuch, Luana Albertani; Andrade, Marcio Roberto Magalhães de; Metodiev, Daniel; Carvalho, Adenilson Roberto; Mendes, Tatiana Sussel Gonçalves; Pryer, Tristan; Egas, Harideva Marturano; Mendes, Rodolfo Moreda; Sousa, Isadora Araújo; Power, Jenny
A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.
Curupira V1.0: Joint Inversion of VES and TEM for Environmental and Mass Movements Studies
(Scientific Research an Academic Publisher) Bortolozo, Cassiano Antonio; Porsani, Jorge Luís; Pryer, Tristan; Benjumea, Jorge Luis Abril; Santos, Fernando Acácio Monteiro dos; Couto, Marco Antonio; Pampuch, Luana Albertani; Mendes, Tatiana Sussel Gonçalves; Metodiev, Daniel; Moraes, Marcio Augusto Ernesto de; Mendes, Rodolfo Moreda; Andrade, Marcio Roberto Magalhães de
An innovative inversion code, named “Curupira v1.0”, has been developed using Matlab to determine the vertical distribution of resistivity beneath the subsoil. The program integrates Vertical Electrical Sounding (VES), successful in shallow subsurface exploration and Time Domain Electromagnetic (TEM) techniques, better suited for deeper exploration, both of which are widely employed in geophysical exploration. These methodologies involve calculating subsurface resistivity through appropriate inversion processes. To address the ill-posed nature of inverse problems in geophysics, a joint inversion scheme combining VES and TEM data has been incorporated into Curupira v1.0. The software has been tested on both synthetic and real-world data, the latter of which was acquired from the Parana sedimentary basin which we summarise here. The results indicate that the joint inversion of VES and TEM techniques offers improved recovery of simulated models and demonstrates significant potential for hydrogeological studies.
Development of a soil moisture forecasting method for a landslide early warning system (LEWS): Pilot cases in coastal regions of Brazil
(Elsevier) Sousa, Isadora Araújo; Bortolozo, Cassiano Antonio; Mendes, Tatiana Sussel Gonçalves; Andrade, Marcio Roberto Magalhães de; Dolif Neto, Giovanni; Metodiev, Daniel; Pryer, Tristan; Howley, Noel; Simões, Silvio Jorge Coelho; Mendes, Rodolfo Moreda
Climate change has increased the frequency of extreme weather events and, consequently, the number of occurrences of natural disasters. In Brazil, among these disasters, floods, flash floods, and landslides account for the highest number of deaths, the latter being the most lethal. Bearing in mind the importance of monitoring areas susceptible to disasters, the REMADEN/REDEGEO project of the National Center for Monitoring and Natural Disaster Alerts (Cemaden) has promoted the installation of a network of soil moisture sensors in regions with a long history of landslides. This network was used in the present paper as a base to develop a system for moisture forecasting in those critical zones. The time series of rainfall and moisture were used in an inversion algorithm to obtain the geotechnical parameters of the soil. Then the geotechnical model was used in a forward calculation with the rainfall prediction to obtain the soil moisture forecast. The landslide events of March 2020 and May 2022 in Guarujá and Recife, respectively, were used as study cases for the developed system. The obtained results indicate that the proposed methodology has the potential to be used as an important tool in the decision-making process for issuing landslide alerts.
Enhancing landslide predictability: Validating geophysical surveys for soil moisture detection in 2D and 3D scenarios
(Elsevier) Bortolozo, Cassiano Antonio; Mendes, Tatiana Sussel Gonçalves; Egas, Harideva Marturano; Metodiev, Daniel; Moraes, Maiconn Vinicius de; Andrade, Marcio Roberto Magalhães de; Pryer, Tristan; Ashby, Ben; Motta, Mariana Ferreira Benessiuti; Simões, Silvio Jorge Coelho; Pampuch, Luana Albertani; Mendes, Rodolfo Moreda; Moraes, Marcio Augusto Ernesto de
Every year, Brazil grapples with the destructive impact of landslides, typically during the summer season. The National Centre for Monitoring and Alerts of Natural Disasters (Cemaden) places significant emphasis on studying these phenomena to understand their processes and causes more deeply. One key challenge faced in this endeavour is the procurement of geotechnical properties of the soil in high-risk areas, with soil moisture being a crucial factor. Collecting point samples for acquiring these geotechnical parameters is not only costly but also limited in providing a comprehensive two-dimensional or three-dimensional coverage. Therefore, the primary aim of the proposed project is to validate the method of acquiring soil moisture data through geophysical surveys in both 2D and 3D scenarios. Data was gathered from soil moisture stations within Cemaden's network and various collected samples to confirm the results. To generate more controlled yet realistic conditions, a sequence of field infiltration experiments was conducted. The findings, related to the ability of the geoelectric method to define soil moisture, derived from this project form an invaluable foundation for future investigations spearheaded by the Geodynamics Group and its collaborating institutions.
Evaluation of an unmanned aerial vehicle (UAV) for measuring and monitoring natural disaster risk areas
Reiss, Mário Luiz Lopes; Mendes, Tatiana Sussel Gonçalves; Pereira, Felicia França; Andrade, Marcio Roberto Magalhães de; Mendes, Rodolfo Moreda; Simões, Silvio Jorge Coelho; Santos Junior, Roosevelt de Lara; Souza, Sergio Florencio de; Nice
This work presents an evaluation of a small UAV-RPAS-PPK to be used in the generation of digital surface models (DSM), without the need for control points, having as main application the monitoring of disaster risk areas (landslide and flooding). The areas to be measured are difficult to access, which prevents or makes access to the land difficult. In this evaluation, a study area of approximately 13 km² was flown over, an average pixel of 11.6 cm and a total of 417 photos. The equipment used to acquire the images was a SenseFly eBee X, equipped with GNSS PPK for Direct Georeferencing (DG) and a camera model S.O.D.A. In all, 42 ground checkpoints were measured using a dual-frequency GNSS receiver. For both the measurement of the checkpoints and for the Direct Georeferencing (DG) base of the Unmanned Aerial Vehicles (UAV), a relative processing was performed, using the Brazilian Network for Continuous Monitoring (RBMC) as a reference. With this evaluation, it was possible to achieve a result (RMSE) for phototriangulation better than 1.2 pixels for horizontal and 1.5 pixels for vertical, without the need to measure any control points on the ground.
Obtaining 2D soil resistance profiles from the integration of electrical resistivity data and Standard Penetration Test (SPT) and Light Dynamic Penetrometer (DPL) resistance tests - applications in mass movements studies
(Scientific Research Publishing) Bortolozo, Cassiano Antonio; Mendes, Tatiana Sussel Gonçalves; Motta, Mariana Ferreira Benessiuti; Simões, Silvio Jorge Coelho; Pryer, Tristan; Metodiev, Daniel; Andrade, Marcio Roberto Magalhães de; Moraes, Maiconn Vinicius de; Paula, Danielle Silva de; Bastos, Nélio José; Pampuch, Luana Albertani; Mendes, Rodolfo Moreda; Moraes, Marcio Augusto Ernesto de
In Brazil and various regions globally, the initiation of landslides is frequently associated with rainfall; yet the spatial arrangement of geological structures and stratification considerably influences landslide occurrences. The multifaceted nature of these influences makes the surveillance of mass movements a highly intricate task, requiring an understanding of numerous interdependent variables. Recent years have seen an emergence in scholarly research aimed at integrating geophysical and geotechnical methodologies. The conjoint examination of geophysical and geotechnical data offers an enhanced perspective into subsurface structures. Within this work, a methodology is proposed for the synchronous analysis of electrical resistivity geophysical data and geotechnical data, specifically those extracted from the Light Dynamic Penetrometer (DPL) and Standard Penetration Test (SPT). This study involved a linear fitting process to correlate resistivity with N10/SPT N-values from DPL/SPT soundings, culminating in a 2D profile of N10/SPT N-values predicated on electrical profiles. The findings of this research furnish invaluable insights into slope stability by allowing for a two-dimensional representation of penetration resistance properties. Through the synthesis of geophysical and geotechnical data, this project aims to augment the comprehension of subsurface conditions, with potential implications for refining landslide risk evaluations. This endeavor offers insight into the formulation of more effective and precise slope management protocols and disaster prevention strategies.

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