Navegando por Autor "Pryer, Tristan"

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    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.
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    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.
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    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.
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    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.