Development of a soil moisture forecasting method for a landslide early warning system (LEWS): Pilot cases in coastal regions of Brazil

Página do item simplificado
dc.contributor.authorSousa, Isadora Araújo
dc.contributor.authorBortolozo, Cassiano Antonio
dc.contributor.authorMendes, Tatiana Sussel Gonçalves
dc.contributor.authorAndrade, Marcio Roberto Magalhães de
dc.contributor.authorDolif Neto, Giovanni
dc.contributor.authorMetodiev, Daniel
dc.contributor.authorPryer, Tristan
dc.contributor.authorHowley, Noel
dc.contributor.authorSimões, Silvio Jorge Coelho
dc.contributor.authorMendes, Rodolfo Moreda
dc.date.accessioned2025-03-06T18:07:04Z
dc.date.available2025-03-06T18:07:04Z
dc.date.issued22023
dc.description.abstractClimate 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.
dc.description.physical13 p.
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.uriCNPq ( 433481/2018-8)
dc.format.mimetypePDF
dc.identifier.affiliationUniversidade do Vale do Paraíba
dc.identifier.affiliationUniversidade do Estado de São Paulo
dc.identifier.affiliationCentro Nacional de Monitoramento e Alertas de Desastres Naturais
dc.identifier.affiliationUniversity of Bath
dc.identifier.bibliographicCitationSOUSA, Isadora Araújo et al. Development of a soil moisture forecasting method for a landslide early warning system (LEWS): Pilot cases in coastal regions of Brazil. Journal of South American Earth Sciences, v. 131, p. 1-13, 2023. Disponível em:
dc.identifier.doi10.1016/j.jsames.2023.104631
dc.identifier.urihttps://repositorio.univap.br/handle/123456789/618
dc.language.isoen_US
dc.publisherElsevier
dc.rights.holderElsevier
dc.subject.keywordLandslides
dc.subject.keywordSensor network
dc.subject.keywordSoil moisture modeling
dc.subject.keywordData inversion
dc.titleDevelopment of a soil moisture forecasting method for a landslide early warning system (LEWS): Pilot cases in coastal regions of Brazil
dc.typeArtigos de Periódicos

Arquivos

Pacote Original
Agora exibindo 1 - 2 de 2
Nenhuma Miniatura disponível
Nome:
Development of a soil moisture forecasting method for a landslide early warning system (LEWS)- Pilot cases in coastal regions of Brazil.pdf
Tamanho:
10.46 MB
Formato:
Adobe Portable Document Format
Descrição:
Acesso via Capes
Baixar
Imagem de Miniatura
Nome:
Development of a soil moisture forecasting method for a landslide early warning system (LEWS)- Pilot cases in coastal regions of Brazil.pdf
Tamanho:
280.99 KB
Formato:
Adobe Portable Document Format
Baixar
Licença do Pacote
Agora exibindo 1 - 1 de 1
Nenhuma Miniatura disponível
Nome:
license.txt
Tamanho:
1.71 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Baixar

Coleções

Produção acadêmica-PPGPLUR