Dynamics of Mass Movements in an Urban Basin: A Case Study in the Fradinhos Drainage Basin, Vitória, Espírito Santo, Brazil

Dynamics of Mass Movements in an Urban Basin: A Case Study in the Fradinhos Drainage Basin, Vitória, Espírito Santo, Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dynamics of Mass Movements in an Urban Basin: A Case Study in the Fradinhos Drainage Basin, Vitória, Espírito Santo, Brazil Jeniffer Oliveira Nepomuceno do Couto, Julia Effgen, Bianca Vieira, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3925852/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2024 Read the published version in Natural Hazards → Version 1 posted 5 You are reading this latest preprint version Abstract Landslides are a widespread problem in Brazil due to the heavy rainfall typical of tropical environments. In urban areas, landslides can be catastrophic and can lead to significant economic and social losses. To prevent such catastrophes, it is crucial to comprehend the spatial distribution of mass movements in local dynamics. The aim of this study was to evaluate the spatial distribution of areas susceptible to shallow translational slides in the Fradinhos Drainage Basin (FDB), situated in Vitória, state of Espírito Santo (ES). To achieve this, we used the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability ( TRIGRS ) model, along with geotechnical and hydrological data from five sampling points. An extreme rainfall event that lasted 24 days, with an accumulated rainfall of 744 mm was considered. The study revealed that 31% of the basin is unstable, with no significant increase in these areas during the rainfall period. Additionally, 86% of this area is in an Environmental Protection Zone. The results indicate that the FDB has a low susceptibility to shallow landslides, due to the existence of the Environmental Protection Zone, as this zone forms a protective belt at higher slopes. TRIGRS effectively identifies unstable zones and is an useful tool for identifying susceptibility, contributing to local management. Susceptibility shallow slides geomorphology TRIGRS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1 Introduction Urban agglomerations have been expanding in different parts of the world, causing problems associated with landslides, especially those in cities in hot and humid tropical environments (Smyth and Royle 2000 ). A significant issue in urban areas is the improper occupancy and cutting of slopes. This includes occupancy of slopes and construction on concave parts of slopes in an improper manner, which has been increasing with the acceleration of the urbanization process in recent decades, confirming the potentiation of this hydrogeomorphologic process. The report 'World Urbanization Prospects: The 2018 Revision' by the Population Division of the United Nations ( 2019 ) estimates that the world's urban population will reach 6.7 billion by 2050. According to the projections in the United Nations Human Settlements Program's 'World Cities Report' (Khor et al. 2022 ), the urban population is expected to increase by 2.2 billion by 2050. This growth highlights the need for infrastructure planning to meet the demands of the growing population. Based on the 2010 Demographic Census conducted by the Brazilian Institute of Geography and Statistics, the municipality of Vitória had over 87,000 people at risk (IBGE 2010 ). Recent data from the same source indicates population growth and increased demographic density, highlighting the importance of implementing mitigating measures (IBGE 2022 ). Examples of landslides in urban areas can be found in various regions of the world, including Algeria (Bourenane et al. 2022 ), the United States (Fiolleau et al. 2023 ), Romania (Mihai et al. 2014 ), Chile (Lara et al. 2018 ), and Ecuador (Puente-Sotomayor et al. 2021 ), among others. In Brazil, due to the geo-environmental conditions, several studies have been carried out in urban areas with a focus on landslide inventory, monitoring, and modeling in São Paulo (Cerri et al. 2007 ), Rio de Janeiro (Jones 1973 ), Minas Gerais (Nola and Zuquette 2021), Pernambuco (Marengo et al. 2023 ). Work in the neighboring cities of Vila Velha (Effgen and Marchioro 2017 ) and Vitória (Effgen et al. 2018a ) analyzed areas susceptible to mass movements, showing how the disorderly appropriation of geographical space by human activity in urban agglomerations supports the occurrence of landslides. Therefore, the occurrence of landslides in urban areas is a challenge for sustainable and equitable development, between the need for occupation and the carrying capacity of slopes for occupancy, a fact that leads to the need for modeling to verify susceptibility to minimize socioeconomic and environmental impacts. Hence, this study intended to identify the susceptibility to shallow landslides in an urban area in southeastern Brazil as a subsidy for risk mitigation. 2 Study area Vitória, the capital of the state of Espírito Santo, is divided in two parts: a continental part to the north and an archipelago to the south. The largest island, called Vitória Island, is bounded by the Atlantic Ocean to the east and the estuary of the Santa Maria River to the west. During the city's construction, Vitória Island underwent several embankment processes, expanding its boundaries and connecting smaller islands in its vicinity. The Fradinhos Drainage Basin (FDB) covers an area of 2.7km² and is located on Vitória Island, along the eastern portion of the Central Massif of Vitória (Fig. 1 ). Between 1940 and 1950, only the southern portion of Vitória Island was inhabited. However, with the accelerated development process that took place in the state, the population of Vitória increased from approximately 51,000 people to over 200,000 in just 30 years. As a result of limited space, hillsides began to be occupied, leading to numerous mass movements and associated disasters. Most of the events occurred on the upper part of the hillside, but they had a direct impact on the population living in the lower and medium segments of the hillside. The Fradinhos neighborhood, located in the center of the basin, consists of well-established public streets and high-quality residential buildings (Fig. 2 a). At the outlet of the basin, next to Fradinhos, the neighborhood of Cruzamento has a population with low purchasing power, due to complex occupations associated with population growth (Fig. 2 b). The easternmost section makes up the Fonte Grande Park, which was established in 1986, the year following the Morro do Macaco disaster of 1985 (Fig. 3 ). The park’s main objective is to protect and stabilize the slopes in order to safeguard the natural attributes. This is mainly achieved by preventing occupation and protecting against the changes that could occur with slope occupation and associated disasters. The park currently has one of the largest remnants of Atlantic Forest protected by law in an urban area in the country (Espírito Santo 1986; PMV 2022). An inventory of mass movements, based on Civil Defense reports, showed that 84% were shallow landslides, some of which were associated with falling blocks. The rock structure is fractured on the high slopes and near the hilltopswith a gradient of more than 35%. There are some residual soil patches, talus deposits, and semi-buried boulders that can be found in areas with thin soils. The FDB's largest type of geotechnical cover is tallus deposits, which has many associated mass movement records from 1999 to March 2018 (Fig. 4 e 5) (Oliveira et al. 2021 ). For rainfall, based on the Climatological Normal (1961–2021) with records from the automatic station in Vitória (INMET 2022), located approximately four kilometers from the FDB, Vitória has an average monthly rainfall of 109.4 mm. The highest monthly accumulations on record were 746.6 mm (December 2013), 662.8 mm (November 2008), and 406.4 mm (October 2009) (Fig. 6 ). In December 2013, a polar air mass combined with humidity from the Amazon rainforest resulted in the formation of the South Atlantic Convergence Zone (SACZ). The SACZ stayed over Espírito Santo, providing constant rainfall until December 26 (Fig. 7 ). Newspapers and government agencies in the state reported about 23 deaths and widespread damages, including floodings, destruction of bridges and homes, and landslides (Marchioro and Coutinho 2020 ). Marchioro, Silva, Correa ( 2016 ) note that the variability of rainfall in Vitória is mainly influenced by South Atlantic Convergence Zones (SACZ) and polar air masses. 3 Methods 3.1 Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) TRIGRS is a deterministic physic-mathematical model developed by Baum, Savage, and Godt ( 2002 ) in Fortran language. The model combines a hydrological model in transient conditions with a stability model based on the infinite slope equation, following a proposal by Iverson ( 2000 ). This analysis is calculated by the ratio between the forces acting to stabilize and destabilize, called the Factor of Safety (FS), described by the authors for the depth Z, where Φ is the angle of internal friction in degrees, θ the slope angle in degrees, c' the effective soil cohesion in KPa, Ψ the pressure head, Z the soil depth in meters, t the time, ρ w the specific weight of the water and ρ s specific weight of the soil (Eq. 1). $$FS= \frac{tan {\upvarphi }}{tan \theta }+\frac{{c}^{{\prime }}-{\Psi }\left(Z,t\right){{\rho }}_{w} tan {\upvarphi }}{{{\rho }}_{s} Zsen\theta cos\theta }$$ (1) Worldwide, the model has been applied to hillsides in the northwest of the USA to identify the behavior of the pressure head during a rainfall episode, taking into account the influence of the tree canopy (Keim and Skaugset 2003 ); while in Italy Crosta and Frattini ( 2003 ) obtained better results than the other two models used; Frattini et al. ( 2004 ) obtained better results than the scar map for pyroclastic soils in Italy. Chien-Yuan et al. ( 2005 ), analyzed precipitation-induced landslides and debris flows in Taiwan. They observed cracks in the soil and a rupture surface that coincided with the unstable areas on the model-generated map. Aristizábal et al. (2022) highlight in a recent study in Colombia that the increase in rainfall intensity due to global climate change increases the occurrence of shallow slides for soils with high permeability. Still in Colombia country, Marin, Velásquez e Sánchez (2021) added spatially varying rainfall data to the simulation, which is not commonly used. In Brazil, Vieira et al. ( 2018 ) compared the SHALSTAB and TRIGRS models in Serra do Mar, São Paulo. Five scenarios were simulated in the southern region of the country, in Ibirama, Santa Catarina, varying rainfall and water table depth. The results highlighted the model's high sensitivity to these two parameters, suggesting that simulations with this data should be distributed over the basin (Schwarz and Michael 2017 ). Three simulations were conducted in the basin of the Quitite and Papagaio rivers, located west of the Tijuca Massif in Rio de Janeiro, using the model for three different depths. The results indicated that the model is highly sensitive to the initial height of the water table, with instability being overestimated for higher initial heights (two meters) (Guimarães et al. 2019 ). 3.2 Input Model Data The mapping data, along with their respective sources and scales or spatial resolutions, are presented in Table 1 . The digital elevation model (DEM) was generated using contour lines, elevation points, and drainage data, with a spatial resolution of three meters, as proposed by Nage ( 2010 ). Table 1 Cartographic data used, source, and spatial resolution Source Description Scale or Spatial Resolution OLIVEIRA, EFFGEN, MARCHIORO (2021) Inventory of Landslides in Vitória 1999–2018 - IEMA (2012) Contour 5m Elevation Points - Stream 1:25.000 INMET (2022) Vitória Rain Gauge Station (December 2013) Code A612 - Three soil sample collections were executed by Effgen, Oliveira e Marchioro (2018b), and we collected two new soil samples (Fig. 8 ). The last two were defined to spatially represent the basin for possible differences arising from the location of the materials and to integrate all the units of geocoverage (Vitória 2014 ). The modeling was done using the average of the sampled values, as shown in Table 2 . Table 2 Input data Geotechnical and Hydrological Properties Parameters (unit) Technical standard Soil cohesion ( \(\mathcal{c}\) ) 18,32 KPa D3080:2012 (ASTM 2012) Specific weight of the soil ( \({\varvec{\rho }}_{\varvec{s}}\) ) 20 Kg/m³ Angle of internal friction \(\left(\varvec{\varphi }\right)\) 25° Maximum thickness of the soil ( \({\varvec{Z}}_{\varvec{m}\varvec{a}\varvec{x}})\) 1m Ruiz ( 2005 ) Almeida et al ( 2012 ) Embrapa (Silva et al. 2017 ) Specific weight of groudwater ( \({\varvec{\rho }}_{\varvec{s}}\) ) 0,99823 KN/m³ D3080:2012 (ASTM 2012) Initial height of the water table (d) 1m NBR14545 (ABNT 2000) Vertical saturated hydraulic conductivity (Ksat) 1,2x10 − 6 m/s Rate of initial infiltration (I z ) 1.0x10 − 9 m/s Default Hydraulic diffusivity (D 0 ) 5.0x10 − 4 m²/s The December 2013 rainfall episode had the highest monthly accumulation in the 60-year historical series (1961–2021), totaling 744mm. The event began on December 6, 2013, and the highest daily accumulation of 127mm occurred on December 19. The last day of rain was December 26, 2013. For the modeling, this period was divided into four rainy periods (T1, T2, T3 and T4), and the intensity was calculated based on these four episodes (Table 3 ). Table 3 Pluviometric parameters to TRIGRS Date Duration (days) Accumulated Precipitation (mm) Average Rainfall Intensity for Each Event I nZ (m/s) T1 December 5th to 10th 51840s (6 days) 31 5,97x10 − 07 T2 December 11th to 16th 103680s (12 days) 178 3,43x10 − 06 T3 December 17th to 22th 155520s (18 days) 353 6,80x10 − 06 T4 December 23th to 28th 207360s (24 days) 182 3,51x10 − 06 National Meteorological Institute's Vitória Rain Station (INMET, 2022) 3.3 Validation (Inventory) The inventory contains a single point associated with each slip location (scars) or affected residence, according to the reports from the Civil Defense of Vitória, for the period from 1999 to March 2018. The inventory includes 28 landslides, 13 of which were not influenced by occupancy conditions and were therefore used to validate susceptibility maps (Fig. 9 ). Landslides are concentrated in urban areas mainly because it was reported based on calls received by the Civil Defense, where mass movements or even imminent events are reported around occupations. In the FDB, 62% of the scars vary in depth from 30cm to 1m, indicating the most likely rupture zone in the basin. 4 Results 4.1 Susceptibility Maps During the simulation of susceptibility scenarios, only T4 showed differences between unstable and stable areas for the four analyzed rainfall periods. Two polygons increased instability, but did not changed class, resulting in no visual changes (Fig. 10 ). The unstable areas have totaled 31% of the FDB. It was expected that the unstable areas (FS < 1) increase over the course of the rainfall episode, since there would be an increase in humidity in the surface geocovers. However, the same FS values were found for the first three rainfall episodes (T1, T2, and T3). A few increases were found in T4, associated with the higher slopes, but were not considered because it was a rock formation with no geocover development for possible landslides. This is the FDB's response to the previous rainfall conditions: the water infiltrates, the areas with higher instability are those of the upper and middle slope and doesn't change much during the periods evaluated. Despite the decrease in rainfall at T4, the areas identified as unstable remained classified as such. Hermawan et al. ( 2023 ) simulated a constant rainfall event in a volcanic area with steep slopes in a province of Indonesia. They considered the effect of 12 hours of preceding rainfall and identified an increase in unstable areas as time increased. This highlights the importance of preceding rainfall in altering pore pressure and reducing slope stability in steeper portions. Konig, Kux e Corsi (2022) simulated a precipitation episode in an urban watershed in the state of São Paulo, divided into three days. At the start of the simulation, only a few areas were identified where FS < 1, which corresponded to areas where the slope was above 30º. Over time, the FS values decreased on the steeper slopes, and after 72 hours, almost the entire high-slope area was unstable. The model was initially run with a high rainfall intensity (40–70 mm), which decreased significantly on the second day (0–10 mm) and increased back on the third day (30–65 mm). The extended simulated rainfall accumulation time may be the reason for not observing an increase in unstable areas during the rainfall episode. Studies with TRIGRS use rainfall episodes varying between 12h, 24h and 72h. (Alvioli and Baum 2016 ; Dikshit et al. 2019 ; Ávila et al. 2020 e outros). In this study, an intense rainfall event was simulated over a period of 24 days, during which time the water in the basin may have drained, thus minimizing the effect of new rainfall loads. Since there were three days of significant rainfall with approximate values (109mm on day 12, and 127mm on days 19 and 23), the presented behavior obtained similar results. The model is controlled by rainfall intensity and water table elevation, which represent the initial soil moisture conditions to which the model is sensitive (Baum et al. 2002 ; Hermawan et al. 2023 ). Some input parameters, such as simulated time interval, soil thickness, initial water table elevation, and accumulated rainfall, also affect these differences. In the case of FDB, landslides concentrate in anthropized areas, where cuts and fills in steep areas, as well as the discharge of water and sewage alter the slope's equilibrium conditions. This mechanism was also observed in the study by Konig, Kux, and Corsi ( 2022 ). As regards the slope gradient, 92% of the unstable areas are between 45–75% and the remaining 8% are above 75%, which is similar to the results obtained by Baum, Godt and Savage ( 2010 ), Ávila et al ( 2020 ) and others. Research on FDB is currently limited, but Effgen, Oliveira e Marchioro (2018b) found similar results using SHALSTAB. They discovered that 13.83% of the basin area was unconditionally unstable, with a predominance of slopes above 45% and convergence of flows. These findings agree with other results in the literature (Listo et al. 2018 ; Vieira et al. 2018 ; Guimarães et al. 2019 ). Other surveys in the study area and in geomorphologically similar areas have also found this positive relationship between angle increase and unstable areas (Schwarz and Michael 2017 ; Effgen et al. 2018a ). In the Swiss Alps, Bisantini, Molnar e Burlando (2005) identified the same condition of overestimation of instability in sloping areas; in the Alps in Italy (Center-South), Crosta e Frattini (2003) also identify a strong relationship between the determination of unstable areas associated with high slopes (above 50%). The model shows that convex-planar and concave-planar slope forms have larger unstable areas. Urban areas involve various destabilizing processes of the terrain due to the high degree of modification of slope forms by human interventions. However, it is not certain that these factors cause mass movements like in other cases studied. In FDB, modifications are concentrated on the mid-slope and valley bottom. The DEM used has a spatial resolution of 3 meters and does not adequately capture the modifications of the terrain (they do not appear at this resolution), as well as the rapid dynamics of the site during the analyzed time scale. In terms of geocoverage, the model identified 60% of unstable areas corresponding to talus deposits. These areas are associated with higher slopes and are of greater territorial extent. TRIGRS also identified unstable areas associated with rocky outcrops. The residual soil class is found in flatter areas and/or at the tops of slopes, so the model was effective in representing geocovers. The thickness of the geocover adopted was constant for the entire basin because, despite the different thicknesses in each geocover, a pattern was identified in the occurrence of landslides in the inventory that, added to the granulometric test, indicated a thickness of 1m. Even with a single value, the geocover had satisfactory representativeness for the portions greater than 1 m. As for the orientation of the slopes, those facing east stand out, followed by northeast and southeast. This configuration was also observed in the climatic studies of Correa and Albuquerque (2012) and Mattiuzzi e Marchioro (2012), who identified that the slopes to the east receive the entry of wind bringing moisture from the northeast. A mass movement inventory by Oliveira, Effgen, and Marchioro ( 2021 ) found that the majority of landslides also occurred on these east-facing slopes, indicating a greater potential for instability due to the antecedent moisture conditions, possibly associated with moisture intrusion. 4.2 Inventory and validation of susceptibility scenarios The inventory indicates that mass movements were concentrated on slopes with high gradients. Out of the 28 reports inventoried, 50% were on slopes above 45%. Among the 13 records used for validation (landslides without any human influence), 38% were in unstable areas (FS < 1). The cuts made to the slopes increase the inclination, highlighting the significance of a good digital elevation model for studying urban areas, given that the terrain is already in a highly modified condition. The distribution of occurrences appears satisfactory when considering only a few records. However, when considering all 28 records, there is a risk of overestimating unstable areas in urbanized portions, which could lead the model to indicate instability where the land is being used improperly. The methodology for locating the scars was not effective due to the fact that some records were made days later, while others were made when the Civil Defense was not allowed to enter the property, thus associating the point with the land of the residence and not specifically with the scar. For this reason, the inventory identified some particularities. For an example, record number 11 is georeferenced to the house where the displaced material hit, at the base of the hill, within the Fradinhos neighborhood, in a residential area. However, the scar occurred closer to the rocky outcrop called 'Pedra dos Dois Olhos', a few meters above the residence, within the Fonte Grande Park Zone, on a slope greater than 75%. Based on the mentioned characteristics, the distribution of the inventoried occurrences was found to be reasonable when divided into those without the influence of occupancy conditions. This method allows for the identification of georeferenced landslides outside of their actual position and the identification of occurrences with anthropic influence to avoid overestimating areas and forcing the model to satisfy an erroneous condition in cases of simulations with estimated parameters. 4.3 Spatial planning and unstable areas The spatial distribution of unstable areas (FS < 1) when compared to the Municipal Urban Masterplan (Fig. 11 ) indicates that the majority of the zonings are situated in unstable areas, with the Environmental Protection Zone standing out with 86%, revealing the importance of preserving this area of the Central Massif of Vitória. This shows that the definition of this protected area is fulfilling its purpose by preserving the environmental conditions of the hillside and controlling the occupation of areas prone to mass movement. The Special Zone of Social Interest is associated with unstable areas that correspond to 7% of the region. This area comprises the Cruzamento neighborhood, which is known for its low economic status and is located on steep slopes (> 45%). From this perspective, compared to other neighborhoods in FDB, the area may be more susceptible to landslides due to the occupancy conditions associated with the social structure and construction pattern of the location, which is quite different from the rest of the basin. This is reported by Effgen ( 2023 ), as one of the locations exposed to elevated risk of translational landslides. The mass movement report recorded in the inventory within the Cruzamento neighborhood (nº26, Figs. 9 and 12 ) reported a landslide occurrence on a cut slope and block detachment. Additionally, the accumulation of garbage and debris in the area exacerbates the situation. It is common in the area for cuts on the slope to unearth large rocks, destabilizing them. There are also some polygons in the Restricted Occupation Zone (6%) that are in the valley bottom regions identified by the modeling as unstable areas. These cases of unstable areas are associated with medium and high slopes, with a high concentration of streams. We can see that there is human occupation in these areas: at the lower levels there are paved roads, houses and commercial structures occupying the higher slopes. Of the unstable areas, 1% is within the zone of limited occupancy, a place with many houses of higher economical status. 5 Conclusions Most of the FDB area showed a low tendency of translational landslides during the December 2013 rainfall episode, indicating that the slopes have low sensitivity to accumulated rainfall. However, there is a need for continuous monitoring over time and geographical space, and reassessment based on changes in both anthropogenic and natural conditions. The greatest occurrence of shallow landslide type is associated with the talus deposits, which is recurrent in the area studied and in the Central Massif of Vitória. The TRIGRS model showed that the keeping of the Permanent Preservation Zone is important to minimize landslide susceptibility, since this is where the areas of greatest instability are. The distribution of landslides in terms of altimetry classes and slope forms showed a heterogeneous spatial distribution. In terms of slope orientation, the east-facing slopes showed the greatest instability in the basin, possibly related to moisture input. The advantage of the TRIGRS model is to evaluate the distributed safety factor for the watershed, unlike other models that do not allow the input parameters to be varied. The main disadvantage is the increased uncertainty due to the coupled hydrological calculations since the hydrological parameters are not fixed in nature. However, the use of these equations allows a relative assessment for the whole basin, as carried out in this study, with satisfactory results. Thus, the TRIGRS model is an important tool for the analysis of areas of slope instability or stability for landslides, supporting the planning and management of the territory, contributing to the minimization of socio-economic damage and, above all, to the reduction of risk for the exposed population. Declarations Funding This work was supported by the Foundation for Research Support in Espírito Santo (FAPES). Author Jeniffer Oliveira has received research support from FAPES. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests The authors declare that they have non-financial interests to disclose. They have no Conflicts of interest/competing interests. Author Contributions All authors contributed to the conception and design of the study. Jeniffer Oliveira, Julia Effgen, Bianca Vieira, Thelma Mendes, and Eberval Marchioro performed material preparation, data collection, and analysis. Jeniffer Oliveira wrote the first draft of the manuscript, and all authors provided feedback on previous versions. Julia Effgen checked the translation. All authors read and approved the final manuscript. References Almeida BG, Donagemma GK, Ruiz HA, et al (2012) Padronização de Métodos para Análise Granulométrica no Brasil. Empresa Brasileira de Pesquisa Agropecuária (Embrapa) 66:1–11 Alvioli M, Baum RL (2016) Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface. Environmental Modelling & Software 81:122–135. https://doi.org/10.1016/j.envsoft.2016.04.002 American Society for testing and materials (ASTM) (2012) Standard Test Method for Direct Shear Test of Soils Under Consolidated Drained Conditions. 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IOP Conf Ser Earth Environ Sci 1173:012031. https://doi.org/10.1088/1755-1315/1173/1/012031 HIPARC Sistemas e Aerolevantamentos Ltda (2012) Ortofotomosaico bloco 13 - Grande Vitória, colorida, 1/25.000, Pixel 0,25x0,25m, UTM, Datum SIRGAS2000, Zona 24s. Imageamento realizado de 2012 a 2015. Padrão de Exatidão Cartográfica (PEC) classe “A”. IBGE (2010) População de Vitória (análises). Censo 2010. In: Instituto Brasileiro de Geografia e Estatística. https://cidades.ibge.gov.br/brasil/es/vitoria/panorama. Accessed 29 Dec 2023 IBGE (2022) População de Vitória. Censo 2022. In: Instituto Brasileiro de Geografia e Estatística. https://cidades.ibge.gov.br/brasil/es/vitoria/panorama. Accessed 29 Dec 2023 Instituto Nacional de Meteorologia (INMET) (2022) Estações automáticas: Série histórica de Vitória-ES (código A612 - VITÓRIA) Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36:1897–1910. https://doi.org/10.1029/2000WR900090 Jones F (1973) Landslides of Rio de Janeiro and the Serra das Araras Escarpment, Brazil. US Geological Survey 697:42 Keim RF, Skaugset AE (2003) Modelling effects of forest canopies on slope stability. Hydrol Process 17:1457–1467. https://doi.org/10.1002/hyp.5121 Khor N, Arimah B, Otieno R, et al (2022) Envisaging the Future of Cities - World Cities Report 2022. United Nations Human Settlements Programme (UN-Habitat), Nairobi, Kenya Konig T, Kux H, Corsi A (2022) Landslide risk management using the mathematical model TRIGRS. Geosciences (Basel) 41:243–254. https://doi.org/10.5016/geociencias.v41i1.16290 Lara M, Sepúlveda SA, Celis C, et al (2018) Landslide susceptibility maps of Santiago city Andean foothills, Chile. Andean Geology 45:433–442. https://doi.org/10.5027/andgeoV45n3-3151 Listo F de LR, Gomes MCV, Vieira BC (2018) Avalição da variação do Fator de Segurança com o modelo TRIGRS. Revista Brasileira de Geomorfologia 19:. https://doi.org/10.20502/rbg.v19i1.1256 Marchioro E, Coutinho FN (2020) Inundação na Bacia Hidrográfica do Rio Duas Bocas (ES): um evento extremo em 2013. Geografia (Londrina) 30:325–339. https://doi.org/10.5433/2447-1747.2021v30n1p477 Marchioro E, Silva GM, Correa WDSC (2016) A Zona de Convergência do Atlântico Sul e a precipitação pluvial do município de Vila Velha (ES): repercussões sobre as inundações. Geography Department University of Sao Paulo 31:101. https://doi.org/10.11606/rdg.v31i0.108447 Marengo JA, Alcantara E, Cunha AP, et al (2023) Flash floods and landslides in the city of Recife, Northeast Brazil after heavy rain on May 25–28, 2022: Causes, impacts, and disaster preparedness. Weather Clim Extrem 39:1–17. https://doi.org/10.1016/j.wace.2022.100545 Marin RJ, Velásquez MF, Sánchez O (2021) Applicability and performance of deterministic and probabilistic physically based landslide modeling in a data-scarce environment of the Colombian Andes. J South Am Earth Sci 108:. https://doi.org/10.1016/j.jsames.2021.103175 Mattiuzzi HV, Marchioro E (2012) O comportamento dos ventos em Vitória (ES): a gestão e interpretação dos dados climatológicos. Revista Geonorte 3: Mihai B, Savulescu I, Sandric I, Chitu Z (2014) Integration of landslide susceptibility assessment in urban development: a case study in Predeal town, Romanian Carpathians. Area 46:377–388. https://doi.org/10.1111/area.12123 Nage R (2010) On map scale and raster resolution (Arcgis Blog). https://www.esri.com/arcgis-blog/products/product/imagery/on-map-scale-and-raster-resolution/. Accessed 19 Dec 2023 Nogueira V (1985) Landslide at Morro do Macaco in the Tabuazeiro neighborhood in Vitória in the 1980s. Institute Jones dos Santos Neves Journal 4:19 Nola T de SI, Zuquette LV (2021) Procedures of engineering geological mapping applied to urban planning in a data-scarce area: Application in southern Brazil. J South Am Earth Sci 107:1–19. https://doi.org/10.1016/j.jsames.2020.103141 Oliveira J, Effgen JF, Marchioro E (2021) Inventário dos movimentos de massa em uma bacia de drenagem urbana. In: XIII Simpósio Nacional de Geomorfologia. União de Geomorfologia Brasileira (UNB), Juiz de Fora, Minas Gerais, pp 3826–3839 Puente-Sotomayor F, Mustafa A, Teller J (2021) Landslide Susceptibility Mapping of Urban Areas: Logistic Regression and Sensitivity Analysis applied to Quito, Ecuador. Geoenvironmental Disasters 8:. https://doi.org/10.1186/s40677-021-00184-0 Ruiz HA (2005) Incremento da exatidão da análise granulométrica do solo por meio da coleta da suspensão (Silte + Argila). Rev Bras Cienc Solo 29:297–300. https://doi.org/10.1590/S0100-06832005000200015 Schwarz H, Michael GP (2017) Avaliação de estabilidade de encostas com uso do modelo TRIGRS no município de Ibirama - SC. In: XX Simpósio Brasileiro de Recursos Hídricos. Associação Brasileira de Recursos Hídricos, Florianopolis, Santa Catarina Silva AE, Fontana A, Melo A da S, et al (2017) Manual de métodos de análise de solo, 3rd edn. Empresa Brasileira de Pesquisa Agropecuária (Embrapa), Brasília, DF Smyth CG, Royle SA (2000) Urban landslide hazards: incidence and causative factors in Niterói, Rio de Janeiro State, Brazil. Applied Geography 20:95–118. https://doi.org/10.1016/S0143-6228(00)00004-7 State Government of Espírito Santo (1986) Institutionalization of the Fonte Grande State Park and assignment of management to the Municipality of Vitória, the State Capital. BRAZIL United Nations (2019) World Urbanization Prospects: The 2018 Revision. New York: United Nations Vieira BC, Fernandes NF, Augusto Filho O, et al (2018) Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil. Environ Earth Sci 77:260. https://doi.org/10.1007/s12665-018-7436-0 Vitória (2014) Carta Geotécnica do município de Vitória: Arquivos vetoriais 1:16.000 Vitória Municipal City Hall (PMV) (2022) Vitória Parks. https://www.vitoria.es.gov.br/prefeitura/parques. Accessed 17 Aug 2022 Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2024 Read the published version in Natural Hazards → Version 1 posted Reviewers agreed at journal 15 Feb, 2024 Reviewers invited by journal 14 Feb, 2024 Editor invited by journal 07 Feb, 2024 Editor assigned by journal 03 Feb, 2024 First submitted to journal 02 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3925852","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":272993890,"identity":"c22bf5d0-a8c6-47f0-a20c-7e6108917f54","order_by":0,"name":"Jeniffer Oliveira Nepomuceno do Couto","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-7429-8303","institution":"Universidade Federal do Espirito Santo","correspondingAuthor":true,"prefix":"","firstName":"Jeniffer","middleName":"Oliveira Nepomuceno do","lastName":"Couto","suffix":""},{"id":272993891,"identity":"6ddf7496-77ae-4651-b85a-2158bc925dc9","order_by":1,"name":"Julia Effgen","email":"","orcid":"","institution":"UFES: Universidade Federal do Espirito Santo","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Effgen","suffix":""},{"id":272993892,"identity":"c947de81-bdf9-4d88-b6aa-fd67e88b2b71","order_by":2,"name":"Bianca Vieira","email":"","orcid":"","institution":"USP: Universidade de Sao Paulo","correspondingAuthor":false,"prefix":"","firstName":"Bianca","middleName":"","lastName":"Vieira","suffix":""},{"id":272993893,"identity":"ffe59682-47a9-4a67-8fb6-dc6ae16c64e7","order_by":3,"name":"Thelma Silva","email":"","orcid":"","institution":"UFRJ: Universidade Federal do Rio de Janeiro","correspondingAuthor":false,"prefix":"","firstName":"Thelma","middleName":"","lastName":"Silva","suffix":""},{"id":272993894,"identity":"e42ce0cf-daeb-465b-8843-f94347bc3523","order_by":4,"name":"Eberval Marchioro","email":"","orcid":"","institution":"UFES: Universidade Federal do Espirito Santo","correspondingAuthor":false,"prefix":"","firstName":"Eberval","middleName":"","lastName":"Marchioro","suffix":""}],"badges":[],"createdAt":"2024-02-04 02:03:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3925852/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3925852/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11069-024-06956-9","type":"published","date":"2024-10-30T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51330326,"identity":"4c5828b0-1b3a-4cda-bfa8-bcfbfae884fe","added_by":"auto","created_at":"2024-02-19 17:47:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2194795,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area. Created by authors\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/7032574d9bc3146f2ac881e9.jpg"},{"id":51330314,"identity":"774e8d12-701d-4c7f-bdbf-1eb52ed65135","added_by":"auto","created_at":"2024-02-19 17:47:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1554318,"visible":true,"origin":"","legend":"\u003cp\u003eFDB location of\u003cstrong\u003e a\u003c/strong\u003e Fradinhos and \u003cstrong\u003eb\u003c/strong\u003e Cruzamento. Authors collection\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/ecd9f76670154f222832da38.jpg"},{"id":51330321,"identity":"0df7441b-4f7b-44cd-8b0d-c6adb409eb2d","added_by":"auto","created_at":"2024-02-19 17:47:29","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1689078,"visible":true,"origin":"","legend":"\u003cp\u003eThe Tabuazeiro neighborhood in Vitória, Espírito Santo affected by a landslide and rock slide on Morro do Macaco. Jones dos Santos Neves Institute Journal (IJSN, 1985)\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/3ea007bb6d3ac9eb130797c4.jpg"},{"id":51330331,"identity":"eae66935-6e4d-40d9-8d7f-57aeeeb54cf2","added_by":"auto","created_at":"2024-02-19 17:47:31","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1351062,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Elevation, \u003cstrong\u003eb\u003c/strong\u003e slope, \u003cstrong\u003ec\u003c/strong\u003e curvate, and \u003cstrong\u003ed\u003c/strong\u003e aspect with landslides points in Civil Defense reports. By authors\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/3b86d7086ddc2533a547b273.jpg"},{"id":51330365,"identity":"89eb23dd-a3e5-40b0-8c53-666bab909660","added_by":"auto","created_at":"2024-02-19 17:47:36","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1390746,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Mid-slope terrain with the presence of buried rocks; \u003cstrong\u003eb\u003c/strong\u003e a landslide occurred in a road cut, exposing rocks and obstructing traffic, exiting the Fradinhos neighborhood. Authors collection\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/1270e05ea6e41670d41f6160.jpg"},{"id":51330329,"identity":"dd9719d6-b108-45a9-9abf-737d46321d72","added_by":"auto","created_at":"2024-02-19 17:47:31","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":220733,"visible":true,"origin":"","legend":"\u003cp\u003eClimate Normal Graph (1961 by 2021). INMET (2022)\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/480cfd6ec6c9434737f05d03.jpg"},{"id":51330327,"identity":"3c0d5068-02ca-41b5-992a-6a1c70c8b8f2","added_by":"auto","created_at":"2024-02-19 17:47:31","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":212576,"visible":true,"origin":"","legend":"\u003cp\u003eClimate graph (2013). INMET (2022)\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/1cbe4d5152ca6cf3d48e189f.jpg"},{"id":51330328,"identity":"a5aa79d6-1221-4dbc-8da5-8f3511c9dd7c","added_by":"auto","created_at":"2024-02-19 17:47:31","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2525037,"visible":true,"origin":"","legend":"\u003cp\u003eFDB with sampling point distribution in different material types and hydrodynamic characteristics. By authors\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/4a286ae4280374f11c9c67f0.jpg"},{"id":51330323,"identity":"0059d62b-7911-400d-8ea3-d72cae983963","added_by":"auto","created_at":"2024-02-19 17:47:29","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1959524,"visible":true,"origin":"","legend":"\u003cp\u003eFDB Inventory. By authors\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/b0692cab8e91060b4b0b9bea.jpg"},{"id":51330362,"identity":"a83a9a5d-564b-48d6-b1d1-b87e72070324","added_by":"auto","created_at":"2024-02-19 17:47:34","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1252520,"visible":true,"origin":"","legend":"\u003cp\u003eFS with TRIGRS\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/5fc7f178e387317a4ddee64c.jpg"},{"id":51330318,"identity":"a4a95e97-aecf-43cf-bca5-7f18ebe841be","added_by":"auto","created_at":"2024-02-19 17:47:25","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":1726408,"visible":true,"origin":"","legend":"\u003cp\u003eMunicipal Urban Masterplan and unstable class with TRIGRS. By authors\u003c/p\u003e","description":"","filename":"Picture11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/5600bfea2c35614b758878b8.jpg"},{"id":51330324,"identity":"c6e309c1-53ee-4c5b-a51a-008c8080824e","added_by":"auto","created_at":"2024-02-19 17:47:29","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":500543,"visible":true,"origin":"","legend":"\u003cp\u003eLandslide in Cruzamento ( n°26 in the inventory), the two images are located on the side of the houses and indicate the place of \u003cstrong\u003ea \u003c/strong\u003eorigin of the detached material and \u003cstrong\u003eb \u003c/strong\u003ethe place of deposit, according to the sketch. These images were taken by the Civil Defense on April 7, 2016.\u003c/p\u003e","description":"","filename":"Picture12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/0f955dfdb68db5f86cb5b821.jpg"},{"id":68206611,"identity":"da8f617f-5564-4cbc-b622-e6a930d69634","added_by":"auto","created_at":"2024-11-04 16:33:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17122046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3925852/v1/270422b8-7cf2-4a93-ae56-854a2f31adbb.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eDynamics of Mass Movements in an Urban Basin: A Case Study in the Fradinhos Drainage Basin, Vitória, Espírito Santo, Brazil\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eUrban agglomerations have been expanding in different parts of the world, causing problems associated with landslides, especially those in cities in hot and humid tropical environments (Smyth and Royle \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA significant issue in urban areas is the improper occupancy and cutting of slopes. This includes occupancy of slopes and construction on concave parts of slopes in an improper manner, which has been increasing with the acceleration of the urbanization process in recent decades, confirming the potentiation of this hydrogeomorphologic process.\u003c/p\u003e \u003cp\u003eThe report 'World Urbanization Prospects: The 2018 Revision' by the Population Division of the United Nations (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) estimates that the world's urban population will reach 6.7\u0026nbsp;billion by 2050. According to the projections in the United Nations Human Settlements Program's 'World Cities Report' (Khor et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the urban population is expected to increase by 2.2\u0026nbsp;billion by 2050. This growth highlights the need for infrastructure planning to meet the demands of the growing population.\u003c/p\u003e \u003cp\u003eBased on the 2010 Demographic Census conducted by the Brazilian Institute of Geography and Statistics, the municipality of Vit\u0026oacute;ria had over 87,000 people at risk (IBGE \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Recent data from the same source indicates population growth and increased demographic density, highlighting the importance of implementing mitigating measures (IBGE \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExamples of landslides in urban areas can be found in various regions of the world, including Algeria (Bourenane et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the United States (Fiolleau et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Romania (Mihai et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), Chile (Lara et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and Ecuador (Puente-Sotomayor et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), among others.\u003c/p\u003e \u003cp\u003eIn Brazil, due to the geo-environmental conditions, several studies have been carried out in urban areas with a focus on landslide inventory, monitoring, and modeling in S\u0026atilde;o Paulo (Cerri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), Rio de Janeiro (Jones \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1973\u003c/span\u003e), Minas Gerais (Nola and Zuquette 2021), Pernambuco (Marengo et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Work in the neighboring cities of Vila Velha (Effgen and Marchioro \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Vit\u0026oacute;ria (Effgen et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e) analyzed areas susceptible to mass movements, showing how the disorderly appropriation of geographical space by human activity in urban agglomerations supports the occurrence of landslides.\u003c/p\u003e \u003cp\u003eTherefore, the occurrence of landslides in urban areas is a challenge for sustainable and equitable development, between the need for occupation and the carrying capacity of slopes for occupancy, a fact that leads to the need for modeling to verify susceptibility to minimize socioeconomic and environmental impacts. Hence, this study intended to identify the susceptibility to shallow landslides in an urban area in southeastern Brazil as a subsidy for risk mitigation.\u003c/p\u003e"},{"header":"2 Study area","content":"\u003cp\u003eVit\u0026oacute;ria, the capital of the state of Esp\u0026iacute;rito Santo, is divided in two parts: a continental part to the north and an archipelago to the south. The largest island, called Vit\u0026oacute;ria Island, is bounded by the Atlantic Ocean to the east and the estuary of the Santa Maria River to the west. During the city's construction, Vit\u0026oacute;ria Island underwent several embankment processes, expanding its boundaries and connecting smaller islands in its vicinity. The Fradinhos Drainage Basin (FDB) covers an area of 2.7km\u0026sup2; and is located on Vit\u0026oacute;ria Island, along the eastern portion of the Central Massif of Vit\u0026oacute;ria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBetween 1940 and 1950, only the southern portion of Vit\u0026oacute;ria Island was inhabited. However, with the accelerated development process that took place in the state, the population of Vit\u0026oacute;ria increased from approximately 51,000 people to over 200,000 in just 30 years. As a result of limited space, hillsides began to be occupied, leading to numerous mass movements and associated disasters. Most of the events occurred on the upper part of the hillside, but they had a direct impact on the population living in the lower and medium segments of the hillside.\u003c/p\u003e \u003cp\u003eThe Fradinhos neighborhood, located in the center of the basin, consists of well-established public streets and high-quality residential buildings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). At the outlet of the basin, next to Fradinhos, the neighborhood of Cruzamento has a population with low purchasing power, due to complex occupations associated with population growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe easternmost section makes up the Fonte Grande Park, which was established in 1986, the year following the Morro do Macaco disaster of 1985 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The park\u0026rsquo;s main objective is to protect and stabilize the slopes in order to safeguard the natural attributes. This is mainly achieved by preventing occupation and protecting against the changes that could occur with slope occupation and associated disasters. The park currently has one of the largest remnants of Atlantic Forest protected by law in an urban area in the country (Esp\u0026iacute;rito Santo 1986; PMV 2022).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn inventory of mass movements, based on Civil Defense reports, showed that 84% were shallow landslides, some of which were associated with falling blocks. The rock structure is fractured on the high slopes and near the hilltopswith a gradient of more than 35%. There are some residual soil patches, talus deposits, and semi-buried boulders that can be found in areas with thin soils. The FDB's largest type of geotechnical cover is tallus deposits, which has many associated mass movement records from 1999 to March 2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee 5) (Oliveira et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor rainfall, based on the Climatological Normal (1961\u0026ndash;2021) with records from the automatic station in Vit\u0026oacute;ria (INMET 2022), located approximately four kilometers from the FDB, Vit\u0026oacute;ria has an average monthly rainfall of 109.4 mm. The highest monthly accumulations on record were 746.6 mm (December 2013), 662.8 mm (November 2008), and 406.4 mm (October 2009) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn December 2013, a polar air mass combined with humidity from the Amazon rainforest resulted in the formation of the South Atlantic Convergence Zone (SACZ). The SACZ stayed over Esp\u0026iacute;rito Santo, providing constant rainfall until December 26 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Newspapers and government agencies in the state reported about 23 deaths and widespread damages, including floodings, destruction of bridges and homes, and landslides (Marchioro and Coutinho \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Marchioro, Silva, Correa (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) note that the variability of rainfall in Vit\u0026oacute;ria is mainly influenced by South Atlantic Convergence Zones (SACZ) and polar air masses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3 Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 \u003cem\u003eTransient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS)\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eTRIGRS is a deterministic physic-mathematical model developed by Baum, Savage, and Godt (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) in Fortran language. The model combines a hydrological model in transient conditions with a stability model based on the infinite slope equation, following a proposal by Iverson (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis analysis is calculated by the ratio between the forces acting to stabilize and destabilize, called the Factor of Safety (FS), described by the authors for the depth Z, where Φ is the angle of internal friction in degrees, θ the slope angle in degrees, c' the effective soil cohesion in KPa, Ψ the pressure head, Z the soil depth in meters, t the time, ρ\u003csub\u003ew\u003c/sub\u003e the specific weight of the water and ρ\u003csub\u003es\u003c/sub\u003e specific weight of the soil (Eq.\u0026nbsp;1).\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$FS= \\frac{tan {\\upvarphi }}{tan \\theta }+\\frac{{c}^{{\\prime }}-{\\Psi }\\left(Z,t\\right){{\\rho }}_{w} tan {\\upvarphi }}{{{\\rho }}_{s} Zsen\\theta cos\\theta }$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e(1)\u003c/p\u003e \u003cp\u003eWorldwide, the model has been applied to hillsides in the northwest of the USA to identify the behavior of the pressure head during a rainfall episode, taking into account the influence of the tree canopy (Keim and Skaugset \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e); while in Italy Crosta and Frattini (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) obtained better results than the other two models used; Frattini et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) obtained better results than the scar map for pyroclastic soils in Italy. Chien-Yuan et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), analyzed precipitation-induced landslides and debris flows in Taiwan. They observed cracks in the soil and a rupture surface that coincided with the unstable areas on the model-generated map. Aristiz\u0026aacute;bal et al. (2022) highlight in a recent study in Colombia that the increase in rainfall intensity due to global climate change increases the occurrence of shallow slides for soils with high permeability. Still in Colombia country, Marin, Vel\u0026aacute;squez e S\u0026aacute;nchez (2021) added spatially varying rainfall data to the simulation, which is not commonly used.\u003c/p\u003e \u003cp\u003eIn Brazil, Vieira et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) compared the SHALSTAB and TRIGRS models in Serra do Mar, S\u0026atilde;o Paulo. Five scenarios were simulated in the southern region of the country, in Ibirama, Santa Catarina, varying rainfall and water table depth. The results highlighted the model's high sensitivity to these two parameters, suggesting that simulations with this data should be distributed over the basin (Schwarz and Michael \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Three simulations were conducted in the basin of the Quitite and Papagaio rivers, located west of the Tijuca Massif in Rio de Janeiro, using the model for three different depths. The results indicated that the model is highly sensitive to the initial height of the water table, with instability being overestimated for higher initial heights (two meters) (Guimar\u0026atilde;es et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Input Model Data\u003c/h2\u003e \u003cp\u003eThe mapping data, along with their respective sources and scales or spatial resolutions, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The digital elevation model (DEM) was generated using contour lines, elevation points, and drainage data, with a spatial resolution of three meters, as proposed by Nage (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCartographic data used, source, and spatial resolution\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScale or Spatial Resolution\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLIVEIRA, EFFGEN, MARCHIORO (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInventory of Landslides in Vit\u0026oacute;ria 1999\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIEMA (2012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5m\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevation Points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:25.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINMET (2022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVit\u0026oacute;ria Rain Gauge Station (December 2013)\u003c/p\u003e \u003cp\u003eCode A612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThree soil sample collections were executed by Effgen, Oliveira e Marchioro (2018b), and we collected two new soil samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The last two were defined to spatially represent the basin for possible differences arising from the location of the materials and to integrate all the units of geocoverage (Vit\u0026oacute;ria \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The modeling was done using the average of the sampled values, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInput data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeotechnical and Hydrological Properties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameters (unit)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTechnical\u003c/p\u003e \u003cp\u003estandard\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil cohesion (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mathcal{c}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18,32 KPa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eD3080:2012 (ASTM 2012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecific weight of the soil (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\rho }}_{\\varvec{s}}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 Kg/m\u0026sup3;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAngle of internal friction\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\left(\\varvec{\\varphi }\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum thickness of the soil (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{Z}}_{\\varvec{m}\\varvec{a}\\varvec{x}})\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRuiz (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2005\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAlmeida et al (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eEmbrapa (Silva et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecific weight of groudwater (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\rho }}_{\\varvec{s}}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,99823 KN/m\u0026sup3;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD3080:2012 (ASTM 2012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial height of the water table (d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNBR14545 (ABNT 2000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVertical saturated hydraulic conductivity (Ksat)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,2x10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e m/s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRate of initial infiltration (I\u003csub\u003ez\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0x10\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e m/s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eDefault\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydraulic diffusivity (D\u003csub\u003e0\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0x10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e m\u0026sup2;/s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe December 2013 rainfall episode had the highest monthly accumulation in the 60-year historical series (1961\u0026ndash;2021), totaling 744mm. The event began on December 6, 2013, and the highest daily accumulation of 127mm occurred on December 19. The last day of rain was December 26, 2013. For the modeling, this period was divided into four rainy periods (T1, T2, T3 and T4), and the intensity was calculated based on these four episodes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePluviometric parameters to TRIGRS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration (days)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAccumulated Precipitation (mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAverage Rainfall Intensity for Each Event I\u003csub\u003enZ\u003c/sub\u003e (m/s)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 5th to 10th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51840s (6 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,97x10\u003csup\u003e\u0026minus;\u0026thinsp;07\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 11th to 16th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103680s (12 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,43x10\u003csup\u003e\u0026minus;\u0026thinsp;06\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 17th to 22th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155520s (18 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,80x10\u003csup\u003e\u0026minus;\u0026thinsp;06\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 23th to 28th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207360s (24 days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,51x10\u003csup\u003e\u0026minus;\u0026thinsp;06\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNational Meteorological Institute's Vit\u0026oacute;ria Rain Station (INMET, 2022)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Validation (Inventory)\u003c/h2\u003e \u003cp\u003eThe inventory contains a single point associated with each slip location (scars) or affected residence, according to the reports from the Civil Defense of Vit\u0026oacute;ria, for the period from 1999 to March 2018. The inventory includes 28 landslides, 13 of which were not influenced by occupancy conditions and were therefore used to validate susceptibility maps (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLandslides are concentrated in urban areas mainly because it was reported based on calls received by the Civil Defense, where mass movements or even imminent events are reported around occupations. In the FDB, 62% of the scars vary in depth from 30cm to 1m, indicating the most likely rupture zone in the basin.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Susceptibility Maps\u003c/h2\u003e \u003cp\u003eDuring the simulation of susceptibility scenarios, only T4 showed differences between unstable and stable areas for the four analyzed rainfall periods. Two polygons increased instability, but did not changed class, resulting in no visual changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The unstable areas have totaled 31% of the FDB.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIt was expected that the unstable areas (FS\u0026thinsp;\u0026lt;\u0026thinsp;1) increase over the course of the rainfall episode, since there would be an increase in humidity in the surface geocovers. However, the same FS values were found for the first three rainfall episodes (T1, T2, and T3). A few increases were found in T4, associated with the higher slopes, but were not considered because it was a rock formation with no geocover development for possible landslides. This is the FDB's response to the previous rainfall conditions: the water infiltrates, the areas with higher instability are those of the upper and middle slope and doesn't change much during the periods evaluated. Despite the decrease in rainfall at T4, the areas identified as unstable remained classified as such.\u003c/p\u003e \u003cp\u003eHermawan et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) simulated a constant rainfall event in a volcanic area with steep slopes in a province of Indonesia. They considered the effect of 12 hours of preceding rainfall and identified an increase in unstable areas as time increased. This highlights the importance of preceding rainfall in altering pore pressure and reducing slope stability in steeper portions. Konig, Kux e Corsi (2022) simulated a precipitation episode in an urban watershed in the state of S\u0026atilde;o Paulo, divided into three days. At the start of the simulation, only a few areas were identified where FS\u0026thinsp;\u0026lt;\u0026thinsp;1, which corresponded to areas where the slope was above 30\u0026ordm;. Over time, the FS values decreased on the steeper slopes, and after 72 hours, almost the entire high-slope area was unstable. The model was initially run with a high rainfall intensity (40\u0026ndash;70 mm), which decreased significantly on the second day (0\u0026ndash;10 mm) and increased back on the third day (30\u0026ndash;65 mm).\u003c/p\u003e \u003cp\u003eThe extended simulated rainfall accumulation time may be the reason for not observing an increase in unstable areas during the rainfall episode. Studies with TRIGRS use rainfall episodes varying between 12h, 24h and 72h. (Alvioli and Baum \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dikshit et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; \u0026Aacute;vila et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e e outros). In this study, an intense rainfall event was simulated over a period of 24 days, during which time the water in the basin may have drained, thus minimizing the effect of new rainfall loads. Since there were three days of significant rainfall with approximate values (109mm on day 12, and 127mm on days 19 and 23), the presented behavior obtained similar results.\u003c/p\u003e \u003cp\u003eThe model is controlled by rainfall intensity and water table elevation, which represent the initial soil moisture conditions to which the model is sensitive (Baum et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Hermawan et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Some input parameters, such as simulated time interval, soil thickness, initial water table elevation, and accumulated rainfall, also affect these differences. In the case of FDB, landslides concentrate in anthropized areas, where cuts and fills in steep areas, as well as the discharge of water and sewage alter the slope's equilibrium conditions. This mechanism was also observed in the study by Konig, Kux, and Corsi (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs regards the slope gradient, 92% of the unstable areas are between 45\u0026ndash;75% and the remaining 8% are above 75%, which is similar to the results obtained by Baum, Godt and Savage (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), \u0026Aacute;vila et al (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and others. Research on FDB is currently limited, but Effgen, Oliveira e Marchioro (2018b) found similar results using SHALSTAB. They discovered that 13.83% of the basin area was unconditionally unstable, with a predominance of slopes above 45% and convergence of flows. These findings agree with other results in the literature (Listo et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vieira et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Guimar\u0026atilde;es et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOther surveys in the study area and in geomorphologically similar areas have also found this positive relationship between angle increase and unstable areas (Schwarz and Michael \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Effgen et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). In the Swiss Alps, Bisantini, Molnar e Burlando (2005) identified the same condition of overestimation of instability in sloping areas; in the Alps in Italy (Center-South), Crosta e Frattini (2003) also identify a strong relationship between the determination of unstable areas associated with high slopes (above 50%).\u003c/p\u003e \u003cp\u003eThe model shows that convex-planar and concave-planar slope forms have larger unstable areas. Urban areas involve various destabilizing processes of the terrain due to the high degree of modification of slope forms by human interventions. However, it is not certain that these factors cause mass movements like in other cases studied. In FDB, modifications are concentrated on the mid-slope and valley bottom. The DEM used has a spatial resolution of 3 meters and does not adequately capture the modifications of the terrain (they do not appear at this resolution), as well as the rapid dynamics of the site during the analyzed time scale.\u003c/p\u003e \u003cp\u003eIn terms of geocoverage, the model identified 60% of unstable areas corresponding to talus deposits. These areas are associated with higher slopes and are of greater territorial extent. TRIGRS also identified unstable areas associated with rocky outcrops. The residual soil class is found in flatter areas and/or at the tops of slopes, so the model was effective in representing geocovers. The thickness of the geocover adopted was constant for the entire basin because, despite the different thicknesses in each geocover, a pattern was identified in the occurrence of landslides in the inventory that, added to the granulometric test, indicated a thickness of 1m. Even with a single value, the geocover had satisfactory representativeness for the portions greater than 1 m.\u003c/p\u003e \u003cp\u003eAs for the orientation of the slopes, those facing east stand out, followed by northeast and southeast. This configuration was also observed in the climatic studies of Correa and Albuquerque (2012) and Mattiuzzi e Marchioro (2012), who identified that the slopes to the east receive the entry of wind bringing moisture from the northeast. A mass movement inventory by Oliveira, Effgen, and Marchioro (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that the majority of landslides also occurred on these east-facing slopes, indicating a greater potential for instability due to the antecedent moisture conditions, possibly associated with moisture intrusion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Inventory and validation of susceptibility scenarios\u003c/h2\u003e \u003cp\u003eThe inventory indicates that mass movements were concentrated on slopes with high gradients. Out of the 28 reports inventoried, 50% were on slopes above 45%. Among the 13 records used for validation (landslides without any human influence), 38% were in unstable areas (FS\u0026thinsp;\u0026lt;\u0026thinsp;1). The cuts made to the slopes increase the inclination, highlighting the significance of a good digital elevation model for studying urban areas, given that the terrain is already in a highly modified condition.\u003c/p\u003e \u003cp\u003eThe distribution of occurrences appears satisfactory when considering only a few records. However, when considering all 28 records, there is a risk of overestimating unstable areas in urbanized portions, which could lead the model to indicate instability where the land is being used improperly.\u003c/p\u003e \u003cp\u003eThe methodology for locating the scars was not effective due to the fact that some records were made days later, while others were made when the Civil Defense was not allowed to enter the property, thus associating the point with the land of the residence and not specifically with the scar. For this reason, the inventory identified some particularities. For an example, record number 11 is georeferenced to the house where the displaced material hit, at the base of the hill, within the Fradinhos neighborhood, in a residential area. However, the scar occurred closer to the rocky outcrop called 'Pedra dos Dois Olhos', a few meters above the residence, within the Fonte Grande Park Zone, on a slope greater than 75%.\u003c/p\u003e \u003cp\u003eBased on the mentioned characteristics, the distribution of the inventoried occurrences was found to be reasonable when divided into those without the influence of occupancy conditions. This method allows for the identification of georeferenced landslides outside of their actual position and the identification of occurrences with anthropic influence to avoid overestimating areas and forcing the model to satisfy an erroneous condition in cases of simulations with estimated parameters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Spatial planning and unstable areas\u003c/h2\u003e \u003cp\u003eThe spatial distribution of unstable areas (FS\u0026thinsp;\u0026lt;\u0026thinsp;1) when compared to the Municipal Urban Masterplan (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e) indicates that the majority of the zonings are situated in unstable areas, with the Environmental Protection Zone standing out with 86%, revealing the importance of preserving this area of the Central Massif of Vit\u0026oacute;ria. This shows that the definition of this protected area is fulfilling its purpose by preserving the environmental conditions of the hillside and controlling the occupation of areas prone to mass movement.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Special Zone of Social Interest is associated with unstable areas that correspond to 7% of the region. This area comprises the Cruzamento neighborhood, which is known for its low economic status and is located on steep slopes (\u0026gt;\u0026thinsp;45%). From this perspective, compared to other neighborhoods in FDB, the area may be more susceptible to landslides due to the occupancy conditions associated with the social structure and construction pattern of the location, which is quite different from the rest of the basin. This is reported by Effgen (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), as one of the locations exposed to elevated risk of translational landslides. The mass movement report recorded in the inventory within the Cruzamento neighborhood (n\u0026ordm;26, Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e) reported a landslide occurrence on a cut slope and block detachment. Additionally, the accumulation of garbage and debris in the area exacerbates the situation. It is common in the area for cuts on the slope to unearth large rocks, destabilizing them.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere are also some polygons in the Restricted Occupation Zone (6%) that are in the valley bottom regions identified by the modeling as unstable areas. These cases of unstable areas are associated with medium and high slopes, with a high concentration of streams. We can see that there is human occupation in these areas: at the lower levels there are paved roads, houses and commercial structures occupying the higher slopes. Of the unstable areas, 1% is within the zone of limited occupancy, a place with many houses of higher economical status.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eMost of the FDB area showed a low tendency of translational landslides during the December 2013 rainfall episode, indicating that the slopes have low sensitivity to accumulated rainfall. However, there is a need for continuous monitoring over time and geographical space, and reassessment based on changes in both anthropogenic and natural conditions.\u003c/p\u003e \u003cp\u003eThe greatest occurrence of shallow landslide type is associated with the talus deposits, which is recurrent in the area studied and in the Central Massif of Vit\u0026oacute;ria. The TRIGRS model showed that the keeping of the Permanent Preservation Zone is important to minimize landslide susceptibility, since this is where the areas of greatest instability are.\u003c/p\u003e \u003cp\u003eThe distribution of landslides in terms of altimetry classes and slope forms showed a heterogeneous spatial distribution. In terms of slope orientation, the east-facing slopes showed the greatest instability in the basin, possibly related to moisture input.\u003c/p\u003e \u003cp\u003eThe advantage of the TRIGRS model is to evaluate the distributed safety factor for the watershed, unlike other models that do not allow the input parameters to be varied. The main disadvantage is the increased uncertainty due to the coupled hydrological calculations since the hydrological parameters are not fixed in nature. However, the use of these equations allows a relative assessment for the whole basin, as carried out in this study, with satisfactory results.\u003c/p\u003e \u003cp\u003eThus, the TRIGRS model is an important tool for the analysis of areas of slope instability or stability for landslides, supporting the planning and management of the territory, contributing to the minimization of socio-economic damage and, above all, to the reduction of risk for the exposed population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the Foundation for Research Support in Esp\u0026iacute;rito Santo (FAPES). Author Jeniffer Oliveira has received research support from FAPES. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have non-financial interests to disclose. They have no Conflicts of interest/competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the conception and design of the study. Jeniffer Oliveira, Julia Effgen, Bianca Vieira, Thelma Mendes, and Eberval Marchioro performed material preparation, data collection, and analysis. Jeniffer Oliveira wrote the first draft of the manuscript, and all authors provided feedback on previous versions. Julia Effgen checked the translation. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlmeida BG, Donagemma GK, Ruiz HA, et al (2012) Padroniza\u0026ccedil;\u0026atilde;o de M\u0026eacute;todos para An\u0026aacute;lise Granulom\u0026eacute;trica no Brasil. Empresa Brasileira de Pesquisa Agropecu\u0026aacute;ria (Embrapa) 66:1\u0026ndash;11\u003c/li\u003e\n\u003cli\u003eAlvioli M, Baum RL (2016) Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface. Environmental Modelling \u0026amp; Software 81:122\u0026ndash;135. https://doi.org/10.1016/j.envsoft.2016.04.002\u003c/li\u003e\n\u003cli\u003eAmerican Society for testing and materials (ASTM) (2012) Standard Test Method for Direct Shear Test of Soils Under Consolidated Drained Conditions. D3080/D3080M\u003c/li\u003e\n\u003cli\u003eAristiz\u0026aacute;bal Giraldo EV, Garc\u0026iacute;a Aristiz\u0026aacute;bal E, Mar\u0026iacute;n S\u0026aacute;nchez R, et al (2022) Rainfall-intensity effect on landslide hazard assessment due to climate change in north-western Colombian Andes. Revista Facultad de Ingenier\u0026iacute;a Universidad de Antioquia 51\u0026ndash;66. https://doi.org/10.17533/udea.redin.20201215\u003c/li\u003e\n\u003cli\u003eAssocia\u0026ccedil;\u0026atilde;o Brasileira de Normas T\u0026eacute;cnicas (ABNT) (2000) Determina\u0026ccedil;\u0026atilde;o do coeficiente de permeabilidade de solos argilosos a carga vari\u0026aacute;vel. NBR14545\u003c/li\u003e\n\u003cli\u003e\u0026Aacute;vila FF, Alval\u0026aacute; RC, Mendes RM, Amore DJ (2020) The influence of land use/land cover variability and rainfall intensity in triggering landslides: a back-analysis study via physically based models. Natural Hazards 105:1139\u0026ndash;1161. https://doi.org/10.1007/s11069-020-04324-x\u003c/li\u003e\n\u003cli\u003eBaum RL, Godt JW, Savage WZ (2010) Estimating the timing and location of shallow rainfall‐induced landslides using a model for transient, unsaturated infiltration. J Geophys Res Earth Surf 115:. https://doi.org/10.1029/2009JF001321\u003c/li\u003e\n\u003cli\u003eBaum RL, Savage WZ, Godt JW (2002) TRIGRS; a Fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis. Denver, Colorado\u003c/li\u003e\n\u003cli\u003eBisanti B, Molnar P, Burlando P (2005) Predicting rainfall triggered soil slips: a case study in the Emmental Region (Switzerland). In: 3rd Swiss Geoscience Meeting. 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Andean Geology 45:433\u0026ndash;442. https://doi.org/10.5027/andgeoV45n3-3151\u003c/li\u003e\n\u003cli\u003eListo F de LR, Gomes MCV, Vieira BC (2018) Avali\u0026ccedil;\u0026atilde;o da varia\u0026ccedil;\u0026atilde;o do Fator de Seguran\u0026ccedil;a com o modelo TRIGRS. Revista Brasileira de Geomorfologia 19:. https://doi.org/10.20502/rbg.v19i1.1256\u003c/li\u003e\n\u003cli\u003eMarchioro E, Coutinho FN (2020) Inunda\u0026ccedil;\u0026atilde;o na Bacia Hidrogr\u0026aacute;fica do Rio Duas Bocas (ES): um evento extremo em 2013. Geografia (Londrina) 30:325\u0026ndash;339. https://doi.org/10.5433/2447-1747.2021v30n1p477\u003c/li\u003e\n\u003cli\u003eMarchioro E, Silva GM, Correa WDSC (2016) A Zona de Converg\u0026ecirc;ncia do Atl\u0026acirc;ntico Sul e a precipita\u0026ccedil;\u0026atilde;o pluvial do munic\u0026iacute;pio de Vila Velha (ES): repercuss\u0026otilde;es sobre as inunda\u0026ccedil;\u0026otilde;es. 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Applied Geography 20:95\u0026ndash;118. https://doi.org/10.1016/S0143-6228(00)00004-7\u003c/li\u003e\n\u003cli\u003eState Government of Esp\u0026iacute;rito Santo (1986) Institutionalization of the Fonte Grande State Park and assignment of management to the Municipality of Vit\u0026oacute;ria, the State Capital. BRAZIL\u003c/li\u003e\n\u003cli\u003eUnited Nations (2019) World Urbanization Prospects: The 2018 Revision. New York: United Nations\u003c/li\u003e\n\u003cli\u003eVieira BC, Fernandes NF, Augusto Filho O, et al (2018) Assessing shallow landslide hazards using the TRIGRS and SHALSTAB models, Serra do Mar, Brazil. 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Accessed 17 Aug 2022\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Susceptibility, shallow slides, geomorphology, TRIGRS","lastPublishedDoi":"10.21203/rs.3.rs-3925852/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3925852/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLandslides are a widespread problem in Brazil due to the heavy rainfall typical of tropical environments. In urban areas, landslides can be catastrophic and can lead to significant economic and social losses. To prevent such catastrophes, it is crucial to comprehend the spatial distribution of mass movements in local dynamics. The aim of this study was to evaluate the spatial distribution of areas susceptible to shallow translational slides in the Fradinhos Drainage Basin (FDB), situated in Vit\u0026oacute;ria, state of Esp\u0026iacute;rito Santo (ES). To achieve this, we used the \u003cem\u003eTransient Rainfall Infiltration and Grid-Based Regional Slope-Stability\u003c/em\u003e (\u003cem\u003eTRIGRS\u003c/em\u003e) model, along with geotechnical and hydrological data from five sampling points. An extreme rainfall event that lasted 24 days, with an accumulated rainfall of 744 mm was considered. The study revealed that 31% of the basin is unstable, with no significant increase in these areas during the rainfall period. Additionally, 86% of this area is in an Environmental Protection Zone. The results indicate that the FDB has a low susceptibility to shallow landslides, due to the existence of the Environmental Protection Zone, as this zone forms a protective belt at higher slopes. TRIGRS effectively identifies unstable zones and is an useful tool for identifying susceptibility, contributing to local management.\u003c/p\u003e","manuscriptTitle":"Dynamics of Mass Movements in an Urban Basin: A Case Study in the Fradinhos Drainage Basin, Vitória, Espírito Santo, Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-19 17:46:49","doi":"10.21203/rs.3.rs-3925852/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-02-15T08:56:26+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-14T11:24:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Natural Hazards","date":"2024-02-07T16:50:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-02-03T05:36:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Natural Hazards","date":"2024-02-02T20:06:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6618f016-39bc-4898-84ad-2f2c46639f9f","owner":[],"postedDate":"February 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:22:23+00:00","versionOfRecord":{"articleIdentity":"rs-3925852","link":"https://doi.org/10.1007/s11069-024-06956-9","journal":{"identity":"natural-hazards","isVorOnly":false,"title":"Natural Hazards"},"publishedOn":"2024-10-30 15:57:03","publishedOnDateReadable":"October 30th, 2024"},"versionCreatedAt":"2024-02-19 17:46:49","video":"","vorDoi":"10.1007/s11069-024-06956-9","vorDoiUrl":"https://doi.org/10.1007/s11069-024-06956-9","workflowStages":[]},"version":"v1","identity":"rs-3925852","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3925852","identity":"rs-3925852","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}