ORIGINAL PAPER

Susceptibility to shallow landslides in a drainage basinin the Serra do Mar, Sao Paulo, Brazil, predicted usingthe SINMAP mathematical model

Tulius Dias Nery • Bianca Carvalho Vieira

Received: 8 February 2014 / Accepted: 29 April 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract The Serra do Mar mountain range is a fault

scarp with steep slopes that are often affected by shallow

landslides triggered by extreme rainfall. Most of these

events result in casualties and economic and environmental

damage, especially in areas close to urban centers, major

roadways and agricultural areas. The goal of this study was

to evaluate the susceptibility to shallow landslides in the

Serra do Mar, specifically within a drainage basin affected

by such an event in January of 1985. For this purpose, the

mathematical modeling technique of SINMAP was used by

introducing the topographic values from a digital terrain

model as well as geotechnical and hydrological values

from previous studies performed in the Serra do Mar. In all,

32 susceptibility scenarios were generated, and three were

analyzed for this study. These scenarios were validated

using landslide scar maps produced using orthophotogra-

phy; this technique was also used to analyze the functions

of morphological parameters (e.g., slope angle, curvature

and hypsometric features). The basin was classified as

unstable, with landscape rates above 70 % for all three of

the scenarios chosen. A higher landscape frequency was

expected on straight slopes with angles between 30� and

50� under unsaturated soil conditions, as evidenced by low

moisture rates, especially for N–S-facing slopes. The sus-

ceptibility maps generated using this model should prove

useful for other critical parts of the Serra do Mar to

understand better and, above all, predict these landslides,

which annually cause significant damage in Brazil.

Keywords Serra do Mar � Shallow landslides � Digital

terrain model � SINMAP

Introduction

In Brazil between 1928 and 2011, more than 4,000 deaths

occurred because of mass movements. In addition to large

urban centers, such as Rio de Janeiro, Sao Paulo, Recife,

and Salvador, the Serra do Mar mountain range, a fault

scarp that extends 1,500 km along the south and southeast

coast of Brazil and passes through the states of Rio de

Janeiro, Sao Paulo, Parana and Santa Catarina, is often

affected by events of great magnitude. Geological, geo-

technical, and geomorphological characteristics, such as

steep slopes and soil with important hydrological discon-

tinuities and sandy textures along with total rainfall that

can reach up to 4,500 mm/year in some regions, make the

Serra do Mar extremely susceptible to different types of

mass-wasting, especially shallow landslides and debris

flow. For example, in 2010 and 2011, this geological-

geomorphic compartment suffered two major mass move-

ments that together resulted in over 1,200 deaths in the

Serra do Mar region of Rio de Janeiro State (Fig. 1).

Despite being considered an area of high susceptibility,

the Serra do Mar is occupied by various anthropogenic

structures along almost its entire extension, particularly

urban districts, creating numerous risk areas. Given this

scenario, geological, geotechnical and geomorphological

T. D. Nery

National Early Warning and Monitoring Center for Natural

Disasters, Cachoeira Paulista, Brazil

e-mail: tulius.nery@cemaden.gov.br; tuliusdias@usp.br

T. D. Nery

Graduate Program in Physical Geography, University of Sao

Paulo, Sao Paulo, Brazil

B. C. Vieira (&)

Department of Geography, University of Sao Paulo, Prof. Lineu

Prestes Avenue, 338, Cidade Universitaria, Sao Paulo, Brazil

e-mail: biancacv@usp.br

123

Bull Eng Geol Environ

DOI 10.1007/s10064-014-0622-8

studies have been systematically developed since the 1960s

(e.g., Costa Nunes 1969; De Ploey and Cruz 1979; Vargas

et al. 1986; Wolle and Hachich 1989; Lacerda 2007).

Various methods are currently used for the prediction in

space and time of shallow landslides. Among them, phys-

ically based models present many advantages associated

with the physical description of these processes from

mathematical equations. Examples of these models include

the SHALSTAB model (Montgomery and Dietrich 1994),

the dSLAM model (Wu and Sidle 1995), the Stability

Index Mapping, or SINMAP, model (Pack et al. 1998) and

the TRIGRS model (Baum et al. 2002; Bogaart and Troch

2006). However, for Brazil and especially for the Serra do

Mar, the literature still contains few studies using mathe-

matical models to assess the susceptibility to landslides or

considering these models as a tool for use by public

agencies to minimize or even prevent the occupation of

these high-risk areas. Thus, physically based mathematical

models have the potential to reduce the costs of identifying

unstable areas and to improve our understanding of hill

slope failure mechanisms in the Serra do Mar, where there

are few field investigations and extremely difficult areas to

access because of its steep slopes and dense tropical rain-

forest cover.

The scant literature that does exist for Brazil regarding

such applications of these models includes a study by

Guimaraes et al. (2003), who were the first to use a

mathematical model (the SHALSTAB model) to define the

areas of high landslide susceptibility in Rio de Janeiro City.

Listo and Vieira (2012) also used such a model to identify

highly susceptible urban regions, many of which had

already been mapped as high-risk landslide areas. Lopes

et al. (2007), studying the Serra do Mar in the state of Sao

Paulo, used a regional scale and SINMAP along with a

debris flow method to simulate the susceptibility to shallow

landslides and the potential for the transformation of debris

flow from different rainfall events. Similarly, Gomes et al.

(2008) used SHALSTAB to predict shallow landslides and

Fig. 1 General mass-wasting

that occurred in the Serra do

Mar in 2010 (a) and 2011 (b) in

Rio de Janeiro State

(photographs by Bianca

Carvalho Vieira (a) and Nelson

Ferreira Fernandes (b))

T. D. Nery, B. C. Vieira

123

FLO-2D, another mathematical model, to study the debris

flow within two basins located in the coastal ranges of the

city of Rio de Janeiro. Vieira et al. (2010) used TRIGRS to

evaluate the susceptibility of the area to shallow landslides.

Considering its advantages for the prediction of shallow

landslides in steep areas during intense rainfall events, the

objective of this study was to evaluate the susceptibility to

landslides in the Serra do Mar using the SINMAP model.

This research is important because even with the hundreds

of landslides and the great number of deaths every year,

there are few studies using these models to prediction

shallow landslides.

Study area

For this study, the Ultrafertil drainage basin was selected.

This basin is located on a stretch of the Serra do Mar in the

state of Sao Paulo (Fig. 2) and has an area of 2.5 km2 with

altimetric slopes up to 1,000 m, angles between 30� and

40� and a predominance of convex and rectilinear slopes

facing mainly E-SE. This area of the Serra do Mar is

supported by Precambrian metamorphic and igneous rocks,

migmatite, mica schists, gneisses, and granites that

regionally present extremely well-defined structural fea-

tures and a primarily NE-SW orientation.

Fig. 2 Location of the Ultrafertil basin in the Serra do Mar fault scarp in Sao Paulo

Susceptibility to shallow landslides

123

The average rainfall for this stretch of the Serra do Mar

exceeds 3,300 mm/year and occasionally reaches

4,500 mm, with the highest totals between October and

March. The most intense rainfall in the Serra do Mar is

usually caused by an interaction between cold fronts

coming from the Antarctic polar region and the warm

tropical air masses along the Brazilian coast. Furthermore,

the rainfall varies spatially with topographical features that

increase toward the edge of the plateau, and the highest

total rainfall occurs in the higher mountains of the Serra do

Mar.

The event studied here occurred between January 22 and

23, 1985, with precipitation of approximately 380 mm in

48 h. Landslides were recorded in several basins, including

the Ultrafertil basin, in which 1,742 landslides were reg-

istered (Fig. 3) according to Lopes et al. (2007). The

material washed downhill into the main rivers and caused

the formation of debris flows and the flooding of extensive,

low-lying areas that were occupied by residential structures

and industrial units. The latter land use occurs in the

industrial park of Cubatao, which currently contains

approximately 23 industrial units. During this same event,

an industrial pipe containing ammonia ruptured, causing

serious environmental and social damage to the region.

Many of the 1985 landslides occurred in the dense,

preserved areas of the Atlantic forest (Mata Atlantica),

which contains tall species with broad leaves, a quite

complex floristic composition, and degraded vegetation

because of the pollutants emitted for years by the regional

petrochemical industries, especially during the 1970s.

In the Serra do Mar, the surface layers are 1–2 m thick

and have a loamy sand texture; a lower layer that is 3–4 m

thick consists of saprolitic soil with a sandy texture. On the

mountain slopes located in the lower and middle parts of

the Serra do Mar range, the ruptures occur more frequently

at the junction between the colluvium/talus and the residual

material (Lacerda 2007). On the steeper slopes, thinner

layers are in direct contact with the rock, promoting a

parallel flow in most cases, which increases the positive

pressure of the soil water and consequently causes rupture.

However, according to Lacerda (2007), most of the shallow

landslides occur because of the loss of suction resulting

from the increased hydraulic conductivity with depth,

which is promoted by the presence of interconnected

fractures that increase the percolation of rainwater from the

surface to the weathered rock.

Materials and methods

Morphological parameters and mapping of landslide

scars

The morphological parameters (slope angle, aspect, cur-

vature and hypsometric features) were derived from a

digital terrain model with a resolution of 2 m2 that was

built from topographic maps (1:10,000 scale).

To map the scars from the landslides that occurred in

1985, aerial orthophotos at a 1:25,000 scale were obtained

from the National Institute of Space Research (INPE). Two

types of landslide representation were used in this research:

a point-shaped one was used to assist in the validation of

the SINMAP mathematical model, and a polygon-shaped

one was used to assist in the correlation of the scars with

the topographic parameters. In this latter case, the scars

were identified based on a visual analysis of the features,

adopting the following criteria: scar geometry, absence of

vegetation, position on the slope, contour lines and texture

analysis. To evaluate the role of the morphological

parameters, a correlation analyses between the maps of the

Fig. 3 a Mass movements along a stretch of the Serra do Mar in the

state of Sao Paulo that occurred during and after intense rainfall in

January 1985 (sourced from the Institute for Technological Research

of the State of Sao Paulo). b Industrial park that is located in the

foothills of the Serra do Mar and often affected by materials

descending the slopes and disrupting local activities (photograph by

Marcelo F. Gramani)

T. D. Nery, B. C. Vieira

123

slope angles, aspects, curvatures and hypsometric features

and the map of the scars using the number of cells affected

by landslides was performed, as proposed by Gao and

Maro (2009).

Use of the SINMAP model

The model developed by Pack et al. (1998) is based on the

combination of a stability model and a hydrological model

used to define a stability index (SI) (Eq. 1), which is

defined as the probability of a stable slope, assuming a

uniform distribution of the parameters on the uncertainty

margins; this index ranges from 0 (unstable) to 1 (stable).

SI ¼C þ cosh 1 � min R a

Tsinh ; 1� �

r� �

tanu

sinhð1Þ

The variable ‘‘a’’ is the specific catchment area (m2/m).

‘‘C’’ is the dimensionless cohesion of the soil and tree roots

combined (N/m2), h is the angle of the slope (�), and U is

the angle of internal friction (�). The water/soil density

ratio is represented by ‘‘r’’, and R/T is the water recharge

divided by the soil transmissivity (m2/h). These last four

parameters are manually input into the model. A value of 1

indicates that any excess above this limit is assigned to one

flow over the soil surface.

Rainfall data were obtained from a pluviometric post

that collected data every 5 min for the Department of

Water and Energy of the state of Sao Paulo (Departamento

de Aguas e Energia Eletrica do Estado de Sao Paulo—

DAEE) and served as the input parameter for the variable R

(constant recharge) in the calculation of the T/R ratio.

Therefore, in the present study, actual data from January 22

and 23 were used and were separated into three intervals of

6 h each: (1) 0.0000032 m/s; (2) 0.00001 m/s and (3)

0.000036 m/s.

The geotechnical and hydrological data that compose

the cohesion variables (cr and cs) (Table 1) and transmis-

sivity (T) of the model were taken from work previously

performed at the Serra do Mar by Wolle and Carvalho

(1994), Amaral (2007), and Mendes (2008). For the

hydraulic conductivity, the simulations were based on the

values collected in situ by Wolle and Hachich (1989),

assuming only one value for the transmissivity

(T = 1.3 9 10-5 m2/s). These data were obtained in situ

and after testing in the laboratory to evaluate the infiltration

dynamics within the soil and their role in the occurrence of

shallow landslides in the Serra do Mar.

From the information in Table 1 and the values

obtained from the T/R ratio, 32 simulations were per-

formed, changing each parameter relative to the thickness

of the soil (1, 1.5, and 3.5 m) in an attempt to find a

better correlation between the areas of greater suscepti-

bility and the scar map, and thus facilitate an under-

standing of the physical and hydrological disruptions in

the Serra do Mar based on the structure model. This

article presents the top three scenarios. For each scenario,

there was variation in the parameters of cohesion, density,

soil thickness, and the T/R ratio: scenario 1 (1 m thick

soil), scenario 2 (1.5 m thick soil), and scenario 3 (3.5 m

thick soil) (Table 2).

Table 1 Geotechnical parameters of the different instrumented areas of the Serra do Mar

Local/authors Slo. (�) Lit. Solo Textura Thick.

(m)

cd

(KN/m3)

c

(KPa)

U(�)

cw

(KN/m3)

c

(KPa)

U(�)

Study area/parameters

Cubatao (SP)

(Wolle and

Carvalho 1994)

40 Migmatites Superficial Sand-clay 1 14.3 6.0 34 17.1 1.0 34

Saprolite Sand-or Silt 1 a 2 18.0 12.0 45 19.5 4.0 39

43 Superficial Clay-sand 1 16.5 9.5 40 18.2 1.0 36

Saprolite Sand or Silt 1 a 2 18.5 11.0 45 20.1 3.5 39

Ubatuba (SP)

(Mendes

2008)

*10 Migmatites Saprolite Sand-silt 14 NI NI NI 28.2 13.0 31.4

Residual Sand-silt–clay 1 NI NI NI 27.8 9.5 32.9

*15 Charmockies Residual Sand-clay 1 NI NI NI 27.1 10.0 31.6

Saprolite Sand-clay-silt 7 a 8 NI NI NI 27.6 7.0 40.4

Costa Verde

(RJ) (Amaral

Junior 2007)

SI Biotite Gneiss Residual mature Sand-silt–clay 0.1 a 20 13.32 14.5 37 15.56 8.0 32

Residual young Sand-silt 0.2 a 8 14.85 17.5 41 16.98 4.5 42

Saprolite Sand-silt NI 12.5 26.5 32 14.9 10.0 32

Migmatites Residual mature Sand-silt 0.8 a 7 12.72 6.5 42 13.27 5.5 39

Residual young Sand-silt–clay 0.5 a 3 11.03 6.5 45 13.45 1.0 42

Saprolite Sand-silt 0.8 a 30 12.42 12.0 34 13.33 9.0 32

Legend: NI no information, Slo slope, Lit lithology, Thick Thickness, cd dry unit weights, cw wet unit weights, c cohesion, U angle of internal

friction

Susceptibility to shallow landslides

123

Results and discussion

A total of 216 landslide scars from the 1985 event were

mapped in the basin, with a total area of 108,420 m2 and a

sediment volume of approximately 135,525 m3. The shal-

low landslides were sparse and widespread in the basin,

ranging from the gentler slopes closer to the industrial park

to the highest parts of the mountain range and the drainage

divides.

Analysis of morphological parameters

The convex and rectilinear slopes with angles between 30�and 50� were more susceptible to shallow landslides

(Fig. 4a), confirming the results obtained in the Serra do

Mar by other authors, such as De Ploey and Cruz (1979),

Wolle and Hachich (1989), and Vieira et al. (2010).

The greatest concentration of landslides on the convex

slopes can be explained in terms of the differentiated

hydrological behavior of these slopes: the convex mor-

phology allows for material accumulation, leading to lower

shear resistance. In fact, compared with other slope con-

figurations, these convex slopes require more rain to

increase the saturation level and reduce the stability forces

(Reneau and Dietrich 1987). It is believed that the accu-

mulation of 380 mm of precipitation in 48 h may have

favored the generalized occurrence of these processes

along these slopes.

The rectilinear and convex slopes facing W-SW had the

greatest number of landslides (Fig. 4b). The interference of

the slope aspect with the distribution of solar radiation and

rain (Gao and Maro 2009) may explain the occurrence of

various types of processes according to different moisture

levels (Bogaart and Troch 2006). That is, the highest

concentration of these processes on the W-SW slopes can

be associated with a lower loss of moisture that, in addition

to increased weathering activity (Churchill 1982) and a

greater deposition of materials, increases the volume of

water inside the alteration mantle. The explanation for a

significant occurrence of landslides on the E-facing slopes

(Fig. 4b) might include the presence of areas of conver-

gence and divergence of flow above the breaking point,

such as ephemeral channels that can generate saturation

zones above the landslide scar (O’Loughlin 1986).

Fig. 4 Histograms of the morphological parameters. The landslides

occurred on convex and rectilinear slopes with angles greater than 30�(a), with a westward orientation (b), and with altimetric elevations

between 200 and 600 m (c)

Table 2 Values of the physical and hydrological properties used to

simulate the scenarios for the basin

Scenarios 35� S1 S2 S

T/R [m/hr]

Min 46 68 159

Max 142 213 497

Cohesion

Min 0.07 0.06 0.15

Max 0.96 0.83 0.43

Friction angle—U (�)

Min 34 34 34

Max 39 39 39

Soil density (kg/m3) 1,710 1,350 1,330

Water density (kg/m3) 1,000 1,000 1,000

AS plot 1,000 1,000 1,000

Wetness (%) 20 20 20

Legend: T transmissivity, R constant recharge, S Scenarios

T. D. Nery, B. C. Vieira

123

Regarding hypsometric features (Fig. 4c), the landslides

were concentrated mostly between the altimetric elevations of

200 and 600 m on slopes with angles between 30� and 50� in

the areas of intermediate relief, as was also observed by

Gritzner et al. (2001). This higher concentration can be

associated with the development of a weathering mantle

covered by materials transported by rain that consequently

changed the hydrological flow inside these materials, resulting

in rupture (Dai and Lee 2002). Nevertheless, the high occur-

rence may instead be associated with the distribution of the

rainfall intensity along the landmass profile, which increased

in the direction of the plateau, where there was an increase in

the precipitation rate that could increase the soil moisture and

consequently reduce the stability forces in these slopes.

Stability index

The model predicted that 90 % of the landslides would

occur at sites classified as having predictive, unstable

conditions (Fig. 5). The results showed that in all three of

the scenarios, the classes of predictive unstable conditions

(lower threshold, upper threshold, and defended) had the

highest areal rates, thereby conferring a high susceptibility

to shallow landslides under conditions similar to those that

occurred in 1985 (Fig. 6).

The lower and upper threshold limits encompassed more

than 66 % of the basin, characterizing the basin as a region

with a high probability of landslides. Of the 216 recorded

landslides, the greatest number occurred in areas with

lower thresholds and rectilinear slopes.

The lower threshold class encompassed the highest

percentage of the area ([40 % for all three of the scenar-

ios) and the most landslides; however, the highest density

of landslides was associated with the upper threshold class

for all three of the scenarios. This trend was also observed

by Meisina and Scarabelli (2007) and Lopes et al. (2007),

who used the SINMAP model, and by Fernandes et al.

(2004), who used the similar SHALSTAB model. These

Fig. 5 Susceptibility maps for scenarios 1, 2 and 3

Susceptibility to shallow landslides

123

areas are mostly associated with slopes greater than 30�,

which are represented by the middle and upper slopes of

the basin, as shown in the morphological parameter ana-

lysis with the different geotechnical materials that exhibit

different behaviors.

Conversely, the classes with predicted stable conditions

(stable, moderately stable, and quasi-stable) accounted for

less than 30 % of the total area. This value was lower than

that found by Pack et al. (1998) and Yilmaz and Keskin

(2009), who reported values of 66 % and 88 %, respec-

tively. Although they experienced few landslides, these

classes showed high levels of instability for slopes between

0� and 30�.

The highest percentage (6.5 %) of landslides in the

predicted stable classes was observed in scenario 3. Most

of these disturbances occurred on slopes predisposed to

rupture, but due to the characteristics of the model cali-

bration, scenario 3 had the lowest probability of landslides.

Figure 7 illustrates the relationship among the landslide

points, the areas of contribution and the angles of the

slopes. The stability index lines define the boundaries of

the regions included in this relationship (slope angle and

area of contribution), revealing the landslide points that

have potential stability and instability values.

For the slope angle, the landslides occurred between 20�and 50�, confirming the values found by other authors (e.g.,

Pack et al. 1998; Lopes et al. 2007; Terhorst and Kreja

2009). For the contribution area, the greatest number of

landslides occurred under unsaturated conditions, similar to

the results found by Terhorst and Kreja (2009) in the

Swabian Alb region of Germany. However, in a region of

Hawaii, Deb and El-Kadi (2009) observed that the greatest

number of landslides occurred under saturated conditions.

According to Wolle and Hachich (1989), the main rupture

mechanisms in the Serra do Mar (Sao Paulo) are the loss of

soil suction and the decrease in apparent cohesion within

unsaturated soils. In the thick soils of the tropics, an

increased saturated hydraulic conductivity with depth may

establish a vertical downward flow.

The most sensitive parameter of this model was the T/R

ratio. Other authors, such as Meisina and Scarabelli (2007),

observed that cohesion played a more significant role

regarding the percentage of stable and unstable areas. Con-

versely, Zaitchik et al. (2003) concluded that hydraulic

conductivity and friction angle were the most sensitive

parameters during the calibration of the model and that these

parameters were responsible for the susceptibility values.

Conclusions

The SINMAP model showed satisfactory results, predicting

approximately 90 % of the landslides that occurred in

January 1985, even though the geotechnical values of the

soil collected in the basin were not used in this study.

Therefore, this model, or even a similar one, is believed to

have great value for predicting shallow landslides in the

Serra do Mar, which is often affected by these processes,

annually causing numerous fatalities and substantial social

and environmental damage.

Because of the mathematical structure of the SINMAP

model and the generation for different scenarios of sus-

ceptibility maps that were validated using the scar maps of

the shallow landslides from 1985, it was possible to iden-

tify certain of the most important parameters in the initi-

ation of these types of disturbances in the Serra do Mar.

Fig. 6 Histograms showing the areal percentage and the number of

landslides (bold square) for each stability index class. The lower

threshold class presented the highest percentage of area in all of the

scenarios. In scenario 3 (soil depth of 3.5 m), landslides were

identified in areas with a low probability of such occurrences. St

stable, MS moderately stable, QS quasi-stable, LT lower threshold, UT

upper threshold, Unst unstable

T. D. Nery, B. C. Vieira

123

Currently, other mathematical models based on physical

information are being used in the Serra do Mar. In future

studies, in addition to using these models, we intend to collect

geotechnical and hydrological parameters, especially those

that are sensitive for determining the percentage of unstable

areas, to improve the accuracy of the susceptibility maps.

Fig. 7 Slope area (SA) plots for

scenarios 1 (a), 2 (b), and 3

(c) illustrating the relationship

among the landslide point,

catchment area and slope angle.

The stability index lines define

the boundaries of the regions.

For scenarios 1 and 2, the

landslides were concentrated

starting at a slope angle of 20�,

and for scenario 3, the

landslides were concentrated at

30�. In all of the scenarios, the

landslides occurred in

unsaturated areas, and the areas

with lower thresholds were

more susceptible and

experienced more landslides

Susceptibility to shallow landslides

123

Acknowledgments The authors acknowledge the support of the Sao

Paulo Research Foundation (Fundacao de Amparo a Pesquisa do

Estado de Sao Paulo—FAPESP) for the development of this study

and the granting of a Master’s thesis. The authors also thank Eymar

Silva Sampaio Lopes, Paulina Setti Riedel, Antonio Carlos Colan-

gelo, Emerson Galvani, and all of the members of the research group

for their contributions and scientific discussions. This manuscript was

significantly improved by the contributions made by anonymous

reviewers.

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