International Journal of Geosciences, 2013, 4, 30-38 Published Online September 2013 (
Copyright © 2013 SciRes. IJG
Extreme Events Assessment Methodology Coupling Debris
Flow, Flooding and Tidal Levels in the Coastal Floodplain
of the São Paulo North Coast (Brazil)
Rafael de Oliveira Sakai1, Diego Lourenço Cart acho1, Emilia Arasaki1,2, Paolo Alfredini1,
Alessandro Pezzoli3, Wilson Cabral de Sousa Júnior4, Maurizio Rosso3, Luca Magni5
1Polytechnic School of São Paulo University, Department of Hydraulic and Environmental Engineering, Harbour
and Coastal Area of the Hydraulic Laboratory, Avenida Professor Luciano Gualberto, Travessa 3, n. 380, Cidade
Universitaria, São Paulo, Brazil
2National Institute of for Space Research, Av. Dos Astronautas n. 1758, São José dos Campos, São Paulo, Brazil
3Polytechnic of Torino, Engineering Faculty, Department of Environment, Land and Infrastructure Engineering,
Corso Duca degli Abruzzi n. 24, Torino, Italy
4Technological Institute of Aeronautics, Infrastructure Engineering Division, Department of Hydric Resources and
Environmental Sanitation, Praça Marechal Eduardo Gomes n. 50, ITA-IEI,
São José dos Campos, São Paulo, Brazil
5Studio Rosso Ingegneri Associati s.r.l., Corso Principe Oddone, Torino, Italy
Email:,,,,,,, magni@sr
Received June 2013
The North Coastal Region of the State of São Paulo, which comprises the Municipalities of Caraguatatuba, São Sebas-
tião, Ilhabela and Ubatuba, is one of the most prone to flooding and debris flow deposition Brazilian areas, owing to
hydrological extreme rainfall events usually coup led with extreme tidal levels. This risk is also high due to human lives
and material assets, with incr easing population rates and the establishment of large companies such as the Oil industry,
with reduced defense/prevention measures and works. The catastrophic scenario of the city of Caraguatatuba, in March
1967, resulting from one of the most serious natural disasters in Brazil, fosters discussions about probabilities of heavy
rainfall-caused events and rise in the sea level in coastal areas. Hence, this research is a consequence of this reality. The
research is founded on an innovative methodology based on the analysis of past data of rainfall and tidal stations, com-
plemented with debris flow registers in the region of the nor th coastal zone of the State of São Paulo (Brazil). The anay-
sis developed involved the meteorological, hydraulic, geotechnical and statistical knowledge areas. Practical results are
intended to be used for urban planning, designs of macro-drainage, fluvial, maritime projects and debris flow retention
structures. These practical applications will then associate the probability of occurrence of certain types of heavy rai n-
fall-caused events such as flooding or debris flow coupled with a corresponding increase in tidal levels.
Keywords: Meteorology; Hydrology; Maritime Hydraulics; Rainfall; Tidal Levels; Extreme Events; Natural Disasters;
Geomorphology; Debris-Flow; Flooding
1. Introduction
This research is inserted into an area of Civil Engineering,
in the interface between Maritime Hydraulics (tidal le-
vels and hyperconcentrated flows), Hydrology (rainfall)
and Geotechnics (percolation and landslides).
Our main objective was to evaluate heavy rainfall-
caused events combined with tidal levels, and to obtain
practical results applicable to urban planning fluvial and
maritime projects and debris flow retention structures in
the Santo Antonio River Basin (Figure 1), located in the
city of Caraguatatuba, on the North Coast of São Paulo
Coastal areas are subject to severe sea action and pre-
cipitation. The north coastal region of São Paulo is
known for its orographic rainfall, caused by moisture
fronts from the Atlantic Ocean; when they collide with
the mountain range of Serra do Mar, there is a precipita-
tion on the coastal towns. There is a great demand for
studies on the subject, mainly with historical o ccurrences
of disasters in the last century. A ccording to Brigatti and
Sant’Anna Neto [1], the Northern Coast of São Paulo, for
its own natural characteristics and the recent economic
dynamics, is characterized as an area where studies
Copyright © 2013 SciRes. IJG
aimed at better understanding the natural and anthropo-
genic factors are developed, and are extremely important.
For illustrating the magnitude of the 1967 disaster, im-
ages of Caraguatatuba were collected right after the de-
bris flow (Figure 2(a), Figure 2(b), Figure 2(c)). Figure
2(d) shows the city of Caraguatatuba in 2012 (Santo
Antônio River basin), with a population of approximately
100,000 inhabitants. It is no torious that a similar even t to
that of 19 6 7 would cause significant dam ages.
Some consequences of this particular event were:
7.56 million ton of mobilized material;
436 casualties registered, 400 buildings destroyed,
3,000 displaced peo ple among 15,000 inhabitant s ;
4 m t o 5 m high block deposits were formed along the
Santo Antonio River. The larger boulders weighted
between 30 t and 100 t;
widening of the Santo Antonio River: from 10 m to
20 m to 60 m to 80 m in some areas.
As well known, the study of the joint effect between
the tide and the rainfall flooding and debris-flow effect is
one of the most important areas of the knowledge to be
developed in the research community in the new century
Figure 1. Municipalities of the North Coastal Region of São
Paulo State (Brazil).
Figure 2. Aerial photographs of the Santo Antônio river at
different times. (a) scars on mountains after the 1967 rains-
torm; (b) bridge over the Santo Antônio river destroyed by
the debris-fl ow in 1967; (c) Santo Antônio river mouth after
the 1967 rainstorm (five times greater than usual); (d) San-
to Antônio river mouth in 2012.
However most of these analyses were conducted using
numerical modeling and neglecting a detailed statistical
analysis between rainfall effects and tide recorded data
In this study, we developed a multivariate probability
model to study joint risk probability and focusing on the
area of the Sao Paulo North Coast where we currently
find a lack of study and analysis.
This study fits this regional context, and we intend to
provide consistent analyses of historical data of tidal le-
vels and t he ra infall ef fe c ts of flooding and de bri s f l ow.
2. Methods
Given the evident extreme rainfall events such as flood-
ing and debris flows and random sea level behavior, the
discussion on whether there is an interdependence of
these variables and, especially, how they have been de-
veloping face to climate change was fostered.
The methodology described in this item was adapted
from HIDROCONSULT [6], which conducted a similar
study for Cubatão city, which is located in the central
coast of the State of São Paulo.
The methodology adopted was founded as follows:
collection, processing and data validation of tidal le-
vels for the North Coast region of the State of São
collection and processing of rainfall data for the re-
gion of the North Coast of the State of São Paulo;
understanding, development and application of statis-
tical methodology, combined occurrence of rain-tide
for the Caraguatatuba region;
obtaining graphs and tables of probabilities of the
occurrence of certain phenomena involving rainfall
and tides.
Allied to this relationship between both variables
(rainfall and tide level), the debris flow and flooding stu-
dies related to the extreme rainfall events were carried
In this case, the methodology was organized as fol-
collection, processing and data validation of topo-
graphic, geotechnical, rainfall and urban occupation
inputting this data in a digital model (capable of si-
mulating debris flow and flooding);
calibrating and validating the input informatio n based
on the real event which happened in March 1967;
obtaining affected area of debris flow and flooding,
and also their physical parameters such as flow speed
and deposition depth in order to aid future urban
planning and defense works. This analysis will also
be performed considering the tide level associated
with the rainfall event which may trigger these phe-
Copyright © 2013 SciRes. IJG
2.1. Getting the Database
The database was composed of two groups: tidal levels,
rainfall values and geographic data. The characteristics
of these values are explained below.
2.1.1. Tidal Data
The tidal level data come from different sources from
different institutions, as describe d:
IGC tidal station (Cartographic and Geographic In-
stitute) in Ubatuba;
IOUSP tidal station (Institute of Oceanography, USP-
University of São Paulo) in Ubatuba;
CTH tidal station (Hydraulic Technological Center)
on Martin de Sá Beach/Caraguatatuba;
São Sebastião Harbour tidal station;
Buoy of CEBIMar (Marine Biology Center, Univer-
sity of São Paulo) in São Se bastião.
The compilation of information from tidal stations
generated a large database from 1954 to 2005, with some
intermediate gaps. This database comprises over 225,000
hourly values of tidal levels.
2.1.2. Rainfall Data
The composition of the rainfall database in the city of
Caraguatatuba started with searches of data availability
in ANA (Agê ncia Nacional de Aguas) [7].
The E2-046 rainfall station (Caraguatatuba) contains
data from 1943 to 2010, totaling 24,603 daily values of
rainfall heights, and was thus considered in this research.
For the debris flow and flooding simulation, which are
events that require greater data resolution (minimum
hourly rate), the daily values provided by ANA are not
optimal. Hence, a statistical work was necessary in order
to achieve a reliable conversion between both resolu-
2.1.3. Geographic Data
Geographic data comprises topographic, urban occupa-
tion and geotechnical data.
Topographical plans from the Cartographic and Geo-
graphic Institute of the State of São Paulo (IGC-SP) at a
1:2000 scale were used to define the topography of the
lower region of the Santo Antônio basin, associated with
smaller scale maps obtained from Cruz [8] for its higher
The inhabited areas of the municipality were also
mapped in order to better associate the flow and flood-
ing-affected areas to the risks to the population.
Some geotechnical surveys were conducted along a
possible alignment for the escape tunnel from the Parai-
buna Dam, which is located in the highlands right above
Caraguatatuba Serra do Mar. Such surveys were con-
ducted from the higher points of the San Antônio River
basin and its lower ones, located in the Coastal Plain.
The Tables 1 and 2 show some of the soil layers depth
and main soil characteristics.
2.2. Analysis Between Rainfall and Tidal Data
2.2.1. Data Compilation
From the database of tides and rainfall heights, the first
procedure for applying the methodology was performed:
data compilation.
The tides and rainfall values were organized so as to
allow direct relationships between the daily rainfall in the
Santo Antonio River Basin, and its levels in the tidal st a-
tions of the Northern Coast of the State of São Paulo.
Table 3 illustrates how the data, for the month of Jan-
uary 1954, were compiled.
At the end of this step, 9.361 days had been recorded
with the relationship between rainfall and tides (High
tide; Low tide and Mean Sea Level).
2.2.2. Division of Database Into Rainfall Groups
This next step of the methodology divides the database
into groups, based on the accumulated daily rainfall: P
0 mm/day, P 25 mm/day, P 50 mm/day, P 75
mm/day, P 100 mm/da y.
Table 1. Soil layers thickne s s on oi l pipeline of Serra do Mar, Santo Antônio river basin
Residual/Culluvial Soil Depth
Region Bore Hole Elevation
(m) Bore Hole Elevation
Soil Layers (From Shallwer to Deeper)
Residual/Culluvial Soil Depth Slightly Decomposed Bedrock Thickness (m)
Oil Popeline
SP-1 25 8.2 0
SE-1 175.6 8 37.5
SE-16 233.8 9 6
SE-15 315.5 21.8 8.2
SE-13 454.8 10 47.5
SP-2 699.8 15.54 0
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Table 2. Soil layer s thickness on high lands and hills of Serra do Mar, Santo Antônio river basin.
Residual/Culluvial Soil Depth
Region Bore Hole Bore Hole Elevation (m)
Soil Layers (From Shallwer to Deeper)
Soil Depth Decomposed Bedrock
Thickness (m) Slightly Decomposed
Bedrock Thickness (m)
SP-540 718.07 4.5 0 10.3
SP-541 694.25 1.45 5 0
SP-537 767.76 23.9 17.1 10.8
SP-546 742.44 27.2 6.2 6
SP-567 717.52 78.75 4.85 0
SP-550 715.05 2.8 0 0
SP-571 764.36 38.85 0 35.5
SP-722 679.4 3 4.15 3.55
SP-707 708.44 4 51 0
SP-723 609.36 43.33 6.24 0
SP-724 496.36 10.55 0.82 2.42
CFO-1 387.25 14.1 1.9 0.5
SP-783 288.86 10 0 0
SP-782 125.01 30.7 24.3 0
SP-781 299.56 44 2.4 0
SP-780 171.84 4.6 3.9 0.6
Table 3. Example of compilation of daily tidal levels and daily rainfall heights, for the Santo Antônio Basin, in January 1954.
Date Data of tidal station (IBGE Reference) Rainfall (mm/day)
Low Tide (cm) Mean Sea Level (cm) High Tide (cm)
01/01/1954 74.83 26.96 15.17 0
02/01/1954 78.83 34.92 4.17 0
03/01/1954 62.83 13.13 20.17 16.7
04/01/1954 54.83 12.50 60.17 14.5
05/01/1954 85.83 8.54 45.17 7.9
06/01/1954 97.83 19.50 25.17 3.2
07/01/1954 75.83 16.92 25.17 4.2
08/01/1954 56.83 4.87 45.17 0
09/01/1954 57.83 3.83 29.17 0
10/01/1954 67.83 20.21 8.17 0
11/01/1954 64.83 19.54 4.17 0
12/01/1954 44.83 19.79 3.17 0
13/01/1954 34.83 11.83 27.17 0
14/01/1954 31.83 1.21 30.17 0
15/01/1954 59.83 11.08 35.17 0
16/01/1954 64.83 14.17 28.17 0
17/01/1954 71.83 15.29 28.17 0
18/01/1954 64.83 0.00 44.17 0
19/01/1954 77.83 6.67 38.17 1.2
20/01/1954 79.83 12.67 36.17 0
21/01/1954 62.83 8.13 41.17 3.3
22/01/1954 61.83 7.00 37.17 2.5
23/01/1954 61.83 9.92 36.17 0
24/01/1954 42.83 6.00 30.17 0
25/01/1954 39.83 14.67 13.17 0
26/01/1954 38.83 11.25 13.17 0
27/01/1954 26.83 7.08 11.17 0
28/01/1954 40.83 18.46 1.83 0
29/01/1954 51.83 21.83 2.17 0
30/01/1954 48.83 15.46 16.17 0
31/01/1954 57.83 6.38 36.17 0
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The division of the database into groups is an impor-
tant step in the process, because each rainfall track repre-
sents a probabilistic curve of occurrence of rain-tide phe-
nomenon, as demonstrated ahead.
2.2.3. Reorganization of Database, Parameterized by
Tidal Levels
The data were reorganized, after the separation into rain-
fall gro up s , following t he guideline s be l ow:
for each precipitation interval (it is convenient to sep-
arate them into different worksheets), the table was
rearranged in decreasing order, using tidal levels
(higher tides at the top of the table) as a parameter.
This methodology also has to be applied separately to
daily Low tides, daily Mean S ea Level and daily H igh
note that the rainfall values should always be kept
with the equivalences of daily tides;
for each precipitation interval, the major annual
events of tide (for Low tides, smaller annual events
should be chosen) should be selected, because the
Return Period (TR) will be calculated in years.
As a result of this step, there are several tables (one for
each precipitation interval), sorted from the highest to the
lowest tides (Minimum daily Low tides, Highest daily
Means Sea Levels and Highest daily High Tides) with
annual extreme values. It is worth observing that the
event (days) must be repeated at different intervals, for
instance, the same day with rains over 100 mm (P > 100
mm/day) rains over 75 mm (P > 75 mm/day).
2.2.4. C alc ul a t i on of Pro ba bi l i ty of Combined Events
(Rainfa l l Tidal Level)
At this stage, probabilities of occurrence of certain sea
level are calculated, associated with a rainfall range using
a Gumbel mixed-model as suggested by Yue et al. [9].
Table 4 illustrates this step. For each precipitation inter-
val, a different table was generated.
Table 4. Calculation of probability of combined events (P 0 mm/day and Mean Sea Level), for the Santo Antonio Basin.
Mean Sea Level (maximum Annual) IBGE Reference (cm) Day Rainfall (mm) Probabilities of occurrence P (%) Order Nu mber
52.00 30/05/1988 26.2 2.86% 1
49.79 07/07/1989 0 5.71% 2
49.28 22/06/1990 0 8.57% 3
48.93 31/07/1980 4.1 11.43% 4
47.79 15/08/1999 0 14.29% 5
45.33 10/05/1956 3.5 17.14% 6
45.11 13/05/1959 1.6 20.00% 7
44.44 20/02/1995 63.5 22.86% 8
44.42 10/02/1966 0 25.71% 9
43.96 23/11/1970 0 28.57% 10
42.56 11/03/1987 17.8 31.43% 11
42.52 11/06/1993 19.4 34.29% 12
41.13 17/07/2000 3.7 37.14% 13
40.66 17/06/1971 6 40.00% 14
40.59 19/12/1994 15.2 42.86% 15
40.20 07/01/1996 21.8 45.71% 16
39.87 12/02/1998 22.3 48.57% 17
39.43 05/07/1991 0 51.43% 18
37.85 16/07/1992 2.1 54.29% 19
37.52 05/05/1963 0 57.14% 20
36.75 22/05/1978 5.3 60.00% 21
36.57 07/04/1979 13.5 62.86% 22
35.69 10/06/1983 3.2 65.71% 23
35.48 09/12/1982 2.3 68.57% 24
34.93 30/09/1981 1.8 71.43% 25
34.28 26/05/1958 8.8 74.29% 26
33.35 29/07/1955 0 77.14% 27
33.04 15/04/1986 0.5 80.00% 28
32.24 13/12/1972 16.5 82.86% 29
31.37 04/07/1965 0.8 85.71% 30
30.32 26/03/1997 1.1 88.57% 31
30.22 30/03/1964 20.6 91.43% 32
29.62 11/05/1954 1 94.29% 33
12.76 22/12/1977 35.9 97.14% 34
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2.3. Debris-Flow and Flooding Analysis
2.3.1. T opographic D ata Treatment
Data transformation was made from the scanning of pa-
per-formatted documents to the AutoCAD program and
later tracing the contours of the images. For each of them
the elevation was defined, and the data is then exported
to the FLO-2D for subsequent simulation of the event as
suggested by Grimaldi et al. [10].
2.3.2. Rainfall Data Treatment
Different from the previously detailed data treatment
(Item 2.2), the rainfall event simulated here is not based
on a whole series, but only on thos e days which predicted
and culminated in the huge debris flow catastrophe of
March 18th 1967. The daily rainfall values used are
shown in the Table 5.
The processing of turning these daily-based values to
hourly-based data was carried by a CETESB/DNOS [11]
method, the transformation coefficients of which are
shown in the following table. These values are valid for
the State of São Paulo, where the Municipality of Cara-
guatatuba is located.
For the transformation, for example, in order to trans-
form a daily rainfall into an hourly value, it should be
multiplied by the factor 24 h/1 d and the 1 h/24 h factor
must be applied over the result of this operation.
Based on the values shown in Table 5, the conv ersion
factors shown in Table 6 and the qualitative description
of the event described in the literature, the hourly hyeto-
graph was created for the event, being the 0 hour miles-
tone the be ginning of 1 6th March 1967.
Table 5. Daily rainfall observed at three different points of
the Santo Antônio river basin in the week preceding the
disaster of March 18th, 1967.
Station Coordinates
Days of March 1967—Daily
Rainfall (mm)
12 13 14 15 16 17 18
Rio do
S 23˚38' 0.8 6.5 10.7 0.3 6.5 50.4 195.5
W 45˚26'
Caputera S 23˚37' 7.4 0.1 2.7 63.1 7.2 9.2 240.8
W 45˚26'
Fazenda Săo
S ? 10 0 50 0 20 115 420
W ?
Daily Average 13.425 72.4 319.075
Table 6. Conversion factors from daily rainfall values to
smaller time frames.
Relation 24 h/
1 d 12 h/
24 h 6 h/
24 h 1 h/
24 h 30 m/
1 h 15 m/
30 m 5 m/
30 m
Factor 1.14 0.85 0.72 0.42 0.74 0.4 0.34
2.3.3. Debri s Flow and Flooding Model i n g
In possession of sufficient data for modeling the terrain,
the computer program FLO-2D [11] will be used in order
to build, calibrate and validate a simulation model. The
model used in this program can simulate the spreading of
a water-sediment mixed flow on terrains of complex to-
pography and roughness, by following the principles of
conservation of mass and momentum. The model uses
dynamic equations from hydraulics and a finite mesh to
predict the progression of a system flow over a grid of
elements representing topography and buildings.
The input data from terrain topography and rainfall
was inserted and the other necessary input values were
calibrated based on the results of the model comparison
with what re a l ly happened on 18th March 1967.
This simulation was carried by Studio Rosso Ingegneri
Associati s.r.l.
3. Results and Discussion
Based in the methodology described in item 2.2, some
more relevant results from the rainfall and tide level rela-
tions were obtained. Figure 4 shows the graphical result
from the statistical analysis of the previou s item.
From this graph, Table 7 summarizes the main values
useful for both maritime and fluvial hydraulic projects in
the region.
For a macro drainage project, for example, a 50-year
Return Period is considered. By assuming this hypothesis,
it is necessary to adopt a Mean Se a L ev e l of 50.69 cm for
any daily rainfall (P > 0 mm/day). Note that for the same
Return Period (50 years) simultaneou sly with more rainy
days (P > 100 mm/day) a lower Mean Sea Level (40.59
cm) may be assumed; hence, an elevated sea level along
with heavy rain is less likely to occur. Another important
concept is, for example, days with the same rainfall cha-
racteristics (i.e.: P > 0 mm/day), as larger Return Periods
(less likely to occur) are selected, higher sea levels must
be adopted simultaneously.
Figure 3. Graph of hourly rainfall along the previously days
of the catastrophe.
010 20 30 40 50 60 70 80
Rainfall Intensity (mm/h)
Time, starting from the beginning of 16th March 1967 (h)
Hourly Precipitation (mm/h)
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Figure 4. Graph of probabilities (Rainfall × Mean Sea Level).
Table 7. Results applicable to engineering projects (Rainfall × Mean Sea Level).
Rainfall (mm/day) Return Period (TR)-Years
Mean Sea Level (cm)-IBGE Reference
2 5 10 20 50 75 100
>0 38.56 46.11 49.18 50.28 50.69 50.75 50.77
>25 25.74 37.86 43.82 45.75 46.27 46.30 46.31
>50 20.69 30.33 36.77 40.81 43.49 44.11 44.42
>75 14.89 25.62 33.54 39.13 43.13 44.08 44.57
>100 11.95 31.64 37.71 39.81 40.59 40.71 40.76
Complementing the tide level and rainfall analysis,
FLO-2D results were obtained for a defined rainfall input
data, the one described in item 2.3, for two situations:
debris flow and flooding events.
The areas affected were then defined for these situa-
tions and plotted on a map, in order to facilitate the un-
derstanding of the results.
By composing both the results presented in Figures 5,
6 and Table 7, the real catastrophic scenario of an event
of this size is fully characterized.
According to Briga tti and SantAnna Neto [1], regard-
ing the occurrence of floods, flooding and debris flow,
the north coast has unique characteristics, mainly pro-
vided by its physical aspects and land use. The occupa-
tion on the banks of rivers and their mouths, together
with a peculiar atmospheric dynamics and tidal fluctua-
tions, commonly cause serious socio-environmental
The interrelationship ocean-atmosphere-continent is
extremely complex and leads to an unc ertainty region . In
the specific case of the episodes related to floods, flood-
ing and debris flow, many aspects must be considered,
the meteorological factors (mainly related to the cold
fronts going through the region and the variations of
their elements, especially wind, rainfall and atmos-
pheric press ure);
the coastal dynamics (its relations with meteorologi-
cal events, currents and depositional processes that
directly influence the rates of discharge of rivers, be-
sides the tidal dynamics, notably related to spring
tides episodes);
P>0 mm/day
P>50 mm/day
P>100 mm/day
10 20 50
510 20 50
510 20 50
510 20 50
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Figure 5. Flood depth and affected areas.
Figure 6. Debris-flow depth and affected areas.
the land use and anthropogenic influences (change in
surface flow and absorption along the coast).
The North Coast region of the State of São Paulo is
located in an area with important atmospheric activities.
The mountains of Serra do Mar act as a barrier to the
atmospheric flow from the ocean and its presence gives
the region a complex configuration in relation to rainfall,
as noted by Conti [12], and the orographic effect greatly
participates in this dynamic [8].
From the climatic point of view, the element that most
stands out is the rain, with areas that have the highest
total rainfall in Brazil (with an annual average of over
4000 mm/year, 6000 mm/year reached in extreme years).
There is also the presence of rain shadow islands” pro-
vided mainly by the massive island of São Sebastião,
which affects the north of the São Sebastião channel and
the Caraguatatuba bay region. In these areas, total rain-
falls are low er ( around 18 00 mm/year). From the point of
view of the performance of atmospheric systems, the
region is dominated by tropical masses, but due to their
transitionality climate position, it presents constant fron-
tal systems (cold fronts), which, together with the mor-
phological and the Serra do Mar mountains, account for
the most extreme rainfall caused events [13].
These climatic characteristics, coupled with a strong
slope in its the relief, the small extension of the coastal
plain, the shapes of the basins of major rivers and the
ocean dynamics, characterize a fragility region, aggra-
vated by irrational occupation and the construction of
numerous roads, with the presence of irregularly occu-
pied areas and poor projects carried out in areas suscept-
ible to extreme episodes [14,15].
4. Conclusions
The coastal regions of Brazil have constantly suffered
with extreme events, for both, heavy rainfall, and sea
forces (wave s, tides, curre nt s).
The study of natural phenomena must begin with a
continuous collection of data. It is understood as essential
that any analysis be based on collection, storage and
processing of data of natural variables (tidal levels, rain-
fall heights, waves, currents, etc.), to allow treating the
phenomena statistically, linking them to the probabilities
of occurrence. This research is inserted in this initial
From statistical studies, the results can be applied to
Engineering practice. The coastal projects should con-
sider the lessons learned from past events, both with the
direct application of statistical analysis, and by using
mathematical models, such as input data for simulations
of natural events.
In recent decades, an Engineering advanced branch is
committed to discussing, from databases and mathemati-
Copyright © 2013 SciRes. IJG
cal models, whether the projects already built will be
affected by climate change, such as the increase of the
Mean Sea Level, more frequent heavy rainfall and debris
flow events that destroy cities in the coastal floodplain.
Therefore, repair works will become increasingly more
frequent in these regions.
5. Acknowledgements
This paper was suppor ted by Redelitor al, with the proj ect
described in [16], funded by CAPES (Coordination for
the Improvement of Higher Education Personnel). The
authors would also like to thank Promon Engenharia that
encourages its employees to participate in academic re-
search and Studio Rosso Ingegneri Associati s.r.l., which
provided support in the FLO-2D simulation.
[1] N. Brigatti and J. Sant´Anna Neto , “Dinâmica Climática e
Variações do Nível do mar na Geração de Enchentes,
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