REMOTE SENSING
EARTH SCIENCES
RESEARCH JOURNAL
Earth Sci. Res. J. Vol. 27, No. 1 (March, 2023): 59 - 68
Methodological proposal to remote detection and management of areas that are naturally
vulnerable to floods
Lucas Emanuel Servidoni1; Joaquim Ernesto Bernardes Ayer2; Guilherme Henrique Expedito Lense1; Felipe Gomes Rubira1; Velibor Spalevic3;
Branislav Dudic4; Ronaldo Luiz Mincato1*
1
Universidade Federal de Alfenas, Programa de Pós-Graduação em Ciências Ambientais, rua Gabriel Monteiro da Silva, Alfenas, Minas Gerais, Brasil.
https://orcid.org/0000-0003-1741-1706; https://orcid.org/0000-0002-3560-9241; https://orcid.org/0000-0002-6594-8228; https://orcid.org/0000-0001-8127-0325
2
Centro Universitário de Paulínia, Rua Nelson Prodócimo, 495, Jardim Bela Vista, 13145-026, Paulínia, São Paulo, Brasil. https://orcid.org/0000-0003-0612-0663
3
University of Montenegro, Podgorica, Montenegro. https://orcid.org/0000-0002-7800-2909
4
Comenius University, Faculty of Management, Odbojárov, 10, Bratislava, 82005, Slovakia. https://orcid.org/0000-0002-4647-6026
*Corresponding author: e-mail: ronaldo.mincato@unifal-mg.edu.br
ABSTRACT
Floods are the main natural disasters in Brazil, causing loss of life and socioeconomic damage. This work propo- Keywords: Geoprocessing, Natural Disasters,
ses a model for the remote detection of areas that are naturally flood-prone due to the morphometric characte- Remote Sensing, Environmental Risk.
ristics of their relief and drainage networks in the Alto Sapucaí River in Minas Gerais, Brazil. The morphometric
parameters used were the drainage density, river density, relief ratio, roughness index, maintenance coefficient,
form factor and stream surface length. The risk areas had a compactness coefficient of 0.75 and a form factor of
0.56, and both were considered a high risk for floods. The obtained results allowed the identification of a significant predictive equation that suggested a cutoff value of 3.82 for the discriminant function; areas with values
under this cutoff were considered naturally more vulnerable to floods occurrences. These areas were corroborated
with the emergency maps of the municipalities. The map obtained by the proposed model was compared with
the Civil Defense map, and its accuracy, according to the Kappa coefficient, was 0.83, indicating strong similarity
between the two maps.
Propuesta metodológica para la teledetección y gestión de zonas naturalmente vulnerables a las inundaciones
RESUMEN
Las inundaciones son las principales catástrofes naturales en Brasil; causan pérdidas de vidas humanas y daños
socioeconómicos. Este trabajo propone un modelo de detección remota de áreas naturalmente inundables debido a las características morfométricas del relieve y de la red de drenaje en el Alto Sapucaí, en Minas Gerais,
Brasil. Los parámetros morfométricos utilizados fueron la densidad de drenaje, la densidad del río, la relación
de relieve, el índice de rugosidad, el coeficiente de mantenimiento, el factor de forma y la longitud de la superficie del arroyo. Las zonas de riesgo tenían un coeficiente de compacidad de 0,75 y un factor de forma de 0,56,
y ambas se consideraban de alto riesgo de inundación. Los resultados obtenidos permitieron identificar una
ecuación predictiva significativa que sugería un valor de corte de 3,82 para la función discriminante; las zonas
con valores por debajo de este corte se consideraron naturalmente más vulnerables a la ocurrencia de inundaciones. Estas zonas fueron corroboradas por los mapas de emergencia de los municipios. El mapa obtenido por
el modelo propuesto se comparó con el mapa de la Defensa Civil, y su precisión, según el coeficiente Kappa, fue
de 0,83, lo que indica una gran similitud entre los dos mapas.
ISSN 1794-6190 e-ISSN 2339-3459
https://doi.org/10.15446/esrj.v27n1.103542
Palabras clave: Geoprocesamiento; Desastres
Naturales; Teledetección; Riesgo Ambiental.
Record
Manuscript received: 07/07/2022
Accepted for publication: 01/02/2023
How to cite item:
Servidoni, L. E., Bernardes, J. E., Expedito,
G. H., Gomes, R., F., Spalevic, V., Dudic, B.,
& Mincato, R. L. (2023). Methodological
proposal to remote detection and management
of areas that are naturally vulnerable to floods.
Earth Sciences Research Journal, 27(1), 59-68.
https://doi.org/10.15446/esrj.v27n1.103542
60
Lucas Servidoni; Joaquim Bernardes; Guilherme Expedito; Felipe Gomes; Velibor Spalevic; Branislav Dudic; Ronaldo Luiz Mincato
1. Introduction
One of the steps of natural disaster management is to assess environmental
behaviors, such as the influence of landforms on surface and subsurface water
runoff processes. Obtaining information about the dynamics of these landscape
elements enables decision-makers to mitigate and control risk (Arantes et al.,
2021; Mardhel et al., 2021; Tesema, 2021). In this context, prior knowledge of
morphometric landform characteristics and drainage networks allows for the
prevention and mitigation of events that are triggered by natural disasters and
for the precise and efficient allocation of resources for flood event warning and
preparation systems (Waghwala and Agnihotri, 2019; Bogo, 2020).
Floods are natural processes associated with mountain snowmelts, rapid
and intense rains, long-term rains, and extreme hydrometeorological events
such as hurricanes and tropical cyclones (Ward et al., 2020). Thus, despite being
natural events, the uncontrolled development in river plains increases the risks
and socioeconomic damages caused by floods, which, in general, result in loss
of life (Martin-Díaz et al., 2018; Cobbinah et al., 2022). Due to Brazil’s climate
and historically uncontrolled development of flood-prone areas (Fleischmann et
al., 2021), several millions reais are spent annually to combat the adverse effects
of flooding catastrophes (Bitencourt and Rocha, 2014).
The urbanization process imposed by capitalism in peripheral countries
such as Brazil occurred in an accelerated and disorderly way, following the intense
process of industrialization in the 1970s. This process promoted an intense rural
exodus causing a population explosion in urban centers. This migratory wave
could not be adequately absorbed in urban centers, forming clusters of precarious
housing and subjecting the low-income population to settle in areas at risk of
flooding (Fleischmann et al., 2021; Cobbinah et al., 2022).
However, flood risks have worsened due to uncontrolled land changes
associated with climate changes (Arantes et al., 2021); the deleterious effects
of this natural phenomenon are exacerbated by anthropogenic changes in
hydrosedimentological systems (Silva et al., 2018), which have intensified both
in volume and area, leading to an increase in the number of people affected and
displaced by flood events, mainly in urban areas (Molina and González, 2020;
Defesa Civil, 2020).
To assess and map floods, computational analysis of morphometric and
hydrological variables, remote sensing and geographic information systems
(GIS) are indispensable and widely used, due to the low cost of acquiring
images and even free of charge in specialized public agencies. These resources
can make land use management and agricultural and urban development
possible at low cost. They significantly contribute to the generation of strategic
information for coping with floods (Tamiru and Dinka, 2021). Such costs are
even lower than those necessary to carry out field surveys in large areas subject
to flooding in a country with continental dimensions such as Brazil.
In this scenario, geoprocessing and remote sensing techniques enable
preliminary and pilot studies for recognizing flood-prone areas and support land
use planning, development and management (Udin and Matin, 2021). These
techniques reduce the costs and efforts of mapping and disaster management
(Ardaya et al., 2017). In addition, identifying areas naturally vulnerable to
flooding favors the establishment of inspection, policing and control actions
appropriate to their socioeconomic and environmental realities (Ekmekcioglu et
al., 2022). Thus, the development of proposals to analyze and map flood-prone
areas based on the morphometric characteristics of their drainage networks and
landforms is a necessary response to climate change, which increasingly causes
extreme climatic events to occur (Kuntamalla et al., 2018; Lin and Billa, 2021).
This research aims to develop a methodological proposal for remote
detection and management of areas naturally vulnerable to flooding, based on
morphometric and hydrological parameters of hydrographic basins.
2. Materials and methods
The study area comprises 170 hydrographic subbasins of the Alto
Sapucaí (Figure 1), a tributary of the Rio Grande Hydrographic Basin, which
has a volume of 2,813 km2 and an average flow of 146 m3s-1. A main source
of water for the Furnas Hydroelectric Power Plant Reservoir, the Alto Sapucaí
river in southern Minas Gerais is also important for locomotion, fishing,
irrigation, and hydroelectric energy production (Galvão and Bermann, 2015).
However, surrounding municipalities, such as Itajubá, Piranguinho, Santa Rita
do Sapucaí, Piranguçu, and Delfin Moreira, recurrently suffer from floods due
to their history of uncontrolled development (Martins et al., 2019).
The local geomorphology is dominated by denudational units of
crystalline or sedimentary rocks, with an altitude between 816 and 1,482 m. The
geological framework of the area is composed of granite-gneissic complexes
from the Orogenic System of Tocantins (CPRM, 1998; Hasui, 2010). In the
area, red and red yellow Argisols predominate and, secondarily, red Latosols,
Haplic Cambisols and Neosols (Santos et al., 2018). Regarding the hydrography,
the drainage pattern is dendritic, with 1st- and 2nd-order channels with NNESSW orientations and 3rd-, 4th- and 5th-order channels with NE-SW directions
(Ribeiro et al., 2016).
Figure 1. Location map of the Alto Sapucaí hydrographic basin, southern of Minas
Gerais, Brazil.
The climate, according to Köppen’s classification, is tropical in altitude
(Cwa and Cwe), with hot and humid summers and cold and dry winters and
average annual precipitation of 1.600 to 1.865 mm (Aquino et al., 2012). In
southern Minas Gerais, December and January have the highest precipitation
values of 253 and 245 mm, respectively (Martins et al., 2019), with preferential
maximums leeward of Serra da Mantiqueira, which illustrates the orographic
performance in the distribution of precipitation (Campos et al., 2016; Ávila et
al., 2009). The dominant morphoclimatic domain is the Atlantic Forest, with
the seasonal semideciduous forest replaced mainly by pastures and agriculture
(Scolforo et al., 2008).
From the ArcHydro analysis module, 170 hydrographic subbasins were
delimited as representative sampling units of the study area. Subsequently,
the drainage hierarchy was defined according to Strahler (1957). Finally, the
morphometric parameters of the Alto Sapucaí watershed were calculated using
the Shuttle Radar Topography Mission 2 (SRTM 2) digital elevation model
(DEM) with a vertical resolution of 30 m (USGS, 2014), which agrees with the
scale criteria adopted by Gupta et al. (2017).
The DEM was processed in GIS by the Hydrology module of the Spatial
Analyst Tools and ArcHydro toolset to obtain the cartographic base comprising
the slope, altimetry, and hydrography maps. ArcGIS 10.5 Fill extension (ESRI,
2015) was used to reduce failures and errors in the results obtained from the
morphometric and hydrological parameters to remove pixels with anomalous
altimetry values.
The automatic extraction of the drainage network was performed by
the hydrology extension of ArcGIS 10.5 from the processes of generating fill,
flow direction, flow accumulation, con, stream to feature, and watershed files
(ESRI, 2015).
The delimitation of the hydrographic subbasins followed the criteria of
altimetry and relief slope and the areas of flow and accumulation of water,
allowing the precise identification of the watersheds in the basins. The
calculations of morphometric parameters were performed for the 170 sampling
units according to Gupta et al. (2017) and are described in Table 1.
Methodological proposal to remote detection and management of areas that are naturally vulnerable to floods
61
Table 1. Morphometric parameters of the Alto Sapucaí hydrographic basin, southern Minas Gerais, Brazil.
Parameter
Estimator
Variable
Meaning
References
Expresses the number of existing channels
per unit area, indicating the water potential of Strahler (1952)
the region
Stream frequency (Dh)
Dh =
n = Number of channels
A = Area
Drainage density (Dd)
Dd =
C = Channels total length
A = Area
Expresses the influence of the supply and
transport of dendritic material. Indicates the
degree of the anthropization of the channels
Horton (1945)
Relief ratio (Rr)
Rr =
∆a = Altimetric amplitude
L = Chanel length
Relationship between altimetric amplitude
and the length of the main channel
Strahler (1952)
Hm = Altimetric amplitude
Dd = Drainage density
Represents the slope relationship with the
channel lengths. Indicates the degree of
dissection of the watershed
Horton (1945)
Roughness index (Ir)
∆
Ir = Hm x Dd
Compactness coefficient (Kc)
Kc = 0.28
P = Basin perimeter in km
A = Basin area in km²
Indicates the highest or lowest occurrence of
floods
Horton (1945)
Form factor or Gravelius´s
shape index (Kf)
Kf =
A = Basin area in km²
G = Basin axial length
Lower values indicate that the basin is less
prone to flooding
Strahler (1952)
Dd = Drainage density
Indicates the minimum area needed to
maintain a meter of drainage perennial
Schum (1956)
Dd = Drainage density
Indicates the average length traveled by the
flow to the drainage channel
Chistofoletti
(1969)
A = Basin area
P = Basin perimeter
The unit tends as the basin approaches the
circular shape making it more prone to
flooding
Strahler (1952)
Maintenance coefficient (Cm)
Stream surface length (Eps)
Circularity index (Ic)
√
1
Cm =
1000
EPS =
Ic =
2
12 .57
2
1
2.
For the composition and selection of the variables that most affect
the natural propensity to flooding in regions of rugged reliefs, the following
protocol was used. The variables were grouping to identified regions naturally
vulnerable to the occurrence of floods due to the values of morphometric and
hydrological parameters that assess risks to floods, in accordance with relevant
literature (Gupta et al., 2017; Taofik et al., 2017; Kuntamalla et al., 2018).
Empirical data generated by the Civil Defense of Minas Gerais were also
collected (Defesa Civil, 2022), which mapped the areas with occurrences of
flooding in urban areas in the study region.
The cluster analysis results were synthesized in ArcGIS 10.5, generating
maps with clusters of areas with similar morphometric characteristics. This
grouping uses Ward’s minimum variance method and this technical use the
measure of the absolute distances from Manhattan (Mingoti, 2005). In the
ArcGIS software, the areas mapped by civil defense were superimposed on
the areas grouped for each of the morphometric parameters calculated for the
study area, which are: Compactness coefficient (Kc); Drainage density (Dd);
Stream frequency (Sf); Maintenance coefficient (Mc); Roughness index (Ri);
Form factor (Kf) (Cristofolleti, 1974; 1981). The variables were then selected
considering the greatest overlaps between the areas mapped by the civil
defense with the morphometric groupings. To evaluation of the assumptions,
the nonparametric Mann–Whitney test was used (Ferreira, 2009). A maximum
error of 5% was considered to reject the null hypothesis, which was declared as
the nondifference between the groups (p < 0.05).
The variables representing the morphometric and hydrological
parameters were initially assessed in a complete model and adjusted to a more
economical model using the backward method (Mingote, 2005). Fisher’s
discriminant function was proposed as a predictive equation for scoring, and
the classification constant was used as a cutoff point for classifying subbasins
that are naturally vulnerable to flooding (Mingoti, 2005). As a result of Fisher’s
discriminant function, equation 1 was found, which synthesizes the variables
and their weights for the evaluation of areas with a natural propensity for
flooding. Data processing and analysis were performed with the support of the
R statistical package (R Core Team, 2020).
62
Lucas Servidoni; Joaquim Bernardes; Guilherme Expedito; Felipe Gomes; Velibor Spalevic; Branislav Dudic; Ronaldo Luiz Mincato
Where: EFRE = Equation for flood risk evaluation; Kc: Compactness
coefficient; Dd: Drainage density; Dr: Stream frequency; Cm: Maintenance
coefficient; Ir: Roughness index; Kf: Form factor.
To evaluate the proposed model, the data obtained by the discriminant
function were crossed with empirical maps of Civil Defense (Defesa Civil,
2022). Then, 500 points were randomly distributed on the map of areas that
were vulnerable to flooding estimated by the proposed model and on the map
of the observed risk areas, and the Kappa agreement index was calculated to
assess the level of accuracy of the proposed map (Aburas et al., 2021).
3. Results
In this research, we use the concepts of vulnerability and susceptibility
to indicate predisposed/prone terrains for the development of processes in the
physical environment (floods). Already, the concept of risk was used to indicate
areas likely to be affected by natural processes that can cause adverse effects of
losses of life and material by floods.
The cluster analysis identified two groups of hydrographic sub-basins
with similar functions of morphometric and hydrological characteristics: a
group considered safe and a group characterized as naturally vulnerable to
the occurrence of floods; both are described in Table 2. As an indication of
susceptibility to flooding in watersheds, Dd indicates well-drained areas. Such
areas convert rain into flow very quickly, causing flooding in a short period.
The average Dd (Table 2) of the subbasins included in the Alto Sapucaí risk
grouping was 21.65 km2, confirming its vulnerability to floods given the
recurrent cases of flooding in Santa Rita do Sapucaí, Itajubá, Delfin Moreira,
Piranguinho, and Piranguçu by the main river, as pointed out by the Official
Civil Defense Bulletin (Defesa Civil, 2022).
Damage caused by floods mainly occurs between December and March.
The results demonstrate that in the Santa Rita do Sapucaí region, the high
values of Dd associated with extreme hydrometeorological events trigger floods
(Servidoni et al., 2021). Thus, it is necessary to prepare a contingency plan for
the area that includes the hydrological, climatic, geomorphological, pedological
and land use aspects of the hydrographic basin, which also considers the
morphometric behavior of the relief and drainage network, as shown in Table 2.
The calculated roughness index (Ir) indicates the relationship
between the slope and the length of the channels. The greater the Ir is, the
more sloped and dissected is the relief, more notched the shape of the flow
channels is and the greater the gravitational force on the rivers. In the area,
the highest Ir values partially overlap the mainstream in the upstream region
associated with the knickpoints, a significant relief rupture upstream of the
Alto Sapucaí hydrographic basin, resulting from lithological transitions
with different resistance to erosion and regional shear zones linked to the
evolution of Mantiqueira Range, developed during the Brazilian-Pan African
Neoproterozoic Orogeny (Hasui, 2010; Rezende and Castro, 2016; Rezende,
2018; CPRM, 2020; Rezende and Salgado, 2020; Calegari, 2021) (Figure 2).
The Ir values are consistent and agree with the results of the Machado River
hydrographic basin, which also belongs to the Rio Grande hydrographic basin
(Servidoni et al., 2021; 2019).
The rupture illustrated in Figure 2 is inserted into areas with a Dd greater
than 15.01 and a Dr greater than 3.01, classifying the area as well drained.
This relief rupture implies a potential increase in the flow of the main course,
which may cause risks to riverside populations close to urban watercourses
or downstream of the mapped knickpoints (Gailleton et al., 2019). These
characteristics of the downstream risk areas are illustrated by Ribeiro et al.
(2016) in the municipality of the Pouso Alegre, south of Minas Gerais.
Elevation (m)
EFRE = -3.28x10-1 Kc + 2.64x10-4 Dd – 3.62x10-1 Dr – 5.76x10-3 Cm + 8.58
x10-5 Ir – 3.44 Kf
(1)
Longitudinal Stream Profile
1720
1620
1520
1420
1320
1220
1120
1020
920
820
0
20
40
60
80
100
120
140
160
Distance (Km)
Figure 2. Longitudinal profile of the main channel of the Alto Sapucaí
hydrographic basin, southern Minas Gerais, Brazil
The areas in red in Figure 3 indicate subbasins that are vulnerable to
floods due to the morphometric characteristics of the relief and the drainage
network. There is an overlap of risk areas with Itajubá, Piranguinho, Santa Rita
do Sapucaí, Piranguçu, and Delfin Moreira. In 2020, from January to March,
these municipalities declared a state of emergency due to heavy rains (Defesa
Civil, 2020).
Figure 3 identifies areas prone to flooding. Thus, it can be a territorial
planning instrument for the preparation of contingency plans for cities. In
addition, determining risk areas can target priority locations for investments
and projects to contain floods. This allows for directing investments for proper
disaster management in places prone to flooding in the modeled area represented
in Figure 3. The identification of priority areas would enable urban space to be
restructured using sustainable strategies for land use and occupation, inspecting
and monitoring risk areas and planning the consolidation of new urban and
rural areas into safe areas. Maps of flood-prone areas (Figure 3), when linked to
land use and occupation data, can generate strategic information to prepare and
execute contingency plans for floods in the Alto Sapucaí hydrographic basin
(Table 3).
Table 3 presents the calculation of land use areas in the hydrographic
basin. Classes are grouped to synthesize regional land use behavior. The most
representative uses in the basin are Native Vegetation, Pasture, and Agricultural
Areas. They occupy 36.57, 24.09, and 37.70% of the total area, respectively.
However, when observing the relationship of each use with the risk area, their
values are 13.18, 14.66 and 15.21%, respectively. Thus, 14.69% of the basin
is vulnerable to flooding, which, despite the low numerical value, is quite
significant, as this portion of the basin includes areas inhabited by people and
destined for agriculture and livestock; these areas have high risk levels for
damage to economic activities and life.
Table 2. Hydrographic basins, according to morphometric characteristics and parameter values. Alto Sapucaí hydrographic basin, southern Minas Gerais, Brazil.
Area
Safe
Risk
P-valor
Obs
109
66
-
Kc1
1.93
1.13
0.0040
-
Dd2
3.53
21.65
0.001
**
Morphometric Characteristics
Dr2
Ir2
Rr1
2.00
2,117.76
2,265.16
2.12
6,928.39
2,444.41
0.1617
0.0001
0.3286
**
**
-
Eps2
0.14
0.02
0.0001
**
Cm2
283.06
46.22
0.0001
**
Kf1
0.36
0.78
0.0001
-
Ic1
0.32
0.86
0.4030
-
Obs: number of observations; Kc: compactness coefficient; Dd: drainage density; Dr: stream frequency; Ir: roughness index; Rr: relief ratio; Eps: stream
surface length; Cm: maintenance coefficient; Kf: form factor; Ic: circularity index; 1Average; 2median; ** Mann–Whitney test.
Methodological proposal to remote detection and management of areas that are naturally vulnerable to floods
63
Figure 3. Map of areas at risk to floods in the Alto Sapucaí hydrographic basin, southern Minas Gerais, Brazil
Urban patches occupy 31.34 km2 of risk area; however, when observing
the percentage of these areas in vulnerable places, the value is 38.80%
(Table 3). In other words, a significant amount of urban infrastructure historically
occupies areas that are naturally prone to flooding due to the morphometric
characteristics of the relief and the hydrographic network. This is due to the
historical disordered occupation of the riverbanks and soil impermeabilization
of the urban areas of the basin (Hora and Gomes, 2009).
Table 3. Land use in risk areas of the Alto Sapucaí hydrographic basin, southern
Minas Gerais, Brazil.
Land use
Area
(km2)
Area
(%)
Natural Forest
1,029.05
36.57
Agricultural
677.16
Pasture
1,060.94
Rocky Outcrop
Land Use
Risk Area Risk Area
Risk Area
2
(km )
(%)
(%)
135.63
32.80
13.18
24.09
99.32
24.06
14.66
37.70
161.40
39.04
15.21
12.93
0.45
3.74
0.91
28.92
Bare Soil
0.66
0.03
0.12
0.04
18.18
Urban
Infrastructure
31.43
1.11
12.19
2.95
38.78
Water
1.46
0.05
0.85
0.21
58.22
Total
2,813.67
100.00
413.28
100.00
14.69
Adapted from MapBiomas Project (2018).
The subbasins classified as vulnerable to flooding have a Kf value of
0.78, like that obtained by Taofik et al. (2017). This value expresses the flooding
risk in a tropical hydrographic basin with similar morphometric and climatic
characteristics. The Dd value (Figure 4) for the vulnerable cluster is 21.65,
demonstrating a significant accumulation of drainage channels in this area. As
it is a well-drained environment, rainfall-runoff conversion occurs abruptly in
high-intensity or prolonged rainfall events (Taofik et al., 2017).
The value of Kc 0.89 was obtained by Taofik et al. (2017) in a tropical
hydrographic basin. The parity of the results obtained for the two areas
demonstrates that both suffer from floods and have similar morphometric
characteristics. Such values compared to other references show that Kc values
between 0.75 and 1.00 characterize areas prone to flooding (Strahler, 1957;
Christofoletti, 1969; Sangman and Balamurugan, 2017).
The value obtained for Kf was 0.56, indicating that the basin is subject to
floods and flood peaks due to the circular shape of the downstream subbasins
and the Kc values. Furthermore, such areas are concentrated near higher-order
channels, such as the main channel. This can be evidenced by a comparison with
the results of Purohit and Parmar (2017) in the Alaknanda Basin, India. Thus,
it is essential that public administration agencies plan and adopt the necessary
measures to address and mitigate the vulnerability of these areas to extreme
hydrometeorological processes, with consideration given to the environmental
characteristics of each area (Taofik et al., 2017).
The application of cluster analysis allows classification of the
morphometric parameters into two groups. Therefore, it is possible to develop a
discriminant function capable of distinguishing subbasins subject to flood risks
from those that are safe (Equation 1).
EFRE = -3.28x10-1 Kc + 2.64x10-4 Dd – 3.62 .10-1 Dr – 5.76x10-3 Cm
+ 8.58 x10-5 Ir – 3.44 Kf
(2)
Where: EFRE = Equation for flood risk evaluation; Kc: Compactness
coefficient; Dd: Drainage density; Dr: Stream frequency; Cm: Maintenance
coefficient; Ir: Roughness index; Kf: Form factor.
In Alto Sapucaí, the discriminant function defines an EFRE threshold
value of 3.82 for the basin, below which areas are classified as naturally prone
to flooding. Thus, this cutoff value classifies the watershed as a risk or safe area
due to the geomorphological and fluvial characteristics (Figure 3).
The methodological proposal can be applied in spatial clippings of
hydrographic basins and in different federative units, with a view to identifying
areas with natural vulnerability to flooding (Brito et al., 2020). Thus, it is possible
to plan actions and strategies to minimize and overcome the catastrophic effects
of floods.
64
Lucas Servidoni; Joaquim Bernardes; Guilherme Expedito; Felipe Gomes; Velibor Spalevic; Branislav Dudic; Ronaldo Luiz Mincato
Figure 4. Map of the spatial distribution of the morphometric indices calculated for the Alto Sapucaí hydrographic basin, southern Minas Gerais, Brazil. A: Dd: Drainage
density; B: Dr: Stream frequency; C: Eps: Stream surface length; D: Ir: Roughness index; E: Rr: Relief ratio.
Methodological proposal to remote detection and management of areas that are naturally vulnerable to floods
Cluster and discriminant function analyses are quantitative tools capable
of identifying urban and regional planning priorities in areas at risk of flooding.
Consequently, with such resources, governmental and nongovernmental
management and actions can be more efficient. Its correct use could allow that
human occupation of risk areas and loss of life, material goods, and public
infrastructure are avoided.
Another advantage of the method is that it automates the detection of
areas naturally vulnerable to flooding from the discriminant function applied
in GIS. Automation reduces operating costs, and based on prior mapping, field
activities can be concentrated in vulnerable areas.
Currently, remote object detection has been widely developed in
geotechnologies, which reduces technical and operational costs, accelerates
the collection of strategic information, and supports decision-making. In
Brazil, a country of continental dimensions and, historically, a lack of planning
and management for land use and occupation, low-cost and high-efficiency
techniques to identify areas vulnerable to flooding are essential to save lives
and resources (Tsatsaris et al., 2021).
The Kappa (K) test measures the degree of agreement between
proportions derived from dependent samples. More than one method can map
a risk area and not necessarily obtain the same result. Different methods should
identify a risk area, if indeed it is a risk area. However, ideally, the different
methods should achieve the same result (Landis and Koch, 1977).
Absolute agreement between two objects observed by different methods
does not always occur in real life. However, it is possible to measure the
reliability of two observations of the same object by K. This coefficient is based
on the number of concordant responses between two products. Values close
to 1.0 represent total agreement, and those close to 0.0 indicate nonagreement
(Aburas et al., 2021).
Figure 5 illustrates the overlap of the risk map obtained by EFRE with
those mapped by Civil Defense (Defense Civil, 2022). It should be noted
that not all the municipalities surveyed have flood maps. Thus, to obtain
the Kappa Agreement Index, all products available for the study area were
considered. The agreement value was 0.83, which is considered solid or
substantial agreement (Landis and Koch, 1977). However, such a Kappa
concordance value may be higher due to the absence of maps of flooded areas
in some municipalities studied.
65
4. Discussion
According to Brito et al. (2020), it is vital to emphasize the importance
of not waiting for the authorities to assume their responsibilities in risk
management. The needs of communities affected by floods must take precedence
over individual interests and real estate speculation. Due to their vulnerability,
these communities must participate in the disaster management process so that,
in partnership with experts, they can efficiently allocate investments to fight
against and mitigate the socio-economic and environmental impacts of floods
(Bogo, 2020).
However, the management of natural disasters is, above all, the
responsibility of the State, which is the only entity with the legal capacity to act
and regulate the occupation of risk areas. Therefore, authorities must coordinate
efforts; only with the participation of all sectors of society will it be possible
to achieve sustainable management and mitigation of impacts and damage
caused by floods. Unfortunately, government organizations should and need
to standardize procedures, which would imply changes in risk management
protocols. Bureaucracy creates challenges for establishing a unified disaster
management model in Brazil (Brito et al., 2020).
According to data from the João Pinheiro Foundation, 5.87 million
people are part of the population affected by the Brazilian housing deficit in
2019 (FJP, 2019). These families live in marginalized urban spaces, forming
clusters of poverty, and many are in areas that are inappropriate for occupation,
such as slopes and riverbeds.
Brazil experienced one of its most critical summers due to the influence of
the La Niña weather phenomenon. Thus, climate change promotes catastrophic
events of extreme intense rains in southern Bahia and northern Minas Gerais,
in addition to disasters in the cities of Rio de Janeiro and São Paulo, according
to the management report of the Integrated Information System of Disasters
(Civil Defense, 2022).
These increasingly commonplace events demonstrate the relevance of
this type of research. This study sought to identify the area’s most vulnerable
to floods in a simple, objective, cheap, fast and efficient way. For a country
of continental dimensions, such as Brazil, with complex hydrography and
different socioenvironmental contexts, the product derived from this model is
essential for the development of public policies and risk management systems
in Brazilian areas, such as in the metropolitan area of Curitiba, Paraná State
(Nascimento Neto, 2020), in the Itajaí-Açu River area in Blumenau, Santa
Catarina State (Alberton et al., 2021); and in Amazonian cities like Belém, Pará
State (Szlafsztein and Araújo, 2021).
Climate change causes storm events to become more frequent and intense,
so it is essential to predict the identifying patterns, trends, and distribution of
natural phenomena to reduce natural risks. Only in this way will it be possible
to implement land use and occupation planning that values the quality of life
and the sustainability of the environment. Therefore, the EFRE enables the
identification of geomorphological conditions that potentiate flood events in
tropical watersheds and may be an option to manage this problem that has
devastated and claimed many lives in Brazil.
5. Conclusion
Figure 5. Map of the distribution of points to calculate the accuracy of the Kappa
coefficient for the Alto Sapucaí hydrographic basin, southern Minas Gerais, Brazil.
The precision obtained by EFRE is quite satisfactory for the area. From
now on, new works should seek different applications for EFRE, such as the
establishment of quality control measures and model validation (Figure 5).
The discriminant function showed potential to identify areas susceptible
to flooding. It is proposed that a value of 3.82 for the equation for flood risk
evaluation indicates areas vulnerable to flooding and that higher values suggest
a low natural risk of flooding.
The value of the Kappa Index was 0.83, indicating good agreement
between the products obtained by the Equation Flood Risk Evaluation and the
Civil Defense risk maps, demonstrating good accuracy in forecasting areas at
risk of flooding.
The geomorphological characteristics and frequency of storms are the
main natural factors that increase the potential for flooding in the region. Due to
climate change, storm events tend to become more intense and frequent.
Of the eleven municipal seats, five are in areas at risk of flooding; these
areas, Itajubá, Piranguinho, Santa Rita do Sapucaí, Piranguçu and Delfin
Moreira, and have suffered flooding events in the last ten years.
66
Lucas Servidoni; Joaquim Bernardes; Guilherme Expedito; Felipe Gomes; Velibor Spalevic; Branislav Dudic; Ronaldo Luiz Mincato
Public policies to combat floods should be addressed in conjunction with
the housing issue in Brazil, with the participation of vulnerable populations,
providing technical support for land use planning and increasing the security of
marginalized populations in urban areas.
6. Acknowledgments
To the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Brasil” (CAPES) for the doctoral scholarship for the first author.
To the “Fundação de Amparo à Pesquisa do Estado de Minas Gerais”
(FAPEMIG) for the doctoral scholarship for the third author.
This study was funded in part by the “Coordenação de Aperfeiçoamento
de Pessoal de Nível Superior - Brasil” (CAPES) - Finance Code 001.
References
Aburas, M. M., Ho, Y. M, Pradhan, B., Salleh, A. H. & Alaiza, M. Y. D. (2021).
Spatio-temporal simulation of future urban growth trends using an
integrated CA-Markov Model. Arabian Journal of Geosciences, 14(131),
01-12. https://doi.org/10.1007/s12517-021-06487-8
Alberton, G. B., Severo, D. L., Melo, M. N. V., Potelicki, H. & Sartori, A. (2021).
Aplicação de redes neurais artificiais para previsão de enchentes no
Rio Itajaí-Açu em Blumenau, SC, Brasil. Revista Ibero Americana de
Ciências Ambientais, 12(4), 686-696. http://doi.org/10.6008/CBPC21796858.2021.004.0053
Aquino, R. F., Silva, M. L. N., Freitas, D. A. F., Curi, N., Mello, C. R. & Avanzi, J.
C. (2012). Spatial variability of the rainfall erosivity in southern region
of Minas Gerais State, Brazil. Ciência e Agrotecnologia, 36(5), 533542.
https://doi.org/10.1590/S1413-70542012000500006
Arantes, L. T., Carvalho, A. C. P., Lorandi, R., Moschini, L. E. & Di lollo, J. A.
(2021). Surface runoff associated with climate change and land use
and land cover in southeast region of Brazil. Environmental Challenges,
3(100054). https://doi.org/10.1016/j.envc.2021.100054
Ardaya, A. B., Evers, M. & Ribbe, L. (2019). Participatory approaches for disaster
risk governance? Exploring participatory mechanisms and mapping to
close the communication gap between population living in flood risk
areas and authorities in Nova Friburgo Municipality, RJ, Brazil. Land Use
Policy, 88(104103). https://doi.org/10.1016/j.landusepol.2019.104103
Ávila, L. F., Mello, C. R. & Viola, M. R. (2009). Mapeamento da precipitação
mínima provável para o sul de Minas Gerais. Revista Brasileira de
Engenharia Agrícola e Ambiental, 13, 906–915. https://doi.org/10.1590/
S1415-43662009000700013
Bitencourt, N. L. R. & Rocha I. O. (2014). Percepção das populações costeiras
sobre os efeitos dos eventos adversos no extreme sul de Santa Catarina
- Brasil. Journal of Integrated Coastal Zone Management, 14(1), 15-25.
https://doi.org/10.5894/rgci408
Brito, R. P., Miguel, P. L. S. & Pereira, S. C. A. F. (2020). Climate risk Perception
and media framing. RAUSP Management Journal, 55(2), 247-262.
https://doi.org/10.1108/RAUSP-09-2018-0082
Bogo, R. S. (2020). Participatory master plan, territory and floods in Rio do Sul,
State of Santa Catarina. Cadernos Metrópole, 22(48), 555-577. https://
doi.org/10.1590/2236-9996.2020-4810
Calegari, S. S. (2021). Estruturas Rúpteis e Expressão Topográfica na Terminação
Norte da Serra da Mantiqueira, Sudeste do Brasil. [Ph.D. Thesis,
Universidade Federal de Minas Gerais], Belo Horizonte, Brazil.
Campos, B., Pereira, R. A. A., Freitas, C. H. & Barbosa, A. A. (2016). Eventos
extremos de precipitação no Sul de Minas Gerais. Revista Brasileira
de Geografia Física, 9(7), 2325-2340. https://doi.org/10.5935/19842295.20160166
Christofoletti, A. (1969). Análise morfométrica de bacias hidrográficas. Nota
Geomorfológica, 9(18), 35-64.
Christofoletti, A. (1974). Geomorfologia. Universidade de São Paulo, São Paulo,
Brazil, 149pp.
Christofoletti, A. (1981). Geomorfologia fluvial. Edgard Blucher, São Paulo,
Brazil, 152pp.
Cobbinah, P. B., Korah, P. I., Bardoe, J. B., Darkwah, R. M. & Nunbogu, A.
M. (2022). Contested urban spaces in unplanned urbanization:
Wetlands under siege. Cities, 121(103489). https://doi.org/10.1016/j.
cities.2021.103489
Companhia de Pesquisa de Recursos Minerais (CPRM). (1998). Carta Geológica
Guaratinguetá, Escala 1:250.000. Companhia de Pesquisa de Recursos
Minerais, São Paulo, Brazil, 210 pp.
Companhia de Pesquisa de Recursos Minerais (CPRM). (2020). Mapa Geológico
do Estado de Minas Gerais. Escala 1:1.000.000. Companhia de Pesquisa
de Recursos Minerais, Belo Horizonte, Brazil.
Defensa Civil (2020). Boletim Estadual de Proteção e Defesa Civil
2020,
http://www.sistema.defesacivil.mg.gov.br/index.
php?modulo=cce&controller=cce&action=boletimsite (last accessed
January 2022).
Defesa Civil (2022). Sistema Integrado de Informações sobre Desastres Naturais
2022, https://www.gov.br/mdr/pt-br/assuntos/protecao-e-defesa-civil/
sistema-integrado-de-informacoes-sobre-desastres (last accessed
January 2022).
Ekmekcioğlu, O., Koc, K. & Özger, M. (2022). Towards flood risk mapping based
on multi-tiered decision making in a densely urbanized metropolitan
city of Istanbul. Sustainable Cities and Society, 80(103759). https://doi.
org/10.1016/j.scs.2022.103759
Environmental Systems Research Institute (ESRI). (2015). ARCGIS Professional
GIS for the desktop version 10.3. 1st ed., Environmental Systems Research
Institute, Redlands, California, United States, 30 pp.
Ferreira, D. F. (2009). Estatística básica. Universidade Federal de Lavras, Lavras,
Brazil, 664 pp.
Ferreira, G. G., Calmon, P., Fernandes, A. S. A. & Araújo, S. M. V. G. (2019).
Política habitacional no Brasil: uma análise das coalizões de defesa do
Sistema Nacional de Habitação de Interesse Social versus o Programa
Minha Casa, Minha Vida. Urbe Revista Brasileira de Gestão Urbana,
11(e20180012), 1-15. https://doi.org/10.1590/2175-3369.011.001.AO04
Fleischmann, A. S., Brêda, J. P. F., Rudorff, C., Paiva, R. C. D., Collischonn, W.,
Papa, F. & Ravanello, M. M. (2021). River Flood Modeling and Remote
Sensing Across Scales: Lessons from Brazil. Earth Observation for
Flood Applications, 61-103. https://doi.org/10.1016/B978-0-12-8194126.00004-3
Fundação João Pinheiro (FJP). (2019). Deficit habitacional no Brasil – 2016-2019.
Fundação João Pinheiro, Belo Horizonte, Brazil, 169 pp.
Gailleton, B., Mudd, S. M., Club, F. J., Peifer, D. & Hurst, M. D. (2019).
A segmentation approach for the reproducible extraction and
quantification of knickpoints from river long profiles. Earth Surface
Dynamics, 7, 211-230. https://doi.org/10.5194/esurf-7-211-2019
Galvão, L. & Bernann, C. (2015). Crise hídrica e energia: conflitos no uso múltiplo
das águas. Estudos Avançados, 29(84), 43-68. https://doi.org/10.1590/
S0103-40142015000200004
Gupta, D. S., Gosh, P. & Tripathi, S. K. (2017). A Quantitative Morphometric
Analysis of Barhar River Watershed of Mahoba district, U.P., India using
Remote Sensing and GIS. Indian Journal of Science and Technology,
10(11), 1-5. https://doi.org/10.17485/ijst/2017/v10i11/109695
Hasui, Y. (2010). A grande colisão Pré-Cambriana do Sudeste Brasileiro e a
estruturação regional. Geociências, 29(2), 141-169.
Hora, S. B. & Gomes, R. L. (2009). Mapeamento e avaliação do risco a inundação
do Rio Cachoeira em trecho da área urbana do Município de Itabuna/
BA. Sociedade & Natureza, 21(2), 57-75. https://doi.org/10.1590/S198245132009000200005
Horton, R. E. (1945). Erosional development of streams and their drainage basins:
hydrophysical approach to quantitative morphology. GSA Bulletin,
56(3), 275–370. https://doi.org/10.1130/0016-7606(1945)56[275:EDO
SAT]2.0.CO;2
Methodological proposal to remote detection and management of areas that are naturally vulnerable to floods
Kuntamalla, S., Nalla, M. G. S. & Saxena, P. R. (2018). Drainage Basin Analysis
through GIS: A Case study of Lakhnapur Reservoir Watershed in
Rangareddy District, Telangana State, India. International Journal
of Engineering, Science and Mathematics, 7(3), 9-17. https://doi.
org/10.13140/RG.2.2.22464.84484
Landis, J. R. & Koch, G. G. (1977). The measurement of observer agreement
for categorical data. Biometrics, 33(1), 159-174. https://doi.
org/10.2307/2529310
Lin, J. M. & Billa, L. (2021). Spatial prediction of flood-prone areas using
geographically weighted regression. Environmental Advances,
6(100118). https://doi.org/10.1016/j.envadv.2021.100118
Mapbiomas Project. (2018). Coleção 4 Série Anual de Mapas de Cobertura e
Uso de Solo do Brasil, https://mapbiomas.org/en (last accessed January
2022).
Mardhel, V, Pinson, S. & Allier, D. (2021). Description of an indirect method
(IDPR) to determine spatial distribution of infiltration and runoff
and its hydrogeological applications to the French territory. Journal of
Hydrology, 592(125609). https://doi.org/10.1016/j.jhydrol.2020.125609
Martín-Díaz, J., Palma, P., Golijanin, J., Nofre, J., Oliva, M. & Čengić, N.
(2018). The urbanisation on the slopes of SARAJEVO and the rise of
geomorphological hazards during the post-war period. Cities, 72(A),
60-69. https://doi.org/10.1016/j.cities.2017.07.004
Martins, C. M. S., Silva, B. C. & Pons, N. A. D. (2019). Estimativa de cheias
em bacias hidrográficas com base em previsões de precipitação por
conjunto. Revista Brasileira de Geografia Física, 12(5), 1713-1729.
https://doi.org/10.26848/rbgf.v12.5.p1713-1729
Minas Gerais. Secretária de Estado de Meio Ambiente e Desenvolvimento
Sustentável. (2015). Atlas da vulnerabilidade às inundações de
Minas Gerais 2015. 1st ed., Secretária de Estado de Meio Ambiente e
Desenvolvimento Sustentável, Belo Horizonte, Brazil, 231 pp.
Mingoti, S. A. (2007). Análise de dados através de métodos de estatística
multivariada: uma abordagem aplicada. Universidade Federal de Minas
Gerais, Belo Horizonte, Brazil, 293 pp.
Molina, E. C. & González, A. L. M. (2020). Metodología para el análisis de
vulnerabilidad ante inundaciones. Un ejercicio emergente ante el
cambio climático. Economía, sociedad y territorio, 19(61), 543-574.
https://doi.org/10.22136/est20191342
Nascimento, M. C. (2019). Problemas socioambientais causados pelas chuvas em
cidades da região metropolitana de Maceió, Brasil. Revista Bibliográfica
de Geografía y Ciencias Sociales, 24(1276), 1-31. https://doi.org/10.1344/
b3w.0.2019.27489
Nascimento, D. M. & Braga, R. C. Q. (2009). Déficit habitacional: um problema
a ser resolvido ou uma lição a ser aprendida? Risco Revista de Pesquisa
em Arquitetura e Urbanismo, 2(9), 98-109. https://doi.org/10.11606/
issn.1984-4506.v0i9p98-109
Nascimento Neto, P. (2020). A dimensão esquecida da política habitacional:
reflexões a partir do caso da Área Metropolitana de Curitiba (PR).
Cadernos Metrópole, 22(47), 215-246. https://doi.org/10.1590/22369996.2020-4710
Purohit, K. & Parmar, M. K. (2017). Morphometric Analysis and Correlation between
Morphometric Parameters with Mean Basin Altitude and Slope: A case
study of Alaknanda Basin, Uttarakhand, India. GJRA - Global Journal
for Research Analysis, 6(7), 27-30. https://doi.org/10.36106/gjra
R CORE TEAM. (2020). R: A language and enviroment for statistical computing.
http://www.r-project.org/ (last accessed January 2022).
Rezende, E. A. (2018). O papel da dinâmica espaço-temporal da rede hidrográfica
na evolução geomorfológica da alta/média bacia do Rio Grande, sudeste
brasileiro. [Ph.D. Thesis, Universidade Federal de Ouro Preto], Ouro
Preto, Brazil.
Rezende, E. R. & Castro P. T. A. (2016). Variação espacial e condicionantes do
entalhamento fluvial na bacia do Rio Grande, Sul de Minas Gerais.
Revista Brasileira de Geomorfologia, 17(4), 645-659. https://doi.
org/10.20502/rbg.v17i4.1045
67
Rezende, E. A., Salgado, A. A. R. & Castro P. T. A. (2018). Evolução da rede
de drenagem e evidências de antigas conexões entre as bacias dos Rios
Grande e São Francisco no sudeste brasileiro. Revista Brasileira de
Geomorfologia, 19(3), 483-501. https://doi.org/10.20502/rbg.v19i3.1304
Rezende, E. A. & Salgado, A. A. R. (2020). Considerações sobre a gênese do
vale suspenso do alto Rio Preto na borda da Bacia de Resende. Revista
do Departamento de Geografia da USP, 40(1), 49-60. https://doi.
org/10.11606/rdg.v40i0.165775
Ribeiro, A. S., Mincato, R. L., Curi, N. & Kawakubo, F. S. (2016). Vulnerabilidade
ambiental à erosão hídrica em uma sub-bacia hidrográfica pelo processo
analítico hierárquico. Revista Brasileira de Geografia Física, 9(1), 16-31.
https://doi.org/10.26848/rbgf.v9.1.p016-031
Sangman, F. & Balamurugan, G. (2017). Morphometric Analysis of Kakoi
River Watershed for Study of Neotectonic Activity Using Geospatial
Technology. International Journal of Geosciences, 8(11), 1384-1403.
https://doi.org/10.4236/ijg.2017.811081
Santos, H. G., Jacomine, P. K. T., Anjos, L. H. C., Oliveira, V. A., Lumbreras, J. F.,
Coelho, M. R., Almeida, J. A., Araujo Filho, J. C., Oliveira, J. B. & Cunha,
T. J. F. (2018). Brazilian Soil Classification System. Empresa Brasileira de
Pesquisa Agropecuária, Brasília, Brazil, 356 pp.
Schumm, S. A. (1956). Evolution of drainage systems and slopes in badlands
at Perth Amboy, New Jersey. GSA Bulletin, 67(5), 597-646. https://doi.
org/10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2
Scolforo, J. R. S., Mello, J. M. & Silva, C. P. C. (2008). Inventário Florestal de
Minas Gerais: Floresta Estacional Semidecidual e Ombrófila – Florística,
Estrutura, Diversidade, Similaridade, Distribuição diamétrica e de altura,
Volumetria e Tendências de crescimento e Áreas aptas para manejo
florestal. Universidade Federal de Lavras, Lavras, Brazil, 1029 pp.
Servidoni, L. E., Teodoro, A. E. M., Mincato, R. L., & Santos, C. A. (2019).
Avaliação de risco a enchentes e inundações por krigagem ordinária em
sistemas de informação geográfica. Caderno de Geografia, 29(1), 126143. https://doi.org/10.5752/p.2318-2962.2019v29nespp126
Servidoni, L. E., Ayer, J. E. B., Estella, P. V. M., Oliveira, G. H. & Mincato, R. L.
(2021). Atributos morfométricos e hidrológicos da Bacia Hidrográfica
do Alto Sapucaí, Minas Gerais. Revista do Departamento de
Geografia, 41(1), e169817. https://doi.org/10.11606/eISSN.2236-2878.
rdg.2021.169817
Silva, V. P. R., Silva, M. T., Singh, V. P., Souza, E. P., Braga, C. C., Holanda, R. M.,
Almeida, R. S. R., Sousa, F. A. S. & Braga, A. C. R. (2018). Simulation
of stream flow and hydrological response to land-cover changes in a
tropical river basin. Catena, 162, 166-176. https://doi.org/10.1016/j.
catena.2017.11.024
Strahler, A. N. (1957). Quantitative analysis of watershed geomorphology. Eos,
Transactions American Geophysical Union, 38(6), 913-920. https://doi.
org/10.1029/TR038i006p00913
Szlafsztein C. F., & Araújo, A. N. B. (2021). Autonomous flood adaptation
measures in Amazonian cities (Belem, Brazil). Natural Hazards, 108,
1069-1087. https://doi.org/10.1007/s11069-021-04720-x
Tamiru, H., & Dinka, M. O. (2021). Application of ANN and HEC-RAS model
for flood inundation mapping in lower Baro Akobo River Basin,
Ethiopia. Journal of Hydrology: Regional Studies, 36, 100855. https://doi.
org/10.1016/j.ejrh.2021.100855
Taofik, O. K., Innocent, B., Christopher, N., Jidauna, G. G., & James, A. S.
A. (2017). Comparative Analysis of Drainage Morphometry on
Hydrologic Characteristics of Kereke and Ukoghor Basins on Flood
Vulnerability in Makurdi Town, Nigeria. Hydrology, 5(3), 32-40.
https://doi.org/10.11648/j.hyd.20170503.11
Tesema, T. A. (2021). Impact of identical digital elevation model resolution and
sources on morphometric parameters of Tena watershed, Ethiopia.
Heliyon, 7(11), e08345. https://doi.org/10.1016/j.heliyon.2021.e08345
68
Lucas Servidoni; Joaquim Bernardes; Guilherme Expedito; Felipe Gomes; Velibor Spalevic; Branislav Dudic; Ronaldo Luiz Mincato
Tsatsaris, A., Kalogeropoulos, K., Stathopoulos, N., Louka, P., Tsanakas, K.,
Tsesmelis, D. E., Krassanakis, V., Petropoulos, G. P., Pappas, V. &
Chalkias, C. (2021). Geoinformation Technologies in Support of
Environmental Hazards Monitoring under Climate Change: An
Extensive Review. International Journal of Geo-Information, 10(2), 94127. https://doi.org/10.3390/ijgi10020094
Uddin, K. & Matin, M. A. (2021). Potential flood hazard zonation and flood
shelter suitability mapping for disaster risk mitigation in Bangladesh
using geospatial technology. Progress in Disaster Science, 11, 100185.
https://doi.org/10.1016/j.pdisas.2021.100185
United States Geological Survey (USGS) (2014). Shuttle Radar Topography
Mission (SRTM) Version 2. https://earthexplorer.usgs.gov/> (last
accessed January 2022).
Waghwala, R. & Agnihotri, P. G. (2019). Flood risk assessment and resilience
strategies for flood risk management: A case study of Surat City.
International Journal of Disaster Risk Reduction, 40, 101155. https://doi.
org/10.1016/j.ijdrr.2019.101155
Ward, P. J., Blauhut, V., Bloemendaal, N., Daniell, J. E., Ruiter, M. C., Duncan,
M. J., Emberson, R., Jenkins, S. F., Kirschbaum, D., Kunz, M., Mohr,
S., Muis, S., Riddell, G. A., Schäfer, A., Stanley, T., Veldkamp, T. I.
E. & Winsemius, H. C. (2020). Review article: Natural hazard risk
assessments at the global scale. Natural Hazards and Earth System
Sciences, 20, 1069-1096. https://doi.org/10.5194/nhess-20-1069-2020