ORI GIN AL PA PER

Geomorphology and GIS analysis for mapping gullyerosion susceptibility in the Turbolo stream catchment(Northern Calabria, Italy)

Massimo Conforti Pietro P. C. Aucelli Gaetano Robustelli

Fabio Scarciglia

Received: 7 December 2009 / Accepted: 6 August 2010 / Published online: 27 August 2010 Springer Science+Business Media B.V. 2010

Abstract This work summarizes the results of a geomorphological and bivariate statis-tical approach to gully erosion susceptibility mapping in the Turbolo stream catchment

(northern Calabria, Italy). An inventory map of gully erosion landforms of the area has

been obtained by detailed field survey and air photograph interpretation. Lithology, land

use, slope, aspect, plan curvature, stream power index, topographical wetness index and

length-slope factor were assumed as gully erosion predisposing factors. In order to estimate

and validate gully erosion susceptibility, the mapped gully areas were divided in two

groups using a random partitions strategy. One group (training set) was used to prepare the

susceptibility map, using a bivariate statistical analysis (Information Value method) in GIS

environment, while the second group (validation set) to validate the susceptibility map,

using the success and prediction rate curves. The validation results showed satisfactoryagreement between the susceptibility map and the existing data on gully areas locations;

therefore, over 88% of the gullies of the validation set are correctly classified falling in

high and very high susceptibility areas. The susceptibility map, produced using a meth-

odology that is easy to apply and to update, represents a useful tool for sustainable

planning, conservation and protection of land from gully processes. Therefore, this

methodology can be used to assess gully erosion susceptibility in other areas of Calabria, as

well as in other regions, especially in the Mediterranean area, that have similar morpho-

climatic features and sensitivity to concentrated erosion.

M. Conforti (&) G. Robustelli F. ScarcigliaDipartimento di Scienze della Terra, Universita` della Calabria, Via P. Bucci, Cubo 15B,87036 Arcavacata di Rende (CS), Italye-mail: massimo.conforti@unical.it

G. Robustellie-mail: robustelli@unical.it

F. Scarcigliae-mail: scarciglia@unical.it

P. P. C. AucelliDiSAm, Universita` degli Studi di Napoli Parthenope, Centro Direzionale isola C/4,80143 Naples, Italye-mail: pietro.aucelli@uniparthenope.it

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Nat Hazards (2011) 56:881898DOI 10.1007/s11069-010-9598-2

Keywords Gully erosion susceptibility GIS Information value method Calabria

1 Introduction

Gully erosion is one of the erosive processes that mostly contributes to shape the earth

surface (Billi and Dramis 2003). The development of gullies causes the loss of a great

amount of soil and can be considered as one of the principal causes of geo-environmental

degradation in the Mediterranean area (Vandekerckhove et al. 2000; Martnez-Casasnovas

et al. 2003; Vanwalleghem et al. 2005). Researches conducted in SE Spain, SE Portugal

and central Belgium determined that gully erosion generated between 3.4 and 9.7 m3/ha/

year of sediments, representing 4483% of total sediment production on agricultural lands

(Poesen et al. 1998). Generally, the growing interest in studying gully erosion reflects the

need to increase our knowledge on its impacts and controlling factors that vary under a

wide range of causes (Valentin et al. 2005). Gullies are common features on slopes of

mountainous or hilly regions worldwide and involve complex processes controlled by a

variety of closely related factors such as lithology, soil type, climate, topography, land use

and vegetation cover.

Also large areas of South Italy and, in particular, the Calabria territory, which is on the

whole very susceptible to erosion processes (Sorriso-Valvo et al. 1995; ARSSA 2005;

Terranova et al. 2009), are vulnerable to the development of gully erosion, due to the

combination of its peculiar geological, morphological, pedological, climatic characteristics

and very often to unsustainable land management. A recent study by Conforti (2008)

showed that wide portions of the Turbolo stream catchment in northwestern Calabria

(which is highly representative of different areas in the regional territory, in light of its geo-

environmental features and high soil erosion susceptibility conditions) are affected by

erosive processes that occur as linear and/or diffused water erosion. In particular, con-

centrated runoff (mainly responsible for gully erosion) causes a consistent soil loss,

reaching more than 20 t/ha/year on slopes affected by calanchi (Alexander 1980; Morettiand Rodolfi 2000). Therefore, it is of prominent importance to define valid models to

assess the susceptibility of the territory to the development of these processes.

The main objectives of this study have been (a) identification, morphological descrip-

tion and mapping of the areas affected by gullies in the Turbolo stream catchment;

(b) characterization of the main geo-environmental features as factors that control gullies

distribution; and (c) evaluation of gully erosion susceptibility in the study area.

2 Geo-environmental setting of the study area

The Turbolo stream catchment is located in the northwestern portion of Calabria (South

Italy), between 393202300N and 392904900N latitude, 161205700E and 160502100E longi-tude (Fig. 1). The Turbolo stream is a left-side tributary of the Crati river and originates in

the eastern top slope of the Calabrian Coastal Range at more than 1,000 m of altitude,

flowing longitudinally from west to east for a length of about 13 km. Its catchment extends

over an area of about 30 km2, having an elongated and asymmetrical shape. The Turbolo

stream represents a basin of the 5th order with a drainage density equal to 5.16 km-1,

which indicates a rather dense drainage network in a strongly dissected area (Conforti

2008), often controlled by tectonic activity (Tortorici et al. 1995). The drainage pattern is

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dendritic in mountain sub-basins and trellis-like in hilly sub-basins. The climate is an

upland Mediterranean type (Csb, sensu Koppen 1936), with hot, dry summers and pre-cipitations concentrated in mild winters. Mean annual rainfall is about 1,200 mm, with

extremes exceeding 1,600 mm/yr. The rainfall is distributed in 105 rainy days; more than

60% of precipitations fall in the winter period from November to February (December

being the rainiest month reaching 200 mm), snowfall included above 700800 m a.s.l.

Mean annual temperature is 16C, and mean monthly temperatures range between 7C inJanuary and 26C in August (Caloiero et al. 1990; Conforti 2008).

From a geological point of view, the study area is crossed by an important NS Qua-

ternary strike fault (S. FiliS. Marco Argentano, Tortorici et al. 1995); it is responsible for

Fig. 1 Study area location map and spatial distribution of the gully area on the DTM of the Turbolo streamcatchment

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the uplift of the plutonic and metamorphic basement of the Calabrian Coastal Range (west)

with respect to the post-orogenic formations filling the Crati graben (east). Among the

latter, the following terrains outcrop in the study area, from bottom to top (Colella et al.

1987): Late Miocene marine clay and silt, interbedded with chalk and calcarenite layers;

Late Pliocene-Late Pleistocene marine silty clay, passing to sand, silt and conglomerate

and fan-conglomerate, made of igneous and metamorphic clasts in a sandy matrix

(Lanzafame and Zuffa 1976); Holocene alluvial and colluvial deposits occur along the

valley bottoms.

Outcrops of crystalline basement rocks of the Costal Range are limited to the western

part of the study area, where the following tectonic units can be recognized (Amodio-

Morelli et al. 1976): gneiss and schist of the Polia-Copanello and Castagna Units

(Paleozoic), phyllite interbedded with metapelite and quartzite of the Bagni Unit (Triassic),

micaschist interbedded with quartzite, metapelite and metalimestone of the Frido Unit

(Cretaceous), metabasite covered by metalimestone and by polychrome schist of the

Diamante-Terranova Unit. These rocks are intensely fractured and weathered and, very

often, are affected by landslides and deep-seated gravitational slope deformations (Iovine

et al. 2006; Gattinoni 2008).

From a morphological point of view, the western sector of the study area is charac-

terized by steep slopes (average [30), shaped on metamorphic rocks and a high localrelief caused by the strong uplift of the Coastal Range and its consequent dissection

(Tortorici et al.1995). In particular, these slopes show a rectilinear-convex profile and are

often highly dissected by V-shaped valleys (Sorriso-Valvo and Tansi 1996). Gentleslopes, where clayey lithologies outcrop, generally characterize the intermediate western

sector of the basin; denudational processes, mainly landslides and water erosion, sig-

nificantly affect hill slopes. Slope profiles are generally very articulated, with concave-

convex shapes (Sorriso-Valvo and Tansi 1996) and mainly incised by valleys with

concave bottom.

In the eastern sector of the Turbolo watershed, the landscape is characterized by the

presence of terraced surfaces, deeply dissected by V-shaped or concave valleys, caused bythe Quaternary tectonic activity (Carobene et al. 1989). Recent alluvial fans and fluvial

terraces (Holocene) are observed along the main river valleys.

As a result of the different geological, morphological and climatic conditions, several

soil types can be found in the Turbolo basin. According to the soil map of Calabria

(ARSSA 2003), soils range from highly mature (Alfisols) to poorly developed soils

(Inceptisols and Entisols) (sensu USDA 2006), which frequently appear truncated orstrongly degraded at surface by water erosion. Moreover, on the clayey hill slopes most

soils show outstanding vertic features, with a high structural dynamism characterized by

the development of desiccation cracks (due to shrinkage of clays) from the surface in the

dry season, that are subsequently closed by imbibition and consequent swelling of clays in

the following wet season.

In the study area, the main erosive processes that affect the landscape are related to

runoff waters (diffuse and/or linear) and mass movements that cause a rapid evolution of

slopes and valley bottoms (Conforti 2008). Overland flow processes (sheet, rill and gully

erosion) particularly act in areas without vegetation cover, in cultivated fields and pasture

lands. The main causes of water erosion are the intensive land use and cultivation of annual

crops on steep slopes often performed along slope-parallel plowing furrows. Mass

movements are triggered mainly on clayey slopes and on steeply inclined and intensely

weathered metamorphic substrata.

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3 Materials and methods

The first phase of the research has been carried out through a geomorphological study. Air

photograph interpretation and field survey have brought to the assessment of the spatial

distribution of gully erosion processes, allowing an inventory map of gully landforms to be

constructed (Fig. 1). The mapped gully area consists of slope units widely affected by

gully erosion, which represent microbasins.

Because gullying is a threshold-dependent process controlled by a wide range of factors

(Valentin et al. 2005), to assess gully erosion susceptibility, it has been necessary to select

a number of predisposing factors of different nature (geological, morphological, hydro-

logical, etc.), which are suspected to be somehow related to the generation of gully erosion

processes. The predisposing factors used in this work are lithology, land use and a series of

topographical factors: slope, aspect, plan curvature, stream power index (SPI), topo-

graphical wetness index (TWI) and length-slope factor (LS), also known as transmission

capacity index (Moore et al. 1991). All the morphometric parameters were automatically

derived from the DTM with a resolution of 10 9 10 m pixel size, using the management

features offered by the DTM extensions (3D Analyst, Spatial Analyst and Sinmap) of the

ESRI Arcview 3.2 GIS software. The DTM has been produced from digitization of contour

lines and points of the topographical map of Calabria at 1:10000 scale, dating back to

1954; contour lines have been updated by using the Z-map software that allowed to obtain

3D polylines from the stereoscopic models of aerial photographs of 2005. Consequently,

the DTM can be considered as shaped by the gully landforms.

3.1 Analysis of predisposing factors

3.1.1 Lithology

A detailed analysis of the major lithological characteristics has been performed by inte-

grating data from the geological map of Calabria at 1:25000 scale with field survey. In fact,

lithological properties are among the main sources of data related to the geomorphological

features and evaluation of a land (Dai et al. 2001). Special focus has been devoted to

mapping superficial deposits (colluvial, alluvial, slope and landslide deposits), these are

considered as particularly prone to erosion processes.

Gully erosion is particularly related to the lithology and weathering properties of the

material exposed or close to the earth surface. Therefore, the large variety of lithological

types cropping out in the study area has been grouped into eleven classes according to their

compositional characteristics, mechanical properties and expected erodibility (Fig. 2a;

Table 1). Sands and clays are the most widespread lithologies. Pleistocene sand deposits

crop out for the 39% of the study area and mostly in the eastern zone. Pliocene clayey

sediments mainly outcrop in the central sector of the basin reaching about 14% of the basin.

3.1.2 Land use

The type of soil use has a significant influence on the geomorphological stability of a slope;

in general, barren and sparsely vegetated areas are affected by faster erosion and greater

instability than forests (Anabalagan 1992; Dai et al. 2001; Cevik and Topal 2003). The

existence of a plant cover has decreasing effects on gully erosion susceptibility, because it

reduces the erosive action of surface runoff. In the study area, a land use map has been

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derived from color orthophotograph interpretation and field checks. Land use types were

thus grouped into nine classes (Fig. 2b; Table 1). In particular, more than 55% of the area

presents an agricultural and pastoral use, in which the large part of the gullies is included.

3.1.3 Slope

The steepness of slopes is a factor of primary importance in the dynamics of the processes

governing land evolution; in fact, it affects surface runoff, drainage density, soil erosion

etc., (Dramis and Gentili 1977). For this reason, the steepness of the slopes plays a crucial

role in the preparation of the erosive process susceptibility maps in a given territory, in the

specific case of gully erosion. Therefore, steep slopes promote high runoff velocity and

consequent rill and gully initiation (Valentin et al. 2005). In this study, the slope, derived

from the DTM, has been divided in six classes (Fig. 2c). In the Turbolo catchment, gullies

are common in the hilly land with steep slopes (Table 1).

Fig. 2 Predisposing factor maps: a lithology; b land use; c slope; d aspect; e plan curvature; f LS; g SPI;h TWI

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Table 1 Weighting values (Wi) distribution for each class of the selected gully erosion predisposing factors

NpixNi NpixSi DensClass Wi

Lithology

Alluvial deposit 21,293 197 0.009 -1.31

Colluvial deposit 15,291 130 0.009 -1.39

Alluvial fan deposit 20,586 607 0.034 -0.15

Slope deposit 8,891 109 0.012 -1.03

Landslide deposit 17,444 331 0.005 -0.59

Conglomerates 24,151 925 0.038 0.11

Sands 109,829 5,713 0.052 0.42

Clays 40,312 1,566 0.039 0.13

Gneiss 12,157 37 0.003 -2.42

Metalimestone and metapelite 12,347 274 0.026 -0.43

Phyllite/Schist and metabasite 9,273 384 0.052 0.19

Land use

Woodland 81,723 3,590 0.044 0.26

Scrub and herbaceous 36,396 2,807 0.077 0.81

Pasture 28,912 752 0.026 -0.28

Olive groves 62,395 734 0.012 -1.06

Orchard and/or vineyard 3,658 41 0.011 -1.12

Cropland 65,054 925 0.014 -0.88

Barren and abandoned land 7,323 1,441 0.200 1.75

River bed and flooding areas 2,100 5 0.003 -2.62

Urban 6,860 0 0.000 -2.70

Slope

05 45,489 275 0.006 -1.74510 42,930 520 0.012 -1.041015 57,880 1,043 0.018 -0.641520 56,521 1,703 0.030 -0.132030 71,902 4,568 0.064 0.62[30 25,059 2,164 0.086 0.92

Aspect

Flat 27,301 821 0.030 -0.13

N 38,148 986 0.026 -0.28

NE 38,596 1,161 0.030 -0.13

E 47,861 1,216 0.025 -0.30

SE 52,931 1,785 0.034 -0.02

S 29,893 1,411 0.047 0.32

SW 11,944 1,124 0.094 1.01

W 13,435 880 0.066 0.65

NW 30,257 876 0.029 -0.17

SPI

00.6 188,207 4,047 0.022 -0.47

0.61.2 87,477 4,731 0.054 0.46

1.21.8 16,394 1,217 0.074 0.77

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3.1.4 Aspect

Aspect is also considered an important factor in susceptibility studies of denudational

processes (Carrara et al. 1991; Maharaj 1993; Guzzetti et al. 1999; Nagarajan et al. 2000).

Aspect is expressed in degrees from north and clockwise, ranging from 0 to 360. The value

of -1 is used to identify flat surfaces such as flood plains, fluvial terraces. The aspect of a

slope can indirectly influence gully erosion processes, because it controls the exposition to

several climate conditions (duration of sunlight exposition, precipitation intensity, mois-

ture retention, etc.) and the vegetation cover (Dai et al. 2001; Cevik and Topal 2003; Pulice

et al. 2009). Consequently, slope aspect can play a prominent role in rock weathering and

the formation of pedo-regolithic cover. The aspect map of the study area was classified into

nine classes: flat, N, NE, E, SE, S, SW, W and NW (Fig. 2d and Table 1). On this basis, the

aspect classes of the Turbolo stream catchment highlight a fairly homogeneous distribu-

tion. Slopes facing from east to south-east slightly predominate. West and south-west

facing slopes are relatively less frequent.

3.1.5 Plan curvature

Slope plan curvature has been investigated with respect to its effect on gullies triggering

and development (Fig. 2e). The term curvature is theoretically defined as the rate of change

of slope gradient or aspect, usually in a particular direction (Wilson and Gallant 2000).

The curvature value can be evaluated by calculating the reciprocal value of the radius of

curvature of that particular direction and has been obtained directly from the derivatives of

Table 1 continued

NpixNi NpixSi DensClass Wi

1.82.4 2,935 228 0.078 0.82

2.43 432 34 0.079 0.83

33.6 55 6 0.109 1.16

TWI

00.2 78,497 2,014 0.026 -0.29

0.21 75,372 1,616 0.021 -0.47

12 10,804 312 0.029 -0.17

23 126,864 6,321 0.050 0.37

LS

0.0.2 134,380 2,998 0.022 -0.43

0.23 153,986 6,826 0.044 0.26

35 1,995 235 0.118 1.24

510 907 143 0.158 1.53

[10 303 70 0.230 1.90Plan curvature

Concave 26,837 3,824 0.142 1.43

Convex 80,580 2,342 0.029 -0.16

Flat 190,499 4,097 0.022 -0.47

Total areaP

NpixNi = 299,780P

NpixSi = 10,272 DensMap = 0.034

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a topographical surface (Wilson and Gallant 2000). Plan curvature is described as the

curvature of a contour line formed by intersecting a horizontal plane with the surface. The

influence of plan curvature on slope erosion processes is the convergence or divergence of

water during downslope flow. Positive ([0) values of plan curvatures define convexity,negative (\0) values of plan curvatures characterize concavity of slope curvature. Valuesof plan curvatures around zero indicate that the surface is flat. The relationship between

gullies and plan curvatures in the Turbolo catchment shows that gully erosion processes

commonly occur on concave slopes (Table 1).

3.1.6 Length-slope factor

The length-slope factor (LS) is a parameter used in the RUSLE equation to consider the

effect of topography on erosion (Renard et al. 1997). The topographical factor depends on

the slope steepness factor (S) and the slope length factor (L). It is essential to quantify

erosion generated by its influence on surface runoff speed and is considered a sediment

transport capacity index. There are different approaches found in literature for determining

the LS factor in a grid-based DEM. One of them is based on the upslope contributing area

of each cell, which can be calculated with the equations described by Moore and Burch

(1986):

LS fa cellsize=22:13 0:4 sin r=0:0896 1:3

where fa is flow accumulation and is derived from the DEM using a GIS accumulation

algorithm (Lee 2004) and r is slope in degrees. The LS factor was estimated on the basis ofthe flow accumulation and slope steepness (Moore and Burch 1986). Flow accumulation

was computed using the watershed delineation tool of Arcview 3.2. The spatial pattern of

the LS factor is shown in the map of Fig. 2f, and its values have been classified in five

classes. Gullies commonly occur on slopes with high LS values (Table 1).

3.1.7 Stream power index

The stream power index (SPI) (Fig. 2g) is a measure of the erosive power of water flow

based on the assumption that discharge is proportional to the specific catchment area (As)

(Moore et al. 1991).

SPI As tan rwhere As is the specific catchment area in meters and r is the slope gradient in degrees.The index SPI is one of the main factors controlling slope erosion processes, since erosive

power of running water directly influences slope toe erosion and river incision (Nefeslioglu

et al. 2008). It is also indicative of the potential energy available to entrain sediment, so

that areas with high stream power indices have a great potential for erosion (Kakembo

et al. 2009). The values of SPI factor have been classified in six classes. The overlay

between gullies inventory map and the SPI factor map shows that gully erosion processes

frequently occur on slopes with high SPI values (Table 1).

3.1.8 Topographical wetness index

The topographical wetness index (TWI) has been used extensively to describe the effect of

topography on the location and size of saturated source areas of runoff generation. TWI is a

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function of both the slope and the upstream contributing area per unit width orthogonal to

the flow direction. We used this index for this study, because TWI has been proven to be

correlated with soil erosion processes. Moore et al. (1991) proposed for the calculation of

TWI the assumption of steady state conditions and uniform soil properties (i.e. transmis-

sivity is constant throughout the catchment and equal to unity). The implementation of

TWI can be shown as:

TWI lnAs= tan rwhere As is the specific catchment area in meters and r is the slope gradient in degrees.The highest values of TWI index have been mostly recorded in valley bottoms, terraced

surfaces and gentle slopes (Fig. 2h). The values of TWI have been classified in four classes

(Table 1).

3.2 Susceptibility analysis

The second phase of this work was carried out with the implementation of a geo-database

with all the acquired data and the application of a bivariate statistic method (Information

Value, hereinafter InfVal) in GIS environment to estimate the gully erosion susceptibility.

The bivariate procedure is the simplest and the most quantitatively suitable method to

assess geomorphic processes susceptibility, even though a multivariate analysis can be

considered much more rigorous, because predisposing factors are cross-checked simulta-

neously; therefore, we have considered the main advantages of a bivariate-statistics-based

approachits easy updating of susceptibility maps and its ease to be used for land-

planningin respect with the complexity of a multivariate method, based on greater

knowledge of mathematics and statistics. Our choice is also based on the findings provided

by Su`zen and Doyuran (2003), according to which the two statistical methods (bivariate

and multivariate) produce susceptibility maps that converge in 80% of a given study area.

Up to now, the statistical bivariate analysis has been widely adopted to assess landslide

susceptibility (Yin and Yan 1988; Van Westen 1993, 1997; Rautela and Lakhera 2000;

Zezere et al. 2004; Cevik and Topal 2003; Wang and Sassa 2005; Magliulo et al. 2008;

Yalcin 2008). This statistical approach is based on the observed relationships between each

predisposing factor and the distribution of gully areas. The single thematic maps previously

produced for each predisposing factor (lithology, land use, slope, aspect, plan curvature,

SPI, TWI and LS) have been converted in raster format and combined with the whole

gullies inventory map in order to calculate the density of the gully areas for each class of

the predisposing factors; the computed density represents the susceptibility level of the

considered predisposing factor class (Carrara et al. 1995). This procedure has allowed to

obtain all the parameters needed to calculate the weighting values (Wi) for each class of

the selected predisposing factors by means of the InfVal method. In this method, a weight

value for a parameter class is defined as the natural logarithm of the gullies density class

divided by the area of gullies density over the entire study area (Van Westen 1993; Rautela

and Lakhera 2000) and can be expressed with the following formula (Yin and Yan 1988;

Van Westen 1993):

Wi ln DensClasDensMap

ln NpixSi=NpixNiPNpixSi=

PNpixNi

in which W` = weighting value of the class i; DensClas = density of the gullies in theclass i; DensMap = density of the gullies in the whole study area; NpixSi = number of

890 Nat Hazards (2011) 56:881898

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pixels that contains gullies in the class i; NpixNi = number of pixels within the class i;PNpixSi = total number of pixels that contain gullies in the whole study area;PNpixNi = total number of pixels of the whole study area. Each predisposing factor map

has been then reclassified on the basis of the calculated weighting values. Overlay pro-

cedures of the reclassified maps, performed in GIS environment, allowed to calculate, for

each point of the study area, the sum of the weighting values occurring in that given point,

thus obtaining the susceptibility value. The attained ranges of values have been subdivided

into five susceptibility classes (very low, low, moderate, high and very high), using the

natural-breaks technique (Jenks 1989). This technique identifies break point values by

picking the class limits that maximize the differences between classes and minimize the

within-class sum of squared differences. Five gully erosion susceptibility classes (Federici

et al. 2007) have been so obtained allowing to produce the gully erosion susceptibility map

of the Turbolo stream catchment.

In order to validate the susceptibility map, the gully areas dataset has been split into two

subsets using a random partition (Chung and Fabbri 2003). One subset (training set, 65%of all) has been used to obtain the weight and the susceptibility map, by means of the

InfVal method, and the second subset (validation set, remaining 35%) has been used to

validate the susceptibility map analyzing the shapes of success and prediction rate curves(Chung and Fabbri 2003). The prediction model is produced independently from the gullies

of the validation set, so that it can be treated as the result of future gully erosion

processes (Conoscenti et al. 2008).

The gully areas in the validation set and the training set have been, respectively,

overlaid with the susceptibility map, and the area of gullies per susceptibility class has

been derived using zonal statistics. This procedure has allowed to draw the prediction andthe success rate curves. The prediction rate curve allowed us to assess the predictionperformance of the method. A binary diagram has been plotted representing the cumu-

lative percentage of the gully areas in the validation set (y-axis) with respect to thecumulative percentage of the study area (x-axis), ordered according to the decreasingsusceptibility ranking (Remondo et al. 2003). The success rate curve has been obtainedby following the same procedure, but considering the gully areas training set, which have

been used in the prediction model. The success rate curve has been used to indicate thegoodness of fit of the gully erosion susceptibility map (Chung and Fabbri 2003; Remondo

et al. 2003).

4 Results and discussion

4.1 Gully erosion processes

The geomorphological analysis (aerial photographs interpretation and systematic field

checks) shows that the 5% (about 1.45 km2) of the area of the Turbolo stream basin is

affected by many permanent gullies (Figs. 1, 3); they are often characterized by incisions

with subvertical sidewalls and depth locally overcoming 8 m. In the eastern sector of the

basin, where sands and conglomerates outcrop, gully channels are narrow and usually

V-shaped, with almost bare side slopes indicating an active stage of dissection (Fig. 3a).Gullied areas are mainly characterized by dentritic and trellis drainage patterns. Gully

formation is often enhanced from November to February, the rainy season, when many

cultivated fields are unprotected because of seeding practices. Moreover, during heavy rain

events, many gullies reactivate and, in addition to vertical dissection, may frequently

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undergo headcut and valley-side retreat processes causing their lengthening and widening

(Fig. 3b). The presence of tension cracks on top of gully sides often tends to increase

falling phenomena (Collison 2001; Bull and Kirkby 2002; Poesen et al. 2002).

The most evident and spectacular landforms related to gully erosion in the study area

are represented by badlands (calanchi), almost exclusively developed into clayey litho-types (Fig. 3c) with a channel network mainly characterized by a parallel pattern. Both

concentrated runoff and falls/topples along tension cracks can be enhanced by the

occurrence of desiccation cracks (due to shrink/swell dynamics of expandable clays)

developed during dry seasons (Pulice et al. 2009).

The calanchi are often developed along ancient landslide scars, which promoted con-centration of running water (Morgan 2005). The geomorphological survey inside the

badland areas put in evidence that, within the main gullies, small mass movements and

dissecting processes work together to give blunted ridges. On the contrary, vertical dis-

section processes prevail in secondary channels, thus forming narrower and knife-edge

ridges. Moreover, along badland slopes micro-piping and rilling processes operate,

whereas debris flow cones are often accumulated at the mouth of various order drainage

channels (Fig. 3d).

Fig. 3 Gully erosion processes in the Turbolo stream catchment; a Gully formed by retrogressive erosionwith narrow and V-shaped channels; b Active gully erosion during heavy rain events, with evident falls thatcause headcut and flank retreat processes (indicated by red arrows); c Badlands in the clayey lithology;d Debris flow cones accumulated at the mouth of badland channels

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4.2 Gully erosion susceptibility assessment

The density of gully areas and the weighting values obtained using the Information Value

method are reported in Table 1, indicating the magnitude of the class of each predisposing

factor. Positive or negative values of Wi indicate that the considered class of each predis-

posing factor is relevant or not in the development of gullies, respectively (Zezere et al. 2004).

The highest density of gullies, highlighted by Wi = 0.42, occurs in areas where sand

deposits crop out. This result is in accordance with the concentration of about 60% of the

gullies mapped on this lithology. In addition, the highest Wi occurs on the slopes with

concave plan curvature (Wi = 1.43) and slope gradient[30 (Wi = 0.92) consistent sinceof steep and concave slopes that increase the volume and velocity of surface runoff,

causing soil concentrated erosion and high sediment loss (Ndomba et al. 2009). A strong

spatial correlation exists between the gully erosion processes and areas with high value of

SPI. The relevant role of the SPI factor on gully processes is confirmed by positive values

of Wi for all values of SPI, higher than 0.6. Land use factor plays an important role in gully

processes, mainly on barren and abandoned lands (Wi = 1.75), where soil surface is

exposed to raindrop impact and possible accelerated runoff (depending on slope steepness).

On the contrary, gullies density is particularly low where the gneiss bedrock crops out

(Wi = -2.42), on which the LS is low (Wi = -0.43) and SPI is low (Wi = -0.47).

Furthermore, the lowest Wi occurs where slope ranges between 0 and 5 (Wi = -0.84).As a result of the overlay of each predisposing factor map, reclassified on the basis of

the calculated weighting values, a gully erosion susceptibility map has been produced for

the Turbolo watershed (Fig. 4). The weighting values obtained have a minimum of

Fig. 4 Gully erosion susceptibility map of the Turbolo catchment

Nat Hazards (2011) 56:881898 893

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-12.16 and a maximum of 7.39, with an average value of -0.85 and a standard deviation

of 2.81. The computed pixel values have been classified into five groups of susceptibility

that are distributed in the study area as follows: 17% very low, 18% low, 24% moderate,

34% high and 7% very high; therefore, a relevant part of the study area, mainly located in

eastern sector, falls in high to very high susceptible zones. Moreover, susceptibility is

very high in the northern and western portions of the catchment, where clay deposits

mainly outcrop.

The susceptibility map obtained has been further validated. The predictive power of

the susceptibility map has been tested by analyzing their success rate and prediction rate

curves (Chung and Fabbri 2003). This comparison has allowed to verify the spatial

distribution of the gully areas in the susceptibility ranked levels (Conoscenti et al. 2008).

The calculation of the success rate and prediction rate curves for the Turbolo watershed is

shown in Fig. 5. They have very similar shape, showing a high gradient in the first part

and smoothly decrease monotonically. The prediction curve shows that 70% of the total

gully area of the validation set falls within 20% of the most susceptible areas (Fig. 5).

This result confirms both the validity of the susceptibility method and the high spatial

correlation between predisposing factors used for the analysis and the gullies. Further-

more, the validation procedure results show that the predictive power of the model is

generally satisfactory; therefore, about 90% of the gully area of the validation set is

correctly classified falling in high and very high susceptibility classes. This good result

could be overweighted if we consider that the predisposing factors could have some

relationship between each other, in particular slope has been computed also in LS, TWI

SPI factors.

5 Conclusions

In this study, the geomorphological (field survey and air photograph interpretation) and

GIS analyses allowed to characterize the morphological features and spatial distribution of

Fig. 5 Prediction rate and success rate curves that representing the accuracy of the susceptibility modelused (see text for details)

894 Nat Hazards (2011) 56:881898

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gully areas and the main geo-environmental factors that predispose the slopes to their

development in the Turbolo stream catchment (northern Calabria, Italy). Current gully

landforms affect 5% of the watershed. Gully erosion activity is controlled mainly by

geomorphological features and land use. The relationships between gullies and the selected

geo-environmental analyzed factors (lithology, slope gradient, aspect, plan curvature, SPI,

TWI, LS and land use) have been assessed using the Information Value method synthe-

sized in a gully erosion susceptibility map. In this analysis, the important role played by the

geomorphological parameters (slope gradient, slope plan curvature, SPI, etc.) in the gully

erosion processes has been highlighted. It has been observed that the gully erosion pro-

pensity increases rapidly for hill slopes above 20 and on slopes with concave shape.Therefore, the SPI and LS factors have a strong control on the susceptibility to gully

erosion. Lithology and land use appear to play an important role in controlling gully

erosion; in particular, land surfaces shaped in clay and sand deposits, barren and/or covered

by sparse vegetation resulted to be the most prone to gully erosion.

The proposed methodology to assess gully erosion susceptibility, based on a bivariate

statistical method implemented in GIS environment, has been applied using a training data

set and validated with a validation set of gully areas. The results are indicative of the high

quality of the map obtained and showed satisfactory agreement between the susceptibility

map and the gully location data. A validation procedure, based on the analysis of the

shapes of a success and a prediction rate curve, implemented to evaluate the goodness of fit

and the predictive power of the susceptibility map, respectively, showed that the prediction

image is a satisfactory predictor of future gully activity. Therefore, over 88% of the gullies

of the validation set are correctly classified falling in high and very high susceptibility

classes.

Finally, the results showed that the choice of suitable predisposing factors together with

the bivariate statistical method and the application of geographical information systems are

able to successfully identify areas that are susceptible to gully erosion. The produced

susceptibility map, using a methodology easy to apply and to update, represents a useful

tool for sustainable planning, conservation and protection of land from gully processes.

Therefore, this methodology can be used to assess gully erosion susceptibility in other

areas of Calabria, as well as in other similar regions, especially in the Mediterranean area.

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Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy)AbstractIntroductionGeo-environmental setting of the study areaMaterials and methodsAnalysis of predisposing factorsLithologyLand useSlopeAspectPlan curvatureLength-slope factorStream power indexTopographical wetness index

Susceptibility analysis

Results and discussionGully erosion processesGully erosion susceptibility assessment

ConclusionsReferences

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