A new empirical model for estimating calanchi Erosion in Sicily, Italy

Caraballo-Arias, Nathalie Almaru; Conoscenti, Christian; Stefano, Costanza Di; Ferro, Vito

doi:10.1016/j.geomorph.2014.12.017

Cited by 20 publications

(15 citation statements)

References 35 publications

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“…The geomorphological term 'badland' belongs to unique uncovered and shredded landscapes with steep slopes and high erosion rates being inappropriate for any kind of agricultural use (Nadal-Romero et al 2007;Caraballo-Arias et al 2015;Pintér et al 2015). Geological and mainly the lithological factors have the main influence on the evolution of these landforms (FarabegoliAgostini 2000;Neugirg et al 2016) since the occurrence of badlands is significant on soft materials (Caraballo-Arias et al 2015).…”

Section: Introductionmentioning

confidence: 99%

UAS photogrammetry and object-based image analysis (GEOBIA): erosion monitoring at the Kazár badland, Hungary

Bertalan¹,

Túri²,

Szabó³

2016

Landsc. environ.

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A remarkable badland valley is situated near Kazár, NE-Hungary, where rhyolite tuff outcrops as greyish white cliffs and white barren patches. The landform is shaped by gully and rill erosion processes. We performed a preliminary state UAS survey and created a digital surface model and ortophotograph. The flight was operated with manual control in order to perform a more optimal coverage of the aerial images. The overhanging forests induced overexposed photographs due to the higher contrast with the bare tuff surface. The multiresolution segmentation method allowed us to classify the ortophotograph and separate the tuff surface and the vegetation. The applied methods and final datasets in combination with the subsequent surveys will be used for detecting the recent erosional processes of the Kazár badland.

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Section: Introductionmentioning

confidence: 99%

UAS photogrammetry and object-based image analysis (GEOBIA): erosion monitoring at the Kazár badland, Hungary

Bertalan¹,

Túri²,

Szabó³

2016

Landsc. environ.

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“…Finally, the third component influences the distribution of erosion/deposition processes within a calanchi catchment (Figure 6). Caraballo-Arias et al (2015) assumed that the erosion processes developing on calanchi landforms could be explained by the following functional relationship: (10) in which j is a functional symbol, Vc (m 3 ) is the eroded volume of the calanchi, A (m 2 ) is the plane area of its drainage basin, LDN (m) is the total drainage network length contained in the calanchi, s ( m /m) is the mean slope of the calanchi basin, LB (m) is the plane length of the drainage basin, N is the total number of streams in the calanchi, P (m) is the perimeter of the basin, d (m) is the mean diameter of the solid material contained in the basin area, gs (N/m 3 ) is the specific weight of the solid material, i (mm/h) is the mean rainfall intensity and Ks is the soil hydraulic conductivity (mm/h).…”

Section: Modelling Badland Erosion Volumementioning

confidence: 99%

“…(10) includes eleven dimensional physical variables and three fundamental physical units (length, time and force), the same relationship can be expressed by using eight dimensionless groups Pi (i=1 to 8): (11) Choosing as governing variables having independent dimensions, A, gs and i, which are also representative of the basin morphology, soil characteristic and rainfall erosive power of the studied physical system, and applying the P-Theorem, Caraballo-Arias et al (2015) obtained the following functional relationship:…”

Section: Modelling Badland Erosion Volumementioning

confidence: 99%

“…Eq. (14) was calibrated and validated by Caraballo-Arias et al (2015) using four different data sets, each including the morphometric characteristics of a group of small hydrographic units partially or completely covered by calanchi landforms. Two data sets correspond to the twocalanchi areas Anticaglia (18 basins) and Bicchinel (45 basins) and other two data sets were derived from Buccolini et al (2012) (65 calanchi basins) and from Buccolini and Coco (2013) (81 calanchi basins).…”

Section: Modelling Badland Erosion Volumementioning

confidence: 99%

“…(14) could be neglected, the following relationship was obtained by Caraballo-Arias et al (2015): (15) Since the predictive skill of Eq. (15) was found to be sensitive to the relative extent of calanchi landforms within their tributary areas, Caraballo-Arias et al (2015) included the eroded area (AE) in the following dimensionless group place to P9:…”

Section: Reviewmentioning

confidence: 99%

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Assessing, measuring and modelling erosion in calanchi areas: a review

Caraballo-Arias¹,

Ferro²

2016

J Agricult Engineer

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Calanchi are erosion landforms characterised by a heavily dissected terrain with steep, unvegetated slopes and channels with a dendritic pattern, which rapidly incise and extend headwards. Recent literature focusing on badland systems highlights their similarity with other larger fluvial landforms, stating that these behave as a full size laboratory, due to their rapid development in space and time and to the diversity of geomorphic processes involved.In this paper, a brief review of the most important results on badland research is firstly presented. Then, the morphometric similarity between calanchi and other erosion landforms is discussed. Finally, models quantitatively relating the volume of sediments eroded from calanchi landforms and a set of geometric features of their tributary areas, by exploiting the dimensional analysis and the self-similarity theory, are presented.

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Assessment of calanchi and rill–interrill erosion susceptibilities using terrain analysis and geostochastics: A case study in the Oltrepo Pavese, Northern Apennines, Italy

Bosino

Giordani

Quénéhervé

et al. 2020

Earth Surf Processes Landf

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Soil erosion is one of the most important environmental problems distributed worldwide. In the last decades, numerous studies have been published on the assessment of soil erosion and the related processes and forms using empirical, conceptual and physically based models. For the prediction of the spatial distribution, more and more sophisticated stochastic modelling approaches have been proposed – especially on smaller spatial scales such as river basins. In this work, we apply a maximum entropy model (MaxEnt) to evaluate badlands (calanchi) and rill–interrill (sheet erosion) areas in the Oltrepo Pavese (Northern Apennines, Italy). The aim of the work is to assess the important environmental predictors that influence calanchi and rill–interrill erosion at the regional scale. We used 13 topographic parameters derived from a 12 m digital elevation model (TanDEM‐X) and data on the lithology and land use. Additional information about the vegetation is introduced through the normalized difference vegetation index based on remotely sensed data (ASTER images). The results are presented in the form of susceptibility maps showing the spatial distribution of the occurrence probability for calanchi and rill–interrill erosion. For the validation of the MaxEnt model results, a support vector machine approach was applied. The models show reliable results and highlight several locations of the study area that are potentially prone to future soil erosion. Thus, coping and mitigation strategies may be developed to prevent or fight the soil erosion phenomenon under consideration. © 2020 John Wiley & Sons, Ltd.

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A new empirical model for estimating calanchi Erosion in Sicily, Italy

Cited by 20 publications

References 35 publications

UAS photogrammetry and object-based image analysis (GEOBIA): erosion monitoring at the Kazár badland, Hungary

UAS photogrammetry and object-based image analysis (GEOBIA): erosion monitoring at the Kazár badland, Hungary

Assessing, measuring and modelling erosion in calanchi areas: a review

Assessment of calanchi and rill–interrill erosion susceptibilities using terrain analysis and geostochastics: A case study in the Oltrepo Pavese, Northern Apennines, Italy

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