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Hamid Reza Pourghasemi - One of the best experts on this subject based on the ideXlab platform.

  • Spatial Modeling of Gully Erosion Using Linear and Quadratic Discriminant Analyses in GIS and R
    Spatial Modeling in GIS and R for Earth and Environmental Sciences, 2020
    Co-Authors: Alireza Arabameri, Hamid Reza Pourghasemi
    Abstract:

    Abstract Gully Erosion is one of the most important types of water Erosion that causes the destruction of agricultural and range lands in arid and semiarid areas. The main purpose of this study was to produce Gully Erosion susceptibility maps (GESMs) using R-based data-mining linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) models and to compare their performances in Shahroud Watershed, Semnan Province, Iran. The important input factors for Gully Erosion susceptibility assessment were obtained from different sources such as literature reviews and field surveys. First, 172 Gully Erosion locations were obtained using Google Earth images and extensive field surveys. Then, the Gully inventory map was randomly classified into two datasets: 70% (121 Gully locations) for training the models and 30% (51 Gully locations) for validation purposes. Second, 12 Gully Erosion conditioning factors, including elevation, slope degree, slope aspect, plan curvature, distance from river, drainage density, convergence index, topography wetness index, distance from road, land use/land cover, normalized difference vegetation index, and lithology were selected. Subsequently, GESMs created using LDA and QDA models in R statistical software and they were divided into four classes including low, moderate, high, and very high. Finally, the validation dataset, which was not used in the modeling process, was considered to validate GESMs using the receiver operating characteristics curve. Results of validation showed that LDA and QDA models with area under the curve values of 0.875 and 0.8620 are good predictors for Gully Erosion susceptibility mapping. Also, the results indicate that in LDA and QDA models, 13.44% and 22.61% of total area is located in the very high susceptibility class to soil Erosion, respectively. The outcome of this research could represent a fundamental tool for sustainable land use planning, protecting the land from water-related soil Erosion processes, and Gully Erosion hazard mitigation in the study area.

  • Gully Erosion Susceptibility Mapping Based on Bayesian Weight of Evidence
    Gully Erosion Studies from India and Surrounding Regions, 2019
    Co-Authors: Pravat Kumar Shit, Gouri Sankar Bhunia, Hamid Reza Pourghasemi
    Abstract:

    Identifying Gully Erosion susceptibility in cultivated region is important for the manager and decision makers. The present study demonstrated the application of the weight of evidence (WoE) model (a Bayesian probability model) for Gully Erosion susceptibility mapping using geographic information system (GIS) and remote sensing (RS) tools in the southwestern part of West Bengal, India. Eight Gully Erosion conditioning geo-environmental factors were considered for the susceptibility analysis, such as lithology, geomorphology, soil type, land use, slope, slope length (LS), stream power index (SPI), and wetness index (WI). Tests of conditional independence were performed for the selection of eight Gully conditioning factors. Finally, Gully Erosion susceptibility map was prepared using the ratings of each Gully conditioning factor. The resultant susceptibility map was validated using the area under the curve (AUC) method. The results indicated that the WoE model had an AUC value of 67.8%. Therefore, the WoE model is useful in Gully Erosion susceptibility mapping and helps decision makers in land-use planning.

  • A Review on the Gully Erosion and Land Degradation in Iran
    Gully Erosion Studies from India and Surrounding Regions, 2019
    Co-Authors: Mohsen Hosseinalizadeh, Mohammad Alinejad, Ali Mohammadian Behbahani, Farhad Khormali, Narges Kariminejad, Hamid Reza Pourghasemi
    Abstract:

    Water-induced soil Erosion is one of the main causes of land degradation. In this category, Gully Erosion is the most important type of Erosion which causes different problems and occurs in various pedo-climatic regions of Iran. For this study, around 60 relevant Gully Erosion case studies in the last decades with acceptable spatial patterns were considered. The most important control factors and analysis methods were considered. Most of the studies were carried out in semiarid and arid climatic regions. Recently, data mining and high techniques are commonly used in Gully Erosion susceptibility studies. Gully Erosion was recorded in different climatic regions with annual rainfall range of 81–1200 mm. It also occurred in different topographic conditions (mean slope 2–27%) and different lithological units. Gully headcut retreatment varied from 0.99 to 1.4 m year−1 in various pedo-climatic regions, and ephemeral Gully Erosion in semiarid climate of Iranian Loess Plateau has resulted in a soil loss of 4 t ha−1 year−1. Based on the obtained results, enough studies paid to Gully Erosion and various controlling factors have been determined. So its remediation and control should be regarded in future studies.

  • Mapping and Preparing a Susceptibility Map of Gully Erosion Using the MARS Model
    Gully Erosion Studies from India and Surrounding Regions, 2019
    Co-Authors: Mahdis Amiri, Hamid Reza Pourghasemi
    Abstract:

    Preparing and mapping Gully Erosion (GE) is a basic instrumentation to land use projecting and reducing destruction of the land. The purpose of the current investigation was to assess Gully Erosion spatial modeling using multivariate adaptive regression spline (MARS) model in Maharlou watershed, Fars Province, Iran. The current study is consisted from two important parts including (1) recognizing dependent and variables, e.g., Gully Erosion inventory map (GEIM) and Gully effective agents, and (2) running a famous machine learning algorithm named the MARS in order to Gully Erosion mapping. Gully Erosion inventory map is randomly separated into two categories: training and validation datasets. Then, nine causative factors including land use, distance from rivers, clay percent, geology, pH, NDVI, drainage density, distance from roads, and slope direction are recognized, and their maps are classified in the ArcGIS. Also, the GESM was created using the MARS model in the R statistical environment. The outcomes of the MARS technique of the 30% of the unused Gully points used in the modeling procedure based on the ROC curve. Results demonstrated that the ultimate Gully Erosion map had a top precision with AUC values 96.3% for accuracy data set.

  • Gully Erosion Susceptibility Assessment Through the SVM Machine Learning Algorithm (SVM-MLA)
    Gully Erosion Studies from India and Surrounding Regions, 2019
    Co-Authors: Hamid Reza Pourghasemi, Amiya Gayen, Sk. Mafizul Haque
    Abstract:

    Gully Erosion susceptibility mapping (GESM) is a valuable tool for sustainable land use management and reducing soil Erosion. Gully Erosion and its formation are a natural process; it greatly threatens agriculture, environment, ecosystem disruption, and natural resources. The objective of this present study is to develop a GESM by implementation of well acceptable SVM learning algorithm in Golestan Province, Kalaleh Township, Iran. Primarily, Gully sites were obtained by comprehensive field observations. After that, 12 Gully Erosion predisposing factors were selected to assess the Gully Erosion susceptibility map. The 12 conditioning factors were aspect, altitude, drainage density, lithology, slope angle, slope length, distance from river, profile curvature, drainage density, TWI, distance from road, and plan curvature. Finally, Gully Erosion susceptibility map was prepared using the SVM model in “R” environment. In the final stage, assessment of the prediction accuracy of the susceptibility model with the help of training (70%) and validation datasets (30%) of Gully location was done. The predicted susceptibility map was validated with the help of receiver operating characteristic (ROC) curve, true skill statistics (TSS), and deviance value. The results indicated that the areas under the curve (AUC) were calculated as 94.3% and 97.0% based on validation and training dataset, respectively. Furthermore, the TSS, deviance, and correlation values were 0.84, 0.50, and 0.85, respectively. So, the results of other indices including, sensitivity, specificity, and Cohen’s Kappa (CK) showed that SVM model has reasonable prediction accuracy for the cases of Gully Erosion susceptibility assessment. As regards the SVM model, a total area of 11.66% was identified as the hazard prone area of the mentioned Town ship. So, it is concluded that the Gully Erosion map serves as an important tool for protective action and watershed management, specifically at the initiation of the Gully to protect the development of land degradation.

Jean Poesen - One of the best experts on this subject based on the ideXlab platform.

  • Gully Erosion and control in the Tembien Highlands
    Geo-trekking in Ethiopia’s Tropical Mountains, 2019
    Co-Authors: Amaury Frankl, Jean Poesen, Etefa Guyassa, Jan Nyssen
    Abstract:

    Over the past decades, many investments in soil conservation have been made to limit the negative effects of Gully Erosion in Dogu’a Tembien. Gully Erosion remains, however, a key soil Erosion process resulting in land degradation in the fragile environment (Photo 22.1).

  • Gully Erosion as a natural and human induced hazard
    Natural Hazards, 2015
    Co-Authors: Ion Ionita, Michael A Fullen, Wojciech Zglobicki, Jean Poesen
    Abstract:

    The Author(s) 2015. This article is published with open access at Springerlink.com Gully Erosion is an important environmental threat throughout the world and affects multiple soil and land functions. There is ample physical evidence of intense Gully Erosion occurring at various times in the past in different parts of the world. Gullies are one of the few sources of morphological evidence in the landscape of past phases of intense soil Erosion, reflecting the impact of environmental change (especially due to interactions between geomorphological features, changes in land use and extreme climatic events). Gully Erosion represents a major sediment source, although Gully channels often occupy \5 % of the area of a catchment. The development of gullies increases run-off and sediment connectivity in the landscape, hence increasing the risk of flooding and reservoir sedimentation (Verstraeten and Poesen 1999; Poesen et al. 2003). Assessing interactions between environmental change and land degradation is a key issue for environmental scientists, land managers and policy-makers.

  • challenges in Gully Erosion research
    Landform Analysis, 2011
    Co-Authors: Jean Poesen
    Abstract:

    Although the number of publications on Gully Erosion has increased over the last decade, there are still various as- pects of Gully Erosion that deserve more research efforts. Some of these, discussed in this contribution, are Gully Erosion in historical times, measuring techniques, processes of Gully initiation, development and infilling, the interaction between Gully Erosion with hydrological and other soil degradation processes (e.g. piping, landsliding, tillage Erosion and Erosion induced by land levelling), Gully Erosion models, effective and efficient Gully prevention and control measures. A better understand- ing of these aspects would allow one to better predict the impact of environmental change, Gully prevention and control mea- sures on Gully Erosion and Gully infilling rates at a range of temporal and spatial scales and for various types of environments, and the effects of Gully Erosion on sediment yield, hydrological process intensities and landscape evolution.

  • assessment of Gully Erosion rates through interviews and measurements a case study from northern ethiopia
    Earth Surface Processes and Landforms, 2006
    Co-Authors: Jean Poesen, Jan Nyssen, M Veyretpicot, J Moeyersons, Mitiku Haile, Jozef Deckers, Joke Dewit, J Naudts, Kassa Teka
    Abstract:

    Gullying has been widespread in the Ethiopian Highlands during the 20th century. It threatens the soil resource, lowers crop yields in interGully areas through enhanced drainage and desiccation, and aggravates flooding and reservoir siltation. Knowing the age and rates of Gully development during the last few decades will help explain the reasons for current land degradation. In the absence of historical written or photographic documentation, the AGERTIM method (Assessment of Gully Erosion Rates Through Interviews and Measurements) has been developed. It comprises measurements of contemporary Gully volumes, monitoring of Gully evolution over several years and semi-structured interview techniques. Gully Erosion rates in the Dogu'a Tembien District, Tigray, Ethiopia, were estimated in three representative case-study areas. In Dingilet, Gullying started around 1965 after gradual environmental changes (removal of vegetation from cropland in the catchment and eucalyptus plantation in the valley bottom); rill-like incisions grew into a Gully, which increased rapidly in the drier period between 1977 and 1990. The estimated evolution of the total Gully volume in the other areas show patterns similar to those of the Dingilet Gully. Average Gully Erosion rate over the last 50 years is 6·2 t ha−1 a−1. Since 1995, no new gullies have developed in the study area. Area-specific short-term Gully Erosion rates are now on average 1·1 t ha−1 a−1. The successful application of the AGERTIM method requires an understanding of the geomorphology of the study area and an integration of the researchers with the rural society. It reveals that rapid Gully development in the study area is some 50 years old and is mainly caused by human-induced environmental degradation. Under the present-day conditions of ‘normal’ rain and catchment-wide soil and water conservation, Gully Erosion rates are decreasing. Copyright © 2006 John Wiley & Sons, Ltd.

  • Gully Erosion impacts factors and control
    Catena, 2005
    Co-Authors: Christian Valentin, Jean Poesen, Yong Li
    Abstract:

    Gully Erosion attracts increasing attention from scientists as reflected by two recent international meetings [Poesen and Valentin (Eds.), Catena 50 (2–4), 87–564; Li et al., 2004. Gully Erosion Under Global Change. Sichuan Science Technology Press, Chengu, China, 354 pp.]. This growing interest is associated with the increasing concern over off-site impacts caused by soil Erosion at larger spatial scales than the cultivated plots. The objective of this paper is to review recent studies on impacts, factors and control of Gully Erosion and update the review on dGully Erosion and environmental change: importance and research needsT [Poesen et al., 2003. Catena 50 (2–4), 91–134.]. For the farmers, the development of gullies leads to a loss of crop yields and available land as well as an increase of workload (i.e. labour necessary to cultivate the land). Gullies can also change the mosaic patterns between fallow and cultivated fields, enhancing hillslope Erosion in a feedback loop. In addition, gullies tend to enhance drainage and accelerate aridification processes in the semi-arid zones. Fingerprinting the origin of sediments within catchments to determine the relative contributions of potential sediment sources has become essential to identify sources of potential pollution and to develop management strategies to combat soil Erosion. In this respect, tracers such as carbon, nitrogen, the nuclear bomb-derived radionuclide 137 Cs, magnetics and the strontium isotopic ratio are increasingly used to fingerprint sediment. Recent studies conducted in Australia, China, Ethiopia and USA showed that the major part of the sediment in reservoirs might have come from Gully Erosion. Gullies not only occur in marly badlands and mountainous or hilly regions but also more globally in soils subjected to soil crusting such as loess (European belt, Chinese Loess Plateau, North America) and sandy soils (Sahelian zone, north-east Thailand) or in soils prone to piping and tunnelling such as dispersive soils. Most of the time, the Gullying processes are triggered by

Giuliano Rodolfi - One of the best experts on this subject based on the ideXlab platform.

  • Gully Erosion modelling and landscape response in the Mbuluzi River catchment of Swaziland
    Catena, 2020
    Co-Authors: Aleksey Sidorchuk, Michael Märker, Sandro Moretti, Giuliano Rodolfi
    Abstract:

    Abstract In southern African countries soil Erosion and the related problems, such as water quality issues or decreasing soil productivity, are the main topics affecting the inhabitants of both rural and urban areas. Therefore, the attention has been recently placed on those problems related to soil Erosion. This can also be documented by an increasing number of studies carried out on Erosion and by the development and application of Erosion models. Nevertheless, Gully Erosion phenomena have been widely neglected in Erosion modelling. This is because the development of Erosion models was focused on those regions with an intense agriculture typical of developed countries on the one hand, and because of the spatial and temporal heterogeneity of Gully Erosion processes on the other hand. This study regards the identification of Gully Erosion forms and processes in the Mbuluzi River catchment (Kingdom of Swaziland) by using the Erosion Response Units (ERU) concept. The following modelling of Gully Erosion was done through the stable Gully model [Catena 37 (1999) 401]. The input data were obtained through the application of remote sensing techniques (API method) and GIS-analyses. The example from Swaziland shows that the applied methods are able to identify areas affected by Gully Erosion. Furthermore, it is possible to estimate the amount of soil loss due to Gully Erosion, which, for example, is not taken into consideration by the USLE-type models.

  • Gully Erosion modelling and landscape response in the Mbuluzi River catchment of Swaziland
    Catena, 2003
    Co-Authors: Aleksey Sidorchuk, Michael Märker, Sandro Moretti, Giuliano Rodolfi
    Abstract:

    In southern African countries soil Erosion and the related problems, such as water quality issues or decreasing soil productivity, are the main topics affecting the inhabitants of both rural and urban areas. Therefore, the attention has been recently placed on those problems related to soil Erosion. This can also be documented by an increasing number of studies carried out on Erosion and by the development and application of Erosion models. Nevertheless, Gully Erosion phenomena have been widely neglected in Erosion modelling. This is because the development of Erosion models was focused on those regions with an intense agriculture typical of developed countries on the one hand, and because of the spatial and temporal heterogeneity of Gully Erosion processes on the other hand. This study regards the identification of Gully Erosion forms and processes in the Mbuluzi River catchment (Kingdom of Swaziland) by using the Erosion Response Units (ERU) concept. The following modelling of Gully Erosion was done through the stable Gully model [Catena 37 (1999) 401]. The input data were obtained through the application of remote sensing techniques (API method) and GIS-analyses. The example from Swaziland shows that the applied methods are able to identify areas affected by Gully Erosion. Furthermore, it is possible to estimate the amount of soil loss due to Gully Erosion, which, for example, is not taken into consideration by the USLE-type models. © 2003 Elsevier Science B.V. All rights reserved.

Shuwen Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Gully Erosion regionalization of black soil area in northeastern china
    Chinese Geographical Science, 2017
    Co-Authors: Jiuchun Yang, Shuwen Zhang, Liping Chang, Fei Li, Tianqi Li
    Abstract:

    Gully Erosion is the frequent and main form of soil Erosion in the black soil area of the northeastern China, which is one of the most important commodity grain production bases in China. It is encroaching upon the fertile farmland there. Regionalization of Gully Erosion can reveal the spatial distribution and regularity of the development of Gully Erosion. Based on the eco-geographical regional background features of the black soil area, this study combined the regionalization with influencing factors of the development of Gully Erosion. GIS spatial analysis, geostatistical analysis, spatial statistics, reclassification, debris polygon processing and map algebra methods were employed. As a result, the black soil area was divided into 12 subregions. The field survey data on type, length, volume and other characteristics indicators of Gully Erosion were used to calibrate the results. Then the features of every subregion, such as where the Gully Erosion is, how serious it is, and why it happens and develops, were expounded. The result is not only an essential prerequisite for Gully Erosion surveys and monitoring, but also an important basis for Gully Erosion prevention.

  • Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China
    Sustainability, 2016
    Co-Authors: Ranghu Wang, Jiuchun Yang, Shuwen Zhang, Liping Chang, Luoman Pu, Chaobin Yang, Lingxue Yu, Kun Bu
    Abstract:

    The black soil region of Northeast China has suffered from severe soil Erosion by water. Hillslope and Gully Erosion are the main Erosion types. The objective of this research was to integrate the assessment of hillslope and Gully Erosion and explore spatial coupling relations between them in the Mushi River sub-catchment using geographical conditions monitoring (GCM) including remote sensing (RS) and geographic information system (GIS) techniques. The revised universal soil loss equation (RUSLE) model and visual satellite image interpretation were used to evaluate hillslope and Gully Erosion, respectively. The results showed that (1) the study area as a whole had slight Erosion due to rill and sheet Erosion, but suffered more serious Gully Erosion, which mainly occurs in cultivated land; (2) GCM contributed to the overall improvement of soil Erosion assessment, but the RUSLE model likely overestimates the Erosion rate in dry land; (3) the hillslope and Gully Erosion were stronger on sunny slopes than on shady slopes, and mainly occurred at middle elevations. When the slope was greater than 15 degrees, the slope was not the main factor restricting the Erosion, while at steeper slopes, the dominant forest land significantly reduced the soil loss; (4) trends of Gully Erosion intensity and density were not consistent with the change in soil Erosion intensity. To our knowledge, this study was one of the first that attempted to integrate Gully Erosion and hillslope Erosion on a watershed scale. The findings of this study promote a better understanding of the spatial coupling relationships between hillslope and Gully Erosion and similarly indicate that GCM, RS, and GIS can be used efficiently in the hilly black soil region of Northeast China to assess hillslope and Gully Erosion.

  • A study of Gully Erosion process in rolling hill region of Northeast China based on GIS
    2013 21st International Conference on Geoinformatics, 2013
    Co-Authors: Tianqi Li, Shuwen Zhang
    Abstract:

    Gully Erosion of tillage land in northeast China cause mass land degradation and threaten the safety of grain production of China. The relationship between the spatial distribution of gullies and topographic factors, such as slope angle, aspect, slope form, SPI and TWI, as well as land use and lithology are discussed in the Keshan County of Heilongjiang province. The topographic factors are derived from Digital Elevation Model, and landuse as well as Gully distribution data were interpreted from satellite images and field survey. Basis on mapped controlling factors, single factor analysis was taken to recognize high risk region of Gully Erosion. The result of overlay analysis showed that nearly 80% of gullies occurred in farmland and concave slope elements; high slope angle and SPI value are identified as the high Gully initiation regions due to the enhancement of runoff convergence. The two patterns of Gully Erosion were identified via the overlay analysis of different substratum. Based on the analysis, two processes of Gully Erosion were identified.

  • Geoinformatics - A study of Gully Erosion process in rolling hill region of Northeast China based on GIS
    2013 21st International Conference on Geoinformatics, 2013
    Co-Authors: Tianqi Li, Shuwen Zhang
    Abstract:

    Gully Erosion of tillage land in northeast China cause mass land degradation and threaten the safety of grain production of China. The relationship between the spatial distribution of gullies and topographic factors, such as slope angle, aspect, slope form, SPI and TWI, as well as land use and lithology are discussed in the Keshan County of Heilongjiang province. The topographic factors are derived from Digital Elevation Model, and landuse as well as Gully distribution data were interpreted from satellite images and field survey. Basis on mapped controlling factors, single factor analysis was taken to recognize high risk region of Gully Erosion. The result of overlay analysis showed that nearly 80% of gullies occurred in farmland and concave slope elements; high slope angle and SPI value are identified as the high Gully initiation regions due to the enhancement of runoff convergence. The two patterns of Gully Erosion were identified via the overlay analysis of different substratum. Based on the analysis, two processes of Gully Erosion were identified.

  • Relationship between Gully Erosion and underlying layers
    2011 International Conference on Multimedia Technology, 2011
    Co-Authors: Tianqi Li, Shuwen Zhang
    Abstract:

    Soil Erosion is an important environment disaster in black soil region due to the reclamation in past 50 years. Gullies in black soil region destroy farmland and it is a huge threatens of grain productivity security. This paper adopted Spot5 image to interpret Gully distribution of study area in northern Nemoer Basin. Basic topography factors were extracted from SRTM elevation data set. The soil data and stratum data was digitized from papery map. Using spatial overlay analysis module in GIS software, this paper analyzed the relationship between property of underlying layers and Gully density distribution. The result shows that soil with high porosity is easily suffered by Gully Erosion, but the surface property is not the decisive factor of distribution of Gully density. In gentle slope region, Gully density has significant relationship with K factor. Along with the increment of slope, the correlation coefficient is decreased. Gully density in different stratum layers shows that there are two patters in Gully density distribution due to stratum property. One leads to gullies with shallow depth and wide width; the other one leads to deep gullies with narrow width. Single factor of Gully Erosion can hardly correlate with Gully density very well, there is a demand of study of relationship between component factor and Gully density.

Omid Rahmati - One of the best experts on this subject based on the ideXlab platform.

  • modelling Gully Erosion susceptibility in a semi arid region iran investigation of applicability of certainty factor and maximum entropy models
    Science of The Total Environment, 2019
    Co-Authors: Ali Azareh, Omid Rahmati, Himan Shahabi, Elham Rafieisardooi, Joel B Sankey, Baharin Bin Ahmad
    Abstract:

    Abstract Gully Erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of Gully Erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping Gully Erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to Gully Erosion were considered as predictor variables of Gully Erosion susceptibility. Based on an existing differential GPS survey inventory of Gully Erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional Gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of Gully Erosion susceptibility in this region of Iran. The Gully Erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.

  • Application of Fuzzy Analytical Network Process Model for Analyzing the Gully Erosion Susceptibility
    Advances in Natural and Technological Hazards Research, 2018
    Co-Authors: Bahram Choubin, Omid Rahmati, Nasser Tahmasebipour, Bakhtiar Feizizadeh, Hamid Reza Pourghasemi
    Abstract:

    Soil Erosion is one of the most important processes in land degradation especially in semi-arid areas such as Iran. Awareness from susceptible areas to Erosion is essential for decreasing the damages and restoration of the eroded areas and achieving the sustainable development goals. Thus, the main purposes of this study are prioritizing the effective variables in engender and extend of Gully Erosion and predicting the Gully Erosion susceptibility map in the Kashkan-Poldokhtar Basin, Iran. In order to achieve this purpose, the fuzzy analytical network process (Fuzzy ANP) was applied by means of considering the interrelationship network within the effective criteria on the Gully Erosion. The assessing step were conducted by the fuzzy approach in associate with the expert’s opinions for determining the susceptible areas to Gully Erosion. Eventually, Gully Erosion susceptibility map was produced based on Fuzzy ANP weights and GIS aggregation functions. Results were validated by applying the known gullies collected in field surveys by GPS. The ROC curve was applied to investigate the susceptibility model’s performance. Results of the Fuzzy-ANP was revealed that drainage density, soil texture, and lithology are most important factors for Gully Erosion. In addition, results delivered the accuracy of 90.4% for the study area which is very acceptable. This research highlights that Fuzzy ANP as an efficient approach for producing the susceptibility map of Gully Erosion, especially in an environment with incomplete datasets.

  • Evaluation of different machine learning models for predicting and mapping the susceptibility of Gully Erosion
    Geomorphology, 2017
    Co-Authors: Omid Rahmati, Nasser Tahmasebipour, Ali Haghizadeh, Hamid Reza Pourghasemi, Bakhtiar Feizizadeh
    Abstract:

    Gully Erosion constitutes a serious problem for land degradation in a wide range of environments. The main objective of this research was to compare the performance of seven state-of-the-art machine learning models (SVM with four kernel types, BP-ANN, RF, and BRT) to model the occurrence of Gully Erosion in the Kashkan-Poldokhtar Watershed, Iran. In the first step, a Gully inventory map consisting of 65 Gully polygons was prepared through field surveys. Three different sample data sets (S1, S2, and S3), including both positive and negative cells (70% for training and 30% for validation), were randomly prepared to evaluate the robustness of the models. To model the Gully Erosion susceptibility, 12 geo-environmental factors were selected as predictors. Finally, the goodness-of-fit and prediction skill of the models were evaluated by different criteria, including efficiency percent, kappa coefficient, and the area under the ROC curves (AUC). In terms of accuracy, the RF, RBF-SVM, BRT, and P-SVM models performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.9), which resulted in accurate predictions. Therefore, these models can be used in other Gully Erosion studies, as they are capable of rapidly producing accurate and robust Gully Erosion susceptibility maps (GESMs) for decision-making and soil and water management practices. Furthermore, it was found that performance of RF and RBF-SVM for modelling Gully Erosion occurrence is quite stable when the learning and validation samples are changed.

  • Gully Erosion susceptibility mapping the role of gis based bivariate statistical models and their comparison
    Natural Hazards, 2016
    Co-Authors: Omid Rahmati, Ali Haghizadeh, Hamid Reza Pourghasemi, Farhad Noormohamadi
    Abstract:

    Abstract Gully Erosion is a key issue in natural resource management that often has severe environmental, economic, and social consequences. The objective of the present study is to assess the capability of weights-of-evidence (WofE) and frequency ratio (FR) models for spatial prediction of Gully Erosion susceptibility and characterizing susceptibility conditions at Chavar region, Ilam province, Iran. At first, a Gully Erosion inventory map is prepared, using multiple field surveys. In total, of the 63 gullies which have been identified, 44 (70 %) cases are randomly algorithm selected to build Gully susceptibility models, while the remaining 19 (30 %) cases are used to validate the models. The effectiveness of Gully Erosion susceptibility assessment via GIS-based models depends on appropriate selection of the conditioning factors which play an important role in Gully Erosion. Learning vector quantization (LVQ), one of the supervised neural network methods, is employed in order to estimate variable importance. In this research, the selected conditioning factors are: lithology, land use, distance from river, soil texture, slope degree, slope aspect, plan curvature, topographic wetness index, drainage density, and altitude. Finally, validation of the Gully dataset which has not been utilized during the spatial modeling process is applied to validate the Gully susceptibility maps. The receiver operating characteristic curves for each Gully susceptibility map (i.e., produced by WofE and FR) are drawn, and the areas under the curves (AUC) are calculated. The results show that the Gully Erosion susceptibility map produced by the frequency ratio model (AUC = 78.11 %) functions well in prediction compared with the WofE model (AUC = 70.07 %). Furthermore, LVQ results reveal that distance from river, drainage density, and land use are the most effective factors.