Search results for "Gully erosion"
showing 10 items of 28 documents
Measuring, modelling and managing gully erosion at large scales: A state of the art
2018
Soil erosion is generally recognized as the dominant process of land degradation. The formation and expansion of gullies is often a highly significant process of soil erosion. However, our ability to assess and simulate gully erosion and its impacts remains very limited. This is especially so at regional to continental scales. As a result, gullying is often overlooked in policies and land and catchment management strategies. Nevertheless, significant progress has been made over the past decades. Based on a review of >590 scientific articles and policy documents, we provide a state-of-the-art on our ability to monitor, model and manage gully erosion at regional to continental scales. In this…
Gully erosion susceptibility assessment by means of GIS-based logistic regression: A case of Sicily (Italy)
2014
article i nfo Article history: This research aims at characterizing susceptibility conditions to gully erosion by means of GIS and multivariate statistical analysis. The study area is a 9.5 km 2 river catchment in central-northern Sicily, where agriculture ac- tivities are limited by intense erosion. By means of field surveys and interpretation of aerial images, we prepared a digitalmap of thespatial distribution of 260 gulliesinthestudy area.Inaddition,fromavailable thematicmaps, a 5 m cell size digital elevation model and field checks, we derived 27 environmental attributes that describe the variability of lithology, land use, topography and road position. These attributes were selected f…
Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gully erosion
2019
Assessing the performance of GIS- based machine learning models withdifferent accuracy measures for determining susceptibility togully erosionYounes Garosia, Mohsen Sheklabadia,⁎, Christian Conoscentib, Hamid Reza Pourghasemic,d, Kristof Van Ooste,faFaculty of Agriculture, Department of Soil Science, Bu Ali Sina University, Ahmadi Roshan Avenue, 6517838695 Hamedan, IranbDepartment of Earth and Sea Sciences (DISTEM), University of Palermo, Via Archirafi22, 90123 Palermo, ItalycCollege of Marine Sciences and Engineering, Nanjing Normal University, Nanjing, 210023, ChinadDepartment of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, IraneA- Fo…
Corrigendum to “Assessing the performance of GIS- based machine learning models with different accuracy measures for determining susceptibility to gu…
2020
Evaluation of multi-hazard map produced using MaxEnt machine learning technique.
2021
Abstract Natural hazards are diverse and uneven in time and space, therefore, understanding its complexity is key to save human lives and conserve natural ecosystems. Reducing the outputs obtained after each modelling analysis is key to present the results for stakeholders, land managers and policymakers. So, the main goal of this survey was to present a method to synthesize three natural hazards in one multi-hazard map and its evaluation for hazard management and land use planning. To test this methodology, we took as study area the Gorganrood Watershed, located in the Golestan Province (Iran). First, an inventory map of three different types of hazards including flood, landslides, and gul…
Gully erosion susceptibility mapping using GIS-based multi-criteria decision analysis techniques
2019
Abstract This research introduces a scientific methodology for gully erosion susceptibility mapping (GESM) that employs geography information system (GIS)-based multi-criteria decision analysis. The model was tested in Semnan Province, Iran, which has an arid and semi-arid climate with high susceptibility to gully erosion. The technique for order of preference by similarity to ideal solution (TOPSIS) and the analytic hierarchy process (AHP) multi-criteria decision-making (MCDM) models were integrated. The important aspect of this research is that it did not require gully erosion inventory maps for GESM. Therefore, the proposed methodology could be useful in areas with missing or incomplete …
A methodological comparison of head-cut based gully erosion susceptibility models
2020
Abstract A GIS-based hybrid approach for gully erosion susceptibility mapping (GESM) in the Biarjamand watershed in Iran is presented. A database comprised of 15 geo-environmental factors (GEFs) was compiled and used to predict the spatial distribution of 358 gully locations; 70% (251) of which were extracted for training and 30% (107) for validation. A Dempster-Shafer (DS) statistical model was employed to map susceptibility. Next, the results of four kernels (binary logistic, reg logistic, binary logitraw, and reg linear) of a boosted regression tree (BRT) model were combined to increase the efficiency and accuracy of the mapping. Area under receiver operating characteristics (AUROC), tru…
CART-based gully types classification: a case study in Sicily (Italy)
2015
Gulling is a complex process depending on several factors and involving a wide range of sub-processes. Different types of gullies were distinguished and described in literature. Their contribution to soil erosion changes in relation with the typology and their presence is influenced by different controlling factors. Mapping and classifying gullies is crucial for monitoring soil erosion. So far, no systematic definition of morphological characteristics of the different types of gullies and of their controlling factors has been made. The present work aims to suggest an innovative approach to automatically classify gullies by integrating remote sensing, GIS and a classification algorithm. The …
Data Mining Technique (Maximum Entropy Model) for Mapping Gully Erosion Susceptibility in the Gorganrood Watershed, Iran
2019
Soil erosion is a serious problem affecting most of the countries. This study was carried out in Gorganrood Watershed (Iran), which extends for 10,197 km2 and is severely affected by gully erosion. A gully headcut inven- tory map consisting of 307 gully headcut points was provided by Google Earth images, field surveys, and national reports. Gully conditioning factors including sig- nificant geo-environmental and morphometric variables were selected as predictors. Maximum entropy (ME) model was exploited to model gully susceptibility, whereas the area under the ROC curve (AUC) and draw- ing receiver operating characteristic (ROC) curves were employed to evaluate the performance of the model.…
The role of vegetation on gully erosion stabilization at a severely degraded landscape: A case study from Calhoun Experimental Critical Zone Observat…
2018
Abstract Gully erosion was evidence of land degradation in the southern Piedmont, site of the Calhoun Critical Zone Observatory (CCZO), during the cotton farming era. Understanding of the underlying gully erosion processes is essential to develop gully erosion models that could be useful in assessing the effectiveness of remedial and soil erosion control measures such as gully backfilling, revegetation, and terracing. Development and validation of process-based gully erosion models is difficult because observations of the formation and progression of gullies are limited. In this study, analytic formulations of the two dominant gullying processes, namely, plunge pool erosion and slab failure…