Efficiency of Fuzzy Analytic Hierarchy Process to detect soil erosion vulnerability

Haidara, Imane; Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

doi:10.1016/j.geoderma.2019.07.011

Cited by 44 publications

(12 citation statements)

References 35 publications

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“…Most of them considered various factors affecting soil productivity using standard and adjusted Mediterranean desertification and land use (MEDALUS) approaches [34,35], and/or FAO/UNEP and UNESCO provisional methodology [36]. However, these methods use equal weights for all parameters when mapping LDV, while each criterion has a point value and depends on physical, geomorphological, and environmental impact regarding land degradation [37]. Therefore, the current work is a trial for using AHP to prioritize variables and indices affecting soil performance in Farafra Oasis to be integrated under the GIS environment for allocating LDV zones.…”

Section: Introductionmentioning

confidence: 99%

Land Degradation Vulnerability Mapping in a Newly-Reclaimed Desert Oasis in a Hyper-Arid Agro-Ecosystem Using AHP and Geospatial Techniques

et al. 2021

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Modelling land degradation vulnerability (LDV) in the newly-reclaimed desert oases is a key factor for sustainable agricultural production. In the present work, a trial for usingremote sensing data, GIS tools, and Analytic Hierarchy Process (AHP) was conducted for modeling and evaluating LDV. The model was then applied within 144,566 ha in Farafra, an inland hyper-arid Western Desert Oases in Egypt. Data collected from climate conditions, geological maps, remote sensing imageries, field observations, and laboratory analyses were conducted and subjected to AHP to develop six indices. They included geology index (GI), topographic quality index (TQI), physical soil quality index (PSQI), chemical soil quality index (CSQI), wind erosion quality index (WEQI), and vegetation quality index (VQI). Weights derived from the AHP showed that the effective drivers of LDV in the studied area were as follows: CSQI (0.30) > PSQI (0.29) > VQI (0.17) > TQI (0.12) > GI (0.07) > WEQI (0.05). The LDV map indicated that nearly 85% of the total area was prone to moderate degradation risks, 11% was prone to high risks, while less than 1% was prone to low risks. The consistency ratio (CR) for all studied parameters and indices were less than 0.1, demonstrating the high accuracy of the AHP. The results of the cross-validation demonstrated that the performance of ordinary kriging models (spherical, exponential, and Gaussian) was suitable and reliable for predicting and mapping soil properties. Integrated use of remote sensing data, GIS, and AHP would provide an effective methodology for predicting LDV in desert oases, by which proper management strategies could be adopted to achieve sustainable food security.

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Section: Introductionmentioning

confidence: 99%

Land Degradation Vulnerability Mapping in a Newly-Reclaimed Desert Oasis in a Hyper-Arid Agro-Ecosystem Using AHP and Geospatial Techniques

et al. 2021

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“…To assess erosion vulnerability, a combination of GIS technologies and the multi-criteria decision method (MCDM) can be employed efficiently. In several previous case studies, it was confirmed that the combination of GIS tools and MCDM method in watershed and soil resource analysis, evaluation and vulnerability improves the decision-making process (Jaiswal et al 2015;Haidara et al 2019).…”

Section: Introductionmentioning

confidence: 62%

Identification of critical watershed at risk of soil erosion using morphometric and geographic information system analysis

Benzougagh

Meshram²,

Dridri

et al. 2021

Appl Water Sci

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Morphometric analysis is a pertinent scientific approach in any hydrological analysis, and it is necessary in the progress and management of drainage basin. Identification of areas at risk of erosion, and the prioritization of 48 sub-watersheds of Inaouene basin, was done by using linear, relief and areal aspects of watershed. The research carried out the use of geographic information system spatial data. The linear aspects include stream number, stream sequence, stream length, and bifurcation ratio, mean length of stream order, stream length ratio, mean stream length ratio, and form factor. The areal aspect includes frequency of stream, drainage density, texture ratio, channel length constant, and overland flow maintenance length. Ultimately, the relief dimensions included relief proportion, relief and ruggedness number. The array of compound (Cp) values computed allow us to set the priority ranks and classify the sub-watershed into three priority ranks groups: low, moderate, and high priority. Such morphometric analyses can be used therefore as a watershed erosion status estimator to prioritize land and water conservation initiatives and natural resources management.

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“…Furthermore, most of those 50 studies merely focus on analyzing single landscape factors. Prominently, they are a study on soil erosion following the Universal Soil Loss Equation (USLE) of Wiscehmeir and Smith [2]; a study on soil erosion through the sensitivity of natural environments [3][4][5][6][7][8]; a study on landscape assessment according to quantitative methods with the calculation of erosion indexes following terrain and rainfall [9,10]; a study on the landscape sensitivity in line with space and time based on landscape equilibrium indexes [11,12]; soil erosion indexes were established based on the calculations of potential, practical soil loss indexes, and soil erosion susceptibility (soil erosion and conservation, models of soil erosion and land use, spatial patterns of soil erosion susceptibility) [13][14][15]; approaching landscape analysis in accordance with the analytical hierarchy process (AHP) [16][17][18]; constructing a model calculating erosion rates in terms of landscapes [19][20][21][22][23]; and a study on the geomorphic limitations on landscape sensitivity owing to the climate of tectonically active sites [24][25][26]. It can be seen that the erosion indexes of those studies are derived from only soil erosion or from studying separately on factors that are influential in erosion including terrain, geomorphology, rainfall, and vegetation cover.…”

Section: Introductionmentioning

confidence: 99%

Constructing a spatial analysis model in assessing the sensitivity of landscape erosion in mountainous regions of Vietnam

Kieu¹,

Huong

Van³

2020

SN Appl. Sci.

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This study demonstrates the steps of building a spatial analysis model that is applicable in synthetically assessing the sensitivity of landscape erosion in mountainous regions. Field testing was carried out at Ngu Chi Son commune, Sa Pa district, Lao Cai Province, Vietnam. The primary basis is the application of the GIS spatial analysis model in mapping the landscape structure. Subsequently, depending on the landscape structure map, the analysis model of erosion levels due to erosion factors (rainfall, terrain, the thickness of soil layers, mechanical compositions, vegetation cover, and cultivation measures of human beings) was constructed. The employed algorithms included spatial overlay, spatial interpolation, attribute reclassification, and average indexes. The results of this study have indicated the erosion sensitivity of every landscape unit, which is categorized into five levels: very low, low, medium, high, and very high. Obtained appraisals and sensitivity categorization are important fundaments to issue exploitation orientations and reasonable usages of resources within the researched region. This proves to be a new direction of research with overall potentials in assessing mountainous landscapes.

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Efficiency of Fuzzy Analytic Hierarchy Process to detect soil erosion vulnerability

Cited by 44 publications

References 35 publications

Land Degradation Vulnerability Mapping in a Newly-Reclaimed Desert Oasis in a Hyper-Arid Agro-Ecosystem Using AHP and Geospatial Techniques

Land Degradation Vulnerability Mapping in a Newly-Reclaimed Desert Oasis in a Hyper-Arid Agro-Ecosystem Using AHP and Geospatial Techniques

Identification of critical watershed at risk of soil erosion using morphometric and geographic information system analysis

Constructing a spatial analysis model in assessing the sensitivity of landscape erosion in mountainous regions of Vietnam

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