Diachronic evolution of wetlands in a desert arid climate of the basin of Ouargla (southeastern Algeria) between 1987 and 2009 by remote sensing

Medjani, Fethi; Hamdaoui, Oualid; Djidel, Mohamed; Ducrot, Danielle

doi:10.1007/s12517-015-1958-5

Cited by 6 publications

(3 citation statements)

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“…The latter, together with the Saharan Atlas and the Tellien Atlas, form the main geo-structural units of Algeria. Ouargla is thus sunk into the depression of Oued M'ya, which offers a low topography (-40m) below sea level at Chott Melrhir (in the north) [15]. The geology of the Saharan platform has been investigated through field studies at outcrops, but mainly through oil and gas drilling.…”

Section: Description Of Study Areamentioning

confidence: 99%

Contribution to Geospatial Classification by Using Quality Indices for Irrigation Water in Arid Zones, Case of Ouargla Region, South East Algeria

BOUTELLI,

ZEDDOURI,

BOULMAIZ

2023

FENS

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The purpose of this study is to evaluate the quality of groundwater used for irrigating agricultural areas in the region of Ouargla by using several quality indices and to map the spatial distribution of these indices. This spatial mapping will help create a model for the classification of these resources according to their suitability for irrigation. For this purpose, physicochemical analyses were carried out on samples from 38 wells distributed over the entire territory of the studied region. These include 27 wells that capture Mio-Pliocene groundwater (Terminal Complex) and 11 wells in the Albian groundwater (Intercalary Continental). The thematic maps were developed using a geographic information system (GIS). In this study, we used the following eight indices: potential salinity (PS); residual sodium carbonate (RSC); electrical conductivity (EC); magnesium percent (%Mg 2+ ); sodium percent (%Na + ); permeability index (PI); Kelley's ratio (KR); sodium adsorption ratio (SAR). The global qualitative study of the water used for irrigation shows that these resources fall into three categories (good, permissible, and poor for irrigation). Water quality analysis shows that, based on the magnesium percent (%Mg 2+ ), 18% of the wells can be considered to be of good quality, 74% of the wells are of medium quality (permissible for irrigation), and 8% are of poor quality (unsuitable for irrigation). According to the Wilcox diagram, the waters used in the Ouargla region are of very poor quality. Very excessive mineralization, expressed by the electrical conductivity, was observed for the Mio-Pliocene and Albian waters, where it varies with values in the range of 2340 µS/m to 6520 µS/m and 2330 µS/m to 3840 µS/m, respectively. This conductivity presents a high risk of alkalinization.

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Section: Description Of Study Areamentioning

confidence: 99%

Contribution to Geospatial Classification by Using Quality Indices for Irrigation Water in Arid Zones, Case of Ouargla Region, South East Algeria

BOUTELLI,

ZEDDOURI,

BOULMAIZ

2023

FENS

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“…The final stage of the process is a Sebkha whose sediments are completely sterile, drowned by a few tens of centimeters of water in winter and covered in summer with a white layer of crystallized salts. During the dry season, these areas are subjected to wind erosion, which accentuates the basin topography [43]. In Algeria, as elsewhere in the world, salty soils occupy large areas (3.2 million hectares of the total area).…”

Section: Plant Growth Promoting Microorganisms For Use In Soil Desalinizationmentioning

confidence: 99%

Tailoring Next Generation Plant Growth Promoting Microorganisms as Versatile Tools beyond Soil Desalinization: A Road Map towards Field Application

et al. 2021

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Plant growth promoting bacteria (PGPB) have been the target of intensive research studies toward their efficient use in the field as biofertilizers, biocontrol, and bioremediation agents among numerous other applications. Recent trends in the field of PGPB research led to the development of versatile multifaceted PGPB that can be used in different field conditions such as biocontrol of plant pathogens in metal contaminated soils. Unfortunately, all these research efforts lead to the development of PGPB that failed to perform in salty environments. Therefore, it is urgently needed to address this drawback of these PGPB toward their efficient performance in salinity context. In this paper we provide a review of state-of-the-art research in the field of PGPB and propose a road map for the development of next generation versatile and multifaceted PGPB that can perform in salinity. Beyond soil desalinization, our study paves the way towards the development of PGPB able to provide services in diverse salty environments such as heavy metal contaminated, or pathogen threatened. Smart development of salinity adapted next generation biofertilizers will inevitably allow for mitigation and alleviation of biotic and abiotic threats to plant productivity in salty environments.

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“…In this sense, several studies used remote sensing, field, and laboratory data in order to map gypsum content of soil (Mostephaoui et al 2013) or assess the diachronic evolution of wetlands in desert areas, comparing maximum likelihood classification, support vector machines (SVM), spectral angle mapper, and neural network (Medjani et al 2015). In this latter case, the SVM presented the highest accuracy for the identification of nine classes of humid zones (five classes) and mineral surfaces (four classes).…”

Section: Change Detection and Driving Factorsmentioning

confidence: 99%

Classification methods for detecting and evaluating changes in desertification-related features in arid and semiarid environments

Afrasinei

Melis

Buttau

et al. 2017

Euro-Mediterr J Environ Integr

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Land cover, land use, soil salinization, and sand encroachment, which are desertification-indicating features, were integrated in a diachronic assessment, obtaining quantitative and qualitative information on the ecological state of the land, particularly degradation tendencies. In arid and semi-arid study areas of Algeria and Tunisia, sustainable development requires the understanding of these dynamics as it withstands the monitoring of desertification processes. Both visual interpretation and automated classification approaches have been set up for salt and sand features extraction using historical and present Landsat imagery. The automated one includes a decision tree classifier and an unsupervised classification applied to the principal components extracted from Knepper ratios composite. New spectral indices are employed in the decision tree classifier for the extraction of features of interest. The validation of the classification methods showed that the decision tree had an overall accuracy over 85% in both areas. Integrating results with ancillary spatial data, we could identify driving forces and estimate the metrics of desertification processes. In the Biskra area (Algeria), it emerged that the expansion of irrigated farmland in the past three decades has been contributing to an ongoing secondary salinization of soils, with an increase of over 75%. In the Oum Zessar area (Tunisia), there has been substantial change in several landscape components in the last decades related to increased anthropic pressure and settlement, agricultural policies, and national development strategies. One of the most concerning aspects is the expansion of sand-encroached areas over the last three decades of around 27%.

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Diachronic evolution of wetlands in a desert arid climate of the basin of Ouargla (southeastern Algeria) between 1987 and 2009 by remote sensing

Cited by 6 publications

References 1 publication

Contribution to Geospatial Classification by Using Quality Indices for Irrigation Water in Arid Zones, Case of Ouargla Region, South East Algeria

Contribution to Geospatial Classification by Using Quality Indices for Irrigation Water in Arid Zones, Case of Ouargla Region, South East Algeria

Tailoring Next Generation Plant Growth Promoting Microorganisms as Versatile Tools beyond Soil Desalinization: A Road Map towards Field Application

Classification methods for detecting and evaluating changes in desertification-related features in arid and semiarid environments

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