Implicit modeling of salinity reconstruction by using 3D combined models

Abdellatif, Dehni; Kheloufi, Nourredine; Bouakkaz, Khaled

doi:10.1007/s12665-020-09175-0

Cited by 4 publications

(3 citation statements)

References 47 publications

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“…The field generated from observed resistivity versus geoelectric spread was implemented in IP2Win software for obtaining geoelectrical layering and thickness for each VES point. However, VES surveys were used to compute the geo-electric factors including (L) and (TTR) (Dehni et al 2020).…”

Section: Study Areamentioning

confidence: 99%

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Mapping of groundwater vulnerability using optimized AHP-GOD Models and geospatial factors (Case study: littoral sedimentary aquifer of Ain Temouchent – NW Algeria

Abdellatif

2022

Preprint

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The monitoring and protection of coastal aquifers has become a primary priority and a subject of research with the integration of Vertical Electrical Sounding (VES) in order to map groundwater vulnerability to contamination, and to evaluate their aquifer protective capacity. A study aimed to to identify an exposure level of contamination for a sustainable use of the water resources in the aquifer of Ouled Taoui - Boujema aquifer situated in Ain Temouchent – Algeria. For this purpose, a dataset was established including 170 VES soundings, topography ASTER GDEM, geological maps and finally boreholes were acquired to develop the AHP (Analytical Hierarchy Process) by ordering the weightage of geospatial factors in vulnerability mapping. However, a GOD-LT model (G: groundwater type; O: aquifer overlying strata; D: aquifer depth and L: Longitudinal conductance; T: Topography slope and Th: Thickness) has been evaluated using optimized AHP as predictive model abbreviated GOD-L, GOD-LT and GOD-LTh. Furthermore, these factors are considered as the causal factors of aquifer vulnerability (AVCF’s). The geospatial factors were derived on AHP-WLA (Weight Linear Average) for rating optimization. The pairwise comparison matrix was developed on the AVCF’s factors for AHP-GOD. The validation result showcases that 72% of prediction consistency is optimized for GOD-L model compared to 64% for the standard GOD. The GOD-LT and GOD-Th demonstrated the best reliability under consistency index. However, the vulnerability to pollution is validated by using nitrate concentration, water corrosivity and the degree of aquifer capacity protection and can be efficient mapping for water supply and environmental assessment.

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Section: Study Areamentioning

confidence: 99%

“…Furthermore, areas with  inferior to 0.5 were considered for ground water potential zones within high porosity and permeability. Thus, the values of  for VES surveys are computed using mathematical equation (Dehni et al 2020) (Eq. 4):…”

Section: Vadose Zone Protective Capacitymentioning

confidence: 99%

Mapping of groundwater vulnerability using optimized AHP-GOD Models and geospatial factors (Case study: littoral sedimentary aquifer of Ain Temouchent – NW Algeria

Abdellatif

2022

Preprint

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“…In this case, the necessity of using other sources of data and techniques in combination with RS to achieve vertical soil salinity mapping is highlighted [32]. Modeling of salinity status vertically can present important information for understanding the mechanism of salinization, assessing its properties in different conditions, and extracting significant information from it as a 3D soil body; e.g., especially where salts accumulate in deep soils [32][33][34][35][36]. As the saline-alkaline mechanisms of deep soils in the study area remain unclear to scientists, it is critical to conduct in-depth research into these mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Soil Salinity Estimation by 3D Spectral Space Optimization and Deep Soil Investigation in the Songnen Plain, Northeast China

Ma,

Hao,

Huang

et al. 2024

Sustainability

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Saline–alkaline soil is a severe threat to Sustainable Development Goals (SDGs), but it can also be a precious land resource if properly utilized according to its properties. This research takes the Songnen Plain as the study area. The aim is to figure out the saline–alkaline status and mechanisms for its scientific utilization. Sentinel-2 multispectral imagery is used, and a 3D spectral space optimization method is proposed according to the restrictive relationships among the surface soil salinity index (SSSI), vegetation index (VI), and surface soil wetness index (SSWI) to construct a surface soil salinization–alkalization index (SSSAI) for estimation of the surface soil salinity (SSS). It is testified that SSS can be precisely estimated using the SSSAI (R2 = 0.74) with field verification of 50 surface salinized soil samples. Surface water and groundwater investigations, as well as deep soil exploration, indicate that the salt ions come from groundwater, and alkalinization is a primary problem in the deep soils. Fine-textured clay soils act as interrupted aquifers to prevent salt ions from penetrating and diluting downward with water, which is the cause of the salinization–alkalization problem in the study area. Finally, a sustainable solution for the saline–alkaline land resource is proposed according to the deep soil properties.

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Mapping of the groundwater vulnerability to saline intrusion using the modified GALDIT model (Case: the Ain Temouchent coastal aquifer, (North-Western Algeria))

Bentekhici¹,

Abdellatif

Assia³

2021

Environ Earth Sci

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Implicit modeling of salinity reconstruction by using 3D combined models

Cited by 4 publications

References 47 publications

Mapping of groundwater vulnerability using optimized AHP-GOD Models and geospatial factors (Case study: littoral sedimentary aquifer of Ain Temouchent – NW Algeria

Mapping of groundwater vulnerability using optimized AHP-GOD Models and geospatial factors (Case study: littoral sedimentary aquifer of Ain Temouchent – NW Algeria

Soil Salinity Estimation by 3D Spectral Space Optimization and Deep Soil Investigation in the Songnen Plain, Northeast China

Mapping of the groundwater vulnerability to saline intrusion using the modified GALDIT model (Case: the Ain Temouchent coastal aquifer, (North-Western Algeria))

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