Application of remote sensing and GIS to assess groundwater potential in the transboundary watershed of the Chott-El-Gharbi (Algerian–Moroccan border)

Abstract

Remote sensing (RS) and Geographic Information Systems (GIS) have become widely used in various fields around the world in recent years. In this paper; we attempt to delineate the groundwater potential zone in the transboundary watershed of Chott-El-Gharbi using the integration of RS, GIS methods. Eight influencing thematic layers viz. geology, rainfall, water table level, lineaments density, slope, drainage density, elevation, and land use/land cover were used. Afterward, Analytical Hierarchy Process technique, which offers good functionality for mapping the groundwater potentiality was used, where ranks and weights, assigned to each factor are computed statistically, based on their relative importance in terms of groundwater potential. Then, groundwater potential zones are classified into five categories namely excellent, high, medium, low, and very low zone, which represent 964.48 km2 (7.33%), 1467.30 km2 (11.15%), 7969.51 km2 (60.57%), 2639.52 km2 (20.06%), and 116.19 km2 (0.88%) of the study area, respectively. The very low potential region is found in the southern region of the study area, which is covered by mountains. Moreover, excellent groundwater potential zones are located at the central part of the region of Chott, which has quaternary formations where the infiltration is high. On the other hand, moderate and poor groundwater potential zones cover by the bare lands in the study area. Finally, the results were carefully validated with the yields data of various boreholes in the study area, which reveals an accuracy achievement of 72.41%. The finding of this research constitutes a valuable contribution towards the water resources management, and it forms a significant decision support tool for equitable and sustainable utilization of groundwater resources in the transboundary watershed of Chott-El-Gharbi. The study's findings will also serve as a benchmark for future research and studies, such as hydrogeological modeling.

Assessing the Quality of Treated Wastewater for Irrigation: A Case Study of Ain Sefra Wastewater Treatment Plant

“…According to the classification by Doneen [33], samples with PI values above 75 fall into Class 1, which is acceptable for irrigation. Samples with PI values between 25 and 75% are classified as Class 2, showing good suitability for irrigation [30]. Therefore, all samples in the study area with PI values falling within Class 1 and 2 are suitable for irrigation.…”

“…The Ain Sefra WWTP is in the arid zone of Ain Sefra in the southwestern region of Algeria, at coordinates 27.0514 • N, 0.2285 • W (Figure 1). The area experiences a hot and arid climate, with an annual precipitation of below 190 mm and an average yearly temperature of around 18 • C [30]. This city has a population of approximately 75,000 residents and is at an elevation of 1078 m above sea level [31].…”

An Integrated assessment on LULC changes and Groundwater Quality in Ambattur Zone of Metropolitan Chennai, India

“…True colour composite maps were produced using the red, green, and blue bands (RGB) of each scene in the module "RGB Composite". Subsequently, false colour maps (FCC) using the bands Green, Red, and Infra-red (RGIR) were produced in the same module "RGB Composite" for both scenes (16,17) . These two composite maps are used later in assigning the classes for each cluster of classified images.…”

A GRASS GIS Scripting Framework for Monitoring Changes in the Ephemeral Salt Lakes of Chotts Melrhir and Merouane, Algeria

“…Satellite images serve as data sources in many applications of Earth science, such as in mapping the distribution of dust in arid regions [18], assessing and mapping erosion [19], aquifer characterization [20], evaluating groundwater potential [21], agricultural monitoring of crops [22][23][24][25], hazard risk assessments [26], and geological investigations of rock physics, tectonics, and hydrogeological simulations [27]. The analysis of satellite images can also be used for geophysical assessments in the desert areas of the African Sahara by integrating geological and spatial data modeling [28].…”