Apport de la télédétection, du SIG, de l’hydrochimie et de la modélisation dans l’étude des ressources en eau dans la région de Sétif Cas du bassin versant de Bousselam

Abstract

This thesis develops and applies an integrated, reproducible workflow—combining remote sensing, GIS, hydrochemistry and multi-criteria decision modeling—to de-lineate and understand groundwater recharge potential on the semi-arid high plateau of Sétif, Algeria. It begins with a detailed digitization of the regional geological map to characterize lithological units and aquifer materials. High-resolution ASTER GDEM v3 data are then hydro-conditioned in QGIS to derive drainage density and slope layers that quantify how terrain morphology governs the balance between in-filtration and runoff. Concurrently, NASA-POWER precipitation and temperature records (1980–2019) are processed to generate spatially continuous annual rainfall and temperature surfaces. These surfaces reveal the onset of the recharge period and guide the timing of land-cover classification using Landsat 8 OLI/TIRS im-agery at the moment when aquifer replenishment begins. Landsat 8 OLI/TIRS im-agery—interpreted alongside the geological map—is also employed to extract struc-tural lineaments that control subsurface flow pathways. Field-based hydrochem-ical investigations—including piezometric profiling, major-ion ratio analysis and total dissolved solids (TDS) measurements—trace recharge signatures in ground-water and provide empirical constraints for model calibration. Six thematic lay-ers (lithology, lineament density, slope, drainage density, rainfall intensity and land cover) are weighted through the Analytic Hierarchy Process and overlaid in QGIS to produce a groundwater recharge potential zoning map. Independent split-sample ROC analysis and TDS-based thresholds confirm the model’s ability to discrimi-nate recharge-rich from recharge-poor zones. The results highlight the northern sec-tor—characterized by high rainfall intensity, permeable formations and low drainage density—as the most promising target for recharge enhancement. By integrating ge-ological, geomorphological, climatic and hydrochemical evidence, this methodology provides a robust decision-support tool for prioritizing field investigations and de-signing adaptive water-management strategies in semi-arid basins.