Logistic Regression-based Geomorphological Mapping in the Arabian Platform: Implications for the Paleohydrology and the Paleoclimate of the Arabian Desert
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Throughout the Quaternary, the Arabian Peninsula witnessed alternation between dry and wet periods. During the wet periods, annual precipitation significantly increased leading to recharging the fossil aquifers, elevation of the groundwater table and development of drainage systems and waterfalls along the Central Arabian Arch (CAA). Landforms that were left behind these periods provide valuable clues for deciphering the paleohydrology and paleoclimate of the Arabian Desert. Herein we used logistic regression modeling with topographic analysis to delineate theater-headed valleys (THV) along the CAA. These valleys have peculiar morphometry (e.g. theater-like heads, stubby-looking geometry, U-shaped profiles, occurrence along escarpments and propagation along fractures) and are largely attributed to groundwater sapping and/or megaflooding and water fall erosion. The model uses different topographic datasets including stream power index, plan and profile curvatures, stream density and slope gradient. The model results show that THV are abundant along the plateau escarpments and deep fluvially-incised valleys in the CAA. Additional geological, hydrological and field assessments are required to further characterize the origin of THV and examine the respective roles of groundwater processes and surface water activities in shaping the CAA landscape. This paper presents a novel mapping approach of landforms on a regional scale.
KeywordsMachine learning Mapping Theater-headed valleys Central Arabian arch Groundwater sapping Paleohydrology
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