Abstract

Hydrological modelling of Ar Rub Al Kahli over a very regional scale using the weight of evidence based on pixel calculation and several pieces of evidences is timely consuming. This study aims to modify an approach, which calls a weight of hydrological evidence (WoHE) approach. The approach is based on calculating the logarithmic ratio of the total areas of distribution good (event) and distribution bad (non-event) of features such as faults, palaeochannels and zones of flow accumulation. The approach starts by mapping fault zones, palaeochannels, drainage basins and flow accumulation zones from the Advanced Land Observing Satellite (ALOS) DEM. The proposed approach is an effective approach to improve the hydrological modeling and summarize large datasets over a very regional scale obtained using machine learning, which is used widely in the literature. The results exhibited that the basins of Dhofar has the highest values for the WoHE of 0.0432.

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