Cloud-based remote sensing datasets used in hydrological studies: A review and examples

Water resources are critically important for the continuity of ecosystems and the sustainability of human activities. However, climate change, population growth, and unplanned and rapid changes in land use are increasingly putting pressure on surface and groundwater resources. This situation necessitates an accurate assessment of the temporal and spatial distribution of water and its effective monitoring at the watershed scale. Traditional hydrological observation methods provide high accuracy but, due to their limited spatial coverage and prohibitive costs, they present significant limitations, particularly in regions with insufficient data. In this context, remote sensing technologies offer an approach that enables the acquisition of parameters represented directly and indirectly in hydrological analyses, covering large areas and providing continuity. This study examines the concept of water balance, which forms the basis of hydrology, within the framework of the hydrological cycle. It evaluates the contributions of different remote sensing datasets to the monitoring and assessment of water resources, as well as the limitations of these approaches, in light of studies in the literature. In addition, a representative study area encompassing the Hazar Lake Basin and the Behramaz Basin was selected, and analyses were conducted using the Google Earth Engine (GEE) platform to demonstrate the applicability of the available datasets.