Roohi M, Faeli M, Jamshidi F, Ghasroddashti AP. Snow parameters modeling using remote sensing techniques and HEC-HMS hydrological modeling-case study: Kan Basin.
ENVIRONMENTAL MONITORING AND ASSESSMENT 2023;
195:684. [PMID:
37193863 DOI:
10.1007/s10661-023-11326-2]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/28/2023] [Indexed: 05/18/2023]
Abstract
Floods occur yearly, with great property and human life damage worldwide due to severe climate changes. Snow cover dominates the mountainous areas in winter. Therefore, the river discharge increases significantly in spring, when the snow melts gradually and is accompanied by rain this season. This study aims to evaluate the snow parameters such as snow cover, monthly average snow cover, and snowmelt from early winter to late summer 2020 by using the Terra satellite, MODIS sensor, and the FLDAS model to estimate the amount of water equivalent to snowmelt in the Google Earth Engine system for Kan basin in Tehran province. The hydrological model HEC-HMS was used for assessing the effect of snow parameters on the amount of Kan River discharge in this study. The land use map was extracted by using the image of the Sentinel-2 satellite to acquire more accuracy in this study. Finally, Sentinel-1 radar images were used to evaluate the effect of flood on the area and monitor the changes.
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