Examining the certainty of remote sensing data in models for estimating water resources derived from snowmelt runoff

Subject Areas : climate

Eslam Galehban ¹ , Mehrneg Dosti Rezaei ² , Farhad Nasiri ³

1 - Department of Remote Sensing and GIS, University of Tehran, Tehran, Iran
2 - Master of Science in Remote Sensing and Geographic Information Systems, Faculty of Geography, University of Tehran, Tehran.
3 - Head of Integration and Bilan Group at West Azarbaijan Regional Water Company, West Azerbaijan, Iran.

Received: 2023-04-04 Accepted : 2023-06-21 Published : 2023-06-21

Keywords: runoff, SRM model, remote sensing, Snowmelt,

Abstract :

Shahrchay Dam is one of the main sources for providing drinking water and irrigation to the city of Urmia. The snow reserves in this basin serve as a strategic water supply for the agricultural sector and are utilized as runoff in the lower part of the basin as temperatures rise. Therefore, having information about snow reserves and the runoff derived from them throughout the year is of special importance in water resources management of the basin. There are various methods available for estimating runoff derived from snowmelt, typically using a combination of meteorological data and remote sensing. In this study, the snow cover data from the MODIS, the ERA-LAND reanalysis dataset, and the GPM precipitation database, all of which are products of remote sensing, were used as inputs for the snowmelt runoff model (SRM). The daily runoff resulting from snowmelt in the Shahrchay Dam Basin was estimated using satellite images and products in the water year of (September 2019 to August 2020). And The model outputs were validated based on the daily river discharge data measured by the Barde Sour station. The results indicate that the Snowmelt Runoff Model (SRM) performed well in the studied basin, with a coefficient of determination (R2) exceeding 0.8 and a (DV) -2.21.