Snow parameters modeling using remote sensing techniques and HEC-HMS hydrological modeling-case study: Kan Basin
Mohammad Roohi1, Mehdi Faeli2, Fariba Jamshidi3
1Civil Engineering Department, Shahid Chamran University of Ahvaz, Ahvaz, Iran. mohammad-roohi@stu.scu.ac.ir.
Environmental Monitoring and Assessment
|May 16, 2023
Summary
This study analyzes snowmelt and its impact on river discharge in Tehran's Kan basin using satellite data and hydrological modeling. Findings aid in understanding flood risks and water resource management.
Area of Science:
- Hydrology and Remote Sensing
- Climate Change Impact Assessment
Background:
- Annual floods cause significant global damage, exacerbated by climate change.
- Mountainous snow cover melt in spring, combined with rainfall, leads to increased river discharge.
- Understanding snowmelt dynamics is crucial for flood prediction and water management in snow-dominated regions.
Purpose of the Study:
- To evaluate snow cover, snowmelt, and water equivalent using satellite data and models.
- To assess the impact of snow parameters on Kan River discharge.
- To monitor flood effects and changes in the Kan basin using radar imagery.
Main Methods:
- Utilized Terra satellite (MODIS sensor) and FLDAS model for snow parameter estimation.
- Employed Google Earth Engine for water equivalent calculations.
- Applied HEC-HMS hydrological model to analyze snowmelt's effect on river discharge.
- Extracted land use map using Sentinel-2 satellite imagery.
- Used Sentinel-1 radar images for flood impact assessment and change monitoring.
Main Results:
- Quantified snow cover, snowmelt, and water equivalent for the Kan basin.
- Demonstrated the influence of snow parameters on Kan River discharge patterns.
- Identified flood-affected areas and monitored changes using Sentinel-1 data.
Conclusions:
- Satellite data and hydrological models effectively assess snowmelt impacts on river discharge.
- Accurate snow parameter estimation is vital for flood risk management in mountainous basins.
- Integrated remote sensing and modeling provide valuable insights for water resource management and disaster preparedness.
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