Snow cover monitoring by remote sensing and evaluating melting water effects on karstic springs discharges (a case study from Lasem area)

Abstract

Snowfall is the dominant form of precipitation in high mountainous areas and its driving melt water has an indispensable role in the hydrological cycle and groundwater recharge, particularly in karstic landscapes with high infiltration capacity. Monitoring snow cover area (SCA) and its melting process is essential for the investigation of climatic variables, hydrology, hydrogeology, and water resource management. Prodigious advances of satellite imaginary technology in the past decades made it possible to monitor spatiotemporal distribution of snow and its melting process. In this research, SCA was investigated using cloud-free images of Landsat-8 from December 2014 to June 2016 and Sentinel-2 from November 2015 to June 2016 at Lasem area (north of Iran) by normalized difference snow index. Simultaneously, the discharges of the main karstic springs were monitored over May 2015 to June 2016. The catchment subdivided into three sub-zones based on the hydrogeological characteristics and snow melting time. Fractional SCA time series within each subdomain used to develop snow melting curve in each subzone. Comparison of melting peaks between the 2014–2015 and 2015–2016 water years shows that melting shifted in average 20 days later in 2016 at north-facing subdomains. North-facing slopes show quite fast transmitting time (20–35 days) of the peak snowmelt to the springs, while the south-facing springs are more silent to the recharge pulses (70–80 days), indicating a higher degree of karstification in north-facing domains. More concentrated snowmelt in 2016 led to increasing peak flow by an average of 15% in the springs fed by north-facing domains.