The role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)

Abstract

Abstract. In many Mediterranean mountain regions, the seasonal snowpack is an essential yet poorly known water resource. Here, we examine, for the first time, the spatial distribution and evolution of the snow water equivalent (SWE) during three snow seasons (2013–2016) in the coastal mountains of Lebanon. We run SnowModel (Liston and Elder, 2006a), a spatially distributed, process-based snow model, at 100 m resolution forced by new automatic weather station (AWS) data in three snow-dominated basins of Mount Lebanon. We evaluate a recent upgrade of the liquid water percolation scheme in SnowModel, which was introduced to improve the simulation of the SWE and runoff in warm maritime regions. The model is evaluated against continuous snow depth and snow albedo observations at the AWS, manual SWE measurements, and MODIS snow cover area between 1200 and 3000 m a.s.l. The results show that the new percolation scheme yields better performance, especially in terms of SWE but also in snow depth and snow cover area. Over the simulation period between 2013 and 2016, the maximum snow mass was reached between December and March. Peak mean SWE (above 1200 m a.s.l.) changed significantly from year to year in the three study catchments, with values ranging between 73 and 286 mm w.e. (RMSE between 160 and 260 mm w.e.). We suggest that the major sources of uncertainty in simulating the SWE, in this warm Mediterranean climate, can be attributed to forcing error but also to our limited understanding of the separation between rain and snow at lower-elevations, the transient snowmelt events during the accumulation season, and the high variability of snow depth patterns at the subpixel scale due to the wind-driven blown-snow redistribution into karstic features and sinkholes. Yet, the use of a process-based snow model with minimal requirements for parameter estimation provides a basis to simulate snow mass SWE in nonmonitored catchments and characterize the contribution of snowmelt to the karstic groundwater recharge in Lebanon. While this research focused on three basins in the Mount Lebanon, it serves as a case study to highlight the importance of wet snow processes to estimate SWE in Mediterranean mountain regions.

Snowpack dynamics in the Lebanese mountains from quasi-dynamically downscaled ERA5 reanalysis updated by assimilating remotely sensed fractional snow-covered area

“…The precipitation phase had to be recalculated for the new synthetic temperatures for each ensemble member. Due to the strong dependency of the snowpack over Lebanon on precipitation phase, simple temperature-threshold-based precipitation-phase partitions are not recommended (Fayad and Gascoin, 2020). Instead, we have used the psychrometric energy balance method approach proposed by Harder and Pomeroy (2013), where the precipitation phase is estimated by means of the estimation of the temperature of the falling hydrometeor calculated from the air temperature and relative humidity.…”

“…Some water years showed earlier snowmelt. As the uncertainty of the snow models associated to the forcing is higher than the uncertainty associated by the use of different model parameterizations and model structures (Günther et al, 2019), we hypothesize that such differences were caused by the differences in the precipitation phase partitioning that is challenging to simulate in the areas that remain close to 0 • C during the snow season (Fayad and Gascoin, 2020). The lack of spring snowfalls in some years may have deep implications in the snowpack simulation that are not limited to its effect in the mass balance and the releasing of latent heat by refreezing the liquid precipitation.…”

“…Despite this variability, the thickness and high density exhibited by the snowpack in the Mediterranean climate (Fayad et al, 2017b) makes them an effective water storage system. In addition, high sublimation rates are associated with Mediterranean snowpacks (Fayad and Gascoin, 2020;Herrero et al, 2016;Schulz and de Jong, 2004). The fact that snowpack conditions are close to isothermal during most of the snow season makes them highly sensitive to the current climate warming (Alonso-González et al, 2020a;López-Moreno et al, 2017;Yilmaz et al, 2019).…”

“…Despite their importance, snow observations in the region are scarce (Fayad et al, 2017a), making the study of distributed snow dynamics challenging. Recently, Fayad and Gascoin (2020) developed distributed snowpack simulations over key areas of Mount Lebanon, forcing the model by interpolating observations of the few existing automatic weather stations (AWSs) using the SnowModel by Liston and Elder (2006). They showed the importance of the liquid water percolation scheme given the isothermal condition of the snowpack and estimated the snow water equivalent over three key catchments in the windward western divide of Mount Lebanon.…”

Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)

“…SnowModel has previously been tested with success in a wide range of climates [39], including semi-arid and Mediterranean mountains [17,40,41]. In this study we used the version: SnowModel_2020_05_14.…”