{'fraction_non_alphanumeric': 0.019994287346472437, 'fraction_numerical': 0.00971151099685804, 'mean_word_length': 4.731587561374796, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Evaluation of the snow water resources in Mount Lebanon using observations and modelling

Lebanon’s water resources are under increasing pressure due to economic development, 
demographic growth, unsustainable water resource management, and climate change. The 
Mount- and Anti-Lebanon Mountains are natural water towers for Lebanon as they play an 
important role in enhancing orographic precipitation. Due to the influence of the Mediterranean 
climate, most precipitation above 1200 m a.s.l. falls as snow during winter season. As a result, 
snowmelt is an important contributor to the national water balance. In particular, snowmelt from 
Mount-Lebanon feeds the karst groundwater systems, which provide key water resources to the 
coastal region. Despite the importance of the snow cover in the Lebanese mountains, the actual 
snowpack spatial and temporal variability and its contribution to the spring and river discharges 
in Lebanon remains poorly constrained. The objective of this work is to reduce this lack of 
knowledge using a combination of in situ measurements, remote sensing observations and 
modelling of the snowpack in Mount-Lebanon. 
1. We first present an extensive review of the literature about the snow hydrological 
processes in Mediterranean-like mountain regions. Many studies - mainly from Western USA 
and Southern Europe mountains - emphasize the strong impact of the interannual Mediterranean 
climate variability on the snowpack dynamics. The high incoming solar radiation is an 
important driver of the snowpack energy balance, but the contribution of heat fluxes is stronger 
at the end of the snow season. Snow sublimation and rapid densification are important processes 
to consider. Hybrid approaches combining weather station data with optical remote sensing of 
the snow extent through modelling are recommended to tackle the lack of spatially-distributed 
observations of the meteorological forcing. 
2. Then, we introduce an original dataset on the snow cover in Mount-Lebanon for the 
period 2013-2016. We collected field observations of the snow height (HS), snow water 
equivalent (SWE), and snow density between 1300 and 2900 m a.s.l. in the western slope of 
Mount-Lebanon. In addition, continuous meteorological data were acquired by three automatic 
weather stations located in the snow dominated region of Mount-Lebanon. The MODIS snow 
product was used to compute the daily snow cover area in three snow dominated basins. We 
find that HS and SWE have large variances and that snow density is high. The strong correlation 
between HS and SWE may be useful to reduce the amount of field work for future operational 
monitoring. 
3. Using these data we set up a distributed snowpack energy balance in the Mount- 
Lebanon at 100 m resolution. The model is validated at different scales using the observed 
SWE, snow density, HS and SCA. A simulation with very limited adjustments to the default 
parameterization is found to correctly capture most of the observations. This simulation allows 
the estimation of the SWE evolution and snow melt in the three study basins between 2013 and 
2016. 
This research highlighted the importance of conducting simultaneous field surveys and 
meteorological observations to gain insights into the physical processes driving snowpack 
evolution in Mount-Lebanon. Finally, the influence of snow erosion by wind and the influence 
of dust deposits on snowmelt, remains less known, and are warrant for future research