On the Interest of Optical Remote Sensing for Seasonal Snowmelt Parameterization, Applied to the Everest Region (Nepal)

Abstract

In the central part of the Hindu Kush Himalayan region, snowmelt is one of the main inputs that ensures the availability of surface water outside the monsoon period. A common approach for snowpack modeling is based on the degree day factor (DDF) method to represent the snowmelt rate. However, the important seasonal variability of the snow processes is usually not represented when using a DDF method, which can lead to large uncertainties for snowpack simulation. The SPOT-VGT and the MODIS-Terra sensors provide valuable information for snow detection over several years. The aim of this work was to use those data to parametrize the seasonal variability of the snow processes in the hydrological distributed snow model (HDSM), based on a DDF method. The satellite products were corrected and combined in order to implement a database of 8 day snow cover area (SCA) maps over the northern part of the Dudh Koshi watershed (Nepal) for the period 1998–2017. A revisited version of the snow module of the HDSM model was implemented so as to split it into two parameterizations depending on the seasonality. Corrected 8 day SCA maps retrieved from MODIS-Terra were used to calibrate the seasonal parameterization, through a stochastic method, over the period of study (2013–2016). The results demonstrate that the seasonal parameterization reduces the error in the simulated SCA and increases the correlation with the MODIS SCA. The two-set version of the model improved the yearly RMSE from 5.9% to 7.7% depending on the basin, compared to the one-set version. The correlation between the model and MODIS passes from 0.73 to 0.79 in winter for the larger basin, Phakding. This study shows that the use of a remote sensing product can improve the parameterization of the seasonal dynamics of snow processes in a model based on a DDF method.

Improving Knowledge about Snow by Crossing Qualitative and Quantitative Data from the Everest Region (Nepal)

“…As for satellite images used to assess the extent of snow cover, they are often "biased" by the spatial and temporal resolution of the sensors or by the presence of clouds. Therefore, knowledge of the cryosphere (solid water in the form of ice or snow) is still limited (Bolch et al, 2012;Bouchard et al, 2019;Gurung et al, 2011). All these factors complicate the development and interpretation of climate models in the Himalayas (Nepal et al, 2017;Savéan et al, 2015).…”

“…It was supplemented, from 2000 to 2012, by the MOD10A1 product (Hall et al, 2002) derived from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor at a daily time step and a 15 arcs-secs resolution. All snowpack data is subject to significant uncertainties with regards both quantity and extent (Bouchard et al, 2019).…”

Mieux appréhender la neige par le croisement de données qualitatives et quantitatives dans la région de l’Everest (Népal)

“…Quant aux images satellitaires utilisées pour évaluer l'extension de la couverture neigeuse, elles sont souvent « biaisées » par la résolution spatiale et temporelle des capteurs ou par la présence de nuages. C'est pourquoi les connaissances sur la cryosphere (eau solide sous forme de glace ou de neige) sont encore restreintes (Bolch et al, 2012 ;Bouchard et al, 2019 ;Gurung et al, 2011). Tous ces facteurs compliquent l'élaboration et l'interprétation des modèles climatiques en Himalaya (Nepal et al, 2017 ;Savéan et al, 2015).…”

“…Elle est complétée de 2000 à 2012 par le produit MOD10A1 (Hall et al, 2002), issu du capteur satellitaire MODIS (Moderate Resolution Imaging Spectroradiometer) à un pas de temps journalier et une résolution de 15 arcs-secs. Toutes les données d'enneigement sont sujettes à des incertitudes significatives, qu'il s'agisse de leur quantité ou de leur extension (Bouchard et al, 2019).…”

Processing of VENµS Images of High Mountains: A Case Study for Cryospheric and Hydro-Climatic Applications in the Everest Region (Nepal)

“…This is especially true in the field of snow monitoring [11]. For example, in the Everest region, MODIS (Moderate-Resolution Imaging Spectroradiometer) imagery has been used to help constrain the contributions of snow and ice to streamflow [12][13][14] and to track seasonal migration of the snow line [15]. A new technical step was reached in terms of spatio-temporal resolution with the Copernicus Sentinel platforms from ESA (European Space Agency), and the recent VENµS (Vegetation and Environment New Micro Satellite) program.…”