Shaw, Thomas E., Caro, Alexis, Mendoza, Pablo, Ayala, Álvaro, Pellicciotti, Francesca, Gascoin, Simon and McPhee, James (2020) The Utility of Optical Satellite Winter Snow Depths for Initializing a Glacio‐Hydrological Model of a High‐Elevation, Andean Catchment. Water Resources Research, 56 (8). e2020WR027188. ISSN 0043-1397
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Water Resources Research - 2020 - Shaw - The Utility of Optical Satellite Winter Snow Depths for Initializing a.pdf - Published Version Download (9MB) | Preview |
Abstract
Information about end-of-winter spatial distribution of snow depth is important for seasonal forecasts of spring/summer streamflow in high-mountain regions. Nevertheless, such information typically relies upon extrapolation from a sparse network of observations at low elevations. Here, we test the potential of high-resolution snow depth data derived from optical stereophotogrammetry of Pléiades satellites for improving the representation of snow depth initial conditions (SDICs) in a glacio-hydrological model and assess potential improvements in the skill of snowmelt and streamflow simulations in a high-elevation Andean catchment. We calibrate model parameters controlling glacier mass balance and snow cover evolution using ground-based and satellite observations, and consider the relative importance of accurate estimates of SDICs compared to model parameters and forcings. We find that Pléiades SDICs improve the simulation of snow-covered area, glacier mass balance, and monthly streamflow compared to alternative SDICs based upon extrapolation of meteorological variables or statistical methods to estimate SDICs based upon topography. Model simulations are found to be sensitive to SDICs in the early spring (up to 48% variability in modeled streamflow compared to the best estimate model), and to temperature gradients in all months that control albedo and melt rates over a large elevation range (>2,400 m). As such, appropriately characterizing the distribution of total snow volume with elevation is important for reproducing total streamflow and the proportions of snowmelt. Therefore, optical stereo-photogrammetry offers an advantage for obtaining SDICs that aid both the timing and magnitude of streamflow simulations, process representation (e.g., snow cover evolution) and has the potential for large spatial domains.
| Item Type: | Article |
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| Additional Information: | Funding information: This work recognizes funding from FONDECYT projects 3180145 (T. E. Shaw), 1171032 (J. McPhee), 3170079 (P. Mendoza), and 3190732 (A. Ayala) as well as equipment and field work support by project “Estudio del aporte glaciar en la cuenca del río Maipo,” developed by Cetaqua/Untec for Aguas Andinas, Sociedad del Canal de Maipo y Junta de Vigilancia del río Maipo. Fieldwork was supported by S. Quezada, B. Mir, S. Barros, J. Venegas, E. Aldunate, Y. Videla, and M. Huerta. AWS and flowmeter stations used in the “Estudio del aporte glaciar en la cuenca del río Maipo” were provided by Latina UC and the research group of C. Oberli. This work has been supported by the CNES Tosca and the Programme National de Télédétection Spatiale (PNTS, http://www.insu.cnrs.fr/pnts), Grant PNTS-2018-4. Forcing data, model grids, initial condition maps, parameters, and model run files are provided in the following repository: https://zenodo.org/record/3613951#.XiYSKkaJKUk (doi:10.5281/zenodo.3613951, cited as Shaw, Caro, et al., 2020). We thank scientific editor J. Lundquist and two anomymous reviewers for the valuable comments that improved the quality of the manuscript. |
| Subjects: | F700 Ocean Sciences F800 Physical and Terrestrial Geographical and Environmental Sciences |
| Department: | Faculties > Engineering and Environment > Geography and Environmental Sciences |
| Depositing User: | Elena Carlaw |
| Date Deposited: | 07 Sep 2022 10:50 |
| Last Modified: | 07 Sep 2022 11:00 |
| URI: | https://nrl.northumbria.ac.uk/id/eprint/50047 |
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