An Enkf-Based Scheme for Snow Multivariable Data Assimilation at an Alpine Site

The knowledge of snowpack dynamics is of critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertain...

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Bibliographic Details
Published inJournal of Hydrology and Hydromechanics Vol. 67; no. 1; pp. 4 - 19
Main Authors Piazzi, Gaia, Campo, Lorenzo, Gabellani, Simone, Castelli, Fabio, Cremonese, Edoardo, Cella, Umberto Morra di, Stevenin, Hervé, Ratto, Sara Maria
Format Journal Article
LanguageEnglish
Published Bratislava Sciendo 01.03.2019
De Gruyter Poland
Subjects
Agricultural management
Agricultural production
Agricultural resources
Alpine environments
Basins
Computer simulation
Data
Data Assimilation
Data collection
Dynamics
Energy balance
Energy-balance model
Ensemble Kalman Filter
Flood control
Flood management
Flood prevention
Frameworks
Hydroelectric power
Hydroelectric power generation
Kalman filters
Modelling
Remote sensing
Resource management
Sensitivity analysis
Snow
Snow modeling
Snowpack
Water management
Water resources
Water resources management
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Summary:The knowledge of snowpack dynamics is of critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertainty, an increasing interest focuses on the assimilation of snow-related observations with the purpose of enhancing predictions on snowpack state. The study aims at investigating the effectiveness of snow multivariable data assimilation (DA) at an Alpine site. The system consists of a snow energy-balance model strengthened by a multivariable DA system. An Ensemble Kalman Filter (EnKF) scheme allows assimilating ground-based and remotely sensed snow observations in order to improve the model simulations. This research aims to investigate and discuss: (1) the limitations and constraints in implementing a multivariate EnKF scheme in the framework of snow modelling, and (2) its performance in consistently updating the snowpack state. The performance of the multivariable DA is shown for the study case of Torgnon station (Aosta Valley, Italy) in the period June 2012 - December 2013. The results of several experiments are discussed with the aim of analyzing system sensitivity to the DA frequency, the ensemble size, and the impact of assimilating different observations.
ISSN:0042-790X
0042-790X
1338-4333
DOI:10.2478/johh-2018-0013