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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Precipitation tends to increase with elevation, but the exact magnitude and distribution of this enhancement remain poorly understood. By leveraging 11,000+ spatially distributed, manual measurements of snow depth (snow courses) upstream two reservoirs in the Western European Alps, we showed that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improving modeling accuracy and ultimately our understanding of the water budget.
Preprints
https://doi.org/10.5194/hess-2020-571
https://doi.org/10.5194/hess-2020-571

  26 Nov 2020

26 Nov 2020

Review status: this preprint is currently under review for the journal HESS.

Learning about precipitation orographic enhancement from snow-course data improves water-balance modeling

Francesco Avanzi1, Giulia Ercolani1, Simone Gabellani1, Edoardo Cremonese2, Paolo Pogliotti2, Gianluca Filippa2, Umberto Morra di Cella2,1, Sara Ratto3, Hervè Stevenin3, Marco Cauduro4, and Stefano Juglair4 Francesco Avanzi et al.
  • 1CIMA Research Foundation, Via Armando Magliotto 2, 17100 Savona, Italy
  • 2Climate Change Unit, Environmental Protection Agency of Aosta Valley, Loc. La Maladière, 48-11020 Saint-Christophe, Italy
  • 3Regione Autonoma Valle d’Aosta, Centro funzionale regionale, Via Promis 2/a, 11100 Aosta, Italy
  • 4Direzione Operativa Operations, C.V.A. S.p.A., Via Stazione 31, 11024 Châtillon, Italy

Abstract. Precipitation orographic enhancement depends on both synoptic circulation and topography. Since high-elevation headwaters are often sparsely instrumented, the magnitude and distribution of this enhancement remain poorly understood. Filling this knowledge gap would allow a significant step ahead for hydrologic-forecasting procedures and water management in general. Here, we hypothesized that spatially distributed, manual measurements of snow depth (courses) could provide new insights into this process. We leveraged 11,000+ snow-course data upstream two reservoirs in the Western European Alps (Aosta Valley, Italy) to estimate precipitation orographic enhancement in the form of lapse rates and consequently improve predictions of a snow-hydrologic modeling chain (Flood-PROOFS). We found that Snow Water Equivalent (SWE) above 3000 m ASL was between 2 and 8.5 times higher than recorded cumulative seasonal precipitation below 1000 m ASL, with gradients up to 1000 mm w.e. km−1. Enhancement factors estimated by blending precipitation-gauge and snow-course data were quite consistent between the two hydropower headwaters (median values above 3000 m ASL between 4.1 and 4.8). Including blended gauge-course lapse rates in an iterative precipitation-spatialization procedure allowed Flood-PROOFS to remedy underestimations of both SWE above 3000 m ASL (up to 50 %) and importantly precipitation vs. observed streamflow. Runoff coefficients based on blended lapse rates were also more consistent from year to year that those based on precipitation gauges alone (standard deviation of 0.06 and 0.19, respectively). Thus, snow courses bear a characteristic signature of orographic precipitation, which opens a window of opportunity for leveraging these data sets to improve our understanding of the mountain water budget. This is all the more important due to their essential role in supporting water security and ecosystem services worldwide.

Francesco Avanzi et al.

 
Status: open (until 21 Jan 2021)
Status: open (until 21 Jan 2021)
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Francesco Avanzi et al.

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Short summary
Precipitation tends to increase with elevation, but the exact magnitude and distribution of this enhancement remain poorly understood. By leveraging 11,000+ spatially distributed, manual measurements of snow depth (snow courses) upstream two reservoirs in the Western European Alps, we showed that these courses bear a characteristic signature of orographic precipitation. This opens a window of opportunity for improving modeling accuracy and ultimately our understanding of the water budget.
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