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Multitask Learning with Statistical Parametrization for Ecohydrological Analysis Cover

Multitask Learning with Statistical Parametrization for Ecohydrological Analysis

Open Access
|Dec 2025

Abstract

This paper proposes a novel multi-task statistical learning framework which aims to concurrently address all the environmental challenges in the Alps. The goal is to analyse the effects of lichen and fog on water balance. The objective is the analysis of water balance mechanisms by investigating the contribution of fog and the role of forest age in the water cycle. The methods include advanced multitask learning with statistical modelling techniques. The results shown that interception plays a dominant role in the precipitation and evapotranspiration partitioning, enhanced by lichens. Trees transpiration as lower in the young stand and the evapotranspiration of soil and understory contributed considerably to the water balance at both stands. Moreover, fog caused additional throughfall in mixed fog and rain precipitation.

DOI: https://doi.org/10.2478/trser-2025-0009 | Journal eISSN: 2344-3219 | Journal ISSN: 1841-7051
Language: English
Page range: 1 - 20
Published on: Dec 12, 2025
Published by: Lucian Blaga University of Sibiu
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year
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© 2025 Polina Lemenkova, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.