TY - JOUR

T1 - Python-based statistical analysis of the ecological variables in the Italian Alps

AU - Леменкова, Полина Алексеевна

PY - 2025/6/22

Y1 - 2025/6/22

N2 - The high Alpine region of northern Italy is characterized by unique ecosystems, a complex hydrogeological setting, steep topographic gradients, variety of vegetation types and landscape patches, and varied in climatic and meteorological factors. Alpine ecosystem is even more complex when the vegetation composition is dominated by coniferous trees, since underground flow conditions and directions have unpredictable water quantities. Modelling such ecosystems requires advanced tools of programming and computing approaches, such as Python. This article is focused on the distributed water balance modelling in alpine catchments. The area is dominated by the coniferous forests (spruce, pine) with trees of different age (old >200 years and young, <30 years). Selected trees are covered by epyhytes (lichens). For effective planning and management of the use of water resources, Python-supported estimations and statistical modelling are a necessary approach for environmental forest monitoring. In particular, the highest suitable spatial resolution that can be achieved in water balance estimations is evaluated in a complicated topographical setting of South Tyrolean Alps with limited knowledge of physiographic factors of forest and meteorological variables (precipitation, temperature, air humidity).

AB - The high Alpine region of northern Italy is characterized by unique ecosystems, a complex hydrogeological setting, steep topographic gradients, variety of vegetation types and landscape patches, and varied in climatic and meteorological factors. Alpine ecosystem is even more complex when the vegetation composition is dominated by coniferous trees, since underground flow conditions and directions have unpredictable water quantities. Modelling such ecosystems requires advanced tools of programming and computing approaches, such as Python. This article is focused on the distributed water balance modelling in alpine catchments. The area is dominated by the coniferous forests (spruce, pine) with trees of different age (old >200 years and young, <30 years). Selected trees are covered by epyhytes (lichens). For effective planning and management of the use of water resources, Python-supported estimations and statistical modelling are a necessary approach for environmental forest monitoring. In particular, the highest suitable spatial resolution that can be achieved in water balance estimations is evaluated in a complicated topographical setting of South Tyrolean Alps with limited knowledge of physiographic factors of forest and meteorological variables (precipitation, temperature, air humidity).

KW - Python

KW - modelling

KW - environmental monitoring

KW - climate

KW - statistics

KW - data analysis

UR - https://aseestant.ceon.rs/index.php/jouproman/article/view/57672/28059

U2 - 10.5281/zenodo.15714443

DO - 10.5281/zenodo.15714443

M3 - Article

VL - 13

SP - 102

EP - 112

JO - Journal of Process Management and New Technologies

JF - Journal of Process Management and New Technologies

SN - 2334-735X

IS - 1-2

ER -