Environmental hydrology of water balance analysed by statistical modelling using Python

This work presents the use of remote sensing data for hydrological and environmental analysis with a case of Dolomites Mountains, north Italy. The data includes remote sensing based micrometeorological measurements key hydrological parameters to calculate vertical turbulent fluxes within atmospheric boundary layers in coniferous forests. The period of measurements covered data from 2015. The operational workflow included statistical data processing in which the data were classified into categories of evapotranspiration, temperatures, precipitation, water pressure deficit and radiation obtained from various land cover types. The approach was implemented with aim at climate change and hydrological research and implications in forest ecohydrology in European Alps.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-26
DOI
https://doi.org/10.5281/zenodo.17209553
Primary Topic
Economic, financial, and policy analysis
Type
article
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0.00
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article

Environmental hydrology of water balance analysed by statistical modelling using Python

Zenodo (CERN European Organization for Nuclear Research)
Economic, financial, and policy analysis
article

Environmental hydrology of water balance analysed by statistical modelling using Python

article en

Abstract

This work presents the use of remote sensing data for hydrological and environmental analysis with a case of Dolomites Mountains, north Italy. The data includes remote sensing based micrometeorological measurements key hydrological parameters to calculate vertical turbulent fluxes within atmospheric boundary layers in coniferous forests. The period of measurements covered data from 2015. The operational workflow included statistical data processing in which the data were classified into categories of evapotranspiration, temperatures, precipitation, water pressure deficit and radiation obtained from various land cover types. The approach was implemented with aim at climate change and hydrological research and implications in forest ecohydrology in European Alps.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 36%
Economic, financial, and policy analysis
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