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.
Lemenkova, P. (2025). Environmental hydrology of water balance analysed by statistical modelling using Python. "OVIDIUS" UNIVERSITY ANNALS. SERIES CIVIL ENGINEERING, 27(1), 1-8 [10.5281/zenodo.17209554].
Environmental hydrology of water balance analysed by statistical modelling using Python
Polina Lemenkova
Primo
2025
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


