On Transformation of Vegetation Parameters in Modeling the Response of Terrestrial Heat and Water Balance Components to Possible Climate Changes

A scenario-based methodology has been developed for projecting changes in vegetation parameters used in Earth system parameterization schemes in Russia under the influence of global climate change. The methodology is based on artificial neural networks and reproduces the dependence of these parameters on climatic, edaphic, and orographic factors. For the 2073–2100 projection period and the SSP5-RCP8.5 climate scenario, changes in more than fifty vegetation parameters derived from the ECOCLIMAP physiographic database across Russia were calculated, and maps of the spatial distribution of these changes were constructed. It is shown that changes in the considered parameters by the end of the 21st century for the selected climate scenario are quite noticeable and multidirectional (in terms of the sign). The absolute deviations of the projected values of various parameters from historical ones, averaged over the territory of Russia, range from 5 to 17%.

Authors

Institutions

Publication Details

Journal
Water Resources
Published
2026-03-16
DOI
https://doi.org/10.1134/s0097807825604637
Primary Topic
Climate Change and Environmental Impact
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On Transformation of Vegetation Parameters in Modeling the Response of Terrestrial Heat and Water Balance Components to Possible Climate Changes

E. M. Gusev, O. N. Nasonova
Water Resources
Climate Change and Environmental Impact
article

On Transformation of Vegetation Parameters in Modeling the Response of Terrestrial Heat and Water Balance Components to Possible Climate Changes

E. M. Gusev, O. N. Nasonova
article en

Abstract

A scenario-based methodology has been developed for projecting changes in vegetation parameters used in Earth system parameterization schemes in Russia under the influence of global climate change. The methodology is based on artificial neural networks and reproduces the dependence of these parameters on climatic, edaphic, and orographic factors. For the 2073–2100 projection period and the SSP5-RCP8.5 climate scenario, changes in more than fifty vegetation parameters derived from the ECOCLIMAP physiographic database across Russia were calculated, and maps of the spatial distribution of these changes were constructed. It is shown that changes in the considered parameters by the end of the 21st century for the selected climate scenario are quite noticeable and multidirectional (in terms of the sign). The absolute deviations of the projected values of various parameters from historical ones, averaged over the territory of Russia, range from 5 to 17%.

Water ResourcesVol. 53(2)
Institute of Water Problems (RU)
Climate action
Openalex Percentile: Top 18%
Climate Change and Environmental Impact
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.