Modeling flood zones on the basis of time series forecasting and GIS-technologies by the example of the Republic of Bashkortostan

A specialized GIS Web is proposed, implemented by integrating an artificial neural network and geotechnologies and providing early forecasting and modeling of flood zones up to five days in advance. The methods and algorithms implemented within this GIS Web allow daily forecasting of time series based on retrospective data on water levels and total water inflow, air and water temperature, snow cover thickness and precipitation, wind speed and atmospheric pressure. At the same time, the possibility of early modeling and visualization of river floods is realized only on the basis of the obtained predictive values of the water level. This will enable specialized organizations and services, as well as management bodies to make decisions related to flood control measures in advance and as soon as possible.

Authors

Publication Details

Journal
Computer Optics
Published
2024-12-01
DOI
https://doi.org/10.18287/2412-6179-co-1418
Primary Topic
Geological Studies and Exploration
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling flood zones on the basis of time series forecasting and GIS-technologies by the example of the Republic of Bashkortostan

Palchevsky E.V., L.A. Kromina, L.E. Rodionova, В.В. Антонов et al.
Computer Optics
Geological Studies and Exploration
article

Modeling flood zones on the basis of time series forecasting and GIS-technologies by the example of the Republic of Bashkortostan

Palchevsky E.V., L.A. Kromina, L.E. Rodionova, В.В. Антонов, A.R. Fakhrullina
article en

Abstract

A specialized GIS Web is proposed, implemented by integrating an artificial neural network and geotechnologies and providing early forecasting and modeling of flood zones up to five days in advance. The methods and algorithms implemented within this GIS Web allow daily forecasting of time series based on retrospective data on water levels and total water inflow, air and water temperature, snow cover thickness and precipitation, wind speed and atmospheric pressure. At the same time, the possibility of early modeling and visualization of river floods is realized only on the basis of the obtained predictive values of the water level. This will enable specialized organizations and services, as well as management bodies to make decisions related to flood control measures in advance and as soon as possible.

Computer OpticsVol. 48(6)
Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 49%
Geological Studies and Exploration
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.