18
Development of the Approach
for the Complex Prediction of Spring
Floods
A. A. Volchak, D. A. Kostiuk, D. O. Petrov, and
N. N. Sheshko
Abstract
Snow storage influence on the flood situation
and the contemporary approaches to determine water content in a snow cover are
discussed. An artificial neural network application is proposed and tested to improve the
accuracy of snow water equivalent retrieval
from the satellite microwave radiometer-based
measurements and to predict the water discharge in a river flow control point. A method
of inundation zone outline calculation in case
of river flood situation is proposed and
evaluated.
Keywords
Flood Á River Á Snow Á Radio-temperature Á
Forecast
18.1 Snow Storage Influence
on the Flood Situation
Prediction of the flood evolution is a complicated
task, which makes it necessary to take into
account a lot of factors. Particularly, long spring
flood is typical for water regime of some rivers,
having nourishment of a mixed type with prevailing snow one. Therefore, taking into account
the dynamics of snow storage accumulation
allows to increase the prediction accuracy and to
make more effective organizational and technical
measures to level out flood consequences.
Snow storage in the beginning of the active
melting period is the main source of the maximal
discharges causing material and social damage.
Besides the amount of snow, weather also makes
substantial influence on the spring flood formation. Therefore, it is possible to predict the volume of the spring river flow based on the
estimation of water, stored in the form of a snow
over the watershed. Temperatures and rainfalls
mid-term prediction allows in their turn to estimate the snow melting intensity and the corresponding maximum discharge of the river, which
is possible in the flood time.
A. A. Volchak (&) Á D. A. Kostiuk Á D. O. Petrov Á
N. N. Sheshko
Brest State Technical University, 267, Moskovskaya
Str., Brest 224017, Belarus
e-mail: volchak@tut.by
D. A. Kostiuk
e-mail: dmitriykostiuk@gmail.com
D. O. Petrov
e-mail: polegdo@gmail.com
N. N. Sheshko
e-mail: optimum@tut.by
© Springer Nature Switzerland AG 2021
B. W. Pandey and S. Anand (eds.), Water Science and Sustainability, Sustainable Development Goals Series,
https://doi.org/10.1007/978-3-030-57488-8_18
235
Development of the Approach
for the Complex Prediction of Spring
Floods
A. A. Volchak, D. A. Kostiuk, D. O. Petrov, and
N. N. Sheshko
Abstract
Snow storage influence on the flood situation
and the contemporary approaches to determine water content in a snow cover are
discussed. An artificial neural network application is proposed and tested to improve the
accuracy of snow water equivalent retrieval
from the satellite microwave radiometer-based
measurements and to predict the water discharge in a river flow control point. A method
of inundation zone outline calculation in case
of river flood situation is proposed and
evaluated.
Keywords
Flood Á River Á Snow Á Radio-temperature Á
Forecast
18.1 Snow Storage Influence
on the Flood Situation
Prediction of the flood evolution is a complicated
task, which makes it necessary to take into
account a lot of factors. Particularly, long spring
flood is typical for water regime of some rivers,
having nourishment of a mixed type with prevailing snow one. Therefore, taking into account
the dynamics of snow storage accumulation
allows to increase the prediction accuracy and to
make more effective organizational and technical
measures to level out flood consequences.
Snow storage in the beginning of the active
melting period is the main source of the maximal
discharges causing material and social damage.
Besides the amount of snow, weather also makes
substantial influence on the spring flood formation. Therefore, it is possible to predict the volume of the spring river flow based on the
estimation of water, stored in the form of a snow
over the watershed. Temperatures and rainfalls
mid-term prediction allows in their turn to estimate the snow melting intensity and the corresponding maximum discharge of the river, which
is possible in the flood time.
A. A. Volchak (&) Á D. A. Kostiuk Á D. O. Petrov Á
N. N. Sheshko
Brest State Technical University, 267, Moskovskaya
Str., Brest 224017, Belarus
e-mail: volchak@tut.by
D. A. Kostiuk
e-mail: dmitriykostiuk@gmail.com
D. O. Petrov
e-mail: polegdo@gmail.com
N. N. Sheshko
e-mail: optimum@tut.by
© Springer Nature Switzerland AG 2021
B. W. Pandey and S. Anand (eds.), Water Science and Sustainability, Sustainable Development Goals Series,
https://doi.org/10.1007/978-3-030-57488-8_18
235