Open AccessLong-term forecast model of spring runoff on the Belaya river
Author(s) -
D. Yu. Vasil’ev,
Dimitar Vasilev,
V. V. Vodopyanov,
В. В. Водопьянов,
G. S. Zayzeva,
Г С Зайцева,
Sh. I. Zakirzyanov,
Ш. И. Закирзянов,
В. В. Семенов,
В. А. Семенов,
Ж. Т. Сивохип,
Ж. Т. Сивохип,
А. А. Чибилев,
А А Чибилёв
Publication year - 2019
Publication title -
doklady akademii nauk. rossijskaâ akademiâ nauk
Language(s) - English
Resource type - Journals
ISSN - 0869-5652
DOI - 10.31857/s0869-56524866723-726
Subject(s) - hydrometeorology , surface runoff , term (time) , stability (learning theory) , reliability (semiconductor) , spring (device) , water balance , hydrology (agriculture) , mathematics , meteorology , environmental science , precipitation , statistics , computer science , geology , geotechnical engineering , engineering , geography , physics , mechanical engineering , ecology , power (physics) , quantum mechanics , machine learning , biology
This article presents the results of long-term forecasting of spring runoff in the Belaya River basin, based on the water balance model. To optimize the structure and parameters of the water balance model equations, the Levenberg-Marquardt algorithm was used to impose restrictions on the input data values. The obtained values of the equations’ coefficients were checked according to the criterion D/s adopted in the hydrometeorological service. The reliability of the predictive method used was assessed by statistical calculations of the stability of their parameters and test calculations on an independent sample. All equations obtained during the numerical experiment may be suitable to make forecasts.