Method of Prediction of the Stream Flows in Poorly Gauged and Ungauged Basins

• Autorzy: Kuzmin Vadim , Pivovarova Inna , Shemanaev Kirill , Sokolova Daria , Batyrov Artur , Tran Ngoc Anh , Dang DinhKha

Identyfikatory

DOI

10.12911/22998993/94915

• Języki publikacji: EN

Abstrakty

EN

The underlying principles and content of new technology for automated hydrological predictions of poorly gauged and ungauged basins were reviewed herein. Basin classification principles depending on the availability and spatial-temporal discreteness of the observations of meteorological and hydrological variables were proposed. The prediction procedure for large river systems insufficiently covered by hydrometeorological survey was outlined. The prediction methodology for Sông Sê San river basin, which is the left tributary of Mekong river, was tested. The possible options for preliminary calibration and validation of MLCM3 predictive model (Multi-Layer Conceptual Model, 3rd generation), developed within the framework of set task, were described. The software, implementing the streamflow prediction method for ungauged and poorly gauged special basins of large rivers tributaries, was tested.

Słowa kluczowe

EN

hydrological prediction; basin; mathematic model; parametrization; ungauged basin; hydrometeorological survey

• Wydawca: Polskie Towarzystwo Inżynierii Ekologicznej ; Lublin University of Technology
• Czasopismo: Journal of Ecological Engineering
• Rocznik: 2019
• Tom: Vol. 20, nr 1
• Strony: 180--187
• Opis fizyczny: Bibliogr. 37 poz., rys., tab.

Twórcy

autor

Kuzmin Vadim

• State Hydrological Institute, 23, 2 Line, Vassilievsky Ostrov, St. Petersburg, 199053, Russia
• Russian State Hydrometeorological University, Malookhtinskiy 98, St. Petersburg 195196, Russia

autor

Pivovarova Inna

• Saint-Petersburg Mining University, 2, 21 Line, Vassilievsky Ostrov, St. Petersburg, 199026, Russia

autor

Shemanaev Kirill

• Russian State Hydrometeorological University, Malookhtinskiy 98, St. Petersburg 195196, Russia

autor

Sokolova Daria

• Russian State Hydrometeorological University, Malookhtinskiy 98, St. Petersburg 195196, Russia

autor

Batyrov Artur

• Russian State Hydrometeorological University, Malookhtinskiy 98, St. Petersburg 195196, Russia

autor

Tran Ngoc Anh

• VNU University of Science, Vietnam National University (VNU), 334 Nguyen Trai, Thanh Xuan, Hanoi, Vietnam

autor

Dang DinhKha

• VNU University of Science, Vietnam National University (VNU), 334 Nguyen Trai, Thanh Xuan, Hanoi, Vietnam

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).