Regionalization of hydrological model parameters using gradient boosting machine

The regionalization of hydrological model parameters is key to hydrological predictions in ungauged basins. The commonly used multiple linear regression (MLR) method may not be applicable in complex and nonlinear relationships between model parameters and watershed properties. Moreover, most regiona...

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Vydané v:	Hydrology and earth system sciences Ročník 26; číslo 2; s. 505 - 524
Hlavní autori:	Song, Zhihong, Xia, Jun, Wang, Gangsheng, She, Dunxian, Hu, Chen, Hong, Si
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Katlenburg-Lindau Copernicus GmbH 31.01.2022 Copernicus Publications
Predmet:	Analysis Arid regions Arid zones Calibration Climatic zones Datasets Elevation Evapotranspiration Evapotranspiration processes Heterogeneity Hydrologic models Hydrology Learning algorithms Machine learning Mathematical models Modelling Moisture content Neural networks Parameters Performance evaluation Properties Regression analysis Runoff Saturated soils Soil Soil moisture Soil moisture content Stream discharge Stream flow Variables Water content Watersheds China
ISSN:	1607-7938, 1027-5606, 1607-7938
On-line prístup:	Získať plný text
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