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Exploiting the use of physical information for the calibration of a lumped hydrological model
Author(s) -
Manfreda Salvatore,
Mita Leonardo,
Dal Sasso Silvano Fortunato,
Samela Caterina,
Mancusi Leonardo
Publication year - 2018
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.11501
Subject(s) - streamflow , calibration , baseflow , computer science , hydrological modelling , reliability (semiconductor) , environmental science , hydrology (agriculture) , data mining , drainage basin , statistics , geology , mathematics , climatology , power (physics) , physics , cartography , geotechnical engineering , quantum mechanics , geography
Abstract In hydrological modelling, the challenge is to identify an optimal strategy to exploit tools and available observations in order to enhance model reliability. The increasing availability of data promotes the use of new calibration techniques able to make use of additional information on river basins. In the present study, a lumped hydrological model — designed with the aim of utilizing remotely sensed data — is introduced and calibrated, adopting four different schemes that adopt, to varying extents, available physical information. The physically consistent conceptualization of the hydrological model used allowed development of a step by step calibration based on a combination of information, such as remotely sensed data describing snow cover, recession curves obtained from streamflow measurements, and time series of surface run‐off obtained with a baseflow mathematical filter applied to the streamflow time‐series. Results suggest that the use of physical information in the calibration procedure tends to increase model reliability with respect to approaches where the parameters are calibrated using an overall statistic based, considerably or exclusively, on streamflow data.