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Rainfall characteristics define the value of streamflow observations for distributed watershed model identification
Author(s) -
van Werkhoven Kathryn,
Wagener Thorsten,
Reed Patrick,
Tang Yong
Publication year - 2008
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2008gl034162
Subject(s) - watershed , streamflow , environmental science , distributed element model , identification (biology) , parametric statistics , parametric model , hydrology (agriculture) , geology , computer science , mathematics , geography , statistics , ecology , cartography , drainage basin , physics , geotechnical engineering , quantum mechanics , machine learning , biology
We present evidence that the characteristics of rainfall events strongly control the value of streamflow observations for the identification of distributed watershed models. A series of synthetic rainfall events with different spatio‐temporal extents and dynamics are used to investigate spatially‐distributed global parameter sensitivities for a typical watershed model. The model's parametric sensitivities vary greatly with rainfall distribution characteristics, location of the model cell in relation to the watershed's gauged outlet, and, to a lesser degree, the initial model states. This study demonstrates that the information content of streamflow is a dynamic property and that distributed model identification methodologies should consider the impact of spatio‐temporal rainfall dynamics.