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Sensitivity of the performance of a conceptual rainfall–runoff model to the temporal sampling of calibration data
Author(s) -
Satish Bastola,
Conor Murphy
Publication year - 2012
Publication title -
hydrology research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 48
eISSN - 1996-9694
pISSN - 0029-1277
DOI - 10.2166/nh.2012.061
Subject(s) - calibration , sensitivity (control systems) , surface runoff , temporal resolution , sampling (signal processing) , scaling , environmental science , flood myth , computer science , hydrological modelling , measure (data warehouse) , statistics , mathematics , data mining , geology , climatology , philosophy , theology , ecology , physics , geometry , filter (signal processing) , quantum mechanics , electronic engineering , engineering , computer vision , biology
The effect of the time step of calibration data on the performance of a hydrological model is examined through a numerical experiment where HYMOD, a rainfall–runoff model, is calibrated with data of varying temporal resolution. A simple scaling relationship between the parameters of the model and modelling time step is derived which enables information from daily hydrological records to be used in modelling at time steps much shorter than daily. Model parameters were found to respond differently depending upon the degree of aggregation of calibration data. A loss in performance, especially in terms of the Nash–Sutcliffe measure, is evident when behavioural simulators derived with one modelling time step are used for simulation at another time step. The loss in performance is greater when parameters derived from a longer time step were used for simulating flow with a shorter time step. The application of a simple scaling relationship derived from a multi-time step model calibration significantly decreased the loss in model performance. Such an approach may offer the prospect of conducting higher temporal resolution flood frequency analysis when finer scale data for model calibration are not available or limited.

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