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Exploring streamflow response to effective rainfall across event magnitude scale
Author(s) -
Kokkonen Teemu,
Koivusalo Harri,
Karvonen Tuomo,
Croke Barry,
Jakeman Anthony
Publication year - 2004
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.1423
Subject(s) - hydrograph , streamflow , precipitation , environmental science , magnitude (astronomy) , surface runoff , scale (ratio) , event (particle physics) , hydrology (agriculture) , meteorology , drainage basin , geology , geography , physics , geotechnical engineering , ecology , cartography , quantum mechanics , astronomy , biology
Sets of flow events from four catchments were selected in order to study how dynamics in the conversion of effective rainfall into streamflow depends on the event size. The approach taken was to optimize parameters of a linear delay function and effective rainfall series concurrently from precipitation–streamflow data without imposing a functional form of the precipitation filter a priori . The delay function is an instantaneous unit hydrograph (IUH) having a mathematical form of the two‐parameter gamma distribution. Results from two small research catchments (0·18 and 0·63 km 2 ) with sub‐daily data suggest a clear relationship between the event magnitude and response dynamics. The effect of the sampling frequency of data was addressed by gradually increasing aggregation interval of rainfall and flow data and repeating the optimization for each aggregated dataset. IUHs for different data aggregation intervals (for a single event) tended to be similar unless the aggregation changed the locations of data peaks. IUHs identified in larger catchments (58 and 1235 km 2 ) also showed variability through events; however, no systematic event magnitude dependence, as was visible in the small research catchments, was detected. Finally, the dependency detected in the small catchments was exploited in a rainfall‐runoff model, where the scale parameter of the gamma distribution was linearly related to the effective rainfall intensity. Prediction of peak flows improved when the event dependency was taken into account. Copyright © 2004 John Wiley & Sons, Ltd.