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Spatial and temporal variability in the R‐5 infiltration data set: Déjà vu and rainfall‐runoff simulations
Author(s) -
Loague Keith,
Kyriakidis Phaedon C.
Publication year - 1997
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/97wr01093
Subject(s) - surface runoff , infiltration (hvac) , environmental science , runoff curve number , hydrology (agriculture) , runoff model , spatial variability , spatial distribution , soil science , geology , meteorology , mathematics , statistics , geography , geotechnical engineering , remote sensing , ecology , biology
This paper is a continuation of the event‐based rainfall‐runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi‐physically based rainfall‐runoff model for three large events from the well‐known R‐5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R‐5 infiltration data set [ Loague and Gander , 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R‐5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall‐runoff simulations with the Horton rainfall‐runoff model. The new rainfall‐runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near‐surface hydrologic response of the R‐5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.