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Environmental Modelling & Software
Article . 2007 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Effect of data length on rainfall–runoff modelling

Authors: Boughton, Walter;

Effect of data length on rainfall–runoff modelling

Abstract

Abstract A 64-year data set of daily rainfall and runoff, and average monthly potential evapotranspiration (PET) was split into subsets of 2, 5, 10, 20 and 30 years. Each subset was used to calibrate the AWBM daily rainfall–runoff model. Each subset calibration was then used to estimate runoff from the 64 years of rainfall and PET data. The ratios of calculated to actual total runoff were used to determine the ranges of error from the different lengths of data used for calibration. There was little difference in results from the 2- and 5-year subsets with 90% of estimates of long term runoff in the range of −21% to +31% of the recorded value. Overestimation of long term runoff reduced with length of calibration data of 10 or more years; however, the chances of underestimating were only slightly reduced even with 30 years of calibration data. Some limited repetition of the calculations with the Curve Number rainfall–runoff model indicated that the error characteristics were inherent in the data set and not an artifact of the model used. The ramifications for applications of rainfall–runoff modelling are briefly discussed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Top 10%
Top 10%
Average
Green
bronze