[740] - Quality control of daily rainfall data with neural networks

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Sciuto, G., Bonaccorso, B., Cancelliere, A., Rossi, G., 2009. Quality control of daily rainfall data with neural networks. Journal of Hydrology, 364, 13 - 22. DOI: 10.1016/j.jhydrol.2008.10.008.
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Title(s):Main Title: Quality control of daily rainfall data with neural networks
Description(s):Abstract: A procedure for quality control of daily rainfall, designed to automatically detect erroneous data to be submitted for further manual controls, is herein described. Quality control of daily rainfall data is based on confidence intervals derived by means of neural networks on the basis of contemporaneous data observed at reference stations, since the presence of zero values in the series and the strong variability of precipitation at daily time scale do not allow reliable confidence intervals to be estimated from historical data from the same station. Application of the proposed procedure to automatic stations in Sicily (Italy), enables validation of more than 80% of the data. The accuracy of the procedures is verified by introducing known errors into the available datasets, supposed as correct, and by computing the probabilities of correctly classifying data as validated or not validated.
Identifier(s):DOI: 10.1016/j.jhydrol.2008.10.008
Responsible Party
Creator(s):Author: Guido Sciuto
Author: Brunella Bonaccorso
Author: Antonino Cancelliere
Author: Giuseppe Rossi
Publisher:Elsevier B.V
TR32 Topic:Atmosphere
Subject(s):CRC/TR32 Keywords: Rainfall Data, Quality Control, Neural Networks
File Details
File Name:2009_Scuito_JoH.pdf
Data Type:Text
Size(s):10 Pages
File Size:834 kB (0.814 MB)
Date(s):Date Accepted: 2008-10-09
Mime Type:application/pdf
Data Format:PDF
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
North:-no map data
Measurement Region:Other
Measurement Location:--Other--
Specific Informations - Publication
Article Type:Journal
Source:Journal of Hydrology
Number Of Pages:10
Page Range:13 - 22
Metadata Details
Metadata Creator:Guido Sciuto
Metadata Created:2013-12-02
Metadata Last Updated:2013-12-02
Funding Phase:1
Metadata Language:English
Metadata Version:V40
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