Articles | Volume 21, issue 7
Research article
27 Jul 2017
Research article |  | 27 Jul 2017

A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction

Ashley Wright, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels

Data sets

Model Parameter Estimation Experiment (MOPEX) National Weather Service (NWS)

Short summary
The accurate reduction of hydrologic model input data is an impediment towards understanding input uncertainty and model structural errors. This paper compares the ability of two transforms to reduce rainfall input data. The resultant transforms are compressed to varying extents and reconstructed before being evaluated with standard simulation performance summary metrics and descriptive statistics. It is concluded the discrete wavelet transform is most capable of preserving rainfall time series.