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Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling
Joint Authors
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-08
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Precipitation is the main factor that drives hydrologic modeling; therefore, missing precipitation data can cause malfunctions in hydrologic modeling.
Although interpolation of missing precipitation data is recognized as an important research topic, only a few methods follow a regression approach.
In this study, daily precipitation data were interpolated using five different kernel functions, namely, Epanechnikov, Quartic, Triweight, Tricube, and Cosine, to estimate missing precipitation data.
This study also presents an assessment that compares estimation of missing precipitation data through K th nearest neighborhood ( K NN) regression to the five different kernel estimations and their performance in simulating streamflow using the Soil Water Assessment Tool (SWAT) hydrologic model.
The results show that the kernel approaches provide higher quality interpolation of precipitation data compared with the K NN regression approach, in terms of both statistical data assessment and hydrologic modeling performance.
American Psychological Association (APA)
Lee, Hyojin& Kang, Kwangmin. 2015. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling. Advances in Meteorology،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1052858
Modern Language Association (MLA)
Lee, Hyojin& Kang, Kwangmin. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling. Advances in Meteorology No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1052858
American Medical Association (AMA)
Lee, Hyojin& Kang, Kwangmin. Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling. Advances in Meteorology. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1052858
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1052858