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Assessment of Changes in Precipitation Data Characteristics due to Infilling by Spatially Interpolated Estimates

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Date Issued:
2016
Summary:
Spatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy of optimal weighting interpolation for estimation of missing data in preserving time series characteristics. Rain gauges in the state of Kentucky are used as a case study. Several model performance measures are also evaluated to validate the filling model; followed by time series characteristics to evaluate the accuracy of estimation and preservation of precipitation data characteristics. This study resulted in a definition of region-specific threshold of the maximum length of gaps allowed in a data set at five percent.
Title: Assessment of Changes in Precipitation Data Characteristics due to Infilling by Spatially Interpolated Estimates.
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Name(s): Hachmi, Mohammad, author
Teegavarapu, Ramesh, Thesis advisor
Florida Atlantic University, Degree grantor
College of Engineering and Computer Science
Department of Civil, Environmental and Geomatics Engineering
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2016
Date Issued: 2016
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 124 p.
Language(s): English
Summary: Spatial and temporal interpolation methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these interpolation methods have not been comprehensively checked for their ability to preserve time series characteristics. Assessing the preservation of time series characteristics helps achieving a threshold criteria of length of gaps in a data set that is acceptable to be filled. This study evaluates the efficacy of optimal weighting interpolation for estimation of missing data in preserving time series characteristics. Rain gauges in the state of Kentucky are used as a case study. Several model performance measures are also evaluated to validate the filling model; followed by time series characteristics to evaluate the accuracy of estimation and preservation of precipitation data characteristics. This study resulted in a definition of region-specific threshold of the maximum length of gaps allowed in a data set at five percent.
Identifier: FA00004783 (IID)
Degree granted: Thesis (M.S.)--Florida Atlantic University, 2016.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Precipitation (Meteorology)
Spatial analysis (Statistics)
Geographic information systems--Mathematical models.
Climatic changes--Environmental aspects.
Functions of real variables.
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Links: http://purl.flvc.org/fau/fd/FA00004783
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00004783
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.