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