Date of Award
2012
Document Type
Thesis
Publication Status
Version of Record
Submission Date
October 2026
Abstract
Deterministic and stochastic weighting methods are commonly used methods for estimating missing precipitation rain gauge data based on values recorded at neighboring gauges. However, these spatial interpolation methods seldom check for their ability to preserve site and regional statistics. Such statistics and primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study evaluates the efficacy of traditional interpolation methods for estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky are used as a case study, and several error and performance measures are used to evaluate the trade-offs in accuracy of estimation and preservation of site and regional statistics.
Extent
xiv, 193 p. : ill.
Recommended Citation
El, Sharif Husayn, "Statistics preserving spatial interpolation methods for missing precipitation data" (2012). Electronic Theses and Dissertations 2010 - 2019. 649.
https://digitalcommons.fau.edu/etd_general_6/649
Identifier
FADT3355568
Comments
by Husayn El Sharif.|Thesis (M.S.C.S.)--Florida Atlantic University, 2012.|Includes bibliography.|Mode of access: World Wide Web.|System requirements: Adobe Reader.|by Husayn El Sharif.