{"id":{"repo_id":"houston","oai_identifier":"oai:uh-ir.tdl.org:10657/3191"},"canonical_url":"https://search.dev.ndltd.org/etd/houston/oai:uh-ir.tdl.org:10657/3191","repository":{"repo_id":"houston","name":"University of Houston","base_url":"https://uh-ir.tdl.org/server/oai/request"},"display":{"title":"Three-Dimensional Distance Based Geostatistical Models to Adjust Radar Rainfall Data","abstract":"Accurate and reliable rainfall input is crucial for hydrological modeling studies. Rain gauge collection and weather radar rainfall estimate are two of the most common techniques used for receiving rainfall data at a watershed. This study focuses on the development of three-dimensional (3D) distances based geostatistical models, such as Regression Kriging (RK) and Merging methods, to perform the adjustments of radar rainfall data to the targeted gauge measurements. These models are tested at the Chenyulan River watershed using the rainfall events of five typhoons landed Taiwan in recent years. Two-dimensional (2D) distance based models are also simulated to compare the adjusted rainfall values with those from 3D distance approaches. Results from Ordinary Kriging (OK) and gauge data are also included for comparisons. It is found in general the radar rainfall data can be corrected more accurately using the developed RK or Merging models than OK. Additionally, the adjusted rainfall values from 3D distance based models are similar to those using 2D distance based calculations at most tested stations. Depending on the typhoon events, using 3D distances in the semivariogram and Kriging interpolations is shown to be able to produce improved estimations of radar rainfall rates than 2D distance based calculations.","abstract_html":"Accurate and reliable rainfall input is crucial for hydrological modeling studies. Rain gauge collection and weather radar rainfall estimate are two of the most common techniques used for receiving rainfall data at a watershed. This study focuses on the development of three-dimensional (3D) distances based geostatistical models, such as Regression Kriging (RK) and Merging methods, to perform the adjustments of radar rainfall data to the targeted gauge measurements. These models are tested at the Chenyulan River watershed using the rainfall events of five typhoons landed Taiwan in recent years. Two-dimensional (2D) distance based models are also simulated to compare the adjusted rainfall values with those from 3D distance approaches. Results from Ordinary Kriging (OK) and gauge data are also included for comparisons. It is found in general the radar rainfall data can be corrected more accurately using the developed RK or Merging models than OK. Additionally, the adjusted rainfall values from 3D distance based models are similar to those using 2D distance based calculations at most tested stations. Depending on the typhoon events, using 3D distances in the semivariogram and Kriging interpolations is shown to be able to produce improved estimations of radar rainfall rates than 2D distance based calculations.","abstract_has_math":false,"creators":["Karakoyun, Erkan"],"institution":"University of Houston","degree_name":"Master of Science in Civil Engineering","degree_level":"Masters","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Wang, Keh-Han"],"committee_chairs":[],"committee_members":["Mo, Yi-Lung","Lee, Hyongki","Chu, Ted"],"year":2016,"date_issued":"2016-05","date_published":"2016-05","updated_at":"2026-07-24T02:32:27Z","subjects":["Geostatistical model","Kriging"],"languages":["eng"],"rights":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10657/3191","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Wang, Keh-Han"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Mo, Yi-Lung","Lee, Hyongki","Chu, Ted"]},{"key":"dc:creator","label":"Author","values":["Karakoyun, Erkan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-07-10T18:49:47Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-07-10T18:49:47Z"]},{"key":"dc:date.issued","label":"Date","values":["2016-05"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Civil Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Houston"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Geostatistical model","Kriging"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10657/3191"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Accurate and reliable rainfall input is crucial for hydrological modeling studies. Rain gauge collection and weather radar rainfall estimate are two of the most common techniques used for receiving rainfall data at a watershed. This study focuses on the development of three-dimensional (3D) distances based geostatistical models, such as Regression Kriging (RK) and Merging methods, to perform the adjustments of radar rainfall data to the targeted gauge measurements. These models are tested at the Chenyulan River watershed using the rainfall events of five typhoons landed Taiwan in recent years. Two-dimensional (2D) distance based models are also simulated to compare the adjusted rainfall values with those from 3D distance approaches. Results from Ordinary Kriging (OK) and gauge data are also included for comparisons. It is found in general the radar rainfall data can be corrected more accurately using the developed RK or Merging models than OK. Additionally, the adjusted rainfall values from 3D distance based models are similar to those using 2D distance based calculations at most tested stations. Depending on the typhoon events, using 3D distances in the semivariogram and Kriging interpolations is shown to be able to produce improved estimations of radar rainfall rates than 2D distance based calculations."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Three-Dimensional Distance Based Geostatistical Models to Adjust Radar Rainfall Data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Wang, Keh-Han"],"dc:contributor.committeemember":["Mo, Yi-Lung","Lee, Hyongki","Chu, Ted"],"dc:creator":["Karakoyun, Erkan"],"dc:date.accessioned":["2018-07-10T18:49:47Z"],"dc:date.available":["2018-07-10T18:49:47Z"],"dc:date.issued":["2016-05"],"dc:description.abstract":["Accurate and reliable rainfall input is crucial for hydrological modeling studies. Rain gauge collection and weather radar rainfall estimate are two of the most common techniques used for receiving rainfall data at a watershed. This study focuses on the development of three-dimensional (3D) distances based geostatistical models, such as Regression Kriging (RK) and Merging methods, to perform the adjustments of radar rainfall data to the targeted gauge measurements. These models are tested at the Chenyulan River watershed using the rainfall events of five typhoons landed Taiwan in recent years. Two-dimensional (2D) distance based models are also simulated to compare the adjusted rainfall values with those from 3D distance approaches. Results from Ordinary Kriging (OK) and gauge data are also included for comparisons. It is found in general the radar rainfall data can be corrected more accurately using the developed RK or Merging models than OK. Additionally, the adjusted rainfall values from 3D distance based models are similar to those using 2D distance based calculations at most tested stations. Depending on the typhoon events, using 3D distances in the semivariogram and Kriging interpolations is shown to be able to produce improved estimations of radar rainfall rates than 2D distance based calculations."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10657/3191"],"dc:language.iso":["eng"],"dc:rights":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."],"dc:subject":["Geostatistical model","Kriging"],"dc:title":["Three-Dimensional Distance Based Geostatistical Models to Adjust Radar Rainfall Data"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science in Civil Engineering"],"thesis:institution_name":["University of Houston"]},"updated_at":"2026-07-24T02:32:27Z"}