Remote sensing and GIS based assessment of water scarcity: a case study from Hambantota district, Sri Lanka.

dc.contributor.authorSenanayake, IP
dc.contributor.authorWelivitiya, WDDP
dc.contributor.authorNadeeka, PM
dc.contributor.authorPuswewala, UGA
dc.contributor.authorDissanayake, DMDOK
dc.date.accessioned2014-07-24T15:33:20Z
dc.date.available2014-07-24T15:33:20Z
dc.date.issued2014-07-24
dc.description.abstractSea level anomalies in the South China Sea are greatly influenced by interannual fluctuations. Studies have verified that mean sea level anomalies are negative during El Niño episodes and are positive during La Niña episodes. For this research, records of mean sea level anomalies from multiple satellite altimetry missions were obtained from the Radar Altimetry Database (RADS) web interface. The mean sea level anomalies were computed from 1991 to 2011, both for the entire Philippines and Bolinao, Pangasinan. To further illustrate the variability of sea level anomalies for the strong El Niño and La Niña years, prediction surfaces were generated from the satellite altimetry data using the Local Polynomial Interpolation method in ArcGIS. The distribution of sea level anomalies for the entire Philippines and Bolinao, Pangasinan for the strong El Niño (1991 and 1997) and La Niña (2001 and 2010) episodes were generated. Based on satellite altimetry, the approximate values of mean sea level rise for the Philippines and Bolinao, Pangasinan from 1991 to 2011 were 6.95 millimeters (0.00695 meters) and 7.28 millimeters (0.00728 meters), respectively. The estimated mean sea level anomaly for the entire Philippines from 1991 to 2011 is equivalent to 45.59 millimeters (0.04559 meters) and 38.51 millimeters (0.03851 meters) for Bolinao, Pangasinan. Mean sea level anomalies for the highly vulnerable provinces to climate and weather related risks were also calculated and the correlation between ENSO and mean sea level anomalies was further verified.en_US
dc.identifier.conferenceAsian Conference on Remote Sensing 2013en_US
dc.identifier.departmentDepartment of Earth Resources & Engineeringen_US
dc.identifier.departmentDepartment of Civil Engineeringen_US
dc.identifier.emailugap@civil.mrt.ac.lken_US
dc.identifier.emaildmdok@earth.mrt.ac.lken_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnospp. 705-847
dc.identifier.placeBali, Indonesiaen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/10312
dc.identifier.year2013en_US
dc.language.isoenen_US
dc.source.urihttp://www.academia.edu/7071020/Remote_Sensing_and_GIS_Based_Assessment_of_Water_Scarcity_-_A_Case_Study_from_Hambantota_District_Sri_Lankaen_US
dc.subjectsatellite altimetryen_US
dc.subjectmean sea level anomalyen_US
dc.subjectEl Niño and Southern Oscillatioen_US
dc.titleRemote sensing and GIS based assessment of water scarcity: a case study from Hambantota district, Sri Lanka.en_US
dc.typeConference-Abstracten_US

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