{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-1946"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-1946","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"A comparison of Scs runoff prediction methods for two large watersheds in Sri Lanka","abstract":"The paper presents the methodology and results of a hydrological study of two basins in Sri Lanka. The objective of the study was to evaluate a flood prediction model based on the Soil Conservation Service (SCS) runoff curve method. The study results showed that the application of standard SCS tables and standard abstractions does not adequately predict computed direct runoff. The standard SCS curve number method produced good predictions at optimum initial abstractions (I{dollar}\\sb{\\rm a}{dollar}) for all rainfall gauging stations when compared to Hjelmfelt's (1980), and Hawkins (1993) techniques; This paper also focuses on calibrating curve numbers from rainfall-runoff data. The two methods used in this regard were those of Hjelmfelt (1980, 1991), and Hawkins (1993); The Aningkanda rainfall gauging station in the Nilwala Ganga Basin was a better predictor of runoff than the Mawarella and St. Augustine gauging stations; The Gin Ganga Watershed yielded approximately 73% runoff compared to the 25% yield in the adjoining Nilwala Ganga Watershed. The primary reason for the large difference in water yield could be attributed to the fact that the rainfall gauging stations are relatively closer to the stream flow gauging station in the Gin Ganga basin than the Nilwala Ganga; The SCS unit hydrograph method used in the HEC-1 flood hydrograph package assumed rainfall distributions generated for North American Continental weather. However, using different rainfall distributions did not significantly change the predicted runoff results in the two basins. (Abstract shortened by UMI.).","abstract_html":"The paper presents the methodology and results of a hydrological study of two basins in Sri Lanka. The objective of the study was to evaluate a flood prediction model based on the Soil Conservation Service (SCS) runoff curve method. The study results showed that the application of standard SCS tables and standard abstractions does not adequately predict computed direct runoff. The standard SCS curve number method produced good predictions at optimum initial abstractions (I{dollar}\\sb{\\rm a}{dollar}) for all rainfall gauging stations when compared to Hjelmfelt&#x27;s (1980), and Hawkins (1993) techniques; This paper also focuses on calibrating curve numbers from rainfall-runoff data. The two methods used in this regard were those of Hjelmfelt (1980, 1991), and Hawkins (1993); The Aningkanda rainfall gauging station in the Nilwala Ganga Basin was a better predictor of runoff than the Mawarella and St. Augustine gauging stations; The Gin Ganga Watershed yielded approximately 73% runoff compared to the 25% yield in the adjoining Nilwala Ganga Watershed. The primary reason for the large difference in water yield could be attributed to the fact that the rainfall gauging stations are relatively closer to the stream flow gauging station in the Gin Ganga basin than the Nilwala Ganga; The SCS unit hydrograph method used in the HEC-1 flood hydrograph package assumed rainfall distributions generated for North American Continental weather. However, using different rainfall distributions did not significantly change the predicted runoff results in the two basins. (Abstract shortened by UMI.).","abstract_has_math":false,"creators":["Weragoda, Arjuna Dahrshaka"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Science (MS)","degree_level":"Thesis","degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["David James"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1998,"date_issued":"1998-01-01T08:00:00Z","date_published":"1998-01-01T08:00:00Z","updated_at":"2026-07-24T05:24:53Z","subjects":[],"languages":[],"rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://oasis.library.unlv.edu/rtds/947"],"render_values":[{"text":"https://oasis.library.unlv.edu/rtds/947","href":"https://oasis.library.unlv.edu/rtds/947","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25669/fmru-rev8","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["David James"]},{"key":"dc:creator","label":"Author","values":["Weragoda, Arjuna Dahrshaka"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:publisher","label":"Institution","values":["University of Nevada, Las Vegas"]},{"key":"dc:type","label":"Dc Type","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil and Environmental Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10.25669/fmru-rev8","https://oasis.library.unlv.edu/rtds/947","https://oasis.library.unlv.edu/context/rtds/article/1946/viewcontent/uc.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The paper presents the methodology and results of a hydrological study of two basins in Sri Lanka. The objective of the study was to evaluate a flood prediction model based on the Soil Conservation Service (SCS) runoff curve method. The study results showed that the application of standard SCS tables and standard abstractions does not adequately predict computed direct runoff. The standard SCS curve number method produced good predictions at optimum initial abstractions (I{dollar}\\sb{\\rm a}{dollar}) for all rainfall gauging stations when compared to Hjelmfelt's (1980), and Hawkins (1993) techniques; This paper also focuses on calibrating curve numbers from rainfall-runoff data. The two methods used in this regard were those of Hjelmfelt (1980, 1991), and Hawkins (1993); The Aningkanda rainfall gauging station in the Nilwala Ganga Basin was a better predictor of runoff than the Mawarella and St. Augustine gauging stations; The Gin Ganga Watershed yielded approximately 73% runoff compared to the 25% yield in the adjoining Nilwala Ganga Watershed. The primary reason for the large difference in water yield could be attributed to the fact that the rainfall gauging stations are relatively closer to the stream flow gauging station in the Gin Ganga basin than the Nilwala Ganga; The SCS unit hydrograph method used in the HEC-1 flood hydrograph package assumed rainfall distributions generated for North American Continental weather. However, using different rainfall distributions did not significantly change the predicted runoff results in the two basins. (Abstract shortened by UMI.)."]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["A comparison of Scs runoff prediction methods for two large watersheds in Sri Lanka"]}]}],"canonical_facts":{"dc:contributor":["David James"],"dc:creator":["Weragoda, Arjuna Dahrshaka"],"dc:description.abstract":["The paper presents the methodology and results of a hydrological study of two basins in Sri Lanka. The objective of the study was to evaluate a flood prediction model based on the Soil Conservation Service (SCS) runoff curve method. The study results showed that the application of standard SCS tables and standard abstractions does not adequately predict computed direct runoff. The standard SCS curve number method produced good predictions at optimum initial abstractions (I{dollar}\\sb{\\rm a}{dollar}) for all rainfall gauging stations when compared to Hjelmfelt's (1980), and Hawkins (1993) techniques; This paper also focuses on calibrating curve numbers from rainfall-runoff data. The two methods used in this regard were those of Hjelmfelt (1980, 1991), and Hawkins (1993); The Aningkanda rainfall gauging station in the Nilwala Ganga Basin was a better predictor of runoff than the Mawarella and St. Augustine gauging stations; The Gin Ganga Watershed yielded approximately 73% runoff compared to the 25% yield in the adjoining Nilwala Ganga Watershed. The primary reason for the large difference in water yield could be attributed to the fact that the rainfall gauging stations are relatively closer to the stream flow gauging station in the Gin Ganga basin than the Nilwala Ganga; The SCS unit hydrograph method used in the HEC-1 flood hydrograph package assumed rainfall distributions generated for North American Continental weather. However, using different rainfall distributions did not significantly change the predicted runoff results in the two basins. (Abstract shortened by UMI.)."],"dc:format":["pdf"],"dc:identifier":["10.25669/fmru-rev8","https://oasis.library.unlv.edu/rtds/947","https://oasis.library.unlv.edu/context/rtds/article/1946/viewcontent/uc.pdf"],"dc:publisher":["University of Nevada, Las Vegas"],"dc:rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["A comparison of Scs runoff prediction methods for two large watersheds in Sri Lanka"],"dc:type":["Text"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science (MS)"]},"updated_at":"2026-07-24T05:24:53Z"}