A comparison of Scs runoff prediction methods for two large watersheds in Sri Lanka
type: CreativeWork
description: 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: 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.).
author: Weragoda, Arjuna Dahrshaka
date published: 1998-01-01T08:00:00Z
date modified: 2026-07-24T05:24:53Z
provider: University of Nevada - Las Vegas
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Nevada, Las Vegas

PropertyValue
property ID: DOI
value: 10.25669/fmru-rev8