Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia
Thesis (Ph.D (Civil Engineering))
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| Format: | Thesis |
| Language: | English |
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Universiti Teknologi Malaysia
2024
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| Online Access: | https://openscience.utm.my/handle/123456789/1510 |
| _version_ | 1824446317403832320 |
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| author | Lloyd Ling |
| author_facet | Lloyd Ling |
| author_sort | Lloyd Ling |
| collection | OpenScience |
| description | Thesis (Ph.D (Civil Engineering)) |
| first_indexed | 2025-02-19T01:13:14Z |
| format | Thesis |
| id | oai:openscience.utm.my:123456789/1510 |
| institution | Universiti Teknologi Malaysia - OpenScience |
| language | English |
| last_indexed | 2025-02-19T01:13:14Z |
| publishDate | 2024 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| spelling | oai:openscience.utm.my:123456789/15102024-12-18T10:01:11Z Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia Lloyd Ling Runoff—Data processing Hydrologic models Thesis (Ph.D (Civil Engineering)) The Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide for hydrological problem simulations and engineering designs. However, hydrologists argue the accuracy of the predicted runoff results. The aims of this study are to preserve the basic SCS runoff model structure and develop region specific models under the guide from inferential statistics. This study includes the assessment of the 1954 SCS procedure, derivation of corrected equations, development of a calibrated SCS runoff model and identification of decadal initial abstraction ratio coefficient (?) values and runoff trend in Peninsula Malaysia. The calibration methodology discarded the use of conventional curve number (CN0.2) as input but to produce statistically significant CN0.2 value through the derivation of total abstraction (S) value from 227 rainfall-runoff events from 41 catchments recorded over 30 years. The key equation of initial abstraction, Ia = 0.20S is not a linear correlation as proposed by SCS. Non-parametric inferential statistical assessment concluded that Ia ? 0.2S while the simplified SCS runoff model was not even significant (p>0.05) with its original dataset and therefore, the 1954 SCS proposal of Ia = 0.2S committed type II error. The optimum ? value was 0.051 (alpha = 0.01) to calibrate the SCS runoff model. The collective best representation of the optimum Ia and S values are 8.3 mm and 163 mm, respectively, whereas the best CN0.2 is 71 (p < 0.01, 99% CI from 67 to 76). Decadal optimum ? and Ia values were found to decrease over time with significant decadal runoff uptrend (alpha = 0.01) across every CN0.2 classes due to changes in landuse. Saturation excess runoff concept was incorporated to formulate an urban rainfall-runoff model based on SCS framework. The closed form equation of the critical rainfall amount (Pcrit) was solved to narrow the research gap. The 3D runoff model was created to provide visual analytical information of runoff error of the SCS runoff model. This study offered insights to calibrate the SCS rainfall-runoff model and developed several new extended applications. SCS practitioners are encouraged to carry out regional specific calibration before applying the SCS rainfall-runoff model Universiti Teknologi Malaysia 2024-12-18T01:17:17Z 2024-12-18T01:17:17Z 2017 Thesis Dataset https://openscience.utm.my/handle/123456789/1510 en application/pdf application/pdf application/pdf application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Runoff—Data processing Hydrologic models Lloyd Ling Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title | Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title_full | Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title_fullStr | Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title_full_unstemmed | Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title_short | Deriving the intial abstraction ratio coefficient for runoff prediction in Peninsula Malaysia |
| title_sort | deriving the intial abstraction ratio coefficient for runoff prediction in peninsula malaysia |
| topic | Runoff—Data processing Hydrologic models |
| url | https://openscience.utm.my/handle/123456789/1510 |
| work_keys_str_mv | AT lloydling derivingtheintialabstractionratiocoefficientforrunoffpredictioninpeninsulamalaysia |