Urban flood depth estimate with a new calibrated curve number runoff prediction model
The 1954 Soil Conservation Services (SCS) runoff predictive model was adopted in engineering designs throughout the world. However, its runoff prediction reliability was under scrutiny by recent studies. The conventional curve number (CN) selection methodology is often very subjective and lacks scie...
Saved in:
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2020
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/90168/1/ZulkifliYusop2020_UrbanFloodDepthEstimateWithaNewCalibrated.pdf http://eprints.utm.my/id/eprint/90168/ http://dx.doi.org/10.1109/ACCESS.2020.2964898 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Teknologi Malaysia |
Language: | English |
id |
my.utm.90168 |
---|---|
record_format |
eprints |
spelling |
my.utm.901682021-03-31T06:21:54Z http://eprints.utm.my/id/eprint/90168/ Urban flood depth estimate with a new calibrated curve number runoff prediction model Ling, Lloyd Yusop, Zulkifli Chow, Ming Fai TA Engineering (General). Civil engineering (General) The 1954 Soil Conservation Services (SCS) runoff predictive model was adopted in engineering designs throughout the world. However, its runoff prediction reliability was under scrutiny by recent studies. The conventional curve number (CN) selection methodology is often very subjective and lacks scientific justification while nested soil group catchments complicate the issue with the risk of inappropriate curve number selection which produces unreliable runoff results. The SCS CN model was statistically invalid (α = 0.01 level) and over predicted runoff volume as much as 21% at the Sungai Kerayong catchment in Kuala Lumpur, Malaysia. Blind adoption of the model will commit a type II error. As such, this study presented a new method to calibrate and formulate an urban runoff model with inferential statistics and residual modelling technique to correct the runoff prediction results from the SCS CN model with a corrected equation. The new model out-performed the Asymptotic runoff model and SCS CN runoff model with low predictive model bias, reduced sum of squared errors by 32% and achieved high Nash-Sutcliffe efficiency value of 0.96. The derived urban curve number is 98.0 with 99% confidence interval ranging from 97.8 to 99.5 for Sungai Kerayong catchment. Twenty-five storms generated almost 29 million m3 runoff (11,548 Olympic size swimming pools) from the Sungai Kerayong catchment in this study. 75%-94% of the rain water became runoff from those storms and lost through the catchment, without efficient drainage infrastructure in place, the averaged flood depth reached 6.5 cm while the actual flood depth will be deeper at the flood ponding area near to the catchment outlet. Institute of Electrical and Electronics Engineers Inc. 2020 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/90168/1/ZulkifliYusop2020_UrbanFloodDepthEstimateWithaNewCalibrated.pdf Ling, Lloyd and Yusop, Zulkifli and Chow, Ming Fai (2020) Urban flood depth estimate with a new calibrated curve number runoff prediction model. IEEE Access, 8 . pp. 10915-10923. ISSN 2169-3536 http://dx.doi.org/10.1109/ACCESS.2020.2964898 |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
language |
English |
topic |
TA Engineering (General). Civil engineering (General) |
spellingShingle |
TA Engineering (General). Civil engineering (General) Ling, Lloyd Yusop, Zulkifli Chow, Ming Fai Urban flood depth estimate with a new calibrated curve number runoff prediction model |
description |
The 1954 Soil Conservation Services (SCS) runoff predictive model was adopted in engineering designs throughout the world. However, its runoff prediction reliability was under scrutiny by recent studies. The conventional curve number (CN) selection methodology is often very subjective and lacks scientific justification while nested soil group catchments complicate the issue with the risk of inappropriate curve number selection which produces unreliable runoff results. The SCS CN model was statistically invalid (α = 0.01 level) and over predicted runoff volume as much as 21% at the Sungai Kerayong catchment in Kuala Lumpur, Malaysia. Blind adoption of the model will commit a type II error. As such, this study presented a new method to calibrate and formulate an urban runoff model with inferential statistics and residual modelling technique to correct the runoff prediction results from the SCS CN model with a corrected equation. The new model out-performed the Asymptotic runoff model and SCS CN runoff model with low predictive model bias, reduced sum of squared errors by 32% and achieved high Nash-Sutcliffe efficiency value of 0.96. The derived urban curve number is 98.0 with 99% confidence interval ranging from 97.8 to 99.5 for Sungai Kerayong catchment. Twenty-five storms generated almost 29 million m3 runoff (11,548 Olympic size swimming pools) from the Sungai Kerayong catchment in this study. 75%-94% of the rain water became runoff from those storms and lost through the catchment, without efficient drainage infrastructure in place, the averaged flood depth reached 6.5 cm while the actual flood depth will be deeper at the flood ponding area near to the catchment outlet. |
format |
Article |
author |
Ling, Lloyd Yusop, Zulkifli Chow, Ming Fai |
author_facet |
Ling, Lloyd Yusop, Zulkifli Chow, Ming Fai |
author_sort |
Ling, Lloyd |
title |
Urban flood depth estimate with a new calibrated curve number runoff prediction model |
title_short |
Urban flood depth estimate with a new calibrated curve number runoff prediction model |
title_full |
Urban flood depth estimate with a new calibrated curve number runoff prediction model |
title_fullStr |
Urban flood depth estimate with a new calibrated curve number runoff prediction model |
title_full_unstemmed |
Urban flood depth estimate with a new calibrated curve number runoff prediction model |
title_sort |
urban flood depth estimate with a new calibrated curve number runoff prediction model |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2020 |
url |
http://eprints.utm.my/id/eprint/90168/1/ZulkifliYusop2020_UrbanFloodDepthEstimateWithaNewCalibrated.pdf http://eprints.utm.my/id/eprint/90168/ http://dx.doi.org/10.1109/ACCESS.2020.2964898 |
_version_ |
1696976271278342144 |