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Urban Flood Depth Estimate with a New Calibrated Curve Number Runoff Prediction Model

Floods; Forecasting; Infiltration; Rain; Sewage; Soil conservation; Statistical methods; Storms; Bootstrap; Curve numbers; Drainage infrastructure; Inferential statistics; Rainfall-runoff modeling; Runoff prediction model; Soil conservation services; Sum of squared errors; Runoff

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Main Authors: Ling L., Yusop Z., Chow M.F.
Other Authors: 56203785300
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-257782023-05-29T16:14:10Z Urban Flood Depth Estimate with a New Calibrated Curve Number Runoff Prediction Model Ling L. Yusop Z. Chow M.F. 56203785300 6507841909 57214146115 Floods; Forecasting; Infiltration; Rain; Sewage; Soil conservation; Statistical methods; Storms; Bootstrap; Curve numbers; Drainage infrastructure; Inferential statistics; Rainfall-runoff modeling; Runoff prediction model; Soil conservation services; Sum of squared errors; Runoff 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 (? = 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. � 2013 IEEE. Final 2023-05-29T08:14:09Z 2023-05-29T08:14:09Z 2020 Article 10.1109/ACCESS.2020.2964898 2-s2.0-85078699877 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078699877&doi=10.1109%2fACCESS.2020.2964898&partnerID=40&md5=ea4cb64f10842d6655fe26a809b5c59f https://irepository.uniten.edu.my/handle/123456789/25778 8 8952667 10915 10923 All Open Access, Gold Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Floods; Forecasting; Infiltration; Rain; Sewage; Soil conservation; Statistical methods; Storms; Bootstrap; Curve numbers; Drainage infrastructure; Inferential statistics; Rainfall-runoff modeling; Runoff prediction model; Soil conservation services; Sum of squared errors; Runoff
author2 56203785300
author_facet 56203785300
Ling L.
Yusop Z.
Chow M.F.
format Article
author Ling L.
Yusop Z.
Chow M.F.
spellingShingle Ling L.
Yusop Z.
Chow M.F.
Urban Flood Depth Estimate with a New Calibrated Curve Number Runoff Prediction Model
author_sort Ling L.
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 2023
_version_ 1806426690551808000
score 13.222552

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