Wen Jia TanJen Feng KhorLloyd LingYuk Feng HuangY.F. HuangK.W. TanL. LingK.H. Leong2024-11-132024-11-132018https://doi.org/10.1051/e3sconf/20186507005https://dspace-cris.utar.edu.my/handle/123456789/6979In the past, the <i>CN</i> was determined through SCS handbook. In order to determine runoff prediction using SCS-CN model, selection of <i>CN</i> is important. However, the conventional<i>CN</i>methodology with inappropriate <i>CN</i> selection often produces inconsistent runoff estimation. Thus, the new direct curve number derivation technique based on rainfall-runoff datasets with supervised numerical optimization technique under the guide of inferential statistics was developed to improve the accuracy of surface runoff prediction. Furthermore, the two decimal point <i>CN</i> system was proposed in this study. The optimum <i>CN</i> of Melana site is 90.45 at alpha 0.01 with BCa 99 % confidence interval range from 90.45 to 95.12. The regional specific calibrated SCS-CN model with two decimal point <i>CN</i> derivation technique is out-performed the runoff prediction of conventional SCS-CN model and the asymptotic curve number fitting method.journal-article