摘要：In the past, the CN was determined through SCS handbook. In order to determine runoff prediction using SCS-CN model, selection of CN is important. However, the conventional CN methodology with inappropriate CN 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 CN system was proposed in this study. The optimum CN 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 CN derivation technique is out-performed the runoff prediction of conventional SCS-CN model and the asymptotic curve number fitting method.
其他摘要：In the past, the CN was determined through SCS handbook. In order to determine runoff prediction using SCS-CN model, selection of CN is important. However, the conventional CN methodology with inappropriate CN 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 CN system was proposed in this study. The optimum CN 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 CN derivation technique is out-performed the runoff prediction of conventional SCS-CN model and the asymptotic curve number fitting method.
