Effects of initial abstraction ratios in SCS-CN method on runoff prediction of green roofs in a semi-arid region

Abstract The widespread adoption of green roof technology in urban stormwater management practices requires the use of adequate modelling and evaluating tools. Soil Conservation Service-Curve Number (SCS-CN) method is the most common adopted and simple method for runoff prediction of green roofs. However, the standard initial abstraction ratio is the most ambiguous assumption and requires dedicated adjustments in runoff prediction. In this study, the initial abstraction ratios of green roofs in SCS-CN method were determined using rainfall-runoff event analysis from the simulated rainfall experiments for runoff plots of green roofs. Influences of the standard and modified initial abstraction ratios on runoff estimation of green roofs were investigated and evaluated. Results showed that the calculated Ia/S ratios varied from 0.18 to 0.89, with a median of 0.51. The SCS-CN method for initial abstraction ratios using 0.5 and 0.2 values were underestimated runoff volume, thus they were not appropriately used for runoff prediction of green roofs. However, evaluated results revealed that runoff prediction using Ia/S = 0.05 was significantly improved than that predicted using Ia/S = 0.2. The estimation of green roof runoff using Ia/S = 0.05 provided the best model efficiency MAE, RMSE, NSE and WI among the predictions using the modified initial abstraction ratios of 0.2, 0.5, 0.05 and 0.02. Particularly, the NSE and WI values of Ia/S = 0.05 were improved to 0.88 and 0.97 respectively. Accordingly, the median CN value was modified to 96 while using Ia/S = 0.05. A significantly negative relationship was found between antecedent substrate moisture and Ia/S ratios of green roofs. These results suggested that an optimal initial abstraction ratio of 0.05 with modified CN values used in the SCS-CN method can highly improve the accuracy of runoff prediction for green roofs.