Influence of Initial Abstraction Ratios in NRCS-CN Model on Runoff Estimation of Permeable Brick Pavement Affected by Clogging

The widespread application of permeable pavements in urban stormwater management practices requires a quick and easy model to evaluate their hydrological function during different clogging stages. The Natural Resources Conservation Service-Curve Number (NRCS-CN) method has extensively used for predicting direct runoff from rainfall. However, the standard initial abstraction ratio ( λ ) value of 0.2 in the model is the most ambiguous assumption and requires considerable refinement for the accurate runoff prediction of permeable pavements affected by clogging. This study calibrated the λ values of permeable brick pavement (PBP) with different clogging degrees to obtain an appropriate model to predict the runoff of PBP affected by clogging. The results indicated that the NRCS-CN model with standard λ value of 0.2 indeed overestimated the runoff over PBP surface, particularly at the initial clogging stage. The λ values showed a significant positive correlation with the clogging degree of PBP, while no significant correlation with the rainfall intensity. A function defining the parameter of λ , related to the saturated infiltration rate of PBP was developed. The accuracy of runoff prediction over the clogged PBP surface was greatly improved using the modified NRCS-CN model with the refined λ values. The NSE value rose to 0.96, and the MAE and RMSE values reduced to 2.66 and 3.85, respectively. Furthermore, the curve number ( CN ) values for the clogged PBP based on the calibrated λ values were much more consistent with the actual clogging rule of PBP, exhibiting an increased span and ranging from 35 to 98. Graphical Abstract