Sensitivity and fuzzy uncertainty analyses in the determination of SCS-CN parameters from rainfall-runoff data

Spatial and seasonal variations of curve number (CN) and initial abstraction ratio () in a watershed can result in inaccurate runoff volume estimations when using the US Natural Resources Conservation Service (SCS-CN) method with constant values for these parameters. In this paper, parameters of CN and are considered as calibration parameters and the sensitivity of estimated runoff to these parameters using the SCS-CN method is scrutinized. To incorporate the uncertainty associated with CN and , fuzzy linear regression (FLR) is applied to derive the relationships of CN and with rainfall depth (P) by employing a large dataset of storm events from four watersheds in Iran. Results indicate that the proposed approach provides more accuracy in estimation of runoff volume compared to the SCS method with constant values of CN and , and gives a straightforward technique for evaluating the hydrological effects of CN, , and P on runoff volume.