REASSESSMENT OF SCS-CN INITIAL ABSTRACTION RATIO BASED ON RAINFALL-RUNOFF EVENT ANALYSIS AND SLOPE-ADJUSTED CN IN A SEMIARID CLIMATE OF HALABJA GOVERNORATE
In the SCS-CN model, the initial abstraction ratio () is fixed and assumed to be equal to 0.2, but it was revealed that the estimation of runoff is very sensitive to changes in this ratio and is regionally specific. As there are limited investigations on this ratio, the current study was initiated with the main objective of improving the performance of this model by adjusting and making adjustments for the curve number (CN). To target the above objective, the database was collected from three watersheds situated to the northeast of Iraq within Halabja governorate. The study included analyzing rainfall and actual runoff data, as well as describing the watersheds with reference to land cover and land use, hydrologic soil groups, and morphometric characteristics. Linear least squares and iterative (optimization) methods were used for adjusting the initial abstraction ratio with and without CN adjustment for slope. A host of performance indicators, along with leave-one-out cross-validation, were used for testing the performance of these methods. The results indicated that the analysis of individual rainfall indicated that varied from event to event, and more than 92% of the values were below 0.2 in each watershed. The value tended to decrease insignificantly (P < 0.05) with an increase in rainfall depth. The correlation analysis also revealed that most land use type and watershed characteristics were positively correlated with. CN adjustment led to a reduction in mean absolute error in the range of 5–11% upon applying the traditional SCS-CN method to estimate runoff. It was also noticed that reassessment of by using least squares and optimization techniques offered a more accurate estimation before CN adjustment compared with reevaluation after CN adjustment. The least squares and optimization techniques provided close results, but the latter outperformed the least squares and traditional methods on a watershed scale. The mean absolute percentage error of rainfall estimation dropped from 80% under the traditional SCS-CN method to 51% due to the reassessment of by the optimization technique.
SCS-method, runoff estimation, reassessment of initial abstraction ratio, CN adjustment for slope, Halabja.