Loss Method: NRCS Curve Number Method

a. Loss Method: NRCS Curve Number Method
The U.S. Natural Resource Conservation Service (NRCS) (formerly the Soil Conservation Service (SCS)) Curve Number method used in this study estimates the effective rainfall as a function of the cumulative rainfall, the land use, the soil type and the antecedent moisture condition of the soil. The model is described in detail in the National Engineering Handbook (NEH) (NRCS 2004). It was created based on the analysis of a large number of small and gauged agricultural watersheds throughout the US. Apart from the input precipitation, the method uses a single parameter, the CN to characterize the watershed. The CN quantifies the infiltration capacity and theoretically ranges between 0 (100% of the total
Federal Emergency Management Agency (HEC, 2000). One of the major advantages of this software is the wide selection of different hydrologic models suitable for different environments and under different conditions. Furthermore, HEC-HMS includes options for the calibration of the chosen models against measured precipitation and runoff data. With HEC-HMS being a widely used, complete and flexible software solution for the modeling of the rainfall-runoff process, the applicability rather depends on the suitability of the hydrologic models for a given situation rather than on the software
One of the major limitations of the NRCS Curve Number method, is that during the modeling of a storm event of large duration, the infiltration rate eventually approaches zero (NRCS, 1986). Furthermore, the intensity and duration of the rainfall is neglected in this method so that a 25 mm rainfall in one day, results in the same cumulative loss as a 25 mm rainfall in one hour. Nevertheless it is a simple, predictable and stable method that is widely accepted for use in the U.S. and abroad (HEC, 2000). Furthermore, the computational procedure used in HEC-HMS introduces a time component to the model by computing amounts of excess precipitation for successive intervals in a storm. Since the CN is the only input parameter for this model, a correct estimation is crucial for the accuracy of the modeling