Analysis of the Natural Resources Conservation Service Curve Number Method Using Natural and Frequency-Matched Data Ordering Method

Código

I-EBHE0108

Autores

Abderraman Róger Amorim Brandão, Dimaghi Schwamback, André Simões Ballarin, Paulo Tarso Sanches de Oliveira

Tema

WG 1.05: Comparative understanding of runoff generation processes

Resumo

Hydrological studies often aim to determine the design surface runoff for various engineering disciplines, where the accuracy of the results directly depends on the methods employed. The accuracy of these methods results in economically efficient and effective structures for society. Among these methods, the Curve Number (CN) method of the Natural Resources Conservation Service (NRCS) stands out worldwide, especially in ungauged basins and developing countries. Originally derived from local experiments, the method has generalized to various regions, raising questions about its adequacy due to differences in hydrological processes. This study investigates the comparison between the approach of ranking precipitation and runoff values based on rearranged return periods to have equal return periods, and the use of natural data to determine the best approach. We used three methods of obtaining CN (least squares - LS, Natural Engineering Handbook - NEH, and asymptotic - ASY) and two initial abstraction values (?) (0.05 and 0.2), with a sample of 3398 watersheds. The CN values found indicate that the ranking, for both initial abstraction indices, showed values five units higher in the LS method. For the ASY method, the values were ten units higher for the initial abstraction of ?=0.05 and approximately ten for ?=0.2, while in the NEH method the values were similar for both abstraction indices. Analyzing the values of Kling Gupta Efficiency (KGE), where the methods had good results for the watersheds (KGE>0.5), the results showed that the ranking improves performance in the watersheds for all methods in LS?=0.2: 6.03%, LS?=0.05: 3.53%, ASY?=0.2: 12.42%, ASY?=0.05: 9.27%, NEH?=0.2: 0.78%, NEH?=0.05: 1.47% of the watersheds, compared to the use of natural data. The results indicate that adopting event ranking based on return time benefits the method's accuracy, which can bring positive practical implications for various disciplines where the method is employed, contributing to the management of water resources in different regions where the method is applied.