Abstract
ABSTRACT The Curve Number (CN) method is extensively used for predict surface runoff from storm events. However, remain some uncertainties in the method, such as in the use of an initial abstraction (λ) standard value of 0.2 and on the choice of the most suitable CN values. Here, we compute λ and CN values using rainfall and runoff data to a rural basin located in Midwestern Brazil. We used 30 observed rainfall-runoff events with rainfall depth greater than 25 mm to derive associated CN values using five statistical methods. We noted λ values ranging from 0.005 to 0.455, with a median of 0.045, suggesting the use of λ = 0.05 instead of 0.2. We found a S0.2 to S0.05 conversion factor of 2.865. We also found negative values of Nash-Sutcliffe Efficiency (to the estimated and observed runoff). Therefore, our findings indicated that the CN method was not suitable to estimate runoff in the studied basin. This poor performance suggests that the runoff mechanisms in the studied area are dominated by subsurface stormflow.
Highlights
Hydrological models are simplified representations of real environmental systems
Initial abstraction ratio based on rainfall-runoff event analysis
We noted that 96.7% of the λ values were smaller than 0.2
Summary
Hydrological models are simplified representations of real environmental systems. Such models have been used as simulation and prediction tools that allow the most effective decision considering the environmental, social, and economic interactions of a real system (SOROOSHIAN et al, 2008). Several factors are integrated in the CN method, such as land cover and land use, surface condition, soil class, and antecedent. Runoff condition, which are combined in a single CN parameter (OLIVEIRA et al, 2016) This model covers three different usages; (1) give the return period direct runoff from the same return period rainfall depth; (2) explain rainfall-runoff for individual events; and (3) infer infiltration processes and soil moisture-CN relations (HAWKINS; WARD; WOODWARD, 2009)
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