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A method for calculating curve number of each runoff event on a sloping cropland in the Typical Black Soil Region |
LIU Gang1, XING Wanjun1, JIAO Jian2 |
1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, 100875, Beijing, China; 2. China Institute of Hydropower and Water Research, 100048, Beijing, China |
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Abstract [Background] Accurate prediction of surface runoff is crucial for the simulation of soil erosion and non-point source pollution. The soil conservation service curve number (SCS-CN) model has a simple structure and fewer required parameters, and is thus widely used to predict surface runoff. In various storm events, even for the unchanged land use and management, the parameter-curve number (CN) varies over a wide range, and the lack of understanding of rainfall processes and their influence on runoff may cause the simulated deviations. Moreover, the application of SCS-CN model for runoff prediction of the Typical Black Soil Region in China is limited. [Methods] Therefore, our study intended to optimize the SCS-CN model simulation for the Typical Black Soil Region by proposing a SCS-CN calculation method for each runoff event (CNt) based on observation data for 138 rainfall and runoff events from 7 plots in the Hebei watershed. And the rainfall intensity degree over time during the rainfall process was applied to calculated CNt. Nash-Sutcliffe efficiency (Ef), correlation coefficient (R), and mean relative error (Re) were used in the examination of simulation results that were calculated by CNt. [Results] The ratio for the maximum to minimum CNt value for different plots varied from 1.38-2.24, with an average of 1.81. This study elucidated a significant positive correlation between the ratio of CNt and the average SCS-CN (CN), as well as the ratio of the maximum X-minute rainfall amount (PX) to the total rainfall amount for each rainfall event (P). The ratio of curve number for each rainfall event to the annual mean curve number(CNt/CN)significantly increased with the ratio of maximum X-minute rainfall to total rainfall(PX/P)for the events. When 10≤X≤40, the correlation coefficient between(CNt/CN)and (PX/P)was higher, and(P10/P)was the most significant factor which represented the character of rainfall process that influenced the variation of CNt. The equation for calculating CNt was established based on the logarithmic function between(CNt/CN)and(P10/P). Moreover, the present study provided the parameters for cropland and bare land. For cropland with longitudinal ridge tillage and bare land, rills were easily formed on exposed surfaces during rainfall events, which facilitated the formation of a more stable convection path. For the calculated runoff depth by SCS-CN model with the parameter of CNt, Ef was 0.47, R was 0.77, and Re was -18.9%. The Ef for the SCS-CN model with the parameter of CN was only -1.63. [Conclusions] Adoption of a SCS-CN calculation method for each runoff event(CNt) may improve the prediction performance for SCS-CN model in the Typical Black Soil Region in China.
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Received: 18 November 2019
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