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| Calibration of SCS-CN initial abstraction ratio of a small watershed in Nanjing bamboo forest |
| Yue Jianmin1, Zhang Jinchi1, Zhuang Jiayao1, Xia Yemao2, Liu Xin1 |
| 1.Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province,Nanjing Forestry University, 210037, Nanjing, China; 2.College of Information Technology,Nanjing Forestry University, 210037, Nanjing, China |
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Abstract China has the relatively serious problem of soil and water loss. Runoff is the primary force that results in soil erosion. Accurate calculation of runoff is the key step to predict the soil and water loss, and it contributes to evaluating the efficiency of soil and water conservation practices. SCS-CN model is an empirical model developed by the United States Department of Agriculture, used to calculate the surface runoff of rain. It has the advantages of being simple and efficient. At present, it has been widely applied in different areas and site conditions for runoff calculation. Initial abstraction ratio (λ) is one of the basic input parameters in the SCS-CN method used to forecast surface runoff, and affects the precision of the model. This study was aimed to determine the value of initial abstraction ratio based on the Nanjing Moso bamboo forest watershed and provide reference of the SCS-CN model in this region. According to the measured data about rainfall runoff in the Moso bamboo forest watershed, the value of CN was determined by using the asymptote method. And then the shifty interval of λ was confirmed from the certain value of CN. We chose the data of 10 rainfall events and used the correlation coefficient | R |, model efficiency coefficient E, and the qualification rate to evaluate the parameter λ. The result showed that λ= 0.25,0.3, 0.35 are relatively better than other values when conducting calibration test of the parameters λ,with their correlation coefficients 0.58, 0.54 and 0.49, the model efficiency coefficient -9.42, -5.86 and - 3.14, and the qualification rates 77.80%, 88.90% and 77.80%, respectively. A comprehensive analysis showed that λ= 0.3 was relatively better in the small watershed. Next, we selected data of another 10 rainfall events to simulate the quantities of runoff, and the result showed that the parameter λ=0.3 was closer to the measured surface runoff than λ=0.2 from the SCS model. The model efficiency coefficient E was improved from -16.77 to -1.03. It greatly improves the accuracy of the model. Therefore, calibrating λ=0.3 is the optimal initial abstraction ratio of small watershed in the bamboo forest.
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Received: 26 November 2014
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