| 非点源污染模型AnnAGNPS在三峡库区林农复合小流域模拟效果评定 |
| 摘要点击 2476 全文点击 1623 投稿时间：2008-11-07 修订日期：2009-02-17 |
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| 中文关键词 AnnAGNPS模型 径流 泥沙输出 营养物输出 三峡库区 模拟效果 |
| 英文关键词 AnnAGNPS model runoff sediment loading nutrient loading Three Gorges Reservoir area performance |
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| 中文摘要 |
| 应用连续农业非点源污染AnnAGNPS模型(Annualized AGricultural NonPoint Source Model)模拟三峡库区林农复合小流域的径流、泥沙和营养物输出，以2003年和2004年的小流域观测数据对模型分别进行校准和验证，并以统计参量决定系数(R2)、Nash-Sutcliffe效率系数(E)和相对误差(VE)对模拟结果进行评定.结果表明，径流量模型模拟结果误差在可接受范围之内，模型校准期模拟值VE值为5.0% (R2=0.93, p<0.05)，验证期内模型VE值为6.7% (R2=0.90, p<0.05)；与径流模拟比较，泥沙模拟结果精度较低，校准期内模型VE值为15.1% (R2=0.63, p<0.05)，验证期内模型VE值为26.7% (R2=0.59, p<0.05)；次降水较小，产生径流和泥沙较少时，模型模拟值则偏高，反之则偏低.氮输出模拟决定系数R2值0.68(p<0.05)，略高于磷输出模拟决定系数 (R2=0.65, p<0.05).模型对径流输出的模拟精度高于对泥沙和营养物的输出模拟.在三峡库区农林复合小流域应用AnnAGNPS模型模拟农业非点源污染输出满足流域管理要求. |
| 英文摘要 |
| Watershed models provide a cost-effective and efficient means of estimating the pollutant loadings entering surface waters, especially when combined with traditional water quality sampling and analyses. But there have often been questions about the accuracy or certainty of models and their predictions. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized AGricultural NonPoint Source)Pollution Model, in simulating runoff, sediment loading and nutrient loadings under Three Gorges Reservoir area. Most of model input parameters were sourced from Zigui Forest Ecology Station in Three Gorges Reservoir area, State Forestry Administration. Data year 2003 was used for calibration while data year 2004 was used for validation of the model. The whole evaluation consisted of determining the coefficient of determination (R2), Nash-Sutcliffe coefficient of efficiency (E), and the percentage volume error (VE). Results showed that the model predicted the daily runoff volume within the range of acceptable accuracy. The runoff on a daily basis was underpredicted by 5.0% with R2 of 0.93(p<0.05) during calibration and underpredicted by 6.7% with R2 of 0.90 (p<0.05) during validation. But sediment loading was able to produce a moderate result. The model underpredicted the event-based sediment loading by 15.1% with R2 of 0.63(p<0.05) during calibration and 26.7% with R2 of 0.59 (p<0.05) during validation. For the events of small magnitude, the model generally overpredicted sediment loading, while the opposite was true for larger events. Nitrogen loading prediction was slightly better with R2=0.68 (p<0.05), and phosphorus loading performance was slightly poor with R2=0.65(p<0.05). In general, the model performs well in simulating runoff compare to sediment loading and nutrient loadings, and as a watershed management tools it can be used for Three Gorges Reservoir area conditions that with mixed types of land uses and steep slopes. |
