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区域尺度下硝酸盐淋溶模型的对比研究。

Comparative study of nitrate leaching models on a regional scale.

机构信息

Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands.

Alterra, Wageningen University and Research Centre, P.O. Box 47, 6700 AA Wageningen, The Netherlands.

出版信息

Sci Total Environ. 2014 Nov 15;499:481-96. doi: 10.1016/j.scitotenv.2014.07.030. Epub 2014 Aug 2.

Abstract

In Europe and North America the application of high levels of manure and fertilisers on agricultural land has led to high levels of nitrate concentrations in groundwater, in particular on sandy soils. For the evaluation of the development of the quality of groundwater a sound quantitative basis is needed. In this paper a comparison has been made between observations of nitrate concentrations in the upper groundwater and predictions of nitrate leaching models. Observations of nitrate concentrations in the upper groundwater at three different locations in regions with mainly sandy soils in the eastern and northern part of the Netherlands were used to test the performance of the simulation models to predict nitrate leaching to the upper groundwater. Four different types of simulation models of different levels of complexity and input data requirement were tested. These models are ANIMO (dynamic complex process oriented model), MM-WSV (meta-model), WOG (simple process oriented model) and NURP (semi-empiric model). The performance of the different simulation models was evaluated using statistical criteria. The dynamic complex process oriented ANIMO model showed the best model performance. The MM-WSV meta-model was the second best model, whilst the simple process oriented WOG model produced the worst model performance. The best model performance showed the dynamic complex process oriented ANIMO model in predicting the nitrate concentrations in the upper groundwater of the Klooster catchment. The good performance of the ANIMO model for this catchment can be explained by the additional information about the use of manure and fertilisers at farm level in this study area. The ANIMO model may be a good tool to predict nitrate concentrations in the upper groundwater on a regional scale. However, the use of a detailed process oriented simulation model requires a comprehensive set of input data. If such a comprehensive data-set is not available the MM-WSV model (meta-model) proves to be a good alternative. The WOG and NURP models are suitable for long term (>8 years) predictions of average nitrate concentrations in the upper groundwater on a regional scale.

摘要

在欧洲和北美洲,农业土地大量施用粪肥和化肥导致地下水硝酸盐浓度升高,特别是在沙质土壤上。为了评估地下水质量的发展,需要有一个可靠的定量基础。本文比较了上覆地下水中硝酸盐浓度的观测值和硝酸盐淋溶模型的预测值。在荷兰东部和北部主要为沙质土壤的地区的三个不同地点,观测了上覆地下水中硝酸盐浓度,以检验模拟模型预测硝酸盐淋溶至上覆地下水的性能。测试了四种不同类型的模拟模型,这些模型的复杂性和输入数据要求不同。这些模型分别是 ANIMO(动态复杂过程导向模型)、MM-WSV(元模型)、WOG(简单过程导向模型)和 NURP(半经验模型)。使用统计标准评估了不同模拟模型的性能。动态复杂过程导向的 ANIMO 模型表现出最好的模型性能。MM-WSV 元模型是第二好的模型,而简单过程导向的 WOG 模型则产生了最差的模型性能。在预测 Klooster 流域上覆地下水中硝酸盐浓度方面,动态复杂过程导向的 ANIMO 模型表现出最佳的模型性能。在这个流域中,ANIMO 模型表现良好,原因是在本研究区域中,它可以额外提供有关农场粪肥和化肥使用情况的信息。ANIMO 模型可能是一种很好的工具,可以在区域尺度上预测上覆地下水中的硝酸盐浓度。但是,使用详细的过程导向模拟模型需要一套全面的输入数据。如果没有这样一个全面的数据集,那么 MM-WSV 模型(元模型)则是一个很好的替代方案。WOG 和 NURP 模型适用于在区域尺度上对上覆地下水中硝酸盐浓度进行长期(>8 年)预测。

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