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Identifying dynamical models of nitrate propagation in agricultural drinking water: how can we help agronomists?

机译：确定农业饮用水中硝酸盐传播的动力学模型：我们如何帮助农学家？

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摘要

Since the 50 last years, the rapid development of modern agriculture in industrialised countries has considerably affected the quality of water resources, up to the point to jeopardise the capacity of rural territories to produce drinking water. Hence, agronomy has been interested in the complex nitrate biogeochemical interactions for a long time.While agronomists are able to produce very accurate physical models of nitrate propagation at different scales, their tools have a limited relevance if the information regarding geology or agriculture is missing. Consequently, in many cases, it prevents the specialists of being affirmative about the prediction of their current actions on the water quality. By opposition, a system identification methodology is here presented to predict nitrate concentration in water. It has the advantage of being applicable even when very little knowledge is available. It will be shown how external variables such as rainfall and temperature can play an important role in modelling water pollution systems. The efficiency of the approach, both in terms of prediction and physical insight, is discussed on a real life dataset.
机译：自从过去的50年以来，工业化国家中现代农业的迅速发展已极大地影响了水资源的质量，甚至损害了农村地区生产饮用水的能力。因此，长期以来，农学一直对复杂的硝酸盐生物地球化学相互作用感兴趣。虽然农学家能够产生非常准确的硝酸盐在不同尺度下传播的物理模型，但如果缺少有关地质或农业的信息，他们的工具的相关性就很有限。因此，在许多情况下，这会阻止专家对他们当前对水质采取的行动表示肯定。相对地，这里提出一种系统识别方法来预测水中的硝酸盐浓度。即使没有什么知识，它也具有适用性的优点。它将显示降雨和温度等外部变量如何在水污染系统建模中发挥重要作用。在预测和物理洞察力方面，该方法的效率在现实生活的数据集上进行了讨论。

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