National Institute of Water and Atmospheric Research (NIWA), Gate 10 Silverdale Road, Hamilton, New Zealand.
Sci Total Environ. 2011 Nov 15;409(24):5392-402. doi: 10.1016/j.scitotenv.2011.08.025. Epub 2011 Oct 2.
We used a concentration ratio method to predict yearly and summer averages of stream total nitrogen, nitrate and total phosphorus concentrations at a regional scale. The ratio of the median daily concentration on the flow weighted annual concentration was used. This ratio characterizes the concentration dynamics of a catchment. We took advantage of the commonly used budget type models applied at a regional scale to relate concentrations to loads instead of directly to land uses, as has previously been done. The relationship was modeled with Boosted Regression Trees using catchment and stream characteristics along with loads and flows obtained from the SPARROW budget model. The ratio modeling approach was compared to a direct approach for concentration prediction, and also to a simple method where the mean ratio was used. The modeling performances of the ratio models were overall satisfying (r2 of 49% to 78%), and a better choice than the two other methods tested. This ratio modeling approach is based on a steady state assumption and largely ignores temporal dynamics. As such, this modeling technique does not replace the more physically-based techniques, but allows for hybrid approaches for improved spatial interpolations. This method could be used to predict effectively the impact (at equilibrium) of land use change and management scenarios on water quality at a regional scale.
我们使用浓度比方法来预测区域尺度上的河流总氮、硝酸盐和总磷浓度的年平均值和夏季平均值。该比值是基于流量加权年浓度的中值日浓度计算的。该比值可描述流域的浓度动态。我们利用常用于区域尺度的预算类型模型，将浓度与负荷相关联，而不是像之前那样直接与土地利用相关联。该关系是使用 Boosted Regression Trees 模型，结合从 SPARROW 预算模型中获得的流域和溪流特征、负荷和流量来建模的。我们比较了浓度比模型的预测方法与直接预测方法，以及使用平均比值的简单方法。浓度比模型的建模性能总体令人满意（相关性为 49% 至 78%），优于测试的另外两种方法。这种浓度比建模方法基于稳态假设，在很大程度上忽略了时间动态。因此，这种建模技术不能替代更基于物理的技术，但可以通过混合方法来改善空间插值。这种方法可以有效地用于预测土地利用变化和管理情景对区域尺度水质的影响（在平衡状态下）。
