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Prediction of Nitrate Concentration in Stream Water Based on Watershed Land Use and Stream Flow Rate

机译:基于流域土地利用和河流流量的河流硝酸盐浓度预测。

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Non-point source nitrate loading to stream water can be affected by land use, soiltype, slope of discharging watershed, water flow rate, and storm events. This studyconsiders the effects of land use type, water flow rate and seasonal and regional variationin order to understand and predict transport of nitrate in stream water discharging fromwatersheds along Virginia’s Eastern Shore. A simple regression analysis was performedto check the relationship between nitrate concentration and land use type. Fertilizedland was found to be the strongest contributor to nitrate concentration in stream water.Developed land was also a contributor but with a lower weighting factor. Forested landacted as a significant inhibitor. A predictive model was generated using multipleregression analysis. Besides land use type, nitrate concentration was also significantlyinfluenced by stream flow rate. Other variables, including sampled area, seasonal andregional variation, may be treated as background information, in which they may havesome effect on nitrate concentration, but not significantly enough to be included in thepredictive model. Therefore, stream nitrate concentration levels can be predicted alongthe Eastern Shore of Virginia based on land use type and stream flow rate. Predictionsmay be improved by incorporating other geomorphic or hydrologic information.
机译:流向水的非点源硝酸盐负荷可能会受到土地利用,土壤的影响 分水岭的类型,坡度,水流量和暴雨事件。这项研究 考虑土地使用类型,水流量以及季节和区域变化的影响 为了了解和预测硝酸盐在河水排放中的运输 弗吉尼亚州东部海岸的分水岭。进行了简单的回归分析 检查硝酸盐浓度与土地利用类型之间的关系。受精 人们发现土地是溪流水中硝酸盐浓度的最强贡献者。 发达土地也是一个贡献者,但权重因子较低。林地 起到了重要的抑制作用。预测模型是使用多个 回归分析。除了土地利用类型,硝酸盐浓度也显着 受流率的影响。其他变量,包括采样面积,季节性和 区域差异,可以被视为背景信息,其中可能具有 对硝酸盐浓度有一些影响,但不足以将其包括在内 预测模型。因此,沿流的硝酸盐浓度水平可以预测 基于土地使用类型和河流流量的弗吉尼亚东部海岸。预测 通过合并其他地貌或水文信息可能会有所改善。

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