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首页> 外文期刊>Environmental Science & Technology >Improving bad Estimates for N0_3 and P in Surface Waters by Characterizing the Concentration Response to Rainfall Events
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Improving bad Estimates for N0_3 and P in Surface Waters by Characterizing the Concentration Response to Rainfall Events

机译：通过表征对降雨事件的浓度响应来改善地表水中N0_3和P的错误估算

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摘要

For the evaluation of action programs to reduce surface water pollution, water authorities invest heavily in water quality monitoring. However, sampling frequencies are generally insufficient to capture the dynamical behavior of solute concentrations. For this study, we used on-site equipment that performed semicontinuous (15 min interval) N03 and P concentration measurements from June 2007 to July 2008. We recorded the concentration responses to rainfall events with a wide range in antecedent conditions and rainfall durations and intensities. Through sequential linear multiple regression analysis, we successfully related the NO_3 arid P event responses to high-frequency records of precipitation, discharge, and groundwater levels. We applied the regression models to reconstruct concentration patterns between low-frequency water quality measurements. This new approach significantly improved load estimates from a 20% to a 1% bias for NO_3 and from a 63% to a 5% bias for P. These results demonstrate the value of commonly available precipitation, discharge, and groundwater level data for the interpretation of water quality measurements. Improving load estimates from low-frequency concentration data just requires a period of high-frequency concentration measurements and a conceptual, statistical, or physical model for relating the rainfall event response of solute concentrations to quantitative hydrological changes.
机译：为了评估减少地表水污染的行动计划，水务部门在水质监测方面投入了大量资金。但是，采样频率通常不足以捕获溶质浓度的动力学行为。在本研究中，我们使用了现场设备，该设备从2007年6月至2008年7月进行了半连续（间隔为15分钟）的N03和P浓度测量。我们记录了对降雨事件的浓度响应，以及在先前条件，降雨持续时间和强度下的变化范围很大。 。通过顺序线性多元回归分析，我们成功地将NO_3和P事件事件响应与降水，流量和地下水位的高频记录相关联。我们应用了回归模型来重建低频水质测量之间的浓度模式。这种新方法将负荷估算值从NO_3的偏差从20％提高到1％，将P的偏差从63％提高到了5％。这些结果证明了常用的降水，流量和地下水位数据的解释价值水质测量。改善低频浓度数据的负荷估算仅需要一段时间的高频浓度测量和概念，统计或物理模型，以将降雨事件对溶质浓度的响应与定量水文变化联系起来。

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  • 来源
    《Environmental Science & Technology》 |2010年第16期|p.6305-6312|共8页
  • 作者

    JOACHIM C.ROZEMEIJER; rnYPE VAN DER VELDE; rnFRANS C.VAN GEER; rnGERRIT H. DE ROOIJ; rnPAUL J. J. F.TORFS; rnHANS PETER BROERS;

  • 作者单位

    Department of Physical Geography, Utrecht University, P.O. Box 80125, NL-3508 TC Utrecht, The Netherlands Groundwater and Subsurface Department, Deltares, P.O. Box 85467, NL-3508 AL Utrecht, The Netherlands;

    rnSoil Physics, Ecohydrology and Groundwater Management Group, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen, The Netherlands Groundwater and Subsurface Department, Deltares, P.O. Box 85467, NL-3508 AL Utrecht, The Netherlands;

    rnTNO Geological Survey of The Netherlands, P.O. Box 80015, 3508 TA, Utrecht, The Netherlands Department of Physical Geography, Utrecht University, P.O. Box 80125, NL-3508 TC Utrecht, The Netherlands;

    rnDepartment Soil Physics, Helmholtz Centre for Environmental Research, Theodor-Lieser-Strasse 4, D-06120 Halle, Germany;

    rnSoil Physics, Ecohydrology and Groundwater Management Group, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen, The Netherlands;

    rnGroundwater and Subsurface Department, Deltares, P.O. Box 85467, NL-3508 AL Utrecht, The Netherlands Department Soil Physics, Helmholtz Centre for Environmental Research, Theodor-Lieser-Strasse 4, D-06120 Halle, Germany;

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