首页> 外文期刊>Journal of Environmental Radioactivity >A new general mechanistic river model for radionuclides from single pulse fallouts which can be run by readily accessible driving variables
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A new general mechanistic river model for radionuclides from single pulse fallouts which can be run by readily accessible driving variables

机译:一种新的通用机械河模型,可用于通过单脉冲沉降产生的放射性核素,该模型可以通过易于访问的驱动变量运行

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This paper presents a new general, process-based river model for substances such as radionuclides from single pulse fallouts. The new model has been critically tested using data from 13 European rivers contaminated by radiocesium from the Chernobyl accident. This modelling approach gives radionuclide concentrations in water (total, dissolved and particulate phases; and also concentrations in sediments and fish, but the latter aspects are not discussed in this paper) at defined river sites. The model is based on processes in the upstream river stretch and in the upstream catchment area. The catchment area is differentiated into inflow (≈dry land) areas and outflow (≈ wetland) areas. The model also accounts for time-dependent fixation of substances in the catchment. The catchment area submodel is based on a previous catchment model, which has been tested with very good results for radiocesium, radiostrontium and Ca-concentrations (from liming operations). The new river model is simple to apply in practice since all driving variables may be readily accessed from maps and standard monitoring programs. The driving variables are: latitude, altitude, continentality, catchment area, mean annual precipitation, soil type (percentages or organic and sandy soils), fallout and month of fallout. Modelled values have been compared to independent empirical data from 10 rivers sites (91 data on radiocesium in water) covering a wide domain (catchment areas from 4000 to 180000 km~2, precipitation from 500 to 960 mm/yr and fallout from 1700 to 660000 Bq/m~2). The new model predicts very well - when modelled values are compared to empirical data, the slope is perfect (1.0) and the r~2-value is 0.90. This is good giving the fact that there are also uncertainties in the empirical data, which set a limit to the achieved predictive power, as expressed by the r~2-value.
机译:本文提出了一种新的基于过程的通用河模型,用于处理单脉冲沉积物中的放射性核素等物质。使用来自切尔诺贝利事故的放射性铯污染的13条欧洲河流的数据对新模型进行了严格测试。这种建模方法给出了确定的河水在水中的放射性核素浓度(总相,溶解相和颗粒相;以及沉积物和鱼类的浓度,但本文未讨论后者)。该模型基于上游河段和上游集水区的过程。集水区分为流入(≈干地)区和流出(≈湿地)区。该模型还考虑了流域中物质的时间依赖性固定。汇水面积子模型基于先前的汇水模型,该模型已针对放射性铯,放射性锶和Ca浓度(来自石灰操作)进行了测试,效果非常好。新的河流模型在实践中很容易应用,因为所有行驶变量都可以从地图和标准监控程序中轻松获取。驱动变量是:纬度,海拔,大陆性,集水区,年平均降水量,土壤类型(百分比或有机和沙质土壤),沉降和沉降月份。已将模型值与来自10个河流站点的独立经验数据(91个水中的放射性铯数据)进行了比较,这些数据覆盖了一个宽域(集水区4000至180000 km〜2,降水量500至960 mm / yr,降水量从1700至660000) Bq / m〜2)。新模型的预测非常好-将建模值与经验数据进行比较时,斜率是理想的(1.0),r〜2值为0.90。考虑到实证数据中也存在不确定性,这是一个很好的事实,这给以r〜2-值表示的实现的预测能力设定了限制。

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