Håkanson Lars
Department of Earth Sciences, Institute of Earth Sciences, Uppsala University, Norbyv. 18B, Villav. 16, 752 36 Uppsala, Sweden.
J Environ Radioact. 2005;80(3):357-82. doi: 10.1016/j.jenvrad.2004.10.008.
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 ( approximately dry land) areas and outflow ( approximately wetland) areas. The model also accounts for time-dependent fixation of substances in the catchment. The catchment area sub-model 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 180 000 km(2), precipitation from 500 to 960 mm/yr and fallout from 1700 to 660 000 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.
本文提出了一种全新的、基于过程的河流模型，用于模拟诸如单次脉冲沉降产生的放射性核素等物质。该新模型已通过切尔诺贝利事故中受放射性铯污染的13条欧洲河流的数据进行了严格测试。这种建模方法能够给出特定河流站点水中放射性核素的浓度（总量、溶解相和颗粒相；以及沉积物和鱼类中的浓度，但本文不讨论后两个方面）。该模型基于河流上游河段和上游集水区内的各种过程。集水区被划分为流入区（大致为旱地）和流出区（大致为湿地）。该模型还考虑了集水区内物质随时间的固定情况。集水区子模型基于先前的一个集水区模型，该模型在放射性铯、放射性锶和钙浓度（来自石灰处理作业）方面的测试结果非常理想。新的河流模型在实际应用中很简便，因为所有驱动变量都可以很容易地从地图和标准监测程序中获取。驱动变量包括：纬度、海拔、大陆性、集水区面积、年平均降水量、土壤类型（有机土和砂土的百分比）、沉降量以及沉降月份。已将模拟值与来自10个河流水位点的独立经验数据进行了比较（91个水中放射性铯数据），这些数据覆盖了广泛的区域（集水区面积从4000至180000平方千米，降水量从500至960毫米/年，沉降量从1700至660000贝克勒尔/平方米）。新模型预测效果非常好——当将模拟值与经验数据进行比较时，斜率完美（为1.0），r²值为0.90。考虑到经验数据中也存在不确定性，这给预测能力设定了一个限制（如r²值所表示的），能有这样的结果已经很不错了。
