The solid-liquid distribution coefficient (K_d) is a key input parameter in radioecological models. However, its large variability hampers its usefulness in modelling transport processes as well as its accuracy in representing soil-radionuclide interactions. For the specific case of radiocaesium, the analyses of a Cs K_d soil dataset (769 entries) showed that values varied over a five order of magnitude range, and the resulting Cs K_d best estimate (calculated as a geometric mean = 2.5 × 10³ L kg⁻¹) lacked reliability and representativity. Grouping data and creation of partial datasets based on the experimental approach (short-term (< ~1 yr) vs. long-term experiments (> ~1 yr)) and soil factors affecting Cs interaction (i.e., the ratio of the radiocaesium interception potential (RIP) to the potassium content in soil solution (K_ss); organic matter content (OM) and soil texture) succeeded in reducing variability a few orders of magnitude, with Cs K_d best estimates also differing by one-two orders of magnitude depending on the type of soil and experimental approach. The statistical comparison of the Cs K_d best estimates and related cumulative distribution functions of the partial datasets revealed a relevant effect of the sorption dynamics on Cs K_d values (with long-term values systematically higher than short-term ones), and that the RIP/K_ss ratio was an excellent predictor of Cs K_d for short-term scenarios, whereas the RIP parameter could be predicted on the basis of texture information. The OM threshold to distinguish between OM threshold to distinguish between Mineral and Organic soils subclasses, regarding Cs interaction was determined to be 50% and 90% OM for short- and long-term scenarios, respectively. It was then recommended to select the Cs K_d input data depending on the soils and scenarios to be assessed (e.g., short- vs. long-term; OM %) to improve the reliability and decrease the uncertainty of the radioecological models.

固液分配系数（K _d）是放射生态学模型的关键输入参数。但是，它的大变异性妨碍了它在模拟运输过程中的用处以及在表示土壤-放射性核素相互作用中的准确性。对于放射性铯的具体情况，对Cs K _d土壤数据集（769个条目）的分析显示，值在五个数量级范围内变化，并且得到的Cs K _d最佳估计值（以几何平均值= 2.5×10计算）³  L kg ^-1）缺乏可靠性和代表性。根据实验方法（短期（<〜1年）与实验方法）对数据进行分组和创建部分数据集。长期实验（>〜1年）和影响Cs相互作用的土壤因素（即放射性铯截留势（RIP）与土壤溶液中钾含量（K _ss的比值），有机质含量（OM）和土壤的比值纹理）成功地将变异性降低了几个数量级，根据土壤的类型和实验方法，Cs K _d的最佳估计值也相差一两个数量级。Cs K _d最佳估计值和部分数据集的相关累积分布函数的统计比较显示，吸附动力学对Cs K _d值（长期值系统地高于短期值）具有相关影响，并且RIP / K _SS在短期情况下，比率可以很好地预测Cs K _d，而RIP参数可以根据纹理信息来预测。关于Cs相互作用，用于区分矿物和有机土壤亚类的OM阈值在短期和长期情况下分别确定为50％和90％OM。然后建议根据要评估的土壤和方案（例如，短期与长期； OM％）选择Cs K _d输入数据，以提高可靠性并减少放射生态模型的不确定性。