Estrogens are known to have an adverse impact on the reproductive functions of aquatic animals in natural waters. However, the estrogen levels are usually below the detection limits and vary drastically in the surface water, making it difficult to assess the environmental exposure in watershed management. While dynamic models are useful to bridge the data gaps on estrogen levels in surface water, the complex interconversion among estrogens hinders the accurate calculation of estrogens levels. To address the issue, we developed a kinetic model consisting of three first-order ordinary differential equations to track the concentration change of three key estrogens, estrone (E1), 17α-estradiol (E2α), and 17β-estradiol (E2β) with time resulting from the complex interconversion process. The model was solved by the matrix method and applied to 15 sets of lab data measured both in anaerobic and aerobic conditions as well as in aqueous solutions and solids with various initial estrogen concentrations from earlier studies. The coefficient of determination (R²) values for those datasets range between 0.842 and 0.989, indicating very good accuracy for the application to the natural environment. This kinetic model can help managers to assess the environmental exposure in watershed management and make determinations on effective solutions.

众所周知，雌激素会对自然水域中水生动物的生殖功能产生不利影响。然而，雌激素水平通常低于检测限，并且在地表水中变化很大，因此很难评估流域管理中的环境暴露。虽然动态模型有助于弥合地表水中雌激素水平的数据差距，但雌激素之间复杂的相互转换阻碍了雌激素水平的准确计算。为了解决这个问题，我们开发了一个由三个一阶常微分方程组成的动力学模型来跟踪三种关键雌激素、雌酮 (E1)、17α-雌二醇 (E2α) 和 17β-雌二醇 (E2β) 的浓度随时间的变化由于复杂的相互转换过程。该模型通过矩阵方法求解，并应用于 15 组实验室数据，这些数据在厌氧和需氧条件下以及早期研究中具有各种初始雌激素浓度的水溶液和固体中测量。决定系数（R² ) 这些数据集的值范围在 0.842 和 0.989 之间，表明在自然环境中的应用具有非常好的准确性。该动力学模型可以帮助管理人员评估流域管理中的环境暴露并确定有效的解决方案。