Sensitivity and identifiability analyses are a standard practice in modeling applications to investigate the relative importance of model components that control the system's behavior. In this study, both analyses were implemented to identify the most influential parameters in a coupled hydrodynamic-biogeochemical model applied for three subtropical reservoirs. The one-dimensional General Lake Model coupled to Aquatic EcoDynamics (GLM-AED) was used to simulate the dynamics of dissolved oxygen, total phosphorus, nitrate, ammonium, and chlorophyll-a. Results reveal consistent sensitivity patterns between reservoirs, especially for a subset of temperature multipliers affecting dissolved oxygen and nutrients. In contrast, the sensitivity of chlorophyll-a is highly site-specific. Additionally, the majority of parameters are medium or high sensitive, which indicates the need for a calibration procedure to improve model accuracy. The analyses provide a detailed understanding of the governing ecosystem dynamics as a step forward to model identifiability and guidance for future model calibration.

敏感性和可识别性分析是建模应用程序中的标准做法，用于调查控制系统行为的模型组件的相对重要性。在这项研究中，两种分析都用于确定应用于三个亚热带水库的耦合水动力-生物地球化学模型中最有影响的参数。结合水生生态动力学 (GLM-AED) 的一维 General Lake 模型用于模拟溶解氧、总磷、硝酸盐、铵和叶绿素 a 的动力学。结果揭示了水库之间一致的敏感性模式，特别是对于影响溶解氧和营养物的温度乘数子集。相比之下，叶绿素-a 的敏感性是高度位点特异性的。此外，大多数参数是中等或高度敏感的，这表明需要校准程序来提高模型精度。这些分析提供了对治理生态系统动态的详细理解，作为模型可识别性和未来模型校准指导的一步。