Pathogen, whose abundance is often measured by the concentration of fecal indicator bacteria, is listed as the top cause of waterbody impairments in the US. An accurate estimation of the bacterial loading from watershed is thus fundamentally important for water quality management. Despite advances in watershed modeling, accurate estimation of bacterial load is still very challenging due to large uncertainties associated with bacterial sources, accumulation, and removal in the watershed. We introduce an inverse method using field-measured bacterial concentrations and numerical model-calculated residence time to estimate the bacterial loading from the drainage basin. In this method, an estuary is divided into multiple segments. Water and bacterial fluxes between neighboring segments are computed from a set of linear equations derived based on mass balance equation and the relationship between residence time and water fluxes. Loading to each segment can then be estimated by combining the computed water fluxes and observed bacterial concentrations. The approach accounts for seasonal and interannual variations in hydrodynamics due to tide, river discharge, and estuarine circulations. The method was applied to Nassawadox Creek, a sub-estuary of Chesapeake Bay, where Fecal Coliform concentrations at 46 stations were continuously monitored. The method is verified by the high consistency between estimated loadings and presumably known input loadings in numerical experiments with either constant or time-varying input loadings. With sparse observational data, the inversely estimated loadings agree well with the loadings from a previously calibrated watershed model, demonstrating the reliability of the method. The inverse approach can be used to cross-check the result of watershed models and assess changes in watershed condition. The method is also readily applicable to other types of materials, such as inorganic nutrients.

病原体的丰度通常通过粪便指示菌的浓度来衡量，被列为美国水体损害的主要原因。因此，对流域细菌负荷的准确估算对于水质管理至关重要。尽管分水岭建模取得了进展，但是由于与分水岭中细菌来源，积累和清除相关的不确定性很大，因此准确估算细菌负荷仍然非常具有挑战性。我们采用现场测量的细菌浓度和数值模型计算的停留时间引入反演方法，以估算流域的细菌负荷。在这种方法中，河口被分为多个部分。根据质量平衡方程以及停留时间和水通量之间的关系，根据一组线性方程式计算相邻段之间的水和细菌通量。然后可以通过组合计算出的水通量和观察到的细菌浓度来估算每个部分的负荷。该方法考虑了潮汐，河流流量和河口环流引起的水动力的季节性和年度变化。该方法已应用于切萨皮克湾子河口纳萨瓦多克斯溪 和河口环流。该方法已应用于切萨皮克湾子河口纳萨瓦多克斯溪 和河口环流。该方法已应用于切萨皮克湾子河口纳萨瓦多克斯溪连续监测46个站的粪大肠菌群浓度。在恒定或随时间变化的输入载荷的数值实验中，估计载荷与假定的已知输入载荷之间的高度一致性验证了该方法。利用稀疏的观测数据，反估计的负荷与先前校准的分水岭模型的负荷非常吻合，证明了该方法的可靠性。逆方法可用于交叉检查分水岭模型的结果并评估分水岭状况的变化。该方法也容易适用于其他类型的材料，例如无机营养物。