| This dissertation develops a watershed management framework that integrates environmental protection goals, cost efficiency, and equity considerations. The management framework seeks the cost-minimizing allocation of pollution control responsibilities to reduce phosphorus (P)-loading to streams. Previous research on the allocation problem has developed the least-cost formulation of the problem that addresses both cost efficiency through minimizing total pollution control costs, and hydrological uncertainty through probabilistic water quality constraints. However, the least-cost formulation of the allocation problem does not explicitly consider the distribution of pollution control responsibilities, and hence, distribution of costs among involved parties, which impacts equity. This dissertation advances the research on watershed management by introducing equity into the least-cost allocation problem. In addition, since accurate modeling of P-loading is an important input to the allocation problem, the export coefficients approach used to model P-loading is modified to an erosion-scaled export coefficient approach. The P erosion-scaled export coefficient approach can explain hydrologic variability in predicting the P-loading to the receiving stream, while maintaining the simplicity and low data requirement characteristics of the traditional export coefficient. An improved description of the impact of hydraulic variability on P-loading allows for improved assessment of coefficients uncertainty, which is achieved using Bayesian inference. However, poor quality of streamflow records presents a challenge for adequate understanding and modeling of the hydrological behavior of any watershed. Therefore, a procedure is developed for improving calibration of hydrological models through incorporation of soft information concerning the accuracy of calibration data. Applicability of developed methods in this research is demonstrated using data from the Fishtrap Creek catchment in Lower Nooksack River sub-basin in Washington State. |
