Source water protection (SWP) is an important step in the implementation of a multi-barrier approach that ensures the delivery of safe drinking water. Available decision-making models for SWP primarily use complex mathematical formulations that require large data sets to perform analysis, which limit their use. Moreover, most of them cannot handle interconnection and redundancy among the parameters, or missing information. A fuzzy-based model is proposed in this study to overcome the above limitations. This model can estimate a reduction in the pollutant loads based on selected SWP strategies (e.g., storm water management ponds, vegetated filter strips). The proposed model employs an export coefficient approach and account for the number of animals to estimate the pollutant loads generated by different land usages (e.g., agriculture, forests, highways, livestock, and pasture land). Water quality index is used for the assessment of water quality once these pollutant loads are discharged into the receiving waters. To demonstrate the application of the proposed model, a case study of Page Creek was performed in the Clayburn watershed (British Columbia, Canada). The results show that increasing urban development and poorly managed agricultural areas have the most adverse effects on source water quality. The proposed model can help decision makers to make informed decisions related to the land use and resource allocation.