Effective management of water resources and preservation of aquatic ecosystems are pressing global challenges. With the ongoing impacts of climate change and the increasing demands on water resources, there is a growing need for targeted restoration of degraded inland waters and those experiencing declining levels. To achieve meaningful outcomes, it is essential to establish measures for evaluation the effectiveness of restoration efforts accurately. Such metrics enable clear insights into restoration progress and guide the adaptive management needed for sustainable water resource management. This study addresses critical gaps in current methodologies by introducing two novel, tensor-based approaches to assess inland water restoration programs. Using the Normalized Difference Water Index (NDWI) derived from satellite imagery, these methods significantly enhance spatio-temporal analysis and visualization of water level dynamics, providing more precise insights into restoration impacts over time. The methods are applied to evaluate the effectiveness of the project connecting the Zarineh River to the Simineh River, one of the restoration program of Urmia Lake. The analysis using two newly introduced operators reveals significant water level patterns in the southeastern part of Lake Urmia. First, a substantial increase in water coverage was observed on the left side of the study area in 10 of the 12 months following restoration, indicating the program's effectiveness. Conversely, a reduction in water presence on the right side was noted during 5 months, suggesting areas that need further intervention. These findings demonstrate the value of these methods for tracking water level variations and assessing restoration outcomes effectively.