This work investigates smartphone-based image processing for monitoring reservoir water quality, driven by the necessity for accessible and economical environmental evaluation techniques. The objective is to examine the correlation between water color and essential water quality parameters, including turbidity, total phosphorus, and chlorophyll-a, utilizing basic, readily accessible technology. The concept entails taking water photos from three principal reservoirs in Taiwan—Shimen, Liyutan, and Hushan—utilizing a smartphone camera, succeeded by sophisticated image processing algorithms, encompassing RGB color space analysis and ripple filtering. The findings indicate strong correlations between the G/R ratio obtained from the photos and conventional water quality parameters, particularly turbidity and chlorophyll-a. The correlation analysis yielded R² = 0.72 (p < 0.01) for turbidity and R² = 0.68 (p < 0.05) for chlorophyll-a, confirming the statistical significance of the results.