This paper analyzed high-altitude snow depth data and AMeDAS data in the Yoneshiro River basin and proposed a method for predicting snowmelt runoff using methods other than numerical models. High-risk snowmelt runoff was predicted by setting thresholds for snow depth, precipitation, and temperature data from AMeDAS observations. This prediction method was verified using 2022 data and its practicality was demonstrated. The effectiveness of high-altitude snow depth observations was demonstrated for snowmelt runoff after snow melts at AMeDAS points. In the case of the Yoneshiro River basin, high-risk snowmelt runoff was observed under conditions of a sudden decrease in snow depth of approximately 30 cm or more per three days at high altitudes, temperatures of approximately 10°C or more, and rainfall of approximately 5 mm per day. This result can be used for disaster prevention information and flood control systems during snowmelt runoff in municipalities that do not have flood prediction systems using numerical models, and demonstrated the importance of high-altitude snow observation.