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Flash flooding is one of the most common natural hazards in China, particularly in mountainous areas, and usually causes heavy damage and casualties. However, the forecasting of flash flooding in mountainous regions remains challenging because of the short response time and limited monitoring capacity. This paper aims to establish a strategy for flash flood warnings in mountainous ungauged catchments across humid, semi-humid and semi-arid regions of China. First, we implement a geomorphology-based hydrological model (GBHM) in four mountainous catchments with drainage areas that ranges from 493 to 1601 km(2). The results show that the GBHM can simulate flash floods appropriately in these four study catchments. We propose a method to determine the rainfall threshold for flood warning by using frequency analysis and binary classification based on long-term GBHM simulations that are forced by historical rainfall data to create a practically easy and straightforward approach for flash flood forecasting in ungauged mountainous catchments with drainage areas from tens to hundreds of square kilometers. The results show that the rainfall threshold value decreases significantly with increasing antecedent soil moisture in humid regions, while this value decreases slightly with increasing soil moisture in semi humid and semi-arid regions. We also find that accumulative rainfall over a certain time span (or rainfall over a long time span) is an appropriate threshold for flash flood warnings in humid regions because the runoff is dominated by excess saturation. However, the rainfall intensity (or rainfall over a short time span) is more suitable in semi-humid and semi-arid regions because excess infiltration dominates the runoff in these regions. We conduct a comprehensive evaluation of the rainfall threshold and find that the proposed method produces reasonably accurate flash flood warnings in the study catchments. An evaluation of the performance at uncalibrated interior points in the four gauged catchments provides results that are indicative of the expected performance at ungauged locations. We also find that insufficient historical data lengths (13 years with a 5-year flood return period in this study) may introduce uncertainty in the estimation of the flood/rainfall threshold because of the small number of flood events that are used in binary classification. A data sample that contains enough flood events (10 events suggested in the present study) that exceed the threshold value is necessary to obtain acceptable results from binary classification. (C) 2016 Elsevier B.V. All rights reserved.