Path planning for outdoor operation of ground-based robots, with respect to surface features of the terrain involves recognition of various obstacles. Besides the areas with complicated surface features (elevations, ravines), buildings, and other human-made objects, floodable areas can be potentially dangerous for operation of outdoor robots in irregular terrain. This paper presents the algorithm for floodable areas edge detection (FAED) through analysis of surface features on heightmap. The algorithm respects height values from any points of the map, as well precipitation data in the area of interest, depending on which the wetness of certain areas can increase or decrease. Experiments were performed to compare number of cells in areas, outlined manually and detected with FAED. The experimental results showed that the total number of cells, revealed with FAED, is 17% less at average, than in areas, outlined manually. Hence, the cell array in areas, whose edges were detected with FAED, is more accurate, than with manual edge detection, what enables more efficient heightmap utilization in path planning for ground-based robotic vehicles.