To be useful in a wider range of environments, especially environments that are not sanitized for their use, robots must be able to handle uncertainty in ground conditions. This requires a robot to incorporate new sensors and sources of information, and to be able to use this information to make decisions regarding navigation. When using autonomous mobile robots in unstructured and poorly defined environments, ground condition is of critical importance and is a common cause of failure, an example being the presence of ground water in the operating area. To evaluate a non-contact sensing method to mitigate this risk, Frequency Modulated Continuous Wave (FMCW) radar is integrated with an Unmanned Ground Vehicle (UGV), representing a novel application of FMCW to detect new measurands for Robotic Autonomous Systems (RAS) navigation, informing on ground integrity and adding to the state-of-the-art in sensing for optimized autonomous path planning. In this paper, FMCW is first evaluated in a desktop setting to determine water sensing capability. The FMCW is then fixed to a UGV, and the sensor system is successfully tested and validated in a representative environment containing regions with significant levels of ground water saturation. The successful integration of FMCW radar with autonomous environmental characterization and mapping has the potential to provide new measurands of terrain integrity data, such as the detection of water, snow, ice, oil or other contaminants on the operating surface that may otherwise jeopardize the operation of a UGV.