Intermittent rivers and ephemeral streams (IRES) account for 50% of the world's flows. Climate change leads to an increase in intermittent streams from perennial streams. Recently, IRES have been found to be very important for carbon and nitrogen cycling and ecosystem functions. Despite recent attention towards IRES, spatial and temporal data lack, especially in mountain areas. Conventional measuring techniques depend on devices that have certain limitations, for example, they are placed in the streambed, where they get destroyed or displaced during a heavy stream flow event. This thesis presents a self-developed, low-cost audio sensor that can derive the water level of an IRES using only sound. In addition to an audio sensor, a time-lapse camera constantly documented the streambed and captured the water level at thirty-minute intervals. The water level determined from the images and the audio files is strongly correlated with a 95% coefficient of determination (R2). We can calculate the water level using the audio data with the exponential regression function, as long as there is some water in the stream. This work demonstrates the possibility of an audio sensor to obtain reliable water level data in an IRES and offers a legitimate alternative to conventional measuring methods. This technological advance offers a new affordable, accessible tool that can be widely used and thus increase monitoring of the flow of IRES at a large scale.