Propagation conditions in an underwater acoustic channel are known to vary in time, causing the received signal strength to deviate from the nominal value predicted by a deterministic propagation model. To facilitate large-scale system design in such conditions (e.g. power allocation), we develop a statistical propagation model in which the transmission loss is treated as a random variable. By repetitive computation of acoustic field using ray tracing for a set of varying environmental conditions (surface height, wave activity, small displacements of transmitter and receiver around nominal locations), an ensemble of transmission losses is compiled which is then used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e. to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc.).
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