Modeling water flow of the Rhine River using seasonal long memory

The discharge of the Rhine River is modeled by using flexible seasonal long‐memory models. The memory parameters are estimated by log periodogram regression for every seasonal frequency separately. It turns out that these models fit well the long‐term behavior of the river. Significant long‐range dependence was estimated at annual and semiannual frequencies. These results are robust against elimination of possible deterministic seasonal structures.