With the increasing use of telemetry in the control of water resource systems, a considerable amount of effort is being devoted to the development of models and parameter estimation techniques for on-line use. A variety of models and parameter estimation algorithms have been considered, ranging from complex conceptual models of the soil moisture accounting type, which are traditionally calibrated off-line, to state-space/Kalman filter models which, perhaps, have enjoyed undue popularity in the recent literature due to their mathematical elegance. The fundamental assumptions underlying the various approaches are reviewed, and the validity of these assumptions in the hydrological forecasting context is assessed. The paper draws on some results obtained during a recent workshop at the Institute of Hydrology in making assessments of the relative merits of different models and parameter estimation algorithms; these results have been derived from an intercomparison of a number of real time forecasting models.