“…Camacho and Lees, 1999;Keefer and McQuivey, 1974;Kontur, 1977;Kundzewicz and Dooge, 1985;O'Connor, 1976;Perumal, 1994;Szolgay, 1991Szolgay, , 2004, the discrete linear cascade model (DLCM) (Szollosi-Nagy, 1982, 1989Szilagyi, 2003Szilagyi, , 2004Szilagyi et al, 2005) stands out for several reasons: (a) it is equivalent to the discretized form of the continuous, spatially discrete, kinematic wave equation (Szollosi-Nagy, 1989); (b) it is specifically formulated to deal with discrete data whether in a pulse-or sample-data system framework; (c) it is discretely coincident, which means that for identical inputs (as between the discrete and continuous models), it gives identical outputs at discrete time increments; (d) it does not require numerical iterations (so numerical stability is not an issue) because it is written in a state-space form with the state-and input-transition matrices given explicitly; (e) since it is in a state-space form, linear filtering techniques, such as the Kalman filter (1960), can directly be applied; and last but not the least, (f) with it, the inverse problem of finding the input sequence to a given output sequence (which often is needed to fill data gaps in a streamflow series) is a simple algebraic manipulation.…”