INTRODUCTION

Forecasting the runoff resulting from a rainfall belongs to the classical basic issues of hydrology. It is shown that the pattern recognition method, which is used in as diverse fields as medical diagnosis, mail problems, banking processes, coastal changes and cybernetics (Mizumura, 1988) is useful also in hydrological forecasting. The method dwells on the obvious statement that much and little rainfall correspond to much and little runoff, respectively.

RAINFALL–RUNOFF PROCESS

The physical system of transformation of rainfall into runoff is very complex. Moreover the runoff consists of three components such as surface flow, interflow, and groundwater flow. Therefore, even if the model strictly described the underlying physical phenomena, it would be difficult to solve the governing equations. The rainfall–runoff process is heavily dependent upon many characteristics of each watershed. For the sake of runoff prediction the rainfall–runoff process is treated here as a black box. Thus, one can employ either of such methods as differential equations, integral equations, least square methods, Wiener–Hopf equation, Kalman filtering etc. Yet another approach originating from the pattern recognition methodology will be tackled here.