Modern control concepts in hydrology
Abstract
Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use statespace concepts. The identification schemes are sequential and adaptive and can handle either timeinvariant or timedependent parameters. They are used to identify parameters in the Prasad model of rainfallrunoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trialanderror procedure, and the second using a quasilinearization technique. The proposed approaches offer a systematic way of analyzing the rainfallrunoff process when the input data are imbedded in noise.
 Publication:

IEEE Transactions on Systems Man and Cybernetics
 Pub Date:
 January 1975
 Bibcode:
 1975ITSMC...5...46D
 Keywords:

 Adaptive Control;
 Hydrology;
 Identifying;
 Mathematical Models;
 State Vectors;
 Stochastic Processes;
 Control Theory;
 Estimating;
 Linear Systems;
 Numerical Integration;
 Rain;
 Random Noise;
 Technology Transfer;
 Geophysics