Sensitivity analysis method of system identification and its potential in hydrologic research

Abstract

Sensitivity analysis should be an integral part of nearly every hydrologic study. At an elementary level, sensitivity analysis is useful in studying the relative sensitivity of the result to the data input. Studying the sensitivity of a hydrologic system to changes in its parameters and initial conditions makes it possible not only to gain insight into a system's behavior but to derive simple computational algorithms for the identification of unknown parameters. The fact that sensitivity analysis leads to simple initial‐value problems makes it ideal for mechanization on an analog computer. The computational steps involved in implementing identification algorithms based on sensitivity analysis are relatively simpler than those based on such other methods as quasilinearization. The applicability of this method to identify both lumped and distributed hydrologic systems with deterministic or statistical input‐output data is demonstrated.