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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/518 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/518 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/518 archive 351 disk0/00/00/04/94 2016-01-15 01:43:02 2021-08-27 17:08:13 2016-01-15 01:43:02 monograph show 2 Szollosi-Nagy A. AL1645 pub iis_wat iis_mod iis_frc prog_ren In order to achieve the effective control of water resources systems, one must know the future behavior of the inputs to that particular system. Because of the uncertainties inherent in water resources processes, the prediction algorithm, to be constructed, should include stochastic elements, too. Moreover, the algorithm should be recursive to avoid cumbersome computations and to be able for real-time forecasting. In this paper we present a method which is applicable for both linear and nonlinear hydrologic systems having not completely time-invariant properties. The algorithms are based on the state space description of the processes involved and utilize the Kalman stochastic filtering technique. Due to the unknown nature of noise processes, the basic algorithms were changed to be adaptive. Using the algorithms the joint handling of water quantity and quality data becomes feasible. 1975-05 published RM-75-022 RM-75-022 10 2675 public research_memorandum IIASA, Laxenburg, Austria 25 FALSE info:eu-repo/semantics/book