The Alabama Rainfall-Runoff Model, ARRMby Harold R. Henry, Univ of Alabama, United States,
David K. Hains, Univ of Alabama, United States,
Edmund Burkett, Univ of Alabama, United States,
Walter Schoel, III, Univ of Alabama, United States,
Abstract: ARRM consists of a conceptual state-space model which is cast in a stochastic framework. It uses the W.H. Green and C.A. Ampt method for infiltration, exponential decay for interflow and groundwater contributions, and lumped parameter kinematic routing for overland and channel flows. The stochastic model is built on (1) the deterministic model equations to which noise terms are appended and (2) a set of measurement equations which relate observed flow rates to state variables and to which noise terms are also appended. The R.E. Kalman filter is used to generate online feedback from measured flows to update the state variables and the flow rates. It may also be used to yield the errors of estimate of streamflow forecast values. The application discussed is to real-time modeling of the Coosa River above Rome, Georgia for the purpose of improving flood control operation of Carters and Allatoona reservoirs. Comparisons of simulated hydrographs with observed hydrographs show that ARRM can be effective in flood control operation.
Subject Headings: Rainfall-runoff relationships | Flow measurement | Hydrologic models | Floods | Groundwater flow | Filters | Infiltration | Stochastic processes | North America | United States | Alabama | Georgia | Italy | Europe | Rome
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