Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
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Tank Model using Kalman Filter for Sediment Yield

유사량산정을 위한 Kalman filter를 이용한 탱크모델

  • Lee, Yeong-Hwa (Department of Civil Engineering, Daegu Haany University)
  • Published : 2007.12.31
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Abstract

A tank model in conjunction with Kalman filter is developed for prediction of sediment yield from an upland watershed in Northwestern Mississippi. The state vector of the system model represents the parameters of the tank model. The initial values of the state vector were estimated by trial and error. The sediment yield of each tank is computed by multiplying the total sediment yield by the sediment yield coefficient. The sediment concentration of the first tank is computed from its storage and the sediment concentration distribution(SCD); the sediment concentration of the next lower tank is obtained by its storage and the sediment infiltration of the upper tank; and so on. The sediment yield computed by the tank model using Kalman filter was in good agreement with the observed sediment yield and was more accurate than the sediment yield computed by the tank model.

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References

  1. Lee Y. H., Singh V. P., 1999, Prediction of sediment yield by coupling Kalman filter with instantaneous unit sediment graph, Hydrological Processes, 2861-2875
  2. Lee Y. H., Singh V. P., 2005, Tank model for sediment yield, Water Resources Management, 19, 349-362 https://doi.org/10.1007/s11269-005-7998-y
  3. Sugawara, M., 1979, Automatic calibration of the tank model, Hydrological Science Bulletin, 24, 375-388 https://doi.org/10.1080/02626667909491876
  4. Williams J. R., 1975a, Sediment yield prediction with universal equation using runoff energy factor, In Present and Prospective technology for Predicting Sediment Yields and Sources, 244-52, ARS-S-40, Agricultural Research Service, U.S. department of Agriculture, Washington, D.C
  5. Todini E., 1978, Mutually interactive state parameter (MISP) estimation, Application of Kalman filter, Proc. of AGU Chapman Conference, Univ. of Pittsburgh, 135-151
  6. Wood E. F., Szollosi-Nagy A., 1978, An adaptive algorithm for analyzing short-term structural and parameter changes in hydrologic prediction models, Water Resources Research, Vol.14, No.4, 577-581 https://doi.org/10.1029/WR014i004p00577
  7. Wu C. M., Huang W. C., 1990, Effect of observability in Kalman filtering on rainfall-runoff modeling, Taiwan Water Conservancy Quarterly, 38, 37-47
  8. Bowie A. J., Bolton G. C., 1972, Variations in runoff and sediment yields of two adjacent watersheds as influenced by hydrologic and physical characteristics, Proceeding, Mississippi Water Resources Conference, 37-55, water Resources Research Institute, Mississippi State University, Mississippi State, Mississippi