Flood Forecasting in Regulated Basins Using the Ensemble Extended Kalman Filter with the Storage Function Method
Publication: Journal of Hydrologic Engineering
Volume 15, Issue 12
Abstract
An ensemble extended Kalman filter (EEKF) formulation is applied to a regulated basin. The existing event-based storage function method for the prediction of flow is enhanced to incorporate continuous soil water accounting and to be suitable for application in large watersheds with several tributaries. The formulation is complemented by EEKF, which utilizes flow and reservoir level observations to update catchment soil water and channel states, and reservoir storage estimates predicted by the model. The formulated forecast is suitable for operational application. Ensemble precipitation predictions are generated to serve as input to the forecast system, and the results are intercompared using two different statistical approaches. These predictions together with parametric uncertainty models constitute the basis of the ensemble flow predictions by the model. A case study is presented that demonstrates the implementation and evaluation of the method with respect to the prediction of large flow events in a regulated basin, a tributary to Nakdong River in Korea, using hourly data for the period January 2006–August 2008. A significant finding is that although the calibrated-model simulations reproduce well the observations, without the updating procedure, it forecasted poorly the high-flow events. The EEKF-based forecast system improves the forecast of the high-flow events with respect to time and magnitude and yields higher scores for the probability of detection and false alarm rate associated with the exceedance of high-flow thresholds.
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Acknowledgments
The work described in this paper was sponsored by the Department of Civil and Environmental Engineering, Water Resources Research Institute of Sejong University in Seoul, Korea. Additional support was provided by the Technology Transfer Program of the Hydrologic Research Center in San Diego, Calif.UNSPECIFIEDUNSPECIFIED
References
Bae, D. H. (1997). “Development of stochastic real-time flood forecast system by storage function method.” J. Korea Wat. Resour. Assoc., 30(5), 449–457.
Bae, D. H., and Chung, I. M. (2000). “Development of stochastic-dynamic channel routing model by storage function method.” J. Korea Wat. Resour. Assoc., 33(3), 341–350.
Bae, D. H., Georgakakos, K. P., and Nanda, S. K. (1995). “Operational forecasting with real-time databases.” J. Hydraul. Eng., 121(1), 49–60.
Brady, N. C., and Weil, R. R. (2003). Elements of the nature and properties of soils, Prentice-Hall, New York.
Bras, R. L., and Rodriguez-Iturbe, I. (1985). Random functions and hydrology, Addison-Wesley, Reading, Mass., 559.
Brooks, R. H., and Corey, A. T. (1964). “Hydraulic properties of porous media.” Hydrology papers, Colorado State Univ., Fort Collins, Colo.
Clark, M. P., et al. (2008). “Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model.” Adv. Water Resour., 31(10), 1309–1324.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R. (1984). “A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils.” Water Resour. Res., 20(6), 682–690.
Evensen, G. (1994). “Sequential data assimilation with a nonlinear-geostrophic model using Monte Carlo methods for forecast error statistics.” J. Geophys. Res., 99, 10143–10162.
Georgakakos, K. P. (1986). “A generalized stochastic hydrometeorological model for flood and flash-flood forecasting, 1 Formulation and 2 Case studies.” Water Resour. Res., 22(13), 2083–2106.
Georgakakos, K. P. (2002). “Hydrometeorological models for real time rainfall and flow forecasting.” Mathematical models of small watershed hydrology and applications, V. P. Singh and D. K. Frevert, eds., Water Resources Publications LLC, Highlands Ranch, Colo., 593–655.
Georgakakos, K. P., Bae, D. H. Mullusky, M. G., and Georgakakos, A. P. (1995). “Hydrologic variability in Midwestern drainage basins: Diagnosis, prediction and control.” Preparing for global change: A Midwestern perspective, G. R. Carmichael, E. Folk, and J. L. Schnoor, eds., Chap. II-2, SPB Academic Publishing, Amsterdam, The Netherlands, 61–90.
Georgakakos, K. P., and Smith, D. E. (2001). “Soil moisture tendencies into the next century for the conterminous United States.” J. Geophys. Res., [Atmos.], 106(D21), 27367–27382.
Georgakakos, K. P., and Smith, G. F. (1990). “On improved operational hydrologic forecasting: Results from a WMO real-time forecasting experiment.” J. Hydrol., 114, 17–45.
Johns, C. J., and Mandel, J. (2008). “A two-stage ensemble Kalman filter for smooth data assimilation.” Environ. Ecol. Stat., 15, 101–110.
Lee, J. -K., and Kim, H. (2000). “Flood routing with fuzzy control.” Int. Conf. on Hydroscience and Engineering, ICHE 2000.
Lee, Y. H., and Singh, V. P. (1999). “Tank model using Kalman filter.” J. Hydrol. Eng., 4(4), 344–349.
Madsen, H., and Skotner, C. (2005). “Adaptive state updating in real-time river flow forecasting—A combined filtering and error forecasting procedure.” J. Hydrol., 308, 302–312.
Mohseni, O., and Stefan, H. G. (1998). “A monthly streamflow model.” Water Resour. Res., 34(5), 1287–1298.
Moradkhani, H., Sorooshian, S., Gupta, H. V., and Houser, P. R. (2005). “Dual state parameter estimation of hydrological models using ensemble Kalman filter.” Adv. Water Resour., 28, 135–147.
Park, Y. -I. (1997). “Improvement of the Han River flood forecasting and warning system.” Ministry of Construction and Transportation Rep., Seoul, Republic of Korea.
Puente, C. E., and Bras, R. L. (1987). “Application of nonlinear filtering in the real time forecasting of river flows.” Water Resour. Res., 23(4), 675–682.
Refsgaard, J. C. (1997). “Validation and intercomparison of different updating procedures for real-time forecasting.” Nord. Hydrol., 28, 65–84.
Seo, D. J., Koren, V., and Cajina, N. (2003). “Realtime variation assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting.” J. Hydrometeorol., 4(3), 627–641.
Shamir, E., Carpenter, T. M., Fickenscher, P., and Georgakakos, K. P. (2006). “Evaluation of the NWS operational hydrologic model for the American River Basin.” J. Hydrol. Eng., 11, 392–407.
Shamir, E., and Georgakakos, K. P. (2008). “Implementation of a system for flood forecasting in Korea based on the storage function method and distributed filtering techniques.” Hydrologic Research Center Technical Note No. 37, San Diego.
Vadigepalli, R., and Doyle, F. J. (2003). “Structural analysis of large-scale systems for distributed state estimation and control applications.” Control Eng. Pract., 11, 895–905.
Wang, C. -H., and Bai, Y. -L. (2008). “Algorithm for real-time correction of stream flow concentration based on Kalman filter.” J. Hydrol. Eng., 13(5), 290–296.
World Meteorological Organization (WMO). (1992). “Simulated real-time intercomparison of hydrological models.” Operational Hydrology Rep. No. 38, World Meteorological Organization, Geneva.
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© 2010 ASCE.
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Received: Jun 29, 2009
Accepted: May 15, 2010
Published online: Nov 15, 2010
Published in print: Dec 2010
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