KSCE Journal of Civil Engineering

, Volume 16, Issue 6, pp 1085–1092 | Cite as

Uncertainty of areal average rainfall and its effect on runoff simulation: A case study for the Chungju Dam Basin, Korea

Research Paper Water Engineering

Abstract

This study investigated the relationship between the errors involved in the areal average rainfall estimation and the runoff simulation (hereafter, rainfall and runoff errors). The error statistics of the observed areal average rainfall were estimated and used for the generation of input data for the runoff simulation. The Clark instantaneous unit hydrograph was used for this runoff simulation. The runoff model parameters were estimated using several sets of rainfall-runoff data observed, whose statistics were then used for the sensitive analysis of the model simulation on the parameter sets. The rainfall error in this study was defined as the relative difference between the observed and generated areal average rainfall. On the other hand, the runoff error was designed to consider the runoff volume, peak flow and peak time, respectively. This study was applied to the Chugnju Dam Basin, Korea. The results obtained are as follows: (1) The variation of model parameters estimated in this study were about 30% of their means. Also, the effect of this error in model parameter estimation on runoff simulation was found to be maximum 15% of the peak flow. (2) The estimation error of areal average rainfall was found roughly proportional to the areal average rainfall itself. Both the rainfall and runoff errors were found to have no obvious biases. However, the variance of the peak flow error was found to be significantly higher. (3) The relationship between rainfall error and runoff volume error was roughly one to one, however, the rainfall error has become amplified by more than 50 % and transferred to the peak flow error.

Keywords

rainfall-runoff analysis rainfall error relationship between rainfall and runoff errors 

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References

  1. Arnaud, P., Bouvier, C., Cisneros, L., and Dominguez, R. (2002). “Influence of rainfall spatial variability of flood prediction.” Journal of Hydrology, Vol. 260, Nos. 1–4, pp. 216–230.CrossRefGoogle Scholar
  2. Bras, R. (1990). Hydrology, an introduction to hydrologic science, Addison-Wesley, pp. 154–155.Google Scholar
  3. Boughton, W. (2006). “Calibration of a daily rainfall-runoff model with poor quality data.” Environmental Modelling & Software, Vol. 21, No. 8, pp. 1114–1128.CrossRefGoogle Scholar
  4. Boughton, W. C. (2007). “Effect of data length on rainfall-runoff modeling.” Environmental Modelling & Software, Vol. 22, No. 3, pp. 406–413.CrossRefGoogle Scholar
  5. Brocca, L., Melone, F., and Moramarco, T. (2008). “On the estimation of antecedent wetness conditions in rainfall-runoff modeling.” Hydrol. Process., Vol. 22, No. 5, pp. 629–642.CrossRefGoogle Scholar
  6. Chaubey, I., Haan, C. T., Grunwald, S., and Salisbury, J. M. (1999). “Uncertainty in the model parameters due to spatial variability of rainfall.” Journal of Hydrology, Vol. 220, Nos. 1–2, pp. 48–61.CrossRefGoogle Scholar
  7. Clark, C. O. (1945). “Storage and the unit hydrograph.” Transactions of the American Society of Civil Engineers, Vol. 110, pp. 1419–1446.Google Scholar
  8. Ewen, J., O’Donnell, G., Burton, A., and O’Connel, E. (2006). “Errors and uncertainty in physically-based rainfall-runoff modeling of catchment change effects.” Journal of Hydrology, Vol. 330, Nos. 3–4, pp. 641–650.CrossRefGoogle Scholar
  9. Fontaine, T. (1995). “Rainfall-runoff model accuracy for an extreme flood.” Journal of Hydraulic Engineering, ASCE, Vol. 121, No. 4, pp. 365–374.CrossRefGoogle Scholar
  10. Ford, D. T., Morris, E. C., and Feldman, A. D. (1980). Corps of engineers’ experience with automatic calibration of precipitationrunoff model: Water and related land resource systems, Y. Haimes and J. Kindler (eds.), New York, Pergamon Press, New York, pp. 467–476.Google Scholar
  11. Hydrologic Engineering Center (HEC). (2000). HEC-HMS: Hydrologic modeling system, technical reference manual, U.S. Army Corps of Engineers, Davis, CA, pp. 60–63.Google Scholar
  12. Jeong, K. H., Hur, S. O., Sonn, Y. K., Park, C. W., Ha, S. K., and Kim, N. (2007). “Comparison of hydrologic soil groups with classification method.” 2007 Conference of Korea Water Resources Association, pp. 97–105.Google Scholar
  13. Korea Water Resources Corporation (KOWACO) (2006). Development of the dam safety management system.Google Scholar
  14. Krajewski, W. F., Lakshami, V., Georgakakos, K. P., and Jain, S. C. (1991). “A Monte Carlo study of rainfall sampling effect on a distributed catchment model.” Water Resources Research, Vol. 27, No. 1, pp. 119–128.CrossRefGoogle Scholar
  15. Kuczera, G., Kavetski, D., Franks, S., and Thyer, M. (2006). “Toward a Bayesian total error analysis of conceptual rainfall-runoff models: Characterizing model error using storm-dependent parameters.” Journal of Hydrology, Vol. 331, Nos. 1–2, pp. 161–177.CrossRefGoogle Scholar
  16. Loague, K M. and Freeze, R. A. (1985). “A comparison of rainfallrunoff modeling techniques on small upland catchments.” Water Resources Research, Vol. 21, No. 2, pp. 229–248.CrossRefGoogle Scholar
  17. McMillan, H., J. Freer, F. Pappenberger, T., and Krueger, M. C. (2010). “Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions.” Hydrological Processes, Vol. 24, No. 10, pp. 1270–128Google Scholar
  18. Michaud, J. D. and Sorooshian, S. (1994). “Effect of rainfall sampling errors on simulations of desert flash floods.” Water Resources Research, Vol. 30, No. 10, pp. 2765–2775.CrossRefGoogle Scholar
  19. Ministry of Construction and Transportation (MOCT) (2004). Survey report of the Han river basin.Google Scholar
  20. Montanari, A. (2007). “What do we mean by ‘uncertainty’? the need for a consistent wording about uncertainty assessment in hydrology.” Hydrological Processes, Vol. 21, No. 6, pp. 841–845.CrossRefGoogle Scholar
  21. Nash, J. E. (1957). “The form of the instantaneous unit hydrograph.” International Association of Hydrological Sciences Publication, Vol. 45, No. 3, pp. 114–121.Google Scholar
  22. Oudin, L., Perrin, C., Mathevet, T., Andreassian, V., and Michel, C. (2006). “Impact of biased and randomly corrupted inputs on the efficiency and the parameters of watershed models.” Journal of Hydrology, Vol. 320, Nos. 1–2, pp. 62–83.CrossRefGoogle Scholar
  23. Paturel, J. E., Servat, E., and Vassiliadis, S. A. (1995). “Sensitivity of conceptual rainfall-runoff algorithms to errors in input data — Case of the GR2M model.” Journal of Hydrology, Vol. 168, Nos. 1—4, pp. 111–125.CrossRefGoogle Scholar
  24. Sabol, G. V. (1988). “Clark unit hydrograph and R-parameter estimation.” Journal of Hydraulic Engineering, Vol. 114, No. 1, pp. 103–111.CrossRefGoogle Scholar
  25. Singh, V. P. (1977). “Sensitivity of some runoff models to errors in rainfall excess.” Journal of Hydrology, Vol. 33, Nos. 3–4, pp. 301–318.CrossRefGoogle Scholar
  26. Singh, V. P. and Woolhiser, D. A. (1976). “Sensitivity of linear and nonlinear surface runoff models to input errors.” Journal of Hydrology, Vol. 29, Nos. 3–4, pp. 243–249.CrossRefGoogle Scholar
  27. Troutman, B. M. (1983). “Runoff prediction errors and bias in parameter estimation induced by spatial variability of precipitation.” Water Resources Research, Vol. 19, No. 3, pp. 791–810.CrossRefGoogle Scholar
  28. Yoo, C. and Jung, K. (2001). “Areal average rainfall and its estimation error.” Journal of Korea Water Resources Association, Vol. 34, No. 4, pp. 317–326.Google Scholar
  29. Yoo, C., Kim, J., and Kim, N. (2002). “Estimation errors of area-average rainfall considering the spatial correlation.” Journal of the Korean Society of Civil Engineers, Vol. 22, No. 5-B, pp. 649–656.Google Scholar
  30. Yoo, C. and Shin, J. (2010). “Decision of storage coefficient and concentration time of observed basin using Nash model’s structure.” Journal of Korea Water Resources Association, Vol. 43, No. 6, pp. 559–569.CrossRefGoogle Scholar

Copyright information

© Korean Society of Civil Engineers and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Dept. of Civil and Environmental EngineeringKorea UniversitySeoulKorea

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