Development of dam inflow simulation technique coupled with rainfall simulation and rainfall-runoff model

- Journal title : Journal of Korea Water Resources Association
- Volume 49, Issue 4, 2016, pp.315-325
- Publisher : Korea Water Resources Association
- DOI : 10.3741/JKWRA.2016.49.4.315

Title & Authors

Development of dam inflow simulation technique coupled with rainfall simulation and rainfall-runoff model

Kim, Tae-Jeong; So, Byung-Jin; Ryou, Min-Suk; Kwon, Hyun-Han;

Kim, Tae-Jeong; So, Byung-Jin; Ryou, Min-Suk; Kwon, Hyun-Han;

Abstract

Generally, a natural river discharge is highly regulated by the hydraulic structures, and the regulated flow is substantially different from natural inflow characteristics for the use of water resources planning. The natural inflow data are necessarily required for hydrologic analysis and water resources planning. This study aimed to develop an integrated model for more reliable simulation of daily dam inflow. First, a piecewise Kernel-Pareto distribution was used for rainfall simulation model, which can more effectively reproduce the low order moments (e.g. mean and median) as well as the extremes. Second, a Bayesian Markov Chain Monte Carlo scheme was applied for the SAC-SMA rainfall-runoff model that is able to quantitatively assess uncertainties associated with model parameters. It was confirmed that the proposed modeling scheme is capable of reproducing the underlying statistical properties of discharge, and can be further used to provide a set of plausible scenarios for water budget analysis in water resources planning.

Keywords

Discharge;Rainfall Simulation;Bayesian;Rainfall-Runoff Model;

Language

Korean

References

1.

Anderson, E.A. (1973). "National Weather Service river forecast system : Snow accumulation and ablation model." US Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service.

2.

Burnash, R.J.C., Ferral, R.L., and McGuire, R.A. (1973). "A generalized streamflow simulation system, conceptual modeling for digital computers." Joint Federal, State River Forecast Center, Sacramento, CA.

3.

Diffenbaugh, N.S., Swain, D.L., and Touma, D. (2015). "Anthropogenic warming has increased drought risk in California." Proceedings of the National Academy of Sciences, Vol. 112, No. 13, pp. 3931-3936.

4.

Fallah, B., and Cubasch, U. (2015). "A comparison of model simulations of Asian mega-droughts during the past millenium with proxy reconstructions." Climate of the Past, Vol. 11, No. 2, pp. 253-263.

5.

Gelman, R. (2004). "Cognitive development. Stevens." handbook of experimental psychology.

6.

Hall, P., Sheather, S.J., Jones, M.C., and Marron, J.S. (1991). "On optimal data-based bandwidth selection in kernel density estimation." Biometrika, Vol. 78, No. 2, pp. 263-269.

7.

Hastings, W.K. (1970). "Monte Carlo sampling methods using Markov chains and their applications." Biometrika, Vol. 57, No. 1, pp. 97-109.

8.

Hosking, J.R., and Wallis, J.R. (1987). "Parameter and quantile estimation for the generalized Pareto distribution." Technometrics, Vol. 29, No. 3, pp. 339-349.

9.

Kim, Y.O., Seo, Y.W., Lee, D.R., and Yoo, C.S. (2005). "Potential Effects of global warming on a water resources system in korea." Water International, Vol. 30, No. 3, pp. 400-405.

10.

Kim, T.J., Kwon, H.H., Lee, D.Y., and Yoon, S.K. (2014). "Development of Stochastic Downscaling Method for Rainfall Data Using GCM" Journal of Korea Water Resources Association, Vol. 47, No. 9, pp. 825-838.

11.

Kim. T.J., Jeong, G.I., Kim, K.Y., and Kwon, H.H. (2015). "A Study on Regionalization of Parameters for Sacramento Continuous Rainfall-Runoff Model Using Watershed Characteristics." Journal of Korea Water Resources Association, Vol. 48, No. 10, pp. 793-806.

12.

Kwon, H.H., Kim, J.G., and Park, S.H. (2013). "Derivation of Flood Frequency Curve with Uncertatiny of Rainfall and Rainfall-Runoff Model." Journal of Korea Water Resources Association, Vol. 46, No. 3, pp. 59-71.

13.

Kwon, H.H., Sivakumar, B., Moon, Y.I., and Kim, B.S. (2011). "Assessment of change in design flood frequency under climate change using a multivariate downscaling model and a precipitation-runoff model." Stochastic Environmental Research and Risk Assessment, Vol. 25, No. 4, pp. 567-581.

14.

Kwon, H.H., Brown, C., and Lall, U. (2008). "Climate informed flood frequency analysis and prediction in Montana using hierarchical Bayesian modeling." Geophysical Research Letters, Vol. 35, No. 5. DOI: 10.1029/2007GL032220.

15.

Larson, L., Singh, V.P., and Frevert, D. (2002). "National Weather Service River Forecast System (NWSRFS)." Mathematical models of small watershed hydrology and applications pp. 657-703.

16.

Lima, C.H., and Lall, U. (2010). "Spatial scaling in a changing climate: A hierarchical bayesian model for non-stationary multi-site annual maximum and monthly streamflow." Journal of Hydrology, Vol. 383, No, 3, pp. 307-318.

17.

Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., and Teller, E. (1953). "Equation of state calculations by fast computing machines." The journal of chemical physics, Vol. 21, No. 6, pp. 1087-1092.

18.

Rosenblatt, M. (1956). "Remark on some nonparametric estimates of a density function." The Annals of Mathematical Statistics. Vol. 27, No. 3, pp. 832-837.

19.

Ruppert, D., Sheather, S.J., and Wand, M.P. (1995). "An effective bandwidth selector for local least squares regression." Journal of the American Statistical Association, Vol. 90, No. 432, pp. 1257-1270.

20.

So, B.J., Kwon. H.H., Kim, D.K., and Lee, S.O. (2015). "Modeling of daily rainfall sequence and extremes based on a semiparametric Pareto tail approach at multiple locations." Journal of Hydrology, Vol. 529, pp. 1442-1540.

21.

So, B.J. Development of Multisite Daily Rainfall Simulation Model Using Piecewise Kernel-Pareto Continuous Distribution. Master's Thesis, Chonbuk National University, Jeonju, Jeollabuk, Republic of Korea.

22.

Russo, T.A., Devineni, N., and Lall, U. (2015). "Assessment of Agricultural Water Management in Punjab, India, Using Bayesian Methods." In Sustainability of Integrated Water Resources Management, Springer International Publishing, pp. 147-162.