Preprints
https://doi.org/10.5194/hess-2021-576
https://doi.org/10.5194/hess-2021-576
 
17 Jan 2022
17 Jan 2022
Status: this preprint has been withdrawn by the authors.

Stochastic Generation of Multisite Streamflow for Future Water Resources Vulnerability Assessments: Application over South Korea

Sukwang Ji1 and Kuk-Hyun Ahn2 Sukwang Ji and Kuk-Hyun Ahn
  • 1Graduate Research Assistant, Department of Civil and Environmental Engineering, Kongju National University, Cheon-an, South Korea
  • 2Assistant Professor, Department of Civil and Environmental Engineering, Kongju National University, Cheon-an, South Korea

Abstract. Stochastically generated streamflow time series are increasingly used for various water management and hazard assessment applications. The sequences provide realizations, preserving the temporal and spatial characteristics observed in the historic data. However, the simulations are further desirable to represent nonstationarity to account for past and future interannual oscillations. This study proposes an approach for stochastically generating future multisite daily streamflow to evaluate future water security conditioned on a national-wide relationship between annual daily maximum temperature and annual streamflow. The approach is attractive since it can avoid limitations and uncertainties introduced during realization and bias correction processes for climate model-based rainfall information. Alternatively, this approach relies on high projection skills of temperature variability. While the approach is developed by coupling annual and daily simulations, it includes (1) a wavelet decomposition-based autoregressive simulation to impose the signal of regional climate covariate; (2) clustering-based spatial pattern recognition and simulation; and (3) block bootstrapping and vine copula-based simulation for multisite streamflow simulation. The approach is applied as an example to multiple basins in South Korea. Results show that the generated sequences properly preserve many of the historical characteristics across basins. For future streamflow simulations, significant decreases in streamflow are projected, likely resulting in nontrivial impacts on regional water security. Finally, we conclude with a discussion of possible improvements to further refine the approach.

This preprint has been withdrawn.

Sukwang Ji and Kuk-Hyun Ahn

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-576', Anonymous Referee #1, 18 Jan 2022
  • RC2: 'Comment on hess-2021-576', Anonymous Referee #2, 02 Feb 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-576', Anonymous Referee #1, 18 Jan 2022
  • RC2: 'Comment on hess-2021-576', Anonymous Referee #2, 02 Feb 2022

Sukwang Ji and Kuk-Hyun Ahn

Sukwang Ji and Kuk-Hyun Ahn

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This preprint has been withdrawn.

Short summary
This study proposes an approach for generating future multisite daily streamflow conditioned on a relationship between annual maximum temperature and annual streamflow. The approach can avoid uncertainties during realization for climate model-based rainfall information. Results show that the generated sequences preserve many of the historical characteristics. For future streamflow simulations, significant decreases are projected, likely giving nontrivial impacts on regional water security.