Articles | Volume 22, issue 3
Hydrol. Earth Syst. Sci., 22, 2007–2021, 2018
https://doi.org/10.5194/hess-22-2007-2018
Hydrol. Earth Syst. Sci., 22, 2007–2021, 2018
https://doi.org/10.5194/hess-22-2007-2018

Research article 28 Mar 2018

Research article | 28 Mar 2018

Ensemble modeling of stochastic unsteady open-channel flow in terms of its time–space evolutionary probability distribution – Part 2: numerical application

Alain Dib and M. Levent Kavvas

Related authors

Ensemble modeling of stochastic unsteady open-channel flow in terms of its time–space evolutionary probability distribution – Part 1: theoretical development
Alain Dib and M. Levent Kavvas
Hydrol. Earth Syst. Sci., 22, 1993–2005, https://doi.org/10.5194/hess-22-1993-2018,https://doi.org/10.5194/hess-22-1993-2018, 2018
Short summary
Maximization of the precipitation from tropical cyclones over a target area through physically based storm transposition
Mathieu Mure-Ravaud, Alain Dib, M. Levent Kavvas, and Elena Yegorova
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-665,https://doi.org/10.5194/hess-2017-665, 2018
Preprint withdrawn
Short summary

Related subject area

Subject: Engineering Hydrology | Techniques and Approaches: Stochastic approaches
Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach
Manuela I. Brunner and Eric Gilleland
Hydrol. Earth Syst. Sci., 24, 3967–3982, https://doi.org/10.5194/hess-24-3967-2020,https://doi.org/10.5194/hess-24-3967-2020, 2020
Short summary
Objective functions for information-theoretical monitoring network design: what is optimal?
Hossein Foroozand and Steven V. Weijs
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-148,https://doi.org/10.5194/hess-2020-148, 2020
Revised manuscript accepted for HESS
Short summary
Numerical investigation on the power of parametric and nonparametric tests for trend detection in annual maximum series
Vincenzo Totaro, Andrea Gioia, and Vito Iacobellis
Hydrol. Earth Syst. Sci., 24, 473–488, https://doi.org/10.5194/hess-24-473-2020,https://doi.org/10.5194/hess-24-473-2020, 2020
Short summary
Spatially dependent flood probabilities to support the design of civil infrastructure systems
Phuong Dong Le, Michael Leonard, and Seth Westra
Hydrol. Earth Syst. Sci., 23, 4851–4867, https://doi.org/10.5194/hess-23-4851-2019,https://doi.org/10.5194/hess-23-4851-2019, 2019
Short summary
Technical note: Stochastic simulation of streamflow time series using phase randomization
Manuela I. Brunner, András Bárdossy, and Reinhard Furrer
Hydrol. Earth Syst. Sci., 23, 3175–3187, https://doi.org/10.5194/hess-23-3175-2019,https://doi.org/10.5194/hess-23-3175-2019, 2019
Short summary

Cited articles

Bellin, A., Salandin, P., and Rinaldo, A.: Simulation of dispersion in heterogeneous porous formations - statistics, 1st-order theories, convergence of computations, Water Resour. Res., 28, 2211–2227, https://doi.org/10.1029/92wr00578, 1992.
Cayar, M. and Kavvas, M. L.: Symmetry in nonlinear hydrologic dynamics under uncertainty: ensemble modeling of 2d Boussinesq equation for unsteady flow in heterogeneous aquifers, J. Hydrol. Eng., 14, 1173–1184, https://doi.org/10.1061/(Asce)He.1943-5584.0000112, 2009a.
Cayar, M. and Kavvas, M. L.: Ensemble average and ensemble variance behavior of unsteady, one-dimensional groundwater flow in unconfined, heterogeneous aquifers: an exact second-order model, Stoch. Environ. Res. Risk. A., 23, 947–956, https://doi.org/10.1007/s00477-008-0263-1, 2009b.
Chang, J. S. and Cooper, G.: A practical difference scheme for Fokker–Planck equations, J. Comput. Phys., 6, 1–16, https://doi.org/10.1016/0021-9991(70)90001-X, 1970.
Chaudhry, M. H.: Open-channel flow, in: 2nd Edn., Springer US, New York, 523 pp., 2008.
Short summary
A newly proposed method is applied to solve a stochastic unsteady open-channel flow system (with an uncertain roughness coefficient) in only one simulation. After comparing its results to those of the Monte Carlo simulations, the new method was found to adequately predict the temporal and spatial evolution of the probability density of the flow variables of the system. This revealed the effectiveness, strength, and time efficiency of this new method as compared to other popular approaches.