Upstream flood pattern recognition based on downstream events

Bozorg‐Haddad, Omid; Hamedi, Farzan; Fallah-Mehdipour, Elahe; Loáiciga, Hugo A.

doi:10.1007/s10661-018-6686-3

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…In other words, with an output hydrograph in hand, the goal is to obtain the input hydrograph that generated it through reverse routing. Although less common than the conventional upstream-to-downstream routing, many authors, such as Das (2009), Badfar et al (2021), andHaddad et al (2018), have analyzed such a situation in past studies. However, Koussis et al (2012) warns that simply inverting the calculation between 𝐼 and 𝑂 does not constitute a well-defined problem according to the Muskingum method, and consequently, computational rounding errors or input data errors are expected to be quickly amplified and propagated between numerical iterations.…”

Section: Upstream Routingmentioning

confidence: 99%

Hydrological Modeling based on Weather Forecasting for Effective Water Resource Management in the Piracicaba River Basin, Brazil

Perez,

Tercini,

Bonnecarrère

2023

Preprint

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The occurrence of increasingly recent water scarcity phenomena, coupled with growing demands for water, culminates in complex rules for reservoir operation and compliance with minimum standards for the population. This work details the exploration of hydrological modeling techniques to support decision-making in water resource management, taking as a case study the Piracicaba River Basin, which are served by the Cantareira System and make significant contributions to the development of the state of São Paulo. By using a coupled rainfall-runoff and routing model, the necessary releases were estimated for two reservoirs that serve the region to meet the minimum outflows required at two downstream control sections, one in Atibaia and another in Valinhos. Based on seven-day weather forecast data, the operations were calculated over a two-year simulation period. The results obtained demonstrated compliance with the predicted demands, with a reduction of up to 72% compared to the actual discharged volumes during the same period. Despite inherent simplifications in the modeling process, it was concluded that the model provides accurate results based on precise techniques and can offer information that complements the sustainable management of water resources.

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Section: Upstream Routingmentioning

confidence: 99%

Hydrological Modeling based on Weather Forecasting for Effective Water Resource Management in the Piracicaba River Basin, Brazil

Perez,

Tercini,

Bonnecarrère

2023

Preprint

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“…The numerical solutions for flood routing equations were determined by applying 16 variants of the Runge-Kutta schemes [60][61][62]. The accuracy of these numerical analyses was assessed by comparing them to the analytical solutions provided by Paik (2008) and Nematollahi et al (2021) as benchmark solutions [55,59].…”

Section: Solutions Of Flood Routing Formulasmentioning

confidence: 99%

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Nematollahi

Bakhtiari

Talebbeydokhti

et al. 2022

Water

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Floods are a natural disaster of significant concern because of their considerable damages to people’s livelihood. To this extent, there is a critical need to enhance flood management techniques by establishing proper infrastructure, such as detention basins. Although intelligent models may be adopted for flood management by detention basins, there is a literature gap on the optimum design of such structures while facing flood risks. The presented study filled this research gap by introducing a methodology to obtain the optimum design of detention basins using a stochastic conflict resolution optimization model considering inflow hydrographs uncertainties. This optimization model was developed by minimizing the conditional value-at-risk (CvaR) of flood overtopping, downstream flood damage, and deficit risk of water demand, as well as the deviation of flood overtopping and downstream damage based on non-linear interval number programming (NINP), for four different outlets types via a robust optimization tool, namely the non-dominated sorting genetic algorithm-III (NSGA-III). Conflict resolution was performed using the graph model for conflict resolution (GMCR) technique, enhanced by fuzzy preferences, to comply with the authorities’ priorities. Results indicated that the proposed framework could effectively design optimum detention basins consistent with the regional and hydrological standards.

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“…This inversion process facilitates the realization of real-time operational adjustments for the upstream reservoir. To obtain the operation plan for the upper reaches of the river, Bozorg-Haddad et al [20] proposed two nonlinear Muskingum inversion simulation methods based on Euler equations and Runge-Kutta 4th order equations, and they verified them with historical data. The results showed that the second method had a better fitting effect.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Entire Process of an Interbasin Water Transfer Project for Flow Routing

Ye,

Wang,

Xie

et al. 2024

Water

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The flow routing process plays a crucial role in underpinning the execution of real-time operations within interbasin water transfer projects (IWTPs). However, the water transfer process within the supplying area is significantly affected by the time lag of water flow over extended distances, which results in a misalignment with the water demand process in the receiving area. Hence, there is an imperative need to investigate the flow routing patterns in long-distance water transfer processes. While MIKE11(2014 version) software and the Muskingum method are proficient in simulating flow routing within a water transfer network, they fall short in addressing issues arising from mixed free-surface-pressure flows in water transfer pipelines. This study enhanced the capabilities of the MIKE11(2014 version) software and the Muskingum method by introducing the Preissmann virtual narrow gap method to tackle the challenge of simulating mixed free-surface-pressure flows, a task unattainable by the model independently. This approach provides a clear elucidation of hydraulic characteristics within the water transfer network, encompassing flow rates and routing times. Furthermore, this is integrated with the Muskingum inverse method to compute the actual water demand process within the supplying area. This methodology is implemented in the context of the Han River to Wei River Diversion Project (HTWDP). The research findings reveal that the routing time for the Qinling water conveyance tunnel, under maximum design flow rate conditions, is 12.78 h, while for the south and north main lines, it stands at 15.85 and 20.15 h, respectively. These results underscore the significance of the time lag effect in long-distance water conveyance. It is noteworthy that the average errors between simulated and calculated values for the south and north main lines in the flow routing process are 0.45 m³/s and 0.51 m³/s, respectively. Compared to not using the Preissmann virtual narrow gap method, these errors are reduced by 59.82% and 70.35%, indicating a significant decrease in the discrepancy between simulated and calculated values through the adoption of the Preissmann virtual narrow gap method. This substantially improves the model’s fitting accuracy. Furthermore, the KGE indices for the flow routing model are all above 0.5, and the overall trend of the reverse flow routing process closely aligns with the simulated process. The relative errors for most time periods are constrained within a 5% range, demonstrating the reasonability and precision of the model.

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Upstream flood pattern recognition based on downstream events

Cited by 4 publications

References 15 publications

Hydrological Modeling based on Weather Forecasting for Effective Water Resource Management in the Piracicaba River Basin, Brazil

Hydrological Modeling based on Weather Forecasting for Effective Water Resource Management in the Piracicaba River Basin, Brazil

A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Simulation of the Entire Process of an Interbasin Water Transfer Project for Flow Routing

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