Applying Monte Carlo and classification tree sensitivity analysis to the Zayandehrood River

Nakhaei, Nader; Etemad‐Shahidi, Amir

doi:10.2166/hydro.2011.094

Cited by 12 publications

(7 citation statements)

References 47 publications

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“…Discharge uncertainty relates to diversion system itself, i.e., the flow discharge ability uncertainty of the diversion tunnel [20,21]. Literatures showed that discharge uncertainty of tunnels, river bed and sewers can use triangular distribution to describe, and is suggested by the Chinese code [60,77]. Hence, this paper adopts the triangular distribution to describe the discharge uncertainty, which also received industrial recognition in China [74].…”

Section: Discharge Uncertaintymentioning

confidence: 99%

Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers

Song

Liu

et al. 2020

Energies

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Hydropower is an important renewable energy, and Construction Diversion Risk (CDR) should be highlighted and assessed during hydropower development. Since sediment-rich rivers are widely existing around the world and have great hydro-energy potential, assessing CDR for hydropower development on sediment-rich rivers in terms of engineering feasibility is of significance. This paper proposes a CDR assessment method for the sediment-rich hydropower development environment. The method is concise and practical, reflects diversion uncertainties and correlation, and mainly adopts the Gumbel–Hougaard Copula and the Monte Carlo Simulation. Through simulating flood evolution and sediment impact during diversion, the method can assess CDR basing on the cofferdam overtopping probability. Case results show that the proposed method can achieve CDR assessment on a sediment-rich river and highlights sediment impact on the diversion risk. Through results discussion, the risk feature of construction diversion on sediment-rich rivers is revealed, that sediment impact causes the dynamic and yearly-risen CDR. Hence, our conclusions are: (1) the proposed method is feasible, effective and has industrial potential, and (2) a diversion scheme on sediment-rich rivers is suggested that adopts the design with high or yearly-heightening cofferdams, based on the advanced CDR assessment to cope with the risk features of sediment-rich diversion environments.

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Section: Discharge Uncertaintymentioning

confidence: 99%

Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers

Song

Liu

et al. 2020

Energies

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“…Therefore, even for the same tunnel, the discharge volume varies under different diversion conditions. As the discharge coefficient of diversion tunnels has great relevance to the value of hydraulic roughness, which is undetermined [29,33,34], the uncertainty of diversion discharge can be correlated to the roughness variability, and this roughness variability appears in the triangular distribution [29,33].…”

Section: Diversion System Discharge Uncertaintymentioning

confidence: 99%

Assessment of Sediment Impact on the Risk of River Diversion during Dam Construction: A Simulation-Based Project Study on the Jing River, China

Song

Liu

et al. 2018

Water

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Dams are vital for water resource utilization, and river diversion is key for dam construction safety. As sandy river basins are important exploitation areas that have special diversion features, the impact of sediment on the risk of river diversion during dam construction should be assessed. Diversion uncertainty is the origin of diversion risk, and sediment uncertainty changes the storage and discharge patterns of the diversion system. Two Gumbel-Hougaard (GH) copula functions are adopted to couple the random variables of flood and sediment, so that the sediment impacts on diversion storage and discharge can be obtained by the sampling of flood peaks. Based on variable coupling and sediment amendment, a method of Monte Carlo simulation (MCS) with a water balance calculation can quantitatively assess the risk of sandy river diversion, by evaluating the probability of upstream cofferdam overtopping. By introducing one diversion project on the Jing River in China with a clear water contrast, the risk values of dam construction diversion with or without sediment impacts can be obtained. Results show that the MCS method is feasible for diversion risk assessment; sediment has a negative impact on the risk of river diversion during dam construction, and this degradation effect is more evident for high-assurance diversion schemes.

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“…Currently, water quality is a serious issue, especially for drinking water source areas. Rivers suffering from the effects of anthropogenic activities because of contained pollut-ants would easily decrease their self-purification capacities (Nakhaei and Etemad-Shahidi, 2012). Because a river has a unique self-purification capacity, it is necessary to simulate the pollutant loads from different sources that rivers could withstand.…”

Section: Introductionmentioning

confidence: 99%

“…Also, a number of parameters in certain complex simulation have seldom been report in the literature, meaning that there is little research to compare their accuracies (Melching and Yoon, 1996;Fan et al, 2009). The QUAL series models are useful simulation tools that have been applied extensively in water quality assessment, even in cases where there are not sufficient data for the establishment complex 2D or 3D models (Nakhaei and Etemad-Shahidi, 2012). For example, QUAL2E is a typical computer-aided model among the QUAL series models, the QUAL2Kw model is an the expanded version by Pelletier et al (2006) based on QUAL2K, and it is the latest version of QUAL2E.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, it is generally conluded that the model can form the basis of water quality management (Kannel et al, 2007b;Oliveira et al, 2012). In many studies, DO, BOD, nitrogen, phosphorus and COD have been used as typical indicators to model water quality variations of streams and rivers (Kannel et al, 2007a;Camargo et al, 2010;Nakhaei and Etemad-Shahidi, 2012). The latest QUAL2Kw (i.e., QUAL2Kw version 6) was integrated with non-steady, nonuniform flow using a kinematic wave flow routing approach and has the option to use repeating diel conditions, which is similar to the early version but with either steady or non-steady flows (Department of Ecology of the State of Washington, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Water Quality Risk Assessment for the Laoguanhe River of China Using a Stochastic Simulation Method

Hu¹,

Sun²,

Li³

et al. 2018

J ENV INFORM

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The Laoguanhe River is a major tributary of the Danjiang River, which is the source water for the Danjiangkou Reservoir (i.e., the source reservoir for the middle route of the South-to-North Water Diversion Project in China). This study was intended to provide scientific decision support to help manage the water environment in the Laoguanhe River and maintain high water quality levels for the water diversion project. Risk assessment based on water quality simulation was undertaken in this research. The QUAL2Kw model was used to improve the simulations of the water quality in the Laoguanhe River under sparse data conditions. Latin hypercube sampling (LHS) was used to improve flow inputs for QUAL2Kw. The model was used to calculate water quality risks under several scenarios based on a Markov stochastic process to reflect uncertainties. The simulation results indicated that water quality of the downstream sections of the Laoguanhe River could meet the basic requirements for exporting water to the Danjiangkou Reservoir.

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Applying Monte Carlo and classification tree sensitivity analysis to the Zayandehrood River

Cited by 12 publications

References 47 publications

Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers

Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers

Assessment of Sediment Impact on the Risk of River Diversion during Dam Construction: A Simulation-Based Project Study on the Jing River, China

Water Quality Risk Assessment for the Laoguanhe River of China Using a Stochastic Simulation Method

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