A novel simulation–optimization strategy for stochastic‐based designing of flood control dam: A case study of Jamishan dam

Sharafati, Ahmad; Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Zaher Mundher; Shahid, Shamsuddin

doi:10.1111/jfr3.12678

Cited by 12 publications

(8 citation statements)

References 39 publications

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“…In this case, fluvial flooding occurs when rivers flow overtop their banks or dams/dikes break. Dam overtopping is one of the main reasons for dam break [24]. Pluvial flooding occurs when rainfall volumes exceed the infiltration capacity and the drainage capacity and result in the inundation of urban areas.…”

Section: Causes and Impacts Of Extreme Floodsmentioning

confidence: 99%

Extreme Flood Disasters: Comprehensive Impact and Assessment

Qian

Wang

2022

Water

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Evaluating extreme flood disasters is a prerequisite for decision making in flood management. Existing extreme flood disaster assessments fail to either consider or evaluate comprehensive impacts from social, economic, and environmental aspects. This study first analyzes the causes of extreme flood disasters and subsequently the potential flood consequences in depth. On the basis of this comprehensive analysis, an extreme flood disaster indicator system is developed by taking into account social, economic, and environmental consequences. To assess the comprehensive impacts, we propose a refined social and economic impact evaluation method and a semi-quantitative environmental impact evaluation method, which are applied to Jingjiang Flood Diversion District (JFDD) located in the Yangtze River Basin, and analyze two extreme flood scenarios. The results show that almost all of the JFDD area is flooded with inundation areas of 901.36 km2 and 879.49 km2, respectively. The corresponding affected populations are 0.51 million and 0.5 million. The direct economic losses are 18.83 billion and 14.33 billion, respectively. Moreover, 5 potential pollutant sources and 11 protected areas are inundated under two scenarios. Extreme floods have relatively serious impacts on local ecology and the environment. The proposed methodology can provide effective support for decision makers.

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Section: Causes and Impacts Of Extreme Floodsmentioning

confidence: 99%

Extreme Flood Disasters: Comprehensive Impact and Assessment

Qian

Wang

2022

Water

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“…Obtaining the optimum parameters of the optimization algorithms is a major concern in the current study [ 44 ]. The Taguchi method [ 45 ] aims to select the optimal combination of parameters by calculating the signal-to-noise (SN) ratio through orthogonal tests, which has the advantages of fewer tests, reliable test results, good reproducibility, and simple analysis and calculation, and has been widely used.…”

Section: Improved Sparrow Search Algorithmmentioning

confidence: 99%

Research on SVR Water Quality Prediction Model Based on Improved Sparrow Search Algorithm

Zhang

et al. 2022

Computational Intelligence and Neuroscience

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Multiparameter water quality trend prediction technique is one of the important tools for water environment management and regulation. This study proposes a new water quality prediction model with better prediction performance, which is combined with improved sparrow search algorithm (ISSA) and support vector regression (SVR) machine. For the problems of low population diversity and easily falling into local optimum of sparrow search algorithm (SSA), ISSA is proposed to increase the initial population diversity by introducing Skew-Tent mapping and to help the algorithm jump out of local optimum by using the adaptive elimination mechanism. The optimal values of the penalty factor C and kernel function parameter g of the SVR model are selected using ISSA to make the model have better prediction accuracy and generalization performance. The performance of the ISSA-SVR water quality prediction model is compared with BP neural network, SVR model, and other hybrid models by conducting water quality prediction experiments with actual breeding-water quality data. The experimental results showed that the prediction accuracy of the ISSA-SVR model was significantly higher than that of other models, reaching 99.2%; the mean square deviation (MSE) was 0.013, which was 79.37% lower than that of the SVR model and 75% lower than that of SSA-SVR model, and the coefficient of determination R 2 was 0.98, which was 5.38% higher than that of the SVR model and 7.57% higher than that of the SSA-SVR model, indicating that the ISSA-SVR water quality prediction model has some engineering application value in the field of water body management.

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“…In Egypt, which suffers from frequent seasonal flooding and droughts, as well as water demand for agricultural irrigation, the Aswan Dam largely regulates the extremely uneven distribution of water resources and achieves spatial and temporal deployment of the multi-year runoff from the Nile [129]. The critical factors for the siting of flood control dams include the design height of the dam, which is limited by topographic conditions, hydrological characteristics, and technology, where the height of the dam directly affects the possibility of flooding and, indirectly, the possibility of dam failure [130]. Sumi [131] also pointed out that the relationship between dam height and storage capacity varies greatly between countries, due to differences in geographic conditions; for example, the ratio of storage capacity to dam height is particularly large for dams in the United States, as these dams are often built in gently sloping rivers and wide river valleys.…”

Section: The Influence Of Dam Use On Criteria Selectionmentioning

confidence: 99%

Dam Siting: A Review

Wang

Tian

Cao

2021

Water

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Dams can effectively regulate the spatial and temporal distribution of water resources, where the rationality of dam siting determines whether the role of dams can be effectively performed. This paper reviews the research literature on dam siting in the past 20 years, discusses the methods used for dam siting, focuses on the factors influencing dam siting, and assesses the impact of different dam functions on siting factors. The results show the following: (1) Existing siting methods can be categorized into three types—namely, GIS/RS-based siting, MCDM- and MCDM-GIS-based siting, and machine learning-based siting. GIS/RS emphasizes the ability to capture and analyze data, MCDM has the advantage of weighing the importance of the relationship between multiple factors, and machine learning methods have a strong ability to learn and process complex data. (2) Site selection factors vary greatly, depending on the function of the dam. For dams with irrigation and water supply as the main purpose, the site selection is more focused on the evaluation of water quality. For dams with power generation as the main purpose, the hydrological factors characterizing the power generation potential are the most important. For dams with flood control as the main purpose, the topography and geological conditions are more important. (3) The integration of different siting methods and the siting of new functional dams in the existing research is not sufficient. Future research should focus on the integration of different methods and disciplines, in order to explore the siting of new types of dams.

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A novel simulation–optimization strategy for stochastic‐based designing of flood control dam: A case study of Jamishan dam

Cited by 12 publications

References 39 publications

Extreme Flood Disasters: Comprehensive Impact and Assessment

Extreme Flood Disasters: Comprehensive Impact and Assessment

Research on SVR Water Quality Prediction Model Based on Improved Sparrow Search Algorithm

Dam Siting: A Review

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