Dam Siting: A Review

Abstract

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.

Analysis and Simulation of Improved Seismic Data using Adaptive Processing by National Data Centre Iraq

“…Machine learning features are crucial in enhancing the accuracy and effectiveness of various algorithms and models (Darweesh et al, 2021). By incorporating machine learning features, algorithms can better analyze and interpret complex data patterns, improving decision-making and problem-solving capabilities (Wang et al, 2021). These features can be derived from various sources, such as text mining tools, web indexing and search algorithms, social media inputs, and deep learning algorithms (Anjomshoaa & Curry, 2021).…”

Optimizing Mini Dam Placement for Sustainable Water Management in FUTA: A GIS-MCDA Approach

“…While there are pivotal criteria to be considered in selecting a dam site, the number of criteria for dam site selection cannot be universally uniform. The selection of criteria will depend on factors like literature review, the capacity and intended purpose of the dam, data availability, and the peculiar environmental and social conditions of the study area (Wang et al, 2021). Topographical condition, geological and geomorphological structure, foundation condition, physiographic unit, availability of construction materials, spillway size and location, climatic hazards, earthquake hazards, length and height of the dam, life of the dam, and runoff capacity of streams are the most utilized factors in dam site selection (Luís & Cabral, 2021;Al-Ruzouq et al, 2019a;Noori et al, 2019;Abushandi & Alatawi, 2015).…”

Proposing Optimal Locations for Runoff Harvesting and Water Management Structures in the Hami Qeshan Watershed, Iraq

“…For instance, political variables could lead to neglecting systematic and technical aspects of ideal dam site selection. Inappropriate dam siting might cause adverse effects on processes such as runoff, erosion, and sedimentation, resulting in subsidence (e.g., Mosul Dam, Iraq) [24], landslides (e.g., Vajont Dam, Italy) [25], and mudflows (e.g., Brumadinho Tailings Dam, Brazil) [26], which eventually threaten downstream residents and ecosystems [27,28]. Therefore, analyzing and selecting suitable locations to construct new dams based on detailed scientific techniques are substantial procedures to conserve and manage water resources safely and efficiently.…”