An automated and rapid method for identifying dam wall locations and estimating reservoir yield over large areas. (June 2017)

• Record Type: Journal Article
• Authors: Petheram, C.; Gallant, J.; Read, A.
• Is Part Of: Environmental modelling & software. Volume 92(2017)
• Page Start: 189
• Page End: 201
• Publication Date: 2017-06
• Subjects: DamSite -- Water resource management -- Digital elevation model -- Yield -- Water storage -- Dam optimisation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.02.016
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Global demand for water, food and energy has seen the construction and planning of large dams continue at a steady pace in many parts of the world. However, the process of 'exhaustively' examining all potential dams sites within an area as part of an initial scoping study is still largely undertaken using manual methods. This paper describes DamSite, a series of novel algorithms that construct 'virtual' dam walls at every pixel along every channel within a catchment, including saddle dams where required by the terrain. By repetitively calculating dam and reservoir dimensions, reservoir yield and dam costs along a river network and for incrementally higher dam walls at each location it is possible to identify both optimal dam wall locations and optimal dam wall height at a given location. The DamSite model was tested in two catchments in northern Australia and accurately pin-pointed previously identified potential dam locations. Highlights: Model automatically identifies and evaluates all potential dam sites in a catchment. Calculates reservoir surface area, capacity and yield and dam dimensions and cost. At each site it calculates the height at which the yield to cost ratio is highest. Model output can be conveniently used to rank sites for more detailed investigation. The model accurately pin-pointed the more promising dam sites in testing.