IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
Log On
About IAHRDirectoryCommitteesMy IAHRNews & JournalseLibraryeShopEventsJoin IAHRWorld CongressDonate
spacer.gif
spacer.gif eLibrary
spacer.gif eLibrary
You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 1: Extremes and Variability : Application of the monte carlo technique to riverine sand and gravel extraction analysing risk in ...
Application of the monte carlo technique to riverine sand and gravel extraction analysing risk in complex environmental systems
Author :
River Management challenges arise due to a high level of uncertainty associated with fluvial systems, which respond to random and highly variable processes, in complex and unpredictable ways. This problem is compounded by the lack of understanding of how fluvial and landscape erosion processes interact, and vary in space and time in a catchment. The probability of different outcomes occurring for river management problems can be addressed using a Monte Carlo framework, supported by expert knowledge of fluvial hydraulics, sediment transport and geomorphology. In this example, the Monte Carlo method was used to assess the sustainability and environmental risks associated with a proposed riverine sand and gravel extraction for three different scenarios, within the context of the overall catchment sediment budget. Results demonstrated how the replenishment of excavated river bed material would occur within given time frames with some confidence, and the increasing environmental risk with resulting from additional extraction. Finally, sensitivity analyses showed that a sound understanding of a small number of key variables and parameters could significantly improve confidence in the model prediction.
File Size : 262,706 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 1: Extremes and Variability
Date Published : 01/07/2011
Download Now