Open AccessDYNAMICS OF SEDIMENTATION AND USE OF GENETIC ALGORITHMS FOR ESTIMATING SEDIMENT YIELDS IN A RIVER: A CRITICAL REVIEW
Author(s) -
JAIYEOLA ADESOJI T.,
BWAPWA JOSEPH K.
Publication year - 2015
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/nrm.12064
Subject(s) - sediment , sedimentation , hydrology (agriculture) , hydraulic structure , hydraulic engineering , genetic algorithm , environmental science , computer science , geology , geotechnical engineering , algorithm , geomorphology , machine learning , physics , thermodynamics
The presence of sediments in a river is one of the major factors that characterize the river. The presence of sediment in any water resource is detrimental to its design purpose and it scratches any structure such as bridge foundations, conduit pipes, and turbine blades it comes into contact with while in motion and this leads to their eventual failure under load. The correct estimation of sediment yield transported by a river is indispensable in water resources engineering as sediment affects its hydraulic structure. The use of mathematical modeling algorithms such as genetic algorithms (GA) has proved to be very accurate in predicting sediment load in a river. The analogy behind GA is that genes in DNA functions are manipulated in specific ways through specific transcription operations. Therefore, applying the same logical operators to selected parameters relevant to sediment loads in rivers leads to mathematical prediction of the sediment load. This review article discusses the dynamic of sedimentation and analyses the use of GA as a hydrological model for accurately predicting sediment yield in a river, its potentials and shortcomings while recommending its modification.