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Spatially distributed assessment of channel seepage using geophysics and artificial intelligence

S. Khan; T. Rana; D. Dassanayake; A. Abbas; J. Blackwell; S. Akbar; H. F. Gabriel
Irrigation and Drainage · Vol. 58, Issue 3 · pp. 307-320 · 2009

Abstract

Estimation of channel seepage is an essential task in improving the management of earthen channel systems. The spatial distribution of seepage rates along the channels must be quantified to establish the economic and environmental merit of reducing conveyance losses. In Australia, due to recurring droughts and irrigation induced salinity concerns, there is much pressure to improve the efficiency of existing water resource use. Saving seepage losses from earthen channels has therefore become an important issue for several reasons including the loss of a valuable resource, maintaining channel assets and reducing accessions to groundwater. In this paper spatial distribution of channel seepage was quantified using artificial neural networks (ANNs). The electromagnetic imaging (EM31) data along with hydraulic conductivity, depth and salinity of groundwater were correlated with Idaho seepage meter measurements using the ANNs. It is estimated that over 42 million m 3 of water can be lost annually from 500 km of channel in the Murrumbidgee Irrigation Area. The distributed channel seepage analysis indicates that most significant seepage (>20 mm/day) occurs in less than 32% of the surveyed channel length; therefore it is important to target channel lining investments to the leakiest parts – “hotspots” – of the channel system. Copyright © 2008 John Wiley & Sons, Ltd.

Bibliographic Information

JournalIrrigation and Drainage
PublisherWiley
Publication Date2009-07-01
Publication Year2009
Volume58
Issue3
Pages307-320
Document TypeJournal Article
Print ISSN1531-0353
eISSN1531-0361
DOI10.1002/ird.415
SubjectWater Resources

Access Information

NARA Access Coverage2001-01-01~Current
Journal Homepagehttps://onlinelibrary.wiley.com/loi/15310361
Publisher PageOpen Publisher Page
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