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Title: Airborne Remote Sensing for Detection of Irrigation Canal Leakage

Author
item Huang, Yanbo
item FIPPS, GUY - TEXAS A&M
item MAAS, STEPHAN - TEXAS A&M
item Fletcher, Reginald

Submitted to: International Commission on Irrigation and Drainage Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/4/2009
Publication Date: 6/25/2009
Citation: Huang, Y., Fipps, G., Maas, S., Fletcher, R.S. 2009. Airborne Remote Sensing for Detection of Irrigation Canal Leakage. International Commission on Irrigation and Drainage Journal. 59(5):524-534.

Interpretive Summary: Leaks and seepage are considered as major water losses in irrigation distribution canals. In order to locate leaks and seepage along irrigation distribution canals, a number of methods are available, such as measurement of pressure or flow rate change, acoustic signal analysis of running water, and radar detection of soil moisture content. However, these methods are costly, time-consuming, and labor-intensive and often do not precisely locate leaks, especially in the large command areas of irrigation districts. A quick and cost-effective method of multispectral imaging was developed for identifying irrigation canal locations likely to have leaks and/or seepage. An agricultural aircraft carrying a red spectral camera, a near infrared camera and a thermal spectral camera flew over twenty-four canal segments within eleven irrigation districts in the Lower Rio Grande Valley of Texas. Through image processing and field evaluation this method has been proven highly accurate in identifying canal sites of leaks and seepage.

Technical Abstract: Traditional field survey methods for detection of water leaks in irrigation canal systems are costly and time consuming. In this study, a rapid, cost-effective method was developed for identifying irrigation canal locations likely to have leaks and/or seepage. The method involves the use of a multispectral imager equipped with red, near infrared, and thermal sensors which is mounted on an aircraft and flown at low altitude to collect the images. A three-step process, image acquisition, image processing and field reconnaissance, was developed for processing the imagery and identification of locations likely to have leaks. The method was evaluated in the Lower Rio Grande Valley of Texas, USA. Images were collected of twenty-four selected canal segments within eleven irrigation districts in this region. Evaluation of the imagery indicated that 140 sites had possible canal leakage problems (point leak and/or seepage). A field site evaluation form was developed and used to document the type and severity of the leaks at 28 of the sites. Twenty-six sites were confirmed to have leaks, representing a success rate of 93%. The methods used in this study should have widespread application for detecting leaks and seepage in irrigation canals.