Improving the accuracy of canal seepage detection through geospatial techniques

With climatic change, many western states in the United States are experiencing drought conditions. Numerous irrigation districts are losing significant amount of water from their canal systems due to leakage. Every year, on the average 2 million acres of prime cropland in the US is lost to soil erosion, waterlogging and salinity. Lining of canals could save enormous amount of water for irrigating crops but in present time due to soaring costs of construction and environmental mitigation, adopting such program on a large scale would be excessive. Conventional techniques of seepage detection are expensive, time consuming and labor intensive besides being not very accurate. Technological advancements in remote sensing have made it possible to investigate irrigation canals for seepage sites identification. In this research, band-9 in the [NIR] region and band-45 in the [TIR] region of an airborne MASTER data has been utilized to highlight anomalies along irrigation canal at Phoenix, Arizona. High resolution (1 to 4 meter pixels) satellite images provided by private companies for scientific research and made available by Google to the public on Google Earth is then successfully used to separate those anomalies into water activity sites, natural vegetation, and man-made structures and thereby greatly improving the seepage detection ability of airborne remote sensing. This innovative technique is much faster and cost effective as compared to conventional techniques and past airborne remote sensing techniques for verification of anomalies along irrigation canals. This technique also solves one of the long standing problems of discriminating false impression of seepage sites due to dense natural vegetation, terrain relief and low depressions of natural drainages from true water related activity sites.