Diagnosing irrigation performance and water productivity through satellite remote sensing and secondary data in a large irrigation system of Pakistan

Irrigation policy makers and managers need information on the irrigation performance and productivity of water at various scales to devise appropriate water management strategies, in particular considering dwindling water availability, further threats from climate change, and continually rising population and food demand. In practice it is often difficult to access sufficient water supply and use data to determine crop water consumption and irrigation performance. Energy balance techniques using remote sensing data have been developed by various researchers over the last 20 years, and can be used as a tool to directly estimate actual evapotranspiration, i.e., water consumption. This study demonstrates how remote sensing-based estimates of water consumption and water stress combined with secondary agricultural production data can provide better estimates of irrigation performance, including water productivity, at a variety of scales than alternative options. A principle benefit of the described approach is that it allows identification of areas where agricultural performance is less than potential, thereby providing insights into where and how irrigation systems can be managed to improve overall performance and increase water productivity in a sustainable manner. To demonstrate the advantages, the approach was applied in Rechna Doab irrigation system of Pakistan's Punjab Province. Remote sensing-based indicators reflecting equity, adequacy, reliability and water productivity were estimated. Inter- and intra-irrigation subdivision level variability in irrigation performance, associated factors and improvement possibilities are discussed. (C) 2008 Elsevier B.V. All rights reserved.