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Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

1
Center for Development Research (ZEF), University of Bonn, Genscherallee 3, 53113 Bonn, Germany
2
International Center for Agricultural Research in the Dry Areas (ICARDA), P.O. Box 2416 Cairo, Egypt
3
Environment and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon 440-746, Korea
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 972; https://doi.org/10.3390/rs10060972
Received: 10 April 2018 / Revised: 7 June 2018 / Accepted: 11 June 2018 / Published: 18 June 2018
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Abstract

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ETa was estimated through a surface energy balance system (SEBS) algorithm and the ETa estimates were validated using the advection aridity (AA) method with a R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May–September) (0.37 ± 0.06) and winter (October–April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during 2003–2013. The CV of the mean ETa, within sub-basins and provinces for the entire study period, has an equitable distribution of water from October–January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ETa (0.04–0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ETa (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future. View Full-Text
Keywords: data scarcity; actual evapotranspiration; surface energy balance; irrigation; performance evaluation; remote sensing data scarcity; actual evapotranspiration; surface energy balance; irrigation; performance evaluation; remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Akhtar, F.; Awan, U.K.; Tischbein, B.; Liaqat, U.W. Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan. Remote Sens. 2018, 10, 972.

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