Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/37427
Title: Remote sensing and modelling based framework for valuing irrigation system efficiency and steering indicators of consumptive water use in an irrigated region
Author(s): Usman, Muhammad
Mahmood, Talha
Conrad, Christopher
Bodla, Habib Ullah
Issue Date: 2020
Type: Article
Language: English
Abstract: Water crises are becoming severe in recent times, further fueled by population increase and climate change. They result in complex and unsustainable water management. Spatial estimation of consumptive water use is vital for performance assessment of the irrigation system using Remote Sensing (RS). For this study, its estimation is done using the Soil Energy Balance Algorithm for Land (SEBAL) approach. Performance indicators including equity, adequacy, and reliability were worked out at various spatiotemporal scales. Moreover, optimization and sustainable use of water resources are not possible without knowing the factors mainly influencing consumptive water use of major crops. For that purpose, random forest regression modelling was employed using various sets of factors for site-specific, proximity, and cropping system. The results show that the system is underperforming both for Kharif (i.e., summer) and Rabi (i.e., winter) seasons. Performance indicators highlight poor water distribution in the system, a shortage of water supply, and unreliability. The results are relatively good for Rabi as compared to Kharif, with an overall poor situation for both seasons. Factors importance varies for different crops. Overall, distance from canal, road density, canal density, and farm approachability are the most important factors for explaining consumptive water use. Auditing of consumptive water use shows the potential for resource optimization through on-farm water management by the targeted approach. The results are based on the present situation without considering future changes in canal water supply and consumptive water use under climate change.
URI: https://opendata.uni-halle.de//handle/1981185920/37670
http://dx.doi.org/10.25673/37427
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Sponsor/Funder: Publikationsfonds MLU
Journal Title: Sustainability
Publisher: MDPI
Publisher Place: Basel
Volume: 12
Issue: 22
Original Publication: 10.3390/su12229535
Appears in Collections:Open Access Publikationen der MLU

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