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Revisiting telemetry in Pakistan’s Indus Basin Irrigation System

Author

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  • Bhatti, Muhammad Tousif
  • Anwar, Arif A.
  • Ali Shah, Muhammad Azeem

Abstract

The Indus Basin Irrigation System (IBIS) lacks a system for measuring canal inflows, storages, and outflows that is trusted by all parties, transparent, and accessible. An earlier attempt for telemetering flows in the IBIS did not deliver. There is now renewed interest in revisiting telemetry in Pakistan’s IBIS at both national and provincial scales. These investments are typically approached with an emphasis on hardware procurement contracts. This paper describes the experience from field installations of flow measurement instruments and communication technology to make the case that canal flows can be measured at high frequency and displayed remotely to the stakeholders with minimal loss of data and lag time between measurement and display. The authors advocate rolling out the telemetry system across IBIS as a data as a service (DaaS) contract rather than as a hardware procurement contract. This research addresses a key issue of how such a DaaS contract can assure data quality, which is often a concern with such contracts. The research findings inform future telemetry investment decisions in large-scale irrigation systems, particularly the IBIS.

Suggested Citation

  • Bhatti, Muhammad Tousif & Anwar, Arif A. & Ali Shah, Muhammad Azeem, 2019. "Revisiting telemetry in Pakistan’s Indus Basin Irrigation System," Papers published in Journals (Open Access), International Water Management Institute, pages 11(11):1-20.
  • Handle: RePEc:iwt:jounls:h049422
    DOI: 10.3390/w11112315
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    References listed on IDEAS

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    1. Stephan Kolassa & Roland Martin, 2011. "Percentage Errors Can Ruin Your Day (and Rolling the Dice Shows How)," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 23, pages 21-27, Fall.
    2. Flores, Benito E, 1986. "A pragmatic view of accuracy measurement in forecasting," Omega, Elsevier, vol. 14(2), pages 93-98.
    3. Akhmouch, Aziza & Correia, Francisco Nunes, 2016. "The 12 OECD principles on water governance – When science meets policy," Utilities Policy, Elsevier, vol. 43(PA), pages 14-20.
    4. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    5. Shah, M. Azeem Ali & Anwar, Arif A. & Bell, Andrew Reid & ul Haq, Zia, 2016. "Equity in a tertiary canal of the Indus Basin Irrigation System (IBIS)," Agricultural Water Management, Elsevier, vol. 178(C), pages 201-214.
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