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Lake Urmia crisis and restoration plan: Planning without appropriate data and model is gambling

Danesh Yazdi, M ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jhydrol.2019.06.068
  3. Publisher: Elsevier B.V , 2019
  4. Abstract:
  5. Losing eight meters of water level over a 20-year period from 1996 to 2016 marked the Lake Urmia (LU) as one of the regional environmental crises. This condition has threatened biota life, intensified desertification around the lake, and raised social concerns by adversely impacting the inhabitants’ health and economy. In 2013, the Urmia Lake Restoration National Committee (ULRNC) started implementing certain management practices to stop the drying trend of LU, resulted in the cease of water level drop and stabilization of LU condition in 2016. Nevertheless, the restoration actions have not yet raised the lake to the water level as planned by the roadmap. This paper aims to describe and to assess the LU restoration plans by underscoring the ULRNC achievements, challenges, and shortcomings. In particular, we discuss how the value of data and data-aided modeling has been underestimated by the LU restoration programs, leading to still existing puzzles about the lake interaction with the involving physical processes governing its dynamics. We show how the LU restoration timetable has not fulfilled the planned milestones as evidenced by the inability to capture the anticipated lake water levels, which is partly attributed to the lack of field data and dynamic modeling that could predict the lake response in a more reliable and conservative manner. The current restoration plans should also be revisited to ensure that any practice with the aim of reducing water consumption in the basin is not only environmentally sustainable but also feasible from the socioeconomic perspective. The insights provided by this paper attempt to underscore the value of field data collection for establishing a reliable conceptual model, and for executing pre- and post-monitoring of the lake so that the success or failure of the restoration actions taken by the policymakers can be appropriately evaluated. © 2019 Elsevier B.V
  6. Keywords:
  7. Data-driven modeling ; Environmental sustainability ; Restoration ; Socioeconomic ; Economics ; Image reconstruction ; Sustainable development ; Water levels ; Data-driven model ; Environmental crisis ; Field data collection ; Management practices ; Restoration programs ; Lakes ; Data assimilation ; Desertification ; Environmental planning ; Environmental restoration ; Lake water ; Model validation ; Sustainability ; Water level ; Water quality ; Iran ; Lake Urmia
  8. Source: Journal of Hydrology ; Volume 576 , 2019 , Pages 639-651 ; 00221694 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0022169419306158