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Mitigating the adverse impacts of climate change on river water quality through adaptation strategies: A Case Study of the Ardak Catchment, Northeast Iran

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A Correction to this article was published on 17 August 2024

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Abstract

This study investigates the potential impacts of future climate change on river water quality in Ardak Watershed, Northeast Iran, and proposes adaptation strategies to mitigate adverse effects. The SWAT model is calibrated and verified by Monthly water quality sampling and flow measurements. The premium SWAT-CUP model was utilized for sensitivity analysis and parameter adjustment to simulate runoff, sediment, nitrate, mineral phosphorus, and dissolved oxygen. Future catchment temperature and precipitation were projected using CMhyd statistical downscaling by incorporating four CMIP6 models under SSP scenarios for the near (2025–2049), intermediate (2050–2074), and far (2075–2099) future. The Mianmorgh River experienced increased levels of various pollutants in winter, summer, and autumn but decreased in spring for future periods. In the Abghad River, pollutant levels are expected to increase from late autumn to late winter and decrease in other months. Nitrate increased from the late summer to late winter, then decreased throughout the year. Three adaptation strategies were proposed: reducing rural swage pollutants, creating pasture on 5% of unvegetated land, and combining both. The SWAT model showed responsiveness to the mix scenario, with average reductions of 4—4.5% for suspended solids, 23—16% for inorganic phosphorus, and 16—20% for nitrate for the first strategy. The results revealed that climate change can significantly affect water quality, but its adverse effects can be mitigated with suitable actions. Combined adaptation strategies effectively reduced suspended solids and mineral phosphorus and removed pollutants. Therefore, implementing a combination of effective strategies is more beneficial than individual approaches.

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Data Availability

Part of the data, including hydrological, meteorological, and spatial data confirming the results of this study, is available on request from the corresponding author.

Change history

Notes

  1. https://data.apps.fao.org

  2. vertex.daac.asf.alaska.edu

  3. Swat Parameter Estimator

  4. Sequential Uncertainty Fitting 2

  5. Nash–Sutcliffe Efficiency Index

  6. coefficient of determination

  7. Normalized root mean square error

  8. Standard Wastewater Discharge

  9. Landuse

  10. Total Suspended Solids

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Acknowledgements

The authors extend their utmost gratitude to Prof. Karim Abbaspour for all his kind support.

Funding

The authors got no support from any organisations for their submitted work. No funding or other aid was received for this study's conduct or the manuscript's preparation.

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Authors and Affiliations

Authors

Contributions

“Ali Reza Massah Bavani contributed to the study conception and design. Morteza Nikakhtar performed material preparation, data collection, and analysis. Seyedeh Hoda Rahmati and Iman Babaeian developed the methodology and evaluated the results. Morteza Nikakhtar wrote the first draft of the manuscript, expanded, edited, and confirmed by Ali Reza Massah Bavani. Seyedeh Hoda Rahmati, Ali Reza Massah Bavani, and Iman Babaeian commented on previous manuscript versions. The final content was read and approved by all contributing authors.”

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Correspondence to Seyedeh Hoda Rahmati.

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The original online version of this article was revised: The affiliation details for Morteza Nikakhtar were incorrectly given as ‘Department of Environmental Engineering‑Water Resources, College of Energy and Environment, Branch of Science and Research, Islamic Azad University, Tehran, Iran’ but should have been ‘Department of Environmental Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran’.

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Nikakhtar, M., Rahmati, S.H., Massah Bavani, A.R. et al. Mitigating the adverse impacts of climate change on river water quality through adaptation strategies: A Case Study of the Ardak Catchment, Northeast Iran. Theor Appl Climatol 155, 9131–9147 (2024). https://doi.org/10.1007/s00704-024-05057-8

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