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Quantifying and projection of the relative impacts of climate change and direct human activities on streamflow fluctuations

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  • A. B. Dariane

    (K. N. Toosi University of Technology)

  • E. Pouryafar

    (K. N. Toosi University of Technology)

Abstract

This paper addresses this issue of distinguishing the impact of climate change and human activities on streamflow using data from the Zarrinehrood River basin in Iran. The research was carried out in three main steps. First, considering the mean annual precipitation and potential evapotranspiration as the main climatic parameters, the impacts of climate change and human activities on streamflow were evaluated during the historical period. Then, an approach to naturalize the historical streamflow was proposed, based on agricultural land use changes. Finally, the future trends in temperature, precipitation, and streamflow were projected for 2015–2100 period under three climate change scenarios. The results clearly show that in the study area, human activities have more impacts on the streamflow variations compared to the climate change. It was found that the human activities and especially agricultural land developments caused 21% decrease on the annual streamflow during the historical period. Considering the naturalized and observed streamflow, the changes in the climatic parameters would cause a decrease in the streamflow by nearly 8 to 23% and 14 to 44% during 2015–2100 under the three scenarios. Moreover, when compared to the historical naturalized streamflow, the reduction in future observed flow will be in a warning rate of 28 to 53%. Finally, the share of climate change in future flow reduction was found to be between 29 and 44%, while for the human activities, it is between 56 and 16% emphasizing the importance of reconsidering the trend of current agricultural developments in the area.

Suggested Citation

  • A. B. Dariane & E. Pouryafar, 2021. "Quantifying and projection of the relative impacts of climate change and direct human activities on streamflow fluctuations," Climatic Change, Springer, vol. 165(1), pages 1-20, March.
  • Handle: RePEc:spr:climat:v:165:y:2021:i:1:d:10.1007_s10584-021-03060-w
    DOI: 10.1007/s10584-021-03060-w
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    References listed on IDEAS

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    1. Alireza Dariane & Farzane Karami, 2014. "Deriving Hedging Rules of Multi-Reservoir System by Online Evolving Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3651-3665, September.
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