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Spatial and temporal variability of water stress risk in the Kebir Rhumel Basin, Algeria

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  • Belkhiri, Lazhar

Abstract

This paper presents a methodological framework to conduct a water stress assessment of water resources through water stress index. A modified version of the water stress index was developed and applied for cereal grown in the Kebir Rhumel Basin, Algeria. The water stress index defined as Crop Stress Index (CSI) and derived by accumulating differences in water supply and demand over time to assess the maximum cumulative deficit. The forecasting crop water stress index for cereals was developed here as a way of understanding and hedging risk. The CSI was forecasted using the appropriate climate predictors as predictors in a non-parametric k-nearest neighbors (k-NN) approach that issues probabilistic forecasts. The accuracy of the CSI forecasts in the years 2002–2013 was judged based directional concordance and contingency metrics such as hit, miss and false alarm rate. The results showed that our forecasts were correct 8 out of 12 times, with three misses and just one false alarm. These results confirmed that this is a useful approach in investigating irrigation needs. Finally, it was found that this water stress index is a useful tool to estimate water storage and irrigation requirements in the interest of agricultural water resources.

Suggested Citation

  • Belkhiri, Lazhar, 2021. "Spatial and temporal variability of water stress risk in the Kebir Rhumel Basin, Algeria," Agricultural Water Management, Elsevier, vol. 253(C).
    • Handle: RePEc:eee:agiwat:v:253:y:2021:i:c:s037837742100202x
    DOI: 10.1016/j.agwat.2021.106937
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    References listed on IDEAS

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    1. Soojun Kim & Naresh Devineni & Upmanu Lall & Hung Soo Kim, 2018. "Sustainable Development of Water Resources: Spatio-Temporal Analysis of Water Stress in South Korea," Sustainability, MDPI, vol. 10(10), pages 1-17, October.
    2. Salim Djerbouai & Doudja Souag-Gamane, 2016. "Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Stochastic Models: Case of the Algerois Basin in North Algeria," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2445-2464, May.
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    Cited by:

    1. Sadeeka L. Jayasinghe & Dean T. Thomas & Jonathan P. Anderson & Chao Chen & Ben C. T. Macdonald, 2023. "Global Application of Regenerative Agriculture: A Review of Definitions and Assessment Approaches," Sustainability, MDPI, vol. 15(22), pages 1-49, November.

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