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An Integration of Statistics Temporal Methods to Track the Effect of Drought in a Shallow Mediterranean Lake

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  • Dimitrios Myronidis
  • Dimitrios Stathis
  • Konstantinos Ioannou
  • Dimitrios Fotakis

Abstract

During the last decades, a progressive decrease of water level in shallow Mediterranean lakes was recorded. This contribution tried to identify whether the rapid decrease of the Lake Doiran (N. Greece) water level was associated with drought phenomena. Drought characteristics over the study area were revealed by employing the Standardized Precipitation Index (SPI) in different time scales. Negative trends of the SPI drought index were recognized by using the Mann-Kendall non parametric test, which suggested that drought conditions were intensified through time. The impact of the intense drought phenomena to the lake’s water level became evident by employing the Pearson correlation coefficient. A year ahead forecast of future drought conditions was achieved by training a hybrid ARIMA/ANN model. The predicted results indicated that mild drought conditions should be anticipated in the future and the water level would further drop as well. Copyright Springer Science+Business Media Dordrecht 2012

Suggested Citation

  • Dimitrios Myronidis & Dimitrios Stathis & Konstantinos Ioannou & Dimitrios Fotakis, 2012. "An Integration of Statistics Temporal Methods to Track the Effect of Drought in a Shallow Mediterranean Lake," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(15), pages 4587-4605, December.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:15:p:4587-4605
    DOI: 10.1007/s11269-012-0169-z
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    4. Dimitrios Myronidis & Charalambos Papageorgiou & Stavros Theophanous, 2016. "Landslide susceptibility mapping based on landslide history and analytic hierarchy process (AHP)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 245-263, March.
    5. Papagera, A. & Ioannou, K. & Zaimes, G. & Iakovoglou, V. & Simeonidou, M., 2014. "Simulation and Prediction of Water Allocation Using Artificial Neural Networks and a Spatially Distributed Hydrological Model," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 6(4), pages 1-11, December.
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    7. Zhanqi Wang & Jun Yang & Xiangzheng Deng & Xi Lan, 2015. "Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China," Sustainability, MDPI, vol. 7(2), pages 1-18, February.

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