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Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece

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Abstract

Efficient rainfall/runoff data modeling necessitates field data availability. Remote and rough terrain areas restrict data collection that leads to less reliable simulated models. Consequently, complete geographic databases are the quest to conduct over the catchment under investigation. The hydrologic model developed for this research based on different return periods (2, 5, 10, 25, 50, 100, and 200 years) gave significant discharge outputs. It was found that a basin average precipitation having a return period of 5 years yields a peak discharge of 1032.7 m3/s with the time of peak occurring 23.25 h after the event has started. It results in a volume of 79.9 × 106 m3. A storm event having a return period of 200 years, with basin average rainfall approximately two times more intense than the above yields an enormous discharge of 2191.1 m3/s and an accumulative volume of water of 158.8 × 106 m3. Accordingly, the catchment cannot accommodate such significant volumes of water and flooding becomes unavoidable. Therefore, hydrological, and hydraulic models can support decision-makers in correspondence to the catchment management problems for the sustainable and economic development of the wider area, by providing systematic and consistent information.

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Acknowledgements

This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under Grant No. (G-71-155-1441). The authors, therefore, acknowledge with thanks, DSR technical and financial support.

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Authors and Affiliations

  1. Department of Hydrology and Water Resources Management, Faculty of Meteorology, Environment & Arid Land Agriculture, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Mohamed Elhag

  2. Department of Applied Geosciences, Faculty of Science, German University of Technology in Oman, Muscat, 1816, Oman

    Mohamed Elhag

  3. Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Science (CAS), Beijing, 100094, China

    Mohamed Elhag

  4. Department of Freshwater Resources and Management, Faculty of Aquatic Sciences, Istanbul University, Istanbul, 34470, Turkey

    Nese Yilmaz

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  1. Mohamed Elhag
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Correspondence to Mohamed Elhag.

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Elhag, M., Yilmaz, N. Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece. Environ Earth Sci 80, 35 (2021). https://doi.org/10.1007/s12665-020-09289-5

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