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A framework for climate change assessment in Mediterranean data-sparse watersheds using remote sensing and ARIMA modeling

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Abstract

This study aims to propose a framework for assessing climate change in Mediterranean data-sparse contexts. For that purpose, the 309-km2 Lebanese Nahr Ibrahim watershed, extending over 3% of Lebanon’s surface, was chosen as a representative of the targeted settings. Generally, holistic climate change assessments encompass both climate trend analysis and future forecasting. According to the World Meteorological Organization, a continuous, homogenous, and uninterrupted climatic record for at least 30 years is needed to fulfill these tasks. Often, some Mediterranean watersheds lack such data and are hence characterized by climatic data scarcity. Such is the case of Lebanon where 30 years of wars have considerably disrupted the country’s climatic record. In an effort to overcome this state of data scarcity, remote sensing–derived drought indicators were used to determine the climate’s evolution during the last 28 years. For that purpose, several remote sensing indices were extracted from LANDSAT imageries for the period 1990–2018 at a 3-year interval, and were coupled to meteorological indicators. Forecasting was then performed using autoregressive integrated moving average (ARIMA) models. Meteorological indices showed increased variability of precipitations and aridity periods, while remote sensing indicators collectively revealed slight shifts towards increasing droughts. Projections using ARIMA models forecasted increases of 0.9 °C, 0.7 °C, and 0.8 °C for average, maximal, minimal temperatures, and an average 6 mm decrease of precipitations at the 95% confidence level for the year 2030. The presented approach can serve as a tool for proactive climate change mitigation or adaptation plans.

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Acknowledgments

This research is part of a PhD thesis funded by the National Council of Scientific Research-Lebanon (CNRS-L), Agence Universitaire de la Francophonie (AUF) Lebanon and the Lebanese University. Thanks are extended to the Lebanese Agriculture Institute (LARI)’s Dr. Ihab Jomaa for providing the authors with weather station data. Authors would also like to thank the editor and reviewers for their valuable comments in leveraging the scientific quality of work.

Funding

This research paper was funded by the National Council of Scientific Research-Lebanon (CNRS-L), Agence Universitaire de la Francophonie (AUF) Lebanon and the Lebanese University.

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  1. National Council for Scientific Research – Remote Sensing Center, P.O. Box: 11-8281, Blvrd. Sport City- Birr Hassan, Beirut, Lebanon

    Mario J. Al Sayah, Chadi Abdallah & Talal Darwich

  2. Centre de Recherches en Sciences et Ingénierie, Lebanese University Faculty of Engineering II, Roumieh, Lebanon

    Mario J. Al Sayah & Michel Khouri

  3. Centre d’Études et de Développement des Territoires et de l’Environnement, Université d’Orléans, Orléans, France

    Mario J. Al Sayah & Rachid Nedjai

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Al Sayah, M.J., Abdallah, C., Khouri, M. et al. A framework for climate change assessment in Mediterranean data-sparse watersheds using remote sensing and ARIMA modeling. Theor Appl Climatol 143, 639–658 (2021). https://doi.org/10.1007/s00704-020-03442-7

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