Mersin’in Farklı Kuraklık İndeksleri Aracılığıyla Kuraklık Tehdidinin Araştırılması
Year 2024,
, 71 - 84, 27.02.2024
Mehmet Özgür Çelik
,
Murat Yakar
Abstract
Dünya genelinde küresel iklim değişikliğinin etkileri giderek artmaktadır. Akdeniz havzasında bulunan yerler için küresel iklim değişikliğinin temel olumsuz etkileri arasında kuraklık gelmektedir. Çalışma alanı Türkiye’nin güneyinde Akdeniz havzasında yer alan Mersin’dir ve kuraklık tehdidi altındadır. Bu yüzden, çalışma alanın kuraklık analizi farklı kuraklık indeksleri kullanılarak gerçekleştirilmiştir. Bunun için iklimsel verileri kullanan Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Standardized Precipitation Index (SPI) ve Standardized Precipitation-Evapotranspiration Index (SPEI) standart kuraklık indeksleri tercih edilmiştir. Bu indeksler kuraklık analizinde standart kabul edilmektedir. Söz konusu indeksler hesaplanmış ve grafikler oluşturulmuştur. Buna göre, Mersin’in kuraklık analizi gerçekleştirilmiş ve kuraklık riski altında olduğu saptanmıştır. Ayrıca, gelecek yıllardaki olası durumu tahmin edilmiştir.
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Investigation of Mersin’s Drought-Threat through Different Drought Indexes
Year 2024,
, 71 - 84, 27.02.2024
Mehmet Özgür Çelik
,
Murat Yakar
Abstract
Global climate change is having a growing impact all around the world. Drought is one of the most destructive effects of global climate change in the Mediterranean basin. The study area is Mersin, which is located in southern Türkiye and is threatened by drought. Therefore, a drought analysis of the research area was conducted. Palmer Drought Severity Index (PDSI), Palmer Hydrological Drought Index (PHDI), Standardized Precipitation Index (SPI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were chosen as drought indices that employ climatic data. The indices are considered standard indices in drought analysis. The indices were calculated, and graphs were created. As a result, it was concluded that Mersin is at risk of drought. The prospective condition in the future was also forecasted
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https://doi.org/10.1016/j.agrformet.2022.108848.
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- Bayissa, Y., 2018. Developing an impact-based combined drought index for monitoring crop yield anomalies in the Upper Blue Nile Basin, Ethiopia. CRC Press.https://doi.org/10.1201/9780429399510.
- Beguería, S., Vicente‐Serrano, S.M., Reig, F and Latorre, B., 2014. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International journal of climatology, 34, 3001-3023. https://doi.org/10.1002/joc.3887.
- Bekçi, R.N., 2022. Güneş Potansiyeli Analizi Ve İnternet Tabanlı CBS Uygulaması. Yüksek Lisans Tezi, Mersin Üniversitesi, Fen Bilimleri Enstitüsü, Mersin, 112.
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- Çoruhlu, Y.E. and Çelik, M.Ö., 2022. Protected area geographical management model from design to implementation for specially protected environment area. Land Use Policy, 122, 106357.
https://doi.org/10.1016/j.landusepol.2022.106357.
- Dikici, M. and Aksel, M., 2021. Comparison of drought indices in the case of the Ceyhan Basin. International Journal of Environment and Geoinformatics, 8, 113-125. https://doi.org/10.30897/ijegeo.792379.
- Drisya, J. And Sathish Kumar, D., 2023. Evaluation of the drought management measures in a semi-arid agricultural watershed. Environment, Development and Sustainability, 25, 811-833.
https://doi.org/10.1007/s10668-021-02079-4.
- Dubrovsky, M., Svoboda, M.D., Trnka, M., Hayes, M.J., Wilhite, D.A., Zalud, Z. and Hlavinka, P., 2009. Application of relative drought indices in assessing climate-change impacts on drought conditions in Czechia. Theoretical and Applied Climatology, 96, 155-171. https://doi.org/10.1007/s00704-008-0020-x.
- Hadri, A., Saidi, M.E.M. and Boudhar, A., 2021. Multiscale drought monitoring and comparison using remote sensing in a Mediterranean arid region: a case study from west-central Morocco. Arabian Journal of Geosciences, 14, 1-18.https://doi.org/10.1007/s12517-021-06493-w.
- Hargreaves, G.H. and Samani, Z.A., 1985. Reference crop evapotranspiration from temperature. Applied engineering in agriculture, 1, 96-99. https://doi.org/10.13031/2013.26773.
- Hobbins, M.T., Dai, A., Roderick, M.L. and Farquhar, G. D., 2008. Revisiting the parameterization of potential evaporation as a driver of long‐term water balance trends. Geophysical Research Letters, 35. L12403
https://doi.org/10.1029/2008GL033840.
- İban, M.C., 2022. MODIS Verileri ve VHI İndeksi ile Adana ve Mersin’de Kuraklık Şiddetinin İzlenmesi. 11. Türkiye Ulusal Fotogrametri ve Uzaktan Algılama Birliği (TUFUAB) Teknik Sempozyumu, 12-14 Mayıs 2022, Mersin, Türkiye, 16-19.
- Jacobi, J., Perrone, D., Duncan, L.L. and Hornberger, G. (2013). A tool for calculating the Palmer drought indices. Water Resources Research, 49, 6086-6089.https://doi.org/10.1002/wrcr.20342.
- Karadirek, I. E., 2022. Drought Management. In Water and Wastewater Management: Global Problems and Measures Cham. Springer International Publishing, 27-34.
- Karl, T.R., 1986. The sensitivity of the Palmer Drought Severity Index and Palmer's Z-index to their calibration coefficients including potential evapotranspiration. Journal of Climate and Applied Meteorology, 77-86.
- Katipoğlu, O.M. (2023). Prediction of streamflow drought index for short-term hydrological drought in the semi-arid Yesilirmak Basin using Wavelet transform and artificial intelligence techniques. Sustainability, 15, 1109. https://doi.org/10.3390/su15021109.
- Kheyruri, Y., Sharafati, A. and Shahid, S., 2023. Evaluation of the impact of large-scale atmospheric indicators and meteorological variables on drought in different regions of Iran. Environmental Earth Sciences, 82, 317.
https://doi.org/10.1007/s12665-023-11015-w.
- Kikon, A. and Deka, P.C., 2022. Artificial intelligence application in drought assessment, monitoring and forecasting: a review. Stochastic Environmental Research and Risk Assessment, 36, 1197-1214.
https://doi.org/10.1007/s00477-021-02129-3.
- Kim, T.W., Valdés, J. B. and Aparicio, J., 2002. Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico. Water International, 27, 420-430. https://doi.org/10.1080/02508060208687021.
- Liu, X., Zhu, X., Pan, Y., Li, S., Liu, Y. and Ma, Y., 2016. Agricultural drought monitoring: Progress, challenges, and prospects. Journal of Geographical Sciences, 26, 750-767. https://doi.org/10.1007/s11442-016-1297-9.
- Mishra, A.K. and Desai, V.R., 2005. Spatial and temporal drought analysis in the Kansabati river basin, India. International Journal of River Basin Management, 3, 31-41.https://doi.org/10.1080/15715124.2005.9635243.
- Mishra, A.K. and Singh V.P., 2011. Drought modeling–A review. Journal of Hydrology, 403, 157-175.
https://doi.org/10.1016/j.jhydrol.2011.03.049.
- Mishra, A.K. and Singh, V.P., 2011. Drought modeling–A review. Journal of Hydrology, 403(1-2), 157-175.
https://doi.org/10.1016/j.jhydrol.2011.03.049.
- Mishra, A.K., and Singh V.P., 2009. Analysis of drought severity‐area‐frequency curves using a general circulation model and scenario uncertainty. Journal of Geophysical Research: Atmospheres, 114.
https://doi.org/10.1029/2008JD010986.
- Nie, N., Zhang, W., Chen, H. and Guo, H., 2018. A global hydrological drought index dataset based on gravity recovery and climate experiment (GRACE) data. Water Resources Management, 32, 1275-1290.
https://doi.org/10.1007/s11269-017-1869-1.
- Öztürk, T. ve Gürsoy, F., 2022. Küresel İklim Değişikliğinin Arktik Okyanusu’na Jeopolitik Etkisi. Akdeniz Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22, 117–31. https://doi.org/10.25294/auiibfd.1053878.
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