Drought Monitoring and Forecasting across Turkey: A Contemporary Review

Dilayda Soylu Pekpostalci, Rifat Tur, Ali Danandeh Mehr (), Mohammad Amin Vazifekhah Ghaffari, Dominika Dąbrowska and Vahid Nourani
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Dilayda Soylu Pekpostalci: Department of Civil Engineering, Institute of Natural and Applied Sciences, Akdeniz University, Antalya 07058, Türkiye
Rifat Tur: Department of Civil Engineering, Faculty of Engineering, Akdeniz University, Antalya 07058, Türkiye
Ali Danandeh Mehr: Department of Civil Engineering, Antalya Bilim University, Antalya 07190, Türkiye
Mohammad Amin Vazifekhah Ghaffari: Department of Water Engineering, University of Urmia, Urmia 57561, Iran
Dominika Dąbrowska: Faculty of Natural Sciences, University of Silesia, Bedzinska 60, 41-200 Sosnowiec, Poland
Vahid Nourani: Center of Excellence in Hydroinformatics, Faculty of Civil Engineering, University of Tabriz, Tabriz 51666, Iran

Sustainability, 2023, vol. 15, issue 7, 1-23

Abstract: One of the critical consequences of climate change at both local and regional scales is a change in the patterns of extreme climate events such as droughts. Focusing on the different types of droughts, their quantifying indices, associated indicators, and sources of data (remote sensing (RS)/in situ measurements), this article reviewed the recent studies (from 2010 to 2022) that have explored drought features in Turkey. To this end, a total of 71 articles were selected from the Web of Science (WoS) and Scopus databases. The selected papers were clustered into two categories: (i) drought monitoring studies and (ii) drought forecasting articles. Then, the representative papers were reviewed in detail regarding the implemented indices, models (techniques), case study area, and source of the indicators used to derive drought indices. The review results showed that most of the studies aimed at meteorological drought monitoring and forecasting. An increasing trend was also observed in the use of machine learning for short-term meteorological and hydrological drought prediction. On the other hand, the emerging RS technology and satellite-driven indicators were rarely used in the country. The review showed that there is room for more research on agricultural and hydrological drought monitoring, forecasting, and pattern detection in Turkey.

Keywords: drought forecasting; drought monitoring; drought indices; satellite data; in situ measurement; machine learning models; Türkiye (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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