Determination of drought distribution using palmer drought severity ındex: Case study of Susurluk basin


Abstract views: 89 / PDF downloads: 97

Authors

DOI:

https://doi.org/10.56768/jytp.1.2.03

Keywords:

drought, geographic information system, PDSI, statistical computing, Susurluk Basin

Abstract

The results such as decrease in agricultural production, product quality and change in diversity because of drought create important socio-economic problems. Due to these reasons, it is becoming an increasingly strategic study topic in academic circles. The fact is that it is not observed instantly like natural disasters makes it possible to take necessary measures on a basin basis in case of drought. Accordingly, obtained data, from meteorological stations in the Susurluk Basin, were used in this study. Within the scope of the study, the starting and ending dates, and intensities of dominant dry periods were determined by using the PDSI (Palmer Drought Severity Index). Using data such as precipitation, evaporation, transpiration, and the water holding capacity of soil as inputs, a tool was developed in the R environment for PDSI, and annual values were calculated for each meteorology station by running all inputs in this tool. For calculated PDSI values, spatial and temporal analyze were made using the digital elevation model of the Susurluk Basin using the ordinary cokriging interpolation method in ArcGIS 10.8 program.

Downloads

Download data is not yet available.

References

Anon (1999). Meteorological Characteristic Natural Disasters and Meteorological Measures, Chamber of Meteorological Engineers, Meteorological Characteristic Natural Disasters Report, Ankara.

Anon (2022). Sakarya ve Susurluk Havzaları kuraklık yönetim hazırlanması projesi: Tarım Ve Orman Bakanliği Su Yönetimi Genel Müdürlüğü Taşkın Ve Kuraklık Yönetimi Dairesi Başkanlığı

Anon (2018). Susurluk Nehir Havzası Yönetim Planı: Tarım Ve Orman Bakanliği Su Yönetimi Genel Müdürlüğü Taşkın Ve Kuraklık Yönetimi Dairesi Başkanlığı

FAO Anon (2009). Global agriculture towards 2050, How to feed the World in 2050, 4

HAO, ZC, HAO, FH, SINGH, VP, OUYANG, W., & CHENG, HG (2017). An integrated package for drought monitoring, prediction, and analysis to aid drought modeling and assessment. Environmental Modeling and Software, 91, 199–209.

MCKEE TB, DOESKEN NJ, & KLEIST J (1993). The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th Conference on Applied climatology. Vol. 22. American meteorological Society Boston, MA, pp 179–183.

PALMER W. (1965) Meteorological drought, Research Paper No. 45, US Weather Bureau, Washington, DC :1-59

TAGEM Anon (2018)

THORNTHWAITE, CW (1948). An approach toward a rational classification of climate. Geographical Review, 38, 55–94.

TIRIVARAMBO, S., OSUPILE, D., & ELIASSON, P. (2018). Drought monitoring and analysis: Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI). Physics and Chemistry of the Earth, 106, 1–10.

United Nations Anon (2017). World Population Prospects: The 2017 Revision, Key Findings and Advance Tables, United Nations, Department of Economic and Social Affairs Population Division, 46,

WELLS, N., GODDARD, S., & HAYES, MJ. (2004). A self- calibrating Palmer Drought Severity Index. Journal of Climate, 17, 2335–2351. https://doi. org/10.1175/1520-0442(2004)017 2.0. Co;2.

WWAP (United Nations World Water Assessment Programmed) Anon. (2015). The United Nations World Water Development Report 2015, Water for a sustainable World, 13

Downloads

Published

2022-12-21

How to Cite

Mucan, U. (2022). Determination of drought distribution using palmer drought severity ındex: Case study of Susurluk basin. The Journal of Global Climate Change, 1(2), 63–68. https://doi.org/10.56768/jytp.1.2.03

Issue

Section

ARTICLES