Analysis of spatial variation of temperature trends in the semiarid Euphrates basin using statistical approaches

Katipoğlu, Okan Mert

doi:10.1007/s11600-022-00819-2

Artykuł - szczegóły

Tytuł artykułu

Analysis of spatial variation of temperature trends in the semiarid Euphrates basin using statistical approaches

Autorzy

Katipoğlu Okan Mert

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-022-00819-2

Warianty tytułu

Języki publikacji

Abstrakty

This study analyzes the spatial and temporal distribution of trends on monthly, seasonal, and annual mean temperatures (1967–2017) at 22 stations in the Euphrates Basin of Turkey. The recently proposed innovative trend analysis (ITA) and the nonparametric Mann–Kendall (MK) and Spearman’s rho (SR) test at 5% and 1% significance levels were applied to examine the temporal trends of temperatures. Before using the nonparametric trend analysis, the serial correlation of the temperature data was removed with the pre-whitening (PW) method. Then, MK-Z values were mapped in ArcGIS environment using the Empirical Bayesian Kriging (EBK) method to reveal the spatial variation of temperature trends. As a result, according to the ITA method, increasing temperature trends at 1% significance level dominate almost all periods. Based on the MK and SR tests, it was identified that increase trends were dominant at 1% and 5% significance levels in February, March, April, July, August, Spring, Summer, and Annual periods. According to the spatial temperature trend maps, significant increase trends occupy an important place in most of the basin in February, March, April, June, July, August, Spring, Summer, Winter, and Annual periods. The study results provide important information to water resources managers and decision-makers about the regions at significant risk in climate change in the Euphrates Basin.

Słowa kluczowe

climate change Mann-Kendall test temperature trend Euphrates basin Empirical Bayesian Kriging Şen’s innovative trend analysis

zmiana klimatu test Manna-Kendalla trend temperatury dorzecze Eufratu

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2022

Tom

Vol. 70, no 4

Strony

1899--1921

Opis fizyczny

Bibliogr. 51 poz.

Twórcy

autor

Katipoğlu Okan Mert

okatipoglu@erzincan.edu.tr

Faculty of Engineering and Architecture, Department of Civil Engineering, Erzincan Binali Yildirim University, Erzincan, Turkey

https://orcid.org/0000-0001-6421-6087

Bibliografia

1. Alifujiang Y, Abuduwaili J, Maihemuti B, Emin B, Groll M (2020) Innovative trend analysis of precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan. Atmosphere 11(4):332. https://doi.org/10.3390/atmos11040332
2. Allen M, Dube OP, Solecki W, Aragón-Durand F, Cramer W, Humphreys S, Mulugetta Y (2018) Global warming of 1.5 °C. In: An IPCC Special Report on the impacts of global warming of 1.5° C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Sustainable Development, and Efforts to Eradicate Poverty. Intergovernmental Panel on Climate Change
3. Ay M (2020) Trend and homogeneity analysis in temperature and rainfall series in western Black Sea region, Turkey. Theor Appl Climatol 139(3):837–848. https://doi.org/10.1007/s00704-019-03066-6
4. Bostan P (2017) Basic kriging methods in geostatistics. Yuzuncu Yil Univ J Agric Sci 27:10–20
5. Bostan P (2020) Assessing variations in climate extremes over Euphrates Basin, Turkey. Theor Appl Climatol 141(3):1461–1473. https://doi.org/10.1007/s00704-020-03238-9
6. Cui L, Wang L, Lai Z, Tian Q, Liu W, Li J (2017) Innovative trend analysis of annual and seasonal air temperature and rainfall in the Yangtze River Basin, China during 1960–2015. J Atmos Solar Terr Phys 164:48–59. https://doi.org/10.1016/j.jastp.2017.08.001
7. Demircan M, Gürkan H, Türkoğlu N, Çiçek İ (2018) Relationship between homogeneity breaking points in temperatures and north atlantic oscillation (NAO). In: Paper presented at the international geography symposium on the 30th anniversary of TUCAUM, Ankara
8. Esri (2021a) Performing cross-validation and validation. Retrieved December, 2021a. https://pro.arcgis.com/en/pro-app/latest/help/analysis/geostatistical-analyst/performing-cross-validation-and-validation.htm
9. Esri (2021b) What is empirical Bayesian kriging?. Retrieved December, 2021b. https://desktop.arcgis.com/en/arcmap/latest/extensions/geostatistical-analyst/what-is-empirical-bayesian-kriging-.htm
10. Gribov A, Krivoruchko K (2020) Empirical Bayesian kriging implementation and usage. Sci Total Environ 722:137290. https://doi.org/10.1016/j.scitotenv.2020.137290
11. Gümüş V, Soydan NG, Şimşek O, Algin HM, Aköz MS, Yenigun K (2017) Seasonal and annual trend analysis of meteorological data in Sanliurfa, Turkey. Eur Water 59:131–136
12. Gupta A, Kamble T, Machiwal D (2017) Comparison of ordinary and Bayesian kriging techniques in depicting rainfall variability in arid and semi-arid regions of north-west India. Environ Earth Sci 76(15):1–16. https://doi.org/10.1007/s12665-017-6814-3
13. Gupta N, Banerjee A, Gupta SK (2021) Spatio-temporal trend analysis of climatic variables over Jharkhand, India. Earth Syst Environ 5(1):71–86. https://doi.org/10.1007/s41748-021-00204-x
14. Güven L (2019) Trend analysis of hydro-meteorologoc data in Upper Euphrates Basin. MSc Thesis, Ataturk University Graduate School of Natural and Applied Sciences Erzurum
15. Jain SK, Kumar V, Saharia M (2013) Analysis of rainfall and temperature trends in northeast India. Int J Climatol 33(4):968–978. https://doi.org/10.1002/joc.3483
16. Jerin JN, Islam HT, Islam ARMT, Shahid S, Hu Z, Badhan MA, Elbeltagi A (2021) Spatiotemporal trends in reference evapotranspiration and its driving factors in Bangladesh. Theor Appl Climatol 144(1):793–808. https://doi.org/10.1007/s00704-021-03566-4
17. Kamruzzaman M, Rahman AS, Ahmed MS, Kabir ME, Mazumder QH, Rahman MS, Jahan CS (2018) Spatio-temporal analysis of climatic variables in the western part of Bangladesh. Environ Dev Sustain 20(1):89–108. https://doi.org/10.1007/s10668-016-9872-x
18. Katipoğlu OM (2021) Spatial analysis of seasonal precipitation using various interpolation methods in the Euphrates Basin, Turkey. Acta Geophsica 2:114. https://doi.org/10.21203/rs.3.rs-809129/v1
19. Kendall MG, Gibbons JD (1975) Rank correlation methods, 1970. Griffin, London
20. Khan N, Shahid S, Bin IT, Wang XJ (2019) Spatial distribution of unidirectional trends in temperature and temperature extremes in Pakistan. Theor Appl Climatol 136(3):899–913. https://doi.org/10.1007/s00704-018-2520-7
21. Kim SN, Lee WK, Shin KI, Kafatos M, Seo DJ, Kwak HB (2010) Comparison of spatial interpolation techniques for predicting climate factors in Korea. For Sci Technol 6(2):97–109. https://doi.org/10.1080/21580103.2010.9671977
22. Kisi O (2015) An innovative method for trend analysis of monthly pan evaporations. J Hydrol 527:1123–1129. https://doi.org/10.1016/j.jhydrol.2015.06.009
23. Krivoruchko K (2012) Empirical bayesian kriging. ArcUser Fall 6(10):1145
24. Krivoruchko K, Gribov A (2019) Evaluation of empirical bayesian kriging. Spatial Stat 32:100368
25. Kumari M, Sakai K, Gunarathna M (2018) Are geostatistical interpolation techniques better than deterministic interpolation methods? In: A study in Ulagalla Tank Cascade, Sri Lanka. PAWEES-INWEPF International Conference, Nara, Japan
26. Mahalingam B, Deldar AN, Vinay M (2015) Analysis of selected spatial interpolation techniques for rainfall data. Int J Curr Res Rev 7(7):66
27. Malcheva K, Bocheva L, Marinova T (2019) Mapping temperature and precipitation climate normals over Bulgaria by using ArcGIS Pro 2.4. Bul J Meteorol Hydrol 23(2):61
28. Malik A, Kumar A, Guhathakurta P, Kisi O (2019) Spatial-temporal trend analysis of seasonal and annual rainfall (1966–2015) using innovative trend analysis method with significance test. Arab J Geosci 12(10):1–23. https://doi.org/10.1007/s12517-019-4454-5
29. Mann HB (1945) Non-parametric tests against trend. Econ J Econ Soc 2:245–259
30. Marak JDK, Sarma AK, Bhattacharjya RK (2020) Innovative trend analysis of spatial and temporal rainfall variations in Umiam and Umtru watersheds in Meghalaya, India. Theor Appl Climatol 142(3):1397–1412. https://doi.org/10.1007/s00704-020-03383-1
31. Nourani V, Mehr AD, Azad N (2018) Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann-Kendall and Şen tests. Environ Earth Sci 77(5):1–18. https://doi.org/10.1007/s12665-018-7390-x
32. Rahman MA, Yunsheng L, Sultana N (2017) Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman’s rho tests and ARIMA model. Meteorol Atmos Phys 129(4):409–424. https://doi.org/10.1007/s00703-016-0479-4
33. Reza YM, Javad KD, Mohammad M, Ashish S (2011) Trend detection of the rainfall and air temperature data in the Zayandehrud basin. J Appl Sci 11(12):2125–2134
34. Salas JD, Delleur JW, Yevjevich VM (1980) Applied modeling of hydrologic time series. Water Resources Publications Littleton, Colorado
35. Sanikhani H, Kisi O, Mirabbasi R, Meshram SG (2018) Trend analysis of rainfall pattern over the Central India during 1901–2010. Arab J Geosci 11(15):1–14. https://doi.org/10.1007/s12517-018-3800-3
36. Sen OL, Unal A, Bozkurt D, Kindap T (2011) Temporal changes in the Euphrates and Tigris discharges and teleconnections. Environ Res Lett 6(2):024012
37. Şen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17:1042–1046. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000556
38. Şen Z (2014) Trend identification simulation and application. J Hydrol Eng 19:635–642. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000811
39. Şen Z (2017) Innovative trend significance test and applications. Theor Appl Climatol 127:939–947. https://doi.org/10.1007/s00704-015-1681-x
40. Sensoy S, Türkoğlu N, Akçakaya A, Ekici M, Demircan M, Ulupinar Y, Demirbaş H (2013) Trends in Turkey climate indices from 1960 to 2010. In: 6th atmospheric science symposium (ITU). Istanbul, pp 24–26
41. Serencam U (2019) Innovative trend analysis of total annual rainfall and temperature variability case study: Yesilirmak region, Turkey. Arab J Geosci 12(23):1–9. https://doi.org/10.1007/s12517-019-4903-1
42. Shadmani M, Marofi S, Roknian M (2012) Trend analysis in reference evapotranspiration using Mann-Kendall and Spearman’s Rho tests in arid regions of Iran. Water Resour Manag 26(1):211–224. https://doi.org/10.1007/s11269-011-9913-z
43. Shukla PR, Skeg J, Buendia EC, Masson-Delmotte V, Pörtner HO, Roberts DC, Malley J (2019) IPCC, 2019: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems
44. Sneyers R (1991) On the statistical analysis of series of observations. Science 6:143
45. Von Storch H (1999) Misuses of statistical analysis in climate research. In: Analysis of climate variability, pp 11–26. Springer, Heidelberg. https://doi.org/10.1007/978-3-662-03744-7
46. Vicente-Serrano SM, Saz-Sánchez MA, Cuadrat JM (2003) Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature. Climate Res 24(2):161–180. https://doi.org/10.3354/cr024161
47. Wang Y, Xu Y, Tabari H, Wang J, Wang Q, Song S, Hu Z (2020) Innovative trend analysis of annual and seasonal rainfall in the Yangtze River Delta, eastern China. Atmos Res 231:104673. https://doi.org/10.1016/j.atmosres.2019.104673
48. Xu Y, Xu Y, Wang Y, Wu L, Li G, Song S (2017) Spatial and temporal trends of reference crop evapotranspiration and its influential variables in Yangtze River Delta, eastern China. Theor Appl Climatol 130(3):945–958. https://doi.org/10.1007/s00704-016-1928-1
49. Yu M, Li Q, Hayes MJ, Svoboda MD, Heim RR (2014) Are droughts becoming more frequent or severe in China based on the standardized precipitation evapotranspiration index: 1951–2010? Int J Climatol 34(3):545–558. https://doi.org/10.1002/joc.3701
50. Yurddaş K (2018) Precipitation and temperature changes and trends in Euphrates basin. Msc thesis, Department of Georaphy Institute of Social Sciences. Kahramanmaraş Sütçü Imam University Kahramanmaraş
51. Zhou Z, Wang L, Lin A, Zhang M, Niu Z (2018) Innovative trend analysis of solar radiation in China during 1962–2015. Renew Energy 119:675–689. https://doi.org/10.1016/j.renene.2017.12.052

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Typ dokumentu

Bibliografia

Identyfikator YADDA

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