Abstract
Under the climate change scenario, the identification of drought trends is primarily essential for the efficient utilization of water resources. In this paper, two methods, including traditional Mann-Kendall (MK) and graphical Şen-Innovative Trend (ŞIT), were utilized for Effective Drought Index (EDI) trend detection at 13 meteorological stations situated in the State of Uttarakhand, India. The EDI was computed for 54 years from 1962 to 2015 using monthly rainfall data at the study stations. The magnitude (mm/year) of the EDI was derived by Sen’s-Slope Estimator (SSE) method. In total, 156 series of data were analyzed, and the results showed that the ŞIT method detected a significantly negative/positive trend in 71/60 time series, while the MK method detected a significantly negative/positive trend in 25/9 time series from January to December at the study stations. Magnitude (mm/year) varies from − 0.0275 to 0.0256 (January), − 0.0352 to 0.0343 (February), − 0.0312 to 0.0312 (March), − 0.0343 to 0.0276 (April), − 0.0359 to 0.0237 (May), − 0.0293 to 0.0205 (June), − 0.0234 to 0.0235 (July), − 0.0277 to 0.0405 (August), − 0.0297 to 0.0247 (September), − 0.0288 to 0.0227 (October), − 0.0290 to 0.0241 (November), and − 0.0298 to 0.0236 (December) over the study region. Additionally, the results indicated the supremacy of the ŞIT method by examining the unobserved trend that cannot be detected by the MK method over the study region in the EDI data series. In general, the EDI trend was found negative (decreasing) and positive (increasing), which suggested that more attention should be paid towards drought and wet (i.e., moderate, severe, extreme) at the study stations. The results of this research can be employed for water resource management and understanding the characteristics of climate variation over the study area.
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References
Alami MM, Hayat E, Tayfur G (2017) Proposing a popular method for meteorological drought monitoring in the Kabul River Basin, Afghanistan. Int J Adv Eng Res Sci 4:103–110. https://doi.org/10.22161/ijaers.4.6.12
Ali, Kuriqi, Abubaker, Kisi (2019) Long-term trends and seasonality detection of the observed flow in Yangtze River using Mann-Kendall and Sen’s Innovative Trend method. Water 11:1855. https://doi.org/10.3390/w11091855
Ay M, Kisi O (2015) Investigation of trend analysis of monthly total precipitation by an innovative method. Theor Appl Climatol 120:617–629. https://doi.org/10.1007/s00704-014-1198-8
Banerjee A, Chen R, Meadows ME et al (2020) An analysis of long-term rainfall trends and variability in the uttarakhand himalaya using google earth engine. Remote Sens 12. https://doi.org/10.3390/rs12040709
Byun H-R, Wilhite DA (1999) Objective quantification of drought severity and duration. J Clim 12:2747–2756. https://doi.org/10.1175/1520-0442(1999)012<2747:OQODSA>2.0.CO;2
Caloiero T (2018) SPI trend analysis of New Zealand applying the ITA technique. Geosciences 8. https://doi.org/10.3390/geosciences8030101
Caloiero T (2019) Evaluation of rainfall trends in the South Island of New Zealand through the innovative trend analysis (ITA). Theor Appl Climatol 139:493–504. https://doi.org/10.1007/s00704-019-02988-5
Caloiero T, Coscarelli R, Ferrari E (2018) Application of the innovative trend analysis method for the trend analysis of rainfall anomalies in Southern Italy. Water Resour Manag 32:4971–4983. https://doi.org/10.1007/s11269-018-2117-z
Cengiz TM, Tabari H, Onyutha C, Kisi O (2020) Combined use of graphical and statistical approaches for analyzing historical precipitation changes in the Black Sea Region of Turkey. Water (Switzerland) 12. https://doi.org/10.3390/w12030705
Chandrakar A, Khare D, Krishan R (2017) Assessment of spatial and temporal trends of long term precipitation over Kharun Watershed, Chhattisgarh, India. Environ Process 4:959–974. https://doi.org/10.1007/s40710-017-0273-4
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-Terrestrial Phys 164:48–59. https://doi.org/10.1016/j.jastp.2017.08.001
Dabanlı İ, Şen Z, Yeleğen MÖ, Şişman E, Selek B, Güçlü YS (2016) Trend assessment by the innovative-Şen method. Water Resour Manag 30:5193–5203. https://doi.org/10.1007/s11269-016-1478-4
Danandeh Mehr A, Vaheddoost B (2019) Identification of the trends associated with the SPI and SPEI indices across Ankara. Turkey Theor Appl Climatol 139:1531–1542. https://doi.org/10.1007/s00704-019-03071-9
Dinpashoh Y, Mirabbasi R, Jhajharia D, Abianeh HZ, Mostafaeipour A (2014) Effect of short-term and long-term persistence on identification of temporal trends. J Hydrol Eng 19:617–625. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000819
Dogan S, Berktay A, Singh VP (2012) Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey. J Hydrol 470–471:255–268. https://doi.org/10.1016/j.jhydrol.2012.09.003
Gajbhiye S, Meshram C, Mirabbasi R, Sharma SK (2016) Trend analysis of rainfall time series for Sindh river basin in India. Theor Appl Climatol 125:593–608. https://doi.org/10.1007/s00704-015-1529-4
Güçlü YS, Dabanlı ŞE, Şen Z (2019) Air quality (AQ) identification by innovative trend diagram and AQ index combinations in Istanbul megacity. Atmos Pollut Res 10:88–96. https://doi.org/10.1016/j.apr.2018.06.011
Jain VK, Pandey RP, Jain MK, Byun H-R (2015) Comparison of drought indices for appraisal of drought characteristics in the Ken River Basin. Weather Clim Extrem 8:1–11. https://doi.org/10.1016/j.wace.2015.05.002
Jin X, Qiang H, Zhao L, Jiang S, Cui N, Cao Y, Feng Y (2019) SPEI-based analysis of spatio-temporal variation characteristics for annual and seasonal drought in the Zoige Wetland, Southwest China from 1961 to 2016. Theor Appl Climatol 139:711–725. https://doi.org/10.1007/s00704-019-02981-y
Kendall MG (1975) Rank correlation methods. 4th eds Charles Griffin, London 6
Ketema A, Siddaramaiah DG (2020) Trend and variability of hydrometeorological variables of Tikur Wuha watershed in Ethiopia. Arab J Geosci 13. https://doi.org/10.1007/s12517-020-5139-9
Kim DW, Byun HR (2009) Future pattern of Asian drought under global warming scenario. Theor Appl Climatol 98:137–150. https://doi.org/10.1007/s00704-008-0100-y
Kisi O, Ay M (2014) Comparison of Mann-Kendall and innovative trend method for water quality parameters of the Kizilirmak River. Turkey J Hydrol 513:362–375. https://doi.org/10.1016/j.jhydrol.2014.03.005
Kişi Ö, Santos CAG, da Silva RM, Zounemat-Kermani M (2018) Trend analysis of monthly streamflows using Şen’s innovative trend method. Geofizika. https://doi.org/10.15233/gfz.2018.35.3
Kumar S, Machiwal D, Dayal D (2017) Spatial modelling of rainfall trends using satellite datasets and geographic information system. Hydrol Sci J 62:1636–1653. https://doi.org/10.1080/02626667.2017.1304643
Li R, Huang H, Yu G, Yu H, Bridhikitti A, Su T (2020) Trends of runoff variation and effects of main causal factors in Mun River, Thailand During 1980–2018. Water 12:831. https://doi.org/10.3390/w12030831
Malik A, Kumar A (2020) Spatio-temporal trend analysis of rainfall using parametric and non-parametric tests: case study in Uttarakhand, India. Theor Appl Climatol 140:183–207. https://doi.org/10.1007/s00704-019-03080-8
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 12:328. https://doi.org/10.1007/s12517-019-4454-5
Malik A, Kumar A, Najah Ahmed A, Ming Fai C, Abdulmohsin Afan H, Sefelnasr A, Sherif M, el-Shafie A (2020) Application of non-parametric approaches to identify trend in streamflow during 1976–2007 (Naula watershed). Alexandria Eng J 59:1595–1606. https://doi.org/10.1016/j.aej.2020.04.006
Mann HB (1945) Nonparametric tests against trend. Econometrica. 13:245. https://doi.org/10.2307/1907187
Meshram SG, Singh VP, Meshram C (2017) Long-term trend and variability of precipitation in Chhattisgarh State. India Theor Appl Climatol 129:729–744. https://doi.org/10.1007/s00704-016-1804-z
Meshram SG, Kahya E, Meshram C, Ghorbani MA, Ambade B, Mirabbasi R (2020) Long-term temperature trend analysis associated with agriculture crops. Theor Appl Climatol 140:1139–1159. https://doi.org/10.1007/s00704-020-03137-z
Mishra AK, Singh VP (2009) Analysis of drought severity-area-frequency curves using a general circulation model and scenario uncertainty. J Geophys Res 114:D06120. https://doi.org/10.1029/2008JD010986
Morid S, Smakhtin V, Moghaddasi M (2006) Comparison of seven meteorological indices for drought monitoring in Iran. Int J Climatol 26:971–985. https://doi.org/10.1002/joc.1264
Pingale SM, Khare D, Jat MK, Adamowski J (2014) Spatial and temporal trends of mean and extreme rainfall and temperature for the 33 urban centers of the arid and semi-arid state of Rajasthan. India Atmos Res 138:73–90. https://doi.org/10.1016/j.atmosres.2013.10.024
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.1080/01621459.1968.10480934
Şen Z (2012) Innovative trend analysis methodology. J Hydrol Eng 17:1042–1046. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000556
Şen Z (2014) Trend identification simulation and application. J Hydrol Eng 19:635–642. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000811
Şen Z (2017) Innovative trend significance test and applications. Theor Appl Climatol 127:939–947. https://doi.org/10.1007/s00704-015-1681-x
Sharma A, Goyal MK (2020) Assessment of drought trend and variability in India using wavelet transform. Hydrol Sci J 65:1539–1554. https://doi.org/10.1080/02626667.2020.1754422
Siddik MAZ, Rahman M (2014) Trend analysis of maximum, minimum, and average temperatures in Bangladesh: 1961-2008. Theor Appl Climatol 116:721–730. https://doi.org/10.1007/s00704-014-1135-x
Theil H (1950) A rank-invariant method of linear and polynomial regression analysis, III. Proc K Nederl Akad Wetensch 53:1397–1412
Tosunoglu F, Kisi O (2017) Trend analysis of maximum hydrologic drought variables using Mann–Kendall and Şen’s innovative trend method. River Res Appl 33:597–610. https://doi.org/10.1002/rra.3106
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. https://doi.org/10.1175/2009JCLI2909.1
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
Worku T, Khare D, Tripathi SK (2018) Spatiotemporal trend analysis of rainfall and temperature, and its implication on crop production. J Water Clim Chang 10:799–817. https://doi.org/10.2166/wcc.2018.064
Wu H, Li X, Qian H, Chen J (2019) Improved partial trend method to detect rainfall trends in Hainan Island. Theor Appl Climatol 137:2539–2547
Yacoub E, Tayfur G (2017) Evaluation and assessment of meteorological drought by different methods in Trarza Region. Mauritania Water Resour Manag 31:825–845. https://doi.org/10.1007/s11269-016-1510-8
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
Acknowledgments
The authors would like to thank the India Meteorological Department (IMD), Pune, and Directorate of Research, G.B. Pant University of Agriculture and Technology, Pantnagar, for providing the monthly rainfall time series data of Uttarakhand State for this study.
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Malik, A., Kumar, A., Pham, Q.B. et al. Identification of EDI trend using Mann-Kendall and Şen-Innovative Trend methods (Uttarakhand, India). Arab J Geosci 13, 951 (2020). https://doi.org/10.1007/s12517-020-05926-2
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DOI: https://doi.org/10.1007/s12517-020-05926-2