Skip to main content
Springer Nature Link
Log in

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

This study investigated trends in 35 years (1979–2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen’s slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year−1. The sequential significance of linear trend in MK test-statistics is very strong (R2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced metabolic-activities and shortened crop-duration. Likewise, increased Tmin may result in lesser crop and biomass yields owing to the increased respiration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  • Anderson RL (1942) Distribution of the serial correlation coefficient. Ann Math Stat 13:1–13

    Article  Google Scholar 

  • Asfaw A, Simane B, Hassen A, Bantidar A (2017) Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: A case study in Woleka sub-basin. Weather and Climate Extremes, https://doi.org/10.1016/j.wace.2017.12.002.

  • Basistha A, Goel NK, Arya DS, Gangwar SK (2007) Spatial pattern of trends in Indian sub-divisional rainfall. Jalvigyan Sameeksha 22:47–57

    Google Scholar 

  • Burn DH, Elnur MAH (2002) Detection of hydrologic trends and variability. J Hydrol 255:107–122

    Article  Google Scholar 

  • Cannarozzo M, Noto LV, Viola F (2006) Spatial distribution of rainfall trends in Sicily (1921-2000). Phys Chem Earth 31:1201–1211

    Article  Google Scholar 

  • CDIAC (2013) Ranking of the world's countries by 2013 total CO2 emissions from fossil-fuel burning, cement production, and gas flaring. Carbon Dioxide Information Analysis Center (CDIAC), The United States Department of Energy, US. http://cdiac.ornl.gov/trends/emis/top2013.tot. Accessed 23–02-2017.

  • Chatterjee S, Khan A, Akbari H, Wang Y (2016) Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901-2002), West Bengal, India. Atmos Res 182:54–75

    Article  Google Scholar 

  • Dayal D, Ram B, Shamsudheen M, Swami ML, Patil NV (2009) Twenty years of CAZRI, regional Research Station, Kukma-Bhuj. Regional Research Station, Central Arid Zone Research Institute, Kukma-Bhuj, Gujarat 35pp

    Google Scholar 

  • Deka RL, Mahanta C, Pathak H, Nath KK, Das S (2013) Trends and fluctuations of rainfall regime in the Brahmaputra and Barak basins of Assam, India. Theor Appl Climatol 114(1):61–71

    Article  Google Scholar 

  • Douglas EM, Vogel RM, Kroll CN (2000) Trends in floods and low flows in the United States: impact of spatial correlation. J Hydrol 240:90–105

    Article  Google Scholar 

  • Fisher RA (1992) Statistical methods for research workers. In: Kotz S, Johnson NL (eds) Breakthroughs in statistics. Springer series in statistics (perspectives in statistics). Springer, New York

    Google Scholar 

  • GEC (2011) Trends of changing climate and effects on eco-environment of Kachchh District, Gujarat. Project Report, Gujarat Ecology Commission (GEC), Gandhinagar, Gujarat, 86pp

  • Ghosh S, Luniya V, Gupta A (2009) Trend analysis of Indian summer monsoon rainfall at different spatial scales. Atmos Sci Lett 10(4):285–290

    Google Scholar 

  • Goswami BN, Venugopal V, Sengupta D, Madhusoodanan MS, Xavier PK (2006) Increasing trend of extreme rain events over India in a warming environment. Science 314:1442–1445

    Article  Google Scholar 

  • Goyal MK (2014) Statistical analysis of long term trends of rainfall during 1901-2002 at Assam, India. Water Resour Manag 28:1501–1515

    Article  Google Scholar 

  • Guhathakurta P, Rajeevan M (2006) Trends in the rainfall pattern over India. NCC Research Report (Report No. 2/2006). National Climate Centre (NCC), India Meteorological Department, Pune, India 23p

    Google Scholar 

  • Haan CT (2002) Statistical methods in hydrology. Second edition. Iowa State University Press, Ames, Iowa 496pp

    Google Scholar 

  • Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:219–246

    Article  Google Scholar 

  • Hamilton JP, Whitelaw GS, Fenech A (2001) Mean annual temperature and annual precipitation trends at Canadian biosphere reserves. Environ Monit Assess 67:239–275

    Article  Google Scholar 

  • Hirsch RM, Slack JR, Smith RA (1982) Techniques of trend analysis for monthly water quality data. Water Resour Res 18(1):107–121

    Article  Google Scholar 

  • INCCA (2010) Climate change and India: A 4×4 assessment—a sectoral and regional analysis for 2030s. INCCA Report No. 2, Indian Network for Climate Change Assessment (INCCA), Ministry of Environment & Forests, Government of India, New Delhi

  • Jain SK, Kumar V (2012) Trend analysis of rainfall and temperature data for India. Curr Sci 102(1):37–49

    Google Scholar 

  • Jain SK, Kumar V, Saharia M (2013) Analysis of rainfall and temperature trends in Northeast India. Int J Climatol 33(4):968–978

    Article  Google Scholar 

  • Kar A, Garg BK, Singh MP, Kathju S (eds) (2009) Trends in arid zone research in India. Central Arid Zone Research Institute, Jodhpur, Rajasthan 481pp

    Google Scholar 

  • Kendall MG (1973) Time Series. Charles Griffin and Co. Ltd., London

    Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Charles Griffin and Co. Ltd., London, U.K.

    Google Scholar 

  • Kharol SK, Kaskaoutis DG, Badarinath KVS, Sharma AR, Singh RP (2013) Influence of land use/land cover (LULC) changes on atmospheric dynamics over the arid region of Rajasthan state, India. J Arid Environ 88:90–101

    Article  Google Scholar 

  • Kumar V, Jain SK, Singh Y (2010) Analysis of long-term rainfall trends in India. Hydrol Sci J 55(4):484–496

    Article  Google Scholar 

  • Kumar S, Merwade V, Kinter J III, Niyogi D (2013) Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 20th century climate simulations. J Clim 26(12):4168–4185

    Article  Google Scholar 

  • Lettenmaier DP (1976) Detection of trend in water quality data from record with dependent observations. Water Resour Res 12(5):1037–1046

    Article  Google Scholar 

  • Machiwal D, Jha MK (2008) Comparative evaluation of statistical tests for time series analysis: application to hydrological time series. Hydrol Sci J 53(2):353–366

    Article  Google Scholar 

  • Machiwal D, Jha MK (2012) Hydrologic time series analysis: theory and practice. Springer, Germany and Capital Publishing Company, New Delhi 303pp

    Book  Google Scholar 

  • Machiwal D, Jha MK (2016) Evaluating persistence, and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in western India. Theor Appl Climatol 128:689–708. https://doi.org/10.1007/s00704-016-1734-9

    Article  Google Scholar 

  • Machiwal D, Dayal D, Kumar S (2015) Assessment of reservoir sedimentation in arid region watershed of Gujarat. J Agric Eng, ISAE 52(4):40–49

    Google Scholar 

  • Machiwal D, Kumar S, Dayal D, Mangalassery S (2016a) Identifying abrupt changes and detecting gradual trends of annual rainfall in an Indian arid region under heightened rainfall rise regime. Int J Climatol 37:2719–2733. https://doi.org/10.1002/joc.4875

    Article  Google Scholar 

  • Machiwal D, Kumar S, Dayal D (2016b) Characterizing rainfall of hot arid region by using time series modeling and sustainability approaches: a case study from Gujarat, India. Theor Appl Climatol 124:593–607

    Article  Google Scholar 

  • Mann HB (1945) Non-parametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Martinez CJ, Maleski JJ, Miller MF (2012) Trends in precipitation and temperature in Florida, USA. J Hydrol 452-453:259–281

    Article  Google Scholar 

  • Matalas NC, Langbein WB (1962) Information content of the mean. J Geophys Res 67(9):3441–3448

    Article  Google Scholar 

  • Matalas NC, Sankarasubramanian A (2003) Effect of persistence on trend detection via regression. Water Resour Res 39(12):WR002292

    Article  Google Scholar 

  • McGhee JW (1985) Introductory statistics. West Publishing Co., New York

    Google Scholar 

  • Mukherjee S (2008) Cosmic influence on the sun-earth environment. Sensors 8:7736–7752

    Article  Google Scholar 

  • Pant GB, Rupa Kumar K (1997) Climates of South Asia. John Wiley & Sons, Chichester 320p

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Prusty BAK (2012) Ambient air quality surveillance and indexing in and around mining clusters in western Kachchh region, Gujarat, India. Open J Air Pollut 1:22–30

    Article  Google Scholar 

  • Ramadan HH, Beighley RE, Ramamurthy AS (2013) Temperature and precipitation trends in Lebanon’s largest river: the Litani Basin. J Water Resour Plann Manag, ASCE 139:86–95

    Article  Google Scholar 

  • Rao P, Vivekanandan E (2008) Impact of climate change on Indian marine fisheries. Bay of Bengal news, March–June 2008, Central Marine Fisheries Research Institute (CMFRI), Kerala, India, pp. 32–37

  • Rao BB, Chowdary PS, Sandeep VM, Rao VUM, Venkateswarlu B (2014) Rising minimum temperature trends over India in recent decades: implications for agricultural production. Glob Planet Chang 117:1–8

    Article  Google Scholar 

  • Revadekar JV, Preethi B (2010) Statistical analysis of the relationship between summer monsoon precipitation extremes and food grain yield over India. Int J Climatol 32(3):419–429

    Article  Google Scholar 

  • Saboohi R, Soltani S, Khodagholi M (2012) Trend analysis of temperature parameters in Iran. Theor Appl Climatol 109(3–4):529–547

    Article  Google Scholar 

  • Saha S, Moorthi S, Pan H-L, Wu X, Wang J, Nadiga S, Tripp P, Kistler R, Woollen J, Behringer D, Liu H, Stokes D, Grumbine R, Gayno G, Wang J, Hou Y-T, Chuang H-Y, Juang H-MH, Sela J, Iredell M, Treadon R, Kleist D, Van Delst P, Keyser D, Derber J, Ek M, Meng J, Wei H, Yang R, Lord S, Van Den Dool H, Kumar A, Wang W, Long C, Chelliah M, Xue Y, Huang B, Schemm J-K, Ebisuzaki W, Lin R, Xie P, Chen M, Zhou S, Higgins W, Zou C-Z, Liu Q, Chen Y, Han Y, Cucurull L, Reynolds RW, Rutledge G, Goldberg M (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91:1015–1057

    Article  Google Scholar 

  • Salas JD (1993) Analysis and modeling of hydrologic time series. In: Maidment DR (ed) (editor-in-chief)Handbook of Hydrology. McGraw-Hill, Inc., New York, pp 19.1–19.72

    Google Scholar 

  • Salas JD, Delleur JW, Yevjevich VM, Lane WL (1980) Applied modeling of hydrologic time series. Water Resources Publications, Littleton, Colorado

    Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall's tau. J Am Stat Assoc 63(324):1379–1389

    Article  Google Scholar 

  • Şen Z (2015) Innovative trend significance test and applications. Theor Appl Climatol 127:939–947. https://doi.org/10.1007/s00704-015-1681-x

    Article  Google Scholar 

  • Shah R, Mishra V (2014) Evaluation of the reanalysis products for the monsoon season droughts in India. J Hydrometeorol 15:1575–1591

    Article  Google Scholar 

  • Singh S, Kar A (1996) Integrated natural and human resources appraisal for sustainable development of Kachchh District. Report of Central Arid Zone Research Institute (CAZRI), Jodhpur

    Google Scholar 

  • Snedecor GW, Cochran WG (1980) Statistical methods. Iowa State University Press, Ames, Iowa

    Google Scholar 

  • Sonali P, Kumar DN (2013) Review of trend detection methods and their application to detect temperature changes in India. J Hydrol 476:212–227

    Article  Google Scholar 

  • Talaee PH (2014) Iranian rainfall series analysis by means of nonparametric tests. Theor Appl Climatol 116(3–4):597–607

    Article  Google Scholar 

  • Tian J, Liu J, Wang J, Li C, Nie H, Yu F (2017) Trend analysis of temperature and precipitation extremes in major grain producing area of China. Int J Climatol 37(2):672–687

    Article  Google Scholar 

  • Trenberth KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Klein Tank A, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, Zhai P (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: The Physics Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York

    Google Scholar 

  • Trivedi PC, Joshi HP, Parvez IA (2014) A preliminary study on rainfall pattern before and after the January 26, 2001 Bhuj earthquake (Mw 7.7) over Kachchh region of western peninsular India. Int J Geosci 5:1080–1087

    Article  Google Scholar 

  • Ul Shafiq M, Rasool R, Ahmed P, Dimri AP (2018) Temperature and precipitation trends in Kashmir valley, North West Himalayas. Theor Appl Climatol, DOI: https://doi.org/10.1007/s00704-018-2377-9

  • USEPA (2006) Data quality assessment: statistical methods for practitioners. In: Guidance Document EPA QA/G-9S. Washington D.C, US Environmental Protection Agency (USEPA), Office of Environmental Information

    Google Scholar 

  • Vivekanandan E, Hussain Ali M, Jasper B, Rajagopalan M (2008) Thermal thresholds for coral bleaching in the Indian seas. J Mar Biol Assoc India 50(2):209–214

    Google Scholar 

  • von Storch H (1995) Misuses of statistical analysis in climate research. In: von Storch H, Navarra A (eds) Analysis of climate variability: applications of statistical techniques. Springer, Berlin

    Chapter  Google Scholar 

  • Xia F, Liu X, Xu J, Wang Z, Huang J, Brookes PC (2015) Trends in the daily and extreme temperatures in the Qiantang River basin, China. Int J Climatol 35(1):57–68

    Article  Google Scholar 

  • Xu L, Zhou H, Du L, Yao H, Wang H (2015) Precipitation trends and variability from 1950 to 2000 in arid lands of Central Asia. J Arid Land 7(4):514–526

    Article  Google Scholar 

  • Yang P, Xia J, Zhang Y, Hong S (2017) Temporal and spatial variations of precipitation in Northwest China during 1960–2013. Atmos Res 183:283–295

    Article  Google Scholar 

  • Yue S, Wang CY (2002) Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test. Water Resour Res 38(6):4–1 – 4-7. https://doi.org/10.1029/2001WR000861

    Article  Google Scholar 

  • Yue S, Wang CY (2004) The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18:201–218

    Article  Google Scholar 

  • Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829

    Article  Google Scholar 

  • Zhang X, Vincent LA, Hogg WD, Niitsoo A (2000) Temperature and precipitation trends in Canada during the 20th century. Atmosphere-Ocean 38:395–429

    Article  Google Scholar 

  • Zhang X, Harvey KD, Hogg WD, Yuzyk TR (2001) Trends in Canadian streamflow. Water Resour Res 37(4):987–998

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the reviewers for their useful comments that helped in improving the earlier version of this article.

Author information

Author notes

  1. Ankit Gupta

    Present address: National Remote Sensing Center, Indian Space Research Organization (ISRO), Hyderabad, Andhra Pradesh, India

Authors and Affiliations

  1. ICAR-Central Arid Zone Research Institute (CAZRI), Regional Research Station, Kukma, Bhuj, Gujarat, 370105, India

    Deepesh Machiwal

  2. Regional Remote Sensing Centre-West, NRSC, Indian Space Research Organization (ISRO), DOS, CAZRI Campus, Jodhpur, Rajasthan, 342003, India

    Ankit Gupta

  3. Agricultural and Food Engineering Department, Indian Institute of Technology, Kharagpur, West Bengal, 721302, India

    Madan Kumar Jha

  4. Sir Choturam College of Agricultural Engineering & Technology, Phoenix Foundation, Latur, Maharashtra, 413512, India

    Trupti Kamble

Authors
  1. Deepesh Machiwal
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Ankit Gupta
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Madan Kumar Jha
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Trupti Kamble
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Deepesh Machiwal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Machiwal, D., Gupta, A., Jha, M.K. et al. Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques. Theor Appl Climatol 136, 301–320 (2019). https://doi.org/10.1007/s00704-018-2487-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-018-2487-4