Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India

M. Manikandan *

Agricultural Research Station, Tamil Nadu Agricultural University, Kovilpatti, India.

M. Nagarajan

Agricultural Engineering College and Research Institute, Tamil Nadu Agricultural University, Kumulur, India.

N. Anandaraj

Agricultural College & Research Institute, Tamil Nadu Agricultural University, Eachangkottai, India.

*Author to whom correspondence should be addressed.


Abstract

Analyzing the variability and trends of rainfall plays a major role in water resource planning and management. Changes in rainfall patterns significantly influence the water availability in the irrigation structures and agronomical practices of crops.  This study aimed to investigate the trends and estimate the magnitudes of monthly, seasonal, and annual rainfall series in Tenkasi, Tamil Nadu, India, using 49 years of rainfall data from 1971 to 2019. Sen’s Innovative trend analysis (ITA) method, Mann-Kendall (MK), and Simple Linear Regression (SLR) test were applied to assess the trends at 5 and 10 % significance levels. Trend magnitudes were estimated by Sen’s slope estimator (SSE) and SLR method. Changes in rainfall magnitude with mean values in percentage were estimated for all three slope estimation methods. The results revealed that the ITA method detected more significant trends of rainfall series over other methods. Significant downward trends were exhibited by October and north east monsoon (NEM) rainfall series had a trend magnitude of -0.43 mm/year and -0.04 mm/year. The percentage change in magnitude of the trend from mean values for October and the NEM series was -11.5% and -0.39%. Sub-trends within the October and NEM rainfall series showed that the low rainfall sub-series exhibited no trend, medium and high rainfall sub-series showed a downward trend. This study concluded that, in comparison to traditional trend analysis methods, the ITA method demonstrated a more rigorous investigation of trends. The significant decrease in rainfall during the NEM necessitates greater attention to water resources planning and management, serving as valuable scientific information for both crop planning and water resource management.

Keywords: Innovative trend analysis (ITA), Mann-Kendall, rainfall, regression, slope, trend


How to Cite

Manikandan , M., Nagarajan , M., & Anandaraj , N. (2024). Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India. International Journal of Environment and Climate Change, 14(2), 590–600. https://doi.org/10.9734/ijecc/2024/v14i23974

Downloads

Download data is not yet available.

References

IPCC. Summary for policymakers. In: Global warming of 1.5°C. 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. World Meteorol. Organ. Geneva, Switzerland. 2018;106:32.

Şen Z. Innovative trend analysis methodology. J Hydrol Eng. 2012; 17:1042–1046.

Malik A, Kumar A, Guhathakurta P, Kisi O. Spatial-temporal trend analysis of seasonal and annual rainfall (1966–2015) using innovative trend analysis method with significance test. Arabian Journal of Geosciences. 2019;12:328.

Singh RN, Sah S, Das B, Potekar S, Chaudhary A, Pathak H. Innovative trend analysis of spatio-temporal variations of rainfall in India during 1901–2019. Theoretical and Applied Climatology. 2021;145:821–838.

Sonali P, Nageshkumar D. Review of trend detection methods and their application to detect temperature changes in India. Journal of Hydrology. 2013;476:212–227.

Wang Y, Xu Y, Tabari H, Wang J, Wang Q, Song S, Hu Z. Innovative trend analysis of annual and seasonal rainfall in the Yangtze River Delta, eastern China. Atmospheric Research. 2020; 231:104673.

Gajbhiye S, Meshram C, Mirabbasi R, Sharma SK. Trend analysis of rainfall time series for Sindh river basin in India. Theoretical and Applied Climatology. 2015;125: 593–608.

Dinpashoh Y, Singh VP, Biazar SM, Kavehka S. Impact of climate change on streamflow timing (case study: Guilan Province). Theoretical and Applied Climatology. 2019. Available:https://doi.org/10.1007/s00704-019-02810-2

Kumar S, Machiwal D, Dayal D. Spatial modelling of rainfall trends using satellite datasets and geographic information system. Hydrol Sci J. 2017;62(10):1–18.

Machiwal D, Jha MK. Evaluating persistence and identifying trends and abrupt changes in monthly and annual rainfalls of a semi-arid region in Western India. Theoretical and Applied Climatology. 2017;128: 689–708.

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

Singh R, Sah S, Das B. Spatio-temporal trends and variability of rainfall in Maharashtra, India: analysis of 118 years. Theoretical and Applied Climatology. 2020. Available:https://doi.org/10.1007/s00704-020-03452-5

Marak JDK, Sarma AK, Bhattacharjya RK. Innovative trend analysis of spatial and temporal rainfall variations in Umiam and Umtru watersheds in Meghalaya, India. Theoretical and Applied Climatology. 2020;142:1397–1412.

Pastagia J, Mehta, D. Application of innovative trend analysis on rainfall time series over Rajsamand district of Rajasthan state. Water Supply. 2022;22(9):7189. DOI: 10.2166/ws.2022.276

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

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

Meshram SG, Singh VP, Meshram C. Long-term trend and variability of precipitation in Chhattisgarh State, India. Theoretical and Applied Climatology. 2017;129:729–744.

Machiwal D, Gupta A, Jhaand MK, Kamble T. Analysis of trend in temperature and rainfall time series of an Indian arid region: Comparative evaluation of salient techniques. Theoretical and Applied Climatology. 2018;136:301–320.

Sen PK. Estimates of the regression coefficient based on Kendall’stau. Journal of American Statistical Association; 1968. Available:https://doi.org/10.1080/01621459.1968. 10480934

Machiwal D, Jha MK. Hydrologic time series analysis: Theory and practice. 1sted. New Delhi, India: Springer, Germany and Capital Publishing Company; 2012.

Malik A, Kumar A. Spatio-temporal trend analysis of rainfall using parametric and non-parametric tests: Case study in Uttarakhand, India. Theoretical and Applied Climatology. 2020. Available:https://doi.org/10.1007/s00704-019-03080-8

Sen Z. Trend identification simulation and application. J. Hydrol. Eng. 2014; 19(3):635–642.

Sen Z. Innovative trend significance test and applications. Theoretical and Applied Climatology. 2017;127: 939–947.

Meena HM, Machiwal D, Santra P, Moharana PC, Singh DV. Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India. Theoretical and Applied Climatology; 2018. Available:https://doi.org/10.1007/s00704-018-2510-9

Sanikhani H, Kisi O, Mirabbasi R, Meshram SG. Trend analysis of rainfall pattern over the Central India during 1901–2010. Arabian Journal of Geoscience. 2018;11:437.

Suryavanshi S, Pandey A, Chaube UC, Joshi N. Long-term historic changes in climatic variables of Betwa Basin, India. Theoretical and Applied Climatology. 2014;117:403–418.