Comparative performance of nonparametric methods for detecting rainfall trends in West Garo Hills, Meghalaya, India
Article Main
Abstract
Rainfall variability in Meghalaya’s West Garo Hills significantly impacts agriculture, water resources, and ecological stability, necessitating robust trend analysis for effective climate adaptation. This study examines long-term trends in annual and seasonal rainfall using advanced nonparametric techniques. Rainfall data (1984–2023) were analyzed using Mann-Kendall and its modified variants (MMKY, PWMK, TFPWMK, SMK, CSMK), supported by normality and randomness tests. Statistical diagnostics confirmed non-normality, non-randomness, and autocorrelation in the dataset.The MK test revealed a significant negative trend (Z = -2.697, p = 0.007; slope = -0.0738 mm/year), corroborated by TFPWMK (Z = -2.782, p = 0.0054) and CSMK (Z = -4.0468, p = 5.19e-05). Seasonal MK detected strong seasonal effects (Z = -5.9655, p = 2.44e-09), while autocorrelation-adjusted methods confirmed trend persistence.The novelty lies in a comparative scoring framework that identifies CSMK as the most robust method, offering high statistical power, interpretability, and resilience to autocorrelation and seasonality. These findings support the adoption of climate-resilient agriculture, water conservation, and effective policy planning in Northeast India.
Article Details
Article Details
Keywords
Correlated Seasonal MK test, Modified MK test, Performance , Rainfall, Trend
References
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Kubiak-Wójcicka, K., Pilarska, A. & Kamiński, D. (2021). The analysis of long-term trends in meteorological and hydrological drought occurrences using nonparametric methods — case study of the catchment of the upper Noteć River (central Poland). Atmosphere, 12(9), 1098. https://doi.org/10.3390/atmos12091098
Kumar, S. & Kumar, S. (2015). Rainfall variability analysis and its impact on crop production in Bihar. African Journal of Agricultural Research, 10(9), 983–989. https://doi.org/10.5897/ajar2013.8417
Kumar, S., Kant, S. & Ahmed, R. (2025). Assessment of an extreme heavy rainfall over Meghalaya, India on 16 & 17 June 2022: A case study using meteorological and remote sensing observations. Tropical Cyclone Research and Review, 14(2), 60–70. https://doi.org/10.1016/j.tcrr.2025.02.007
Lahin, F., Singh, N. U. & Singh, R. K. (2017). Assessing climate change impact on rainfall patterns in Northeastern India and its consequences on water resources and rainfed agriculture. Journal of Applied and Natural Science, 9(1), 510–516. https://doi.org/10.31018/jans.v9i1.1234
Papalexiou, S. M. & Montanari, A. (2019). Global and regional increase of precipitation extremes under global warming. Water Resources Research, 55, 4901–4914. https://doi.org/10.1029/2018WR024067
Patle, G. & Libang, T. (2014). Variability and trend analysis of rainfall data of Shillong and Agartala stations of North-East India. Journal of Applied and Natural Science, 6(2), 728–732
Ray, L. I. P. & Sheikh, F. (2013). Estimation of annual maximum rainfall for Central Meghalaya. Journal of Applied and Natural Science, 5(1), 123–129.
Sangma, M. L. K., Reang, H., Patle, G. T. & Dabral, P. P. (2020). Variability and trend analysis of rainfall data of Shillong and Agartala stations of Northeast India. International Journal of Environment and Climate Change, 10(1), 134. https://doi.org/10.9734/ijecc/2020/v10i1130273
Singh, A. M., Elangbam, G., Sharma, G. N., Singh, T. C. & Teresa, K. (2025). Long-term rainfall seasonality trends and abrupt shifts in the Northeast Indian province of Manipur. Discover Sustainability, 6, 881. [https://doi.org/10.1007/s43621-025-01777-7]
SINGH, P. & KUMAR, N. (2022). Analysis of trend and temporal variability in rainfall over Northeast India. MAUSAM, 73(2), 307–314. https://doi.org/10.54302/mausam.v73i2.5479
Tanti, K. K., Saikia, N. M. & Swer, M. (2016). An investigation of trends and variability of rainfall in Shillong city. World academy of science, engineering and technology, International Journal of Environmental and Ecological Engineering, 3(6). http://waset.org/abstracts/environmen tal-and-ecological-engineering/45927
Alashan, S. (2020). Combination of modified Mann–Kendall method and Şen innovative trend analysis. Engineering Reports, 2, e12131. https://doi.org/10.1002/eng2.12131
Barman, N. & Gokhale, S. (2023). Transported aerosols regulate the pre-monsoon rainfall over north-east India: A WRF-Chem modelling study. Atmospheric Chemistry and Physics, 23, 6197–6212. https://doi.org/10.5194/acp-23-6197-2023
Datta, P. & Bose, S. (2020). Assessing the changes in climate extremes over Karbi Anglong district of Assam, North-East India. Spatial Information Research, 28(5), 547. https://doi.org/10.1007/s41324-020-00312-2
Chakraborty, D., Roy, A., Singh, N. U., Saha, S., Das, S. K., Mridha, N., Yumnam, A., Paul, P., Gowda, C.& Biam, K. P., et al. (2025). Assessing climate change impact on rainfall patterns in Northeastern India and its consequences on water resources and rainfed agriculture. Earth, 6(1), 2. https://doi.org/10.3390/earth6010002
Chetia, M., et al. (2025). Rainfall and temperature trends in northeastern states of India: Implications for agricultural productivity (1970–2023). Journal of Agricultural & Environmental Management, 27(2). https://www.researchgate.net/publication/392378249
De, U. K., Apal, M. & Bodosa, K. (2015). Global warming and the pattern of overall climate changes in Sub-Himalayan Assam region of North-East India. International Journal of Ecological Economics and Statistics, 36(3), 88. http://ceser.in/ceserp/index.php/ijees/article/view/3775
Deka, S. (2021). Statistical analysis of long-term rainfall trends in Cherrapunji, Meghalaya, India. Journal of Applied and Natural Science, 13(1), 170–177. https://doi.org/10.31018/jans.v13i1.2442
District and Local Research Station Laboratories. (2023). Rainfall data for West Garo Hills, Meghalaya (1984–2023) [Dataset]. Sangsanggre, Tura, India. Available upon request from the district and local research station laboratories.
Dzupire, N., Ngare, P. & Odongo, L. (2020). A copula-based bivariate model for temperature and rainfall processes. Scientific African, 8, e00365. https://doi.org/10.1016/j.sciaf.2020.e00365
Fuwape, I. & Ogunjo, S. (2018). Modeling of rainy season onset and cessation of tropical rainfall for climate change adaptation in agriculture. arXiv preprint. https://doi.org/10.48550/arXiv.1811.09677
Halder, B., Saha, A. & Das, P. K. (2024). Long-term climate change analysis in northeast India. International Journal of Climatology, 44(12), 6874–6891. https://doi.org/10.1080/19475705.2024.2409206
Hirsch, R. M. & Slack, J. R. (1984). A nonparametric trend test for seasonal data with serial dependence. Water Resources Research, 20(6), 727–732. https://doi.org/10.1029/WR020i006p00727
Homagarani, Y. M., Adlparvar, K., Teimuri, S., Tarrahi, M. J. & Nilchian, F. (2023). The effect of diabetes mellitus on oral health-related quality of life: A systematic review and meta-analysis. Frontiers in Public Health, 11, 1112008. https://doi.org/10.3389/fpubh.2023.1112008
Kamal, N. & Pachauri, S. (2019). Mann–Kendall and Sen’s slope estimators for precipitation trend analysis in northeastern states of India. International Journal of Computer Applications, 177(11), 7. https://doi.org/10.5120/ijca2019919453
Krishi Jagran. (2021, December 1). Farmers in Meghalaya earn the most, according to the government in its report to Lok Sabha. Krishi Jagran. https://krishijagran.com/agriculture-world/farmers-in-meghalaya-earn-the-most-government-in-its-report-to-lok-sabha/
Kubiak-Wójcicka, K., Pilarska, A. & Kamiński, D. (2021). The analysis of long-term trends in meteorological and hydrological drought occurrences using nonparametric methods — case study of the catchment of the upper Noteć River (central Poland). Atmosphere, 12(9), 1098. https://doi.org/10.3390/atmos12091098
Kumar, S. & Kumar, S. (2015). Rainfall variability analysis and its impact on crop production in Bihar. African Journal of Agricultural Research, 10(9), 983–989. https://doi.org/10.5897/ajar2013.8417
Kumar, S., Kant, S. & Ahmed, R. (2025). Assessment of an extreme heavy rainfall over Meghalaya, India on 16 & 17 June 2022: A case study using meteorological and remote sensing observations. Tropical Cyclone Research and Review, 14(2), 60–70. https://doi.org/10.1016/j.tcrr.2025.02.007
Lahin, F., Singh, N. U. & Singh, R. K. (2017). Assessing climate change impact on rainfall patterns in Northeastern India and its consequences on water resources and rainfed agriculture. Journal of Applied and Natural Science, 9(1), 510–516. https://doi.org/10.31018/jans.v9i1.1234
Papalexiou, S. M. & Montanari, A. (2019). Global and regional increase of precipitation extremes under global warming. Water Resources Research, 55, 4901–4914. https://doi.org/10.1029/2018WR024067
Patle, G. & Libang, T. (2014). Variability and trend analysis of rainfall data of Shillong and Agartala stations of North-East India. Journal of Applied and Natural Science, 6(2), 728–732
Ray, L. I. P. & Sheikh, F. (2013). Estimation of annual maximum rainfall for Central Meghalaya. Journal of Applied and Natural Science, 5(1), 123–129.
Sangma, M. L. K., Reang, H., Patle, G. T. & Dabral, P. P. (2020). Variability and trend analysis of rainfall data of Shillong and Agartala stations of Northeast India. International Journal of Environment and Climate Change, 10(1), 134. https://doi.org/10.9734/ijecc/2020/v10i1130273
Singh, A. M., Elangbam, G., Sharma, G. N., Singh, T. C. & Teresa, K. (2025). Long-term rainfall seasonality trends and abrupt shifts in the Northeast Indian province of Manipur. Discover Sustainability, 6, 881. [https://doi.org/10.1007/s43621-025-01777-7]
SINGH, P. & KUMAR, N. (2022). Analysis of trend and temporal variability in rainfall over Northeast India. MAUSAM, 73(2), 307–314. https://doi.org/10.54302/mausam.v73i2.5479
Tanti, K. K., Saikia, N. M. & Swer, M. (2016). An investigation of trends and variability of rainfall in Shillong city. World academy of science, engineering and technology, International Journal of Environmental and Ecological Engineering, 3(6). http://waset.org/abstracts/environmen tal-and-ecological-engineering/45927
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Comparative performance of nonparametric methods for detecting rainfall trends in West Garo Hills, Meghalaya, India. (2025). Journal of Applied and Natural Science, 17(4), 1809-1818. https://doi.org/10.31018/jans.v17i4.6873
