Comparative performance of nonparametric methods for detecting rainfall trends in West Garo Hills, Meghalaya, India
Year: 2025
Type: article
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.
Institutions: Assam Down Town University, Manipur International University
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: diamond
OpenAlex ID: W7116631191
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