Seasonal and Annual Rainfall Trend Analysis in Aurangabad District of Maharashtra State, India Using the Mann–Kendall Test
Harish H Deshpande, Harshada P Deshmukh
International Journal of Environment and Climate Change · pp. 107–116 · Published 5 Feb 2026
10.9734/ijecc/2026/v16i25269Abstract
The analysis of rainfall trends across various stations in the Aurangabad district is essential for understanding regional climate patterns and their implications for agriculture and water resource management. This study employs both descriptive statistics and the Mann-Kendall trend analysis to examine the rainfall data across multiple stations (Year: 1970–2023), including Sillod, Vaijapur, Soageon, Phulambri, and others. Descriptive statistics were used to assess central tendency, variability, and distribution shape, revealing notable differences in average rainfall (mean ranging from 587.96 mm at Sillod to 741.29 mm at Khuldabad) and variability (standard deviations from 174.97 mm at Phulambri to 216.25 mm at Paithan). The analysis also highlighted differences in distribution shapes, with stations like Paithan exhibiting higher kurtosis, indicating more extreme rainfall values. The Mann-Kendall trend analysis, applied to seasonal and annual data, provided insights into temporal trends across stations. The results revealed that Sillod exhibited a statistically significant increasing trend, with a z-score of 2.55 and a p-value of 0.01, suggesting a clear upward trend in rainfall over time. Conversely, other stations like Vaijapur, Soageon, Paithan, and Gangapur showed weaker or insignificant trends. In the Rabi and Summer seasons, most stations displayed minimal or no statistically significant trends. The annual data similarly revealed that Sillod had a significant increasing trend, while the other stations showed relatively stable rainfall patterns. These findings underscore the heterogeneous rainfall patterns across Aurangabad, with some stations experiencing significant changes over time, while others remain relatively stable, providing valuable insights for local agricultural planning and water resource management.
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