Trends of seasonal and annual rainfall of semi-arid districts of Karnataka, India: application of innovative trend analysis approach

Abstract

Trend analysis of rainfall is often carried out in water resources management to understand its distribution over a given region. The cumulative seasonal and annual rainfall derived from monthly datasets spanning 102 years for 11 districts of the semi-arid Karnataka, India, was used for the trend analysis. The two-step homogeneous test approach was carried out on all the time series. Then, lag-1 autocorrelation was conducted only on homogeneous time series. Only 78.18% of the total time series data was detected as homogeneous, and 95.35% of time series data were found to have insigni cant autocorrelation. Then, the Innovative Trend Analysis (ITA) method was applied to 43 homogeneous rainfall time series, MK and SR tests to 41 time series, and mMK test to two time series. The MK and SR tests detected 14.63% of the time series as a signi cant trend, whereas the ITA method could detect 93.02% of the total time series data. The MK and SR tests captured signi cant trends for the winter season in two districts, but the two tests detected a signi cant trend only in one district for the summer season. None could be captured for monsoon season. A signi cant trend was captured for the post-monsoon season in two districts; however, the tests could detect a signi cant trend in one district for annual rainfall. The mMK test revealed a positive trend for the post-monsoon season in a district. The ITA method could capture a signi cant trend for all the seasons in most districts.

Trends and forecasts of extreme rainfall in small, medium and large towns in Burkina Faso: a non-parametric statistical analysis and Holt-Winters Smoothing Method (West Africa)

“…The presence of a trend is indicated by a 1:1 (45°) line in the scatterplot. Coordinates on the 45° line indicate no trend, below it a negative trend and above it an upward trend [2,11]. A detailed interpretation of the ITAM is presented by [14] and recorded in Figure 2 below.…”

Trend Analysis of Rainfall and Detection of Change Point in Terai Zone of West Bengal

“…Significantly, the ITA method eliminates the necessity for prewhitening time series data [14]. The effectiveness of ITA method in detecting rainfall trends was demonstrated in several studies [15,16]. This research seeks to contribute valuable insights in rainfall trends in Cooch Behar district of West Bengal by employing statistical techniques such as Mann-Kendall, Modified Mann-Kendall, and Sen's slope but these methods are highly dependent on sample size and data distribution.…”