Assessing impact of climate change on rainfall patterns of Karaikal region, Puducherry, India

Introduction

Climate change is a global phenomenon that significantly influences atmospheric processes, particularly precipitation patterns. Changes in rainfall distribution, intensity, and frequency can have profound effects on water resource management, agriculture, and overall ecosystem sustainability (IPCC, 2021) [2] . The Indian subcontinent, particularly coastal regions, is highly vulnerable to climate-induced variations in precipitation, making it essential to study long-term trends in regional rainfall patterns (Guhathakurta et al., 2015) [3] . Karaikal is situated on the east coast of India, near latitude 11 N in the deltaic region of the Cauvery, experiences tropical maritime type of climate with small daily range of temperature and moderate rainfall (Pai et al., 2014 and Dash et al., 2009) [8,1] . Karaikal has an annual average rainfall of about 126 cm. 68 percent of which occurs during October to December. The amount of rainfall during the south-west monsoon period is small, being less than 20 per cent of the annual. November is the rainiest month, accounting for about a third of the annual total. The range of variation of annual rainfall is wide (IMD, 2023) [4] . As monsoonal rainfall plays a critical role in agriculture, groundwater recharge, and water resource planning, any alterations in its distribution or intensity can pose challenges to local communities and policymakers (Kripalani & Kulkarni, 1997; Roxy et al., 2017) [6,10] . Several studies have highlighted shifting monsoon patterns across India, with evidence of decreasing rainfall in some regions and increasing extreme rainfall events in others (Rajeevan et al., 2008; Kothawale et al., 2010) [9,5] . However, there is limited region-specific analysis focusing on the long-term rainfall variability in Karaikal. Understanding precipitation trends in this region is crucial, as it can aid in climate adaptation strategies, water conservation planning, and disaster preparedness (Nair et al., 2018) [7] .

Study Area

The Union Territory of Puducherry consists of two districts, viz., Puducherry and Karaikal, situated at different geographical locations isolated from one another. Puducherry District comprises Puducherry, Mahe and Yanam regions. Karaikal region forms the Karaikal District. Karaikal region is about 130 Km. south of Puducherry and is sandwiched by Nagapattinam District of Tamil Nadu. It is located between 10o 49' and 11o 01' N, and 79o 43' and 79o 52' E. Forming part of fertile delta, the Karaikal region is completely covered by the distributaries of Cauvery River. Covered completely by a thick mantle of alluvium of variable thickness, the region is flat having gentle slope towards Bay of Bengal in the east. It is limited on the north by the Nandalar and on the south east by the Vettar. The group of rocks known as Cuddalore formations is contiguous to along with those in the Tanjore District.

Materials and Methods

The daily precipitation records were kindly furnished by the Department of Agronomy, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal, U.T of Puducherry. Subsequently, these data points were methodically categorised according to average seasonal rainfall patterns during the postmonsoon period encompassing January and February. It should be noted that March through May are identified as pre-monsoon months whereas June through September fall within the realm of Southwest monsoon months. Lastly, October to December is acknowledged as Northeast monsoon timeframe. This allowed for the computation of the average annual rainfall for the previous 29 years. The rainfall station in the investigation region of Karaikal, are utilised to calculate twenty nine years of rainfall data (1996-2024). The data were used to calculate weekly, monthly, annual and seasonal average rainfall. The yearly average rainfall was finally calculated and interpreted using the data specified above. The mean, standard deviation (SD), and coefficient of variation (CV) of rainfall were calculated using Microsoft Excel to analyze the variability and distribution of precipitation patterns in the Karaikal region. These statistical measures provide insights into the consistency and fluctuation of rainfall over the study period, aiding in the assessment of longterm climatic trends.

Mean weekly, monthly and annual analysis Co-efficient of variation

Co-efficient, of variation is used to understand the behavior of rainfall in terms of its variability over time. Higher the CV, lower the dependability and vice versa. There is a strong relationship exists between CV and rainfall dependability.

Procedure

The variability of rainfall is determined by working out the CV. It is a unit free measure and always expressed in percentage. The formula based in this method is

Where, CV = Co-efficient of variation.

SD = Standard deviation X = Mean

For doing such analysis, rainfall data from long term records are required atleast for a block of 30 years for more precision on results. The following are the threshold levels of CV for any interpretation.

Period CV Permissible

• Yearly rainfall: It must be < 25 per cent.

• Seasonal rainfall: < 50 per cent.

• Monthly rainfall: < 100 per cent.

• Weekly rainfall: < 150 per cent.

• Daily rainfall: < 250 per cent. (Veeraputhiran et al., 2003) [11] . The rainfall data of Karaikal from 1996-2024 were analysed for CV and the results are presented here under.

The analysed data reveals a higher value for the 13 th std week i.e. 32500% which shows that the dependability of getting 0.10mm is very low. A lowest CV value is found in the 45 th std week (25.7%) which shows that there is a higher dependability of rainfall in this week.

Monthly rainfall (Table 2)

The data indicates that the highest mean monthly rainfall is recorded during November (427.45 mm) followed by October (282.57 mm) and this was 31 and 20 per cent to the total mean annual rainfall respectively. By considering the CV, the month November registered the lowest CV (60%) followed by October (61%) indicating more dependability during these months. For monthly rainfall the threshold level of CV range of 50-100 per cent was associated with July to October and December this indicated the great dependability of rainfall in these months as compared to other months. During January to June highest CV value (more than or equal 100 per cent) indicates the less dependability of getting rainfall during these months.

Annual

The mean annual rainfall of Karaikal was 1347.96 mm and the annual CV is 29.22 percent.

Seasonal rainfall (Table 3)

The data reveals that the highest mean seasonal rainfall of 914.30 mm is recorded during North East Monsoon (NEM) season was followed by Southwest Monsoon (SWM) season (250.46 mm). The mean summer rainfall received is 103.94 mm and that of winter season is 79.25 mm. The contribution to mean annual rainfall by NEM, SWM, summer and winter seasons is 68.94, 18.88, 7.8 and 5.9 per cent respectively Considering the CV it is observed that NEM received the lowest CV (68.85 percent) followed by the SWM (82.15 percent) for summer season (147.19 percent). The highest CV of 157.35 percent is found for winter season indicating higher rainfall variability during this season. Thus from CV study it can be inferred that the possibility of getting higher% rainfall lies with NEM followed by SWM, SUMMER and WINTER.

Conclusion

The present study provides a comprehensive analysis of rainfall variability over the Karaikal region of the Union Territory of Puducherry for a period of 29 years (1996-2024). The findings reveal that Karaikal receives an average annual rainfall of 1347.96 mm, predominantly contributed by the Northeast Monsoon (NEM) season (68.94%), followed by the Southwest Monsoon (SWM) (18.88%), summer (7.8%), and winter (5.9%). The coefficient of variation (CV) analysis highlights substantial inter-annual and intra-seasonal variability, especially during the winter and summer months, indicating reduced predictability and reliability of rainfall in these periods. Notably, the NEM exhibits comparatively lower variability, making it the most dependable rainfall season for the region. However, the observed shifts in rainfall distribution and intensity, including extreme fluctuations in certain weeks and months, suggest the influence of broader climate change phenomena, aligning with trends reported across coastal India. These findings underscore the urgent need for region-specific water management strategies, adaptive agricultural planning, and early warning systems to mitigate the adverse impacts of changing rainfall regimes. Continued monitoring, incorporation of climate models, and integration of satellite and ground-based data are essential to refine predictions and support local climate resilience planning. Ultimately, such data-driven insights can assist policymakers, farmers, and planners in formulating effective climate adaptation and mitigation strategies tailored to Karaikal and similar coastal regions.

Disclaimer (Artificial Intelligence)

Author(s) hereby declare that NO generative AI technologies such as Large Language Models (ChatGPT, COPILOT, etc) and text-to-image generators have been used during writing or editing of this manuscript.

Competing Interests

Authors have declared that no competing interests exist

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