Climate and rainfall trend analysis in Ramanathapuram district, Tamil Nadu

Introduction

Over the past century, the earth's climate has changed in terms of temperature and rainfall variations. Changes in precipitation patterns are the primary effect of climate change. A study of hydrologic design and management techniques is necessary because changes in rainfall brought on by global warming will affect the hydrological cycle, stream flow patterns, and demands (especially in agriculture) (John, 2018) [10] .Researchers from all around the world have investigated climate change in an effort to understand the trajectory of different climatic indicators and define rainfall dynamics at the regional to local level (Singh, 2018, Talchabhadel, 2019, Tito et al., 2020, de Oliveira et al., 2021, Ferreira et al., 2021, Teixeira et al., 2021) [19,22,24,5,6,23] . A natural occurrence known as drought is brought on by a region receiving less rainfall than is anticipated; if this condition persists for an extended length of time, there will eventually be insufficient water to support an array of human endeavours (Lalmuanzuala et al., 2023) [12] . Numerous attempts have previously been attempted in India to identify regional and national rainfall trends ( [18,7,14,25,3,17,15,20] . Trend analysis study has been regarded as a valuable tool since it offers important insights about the likelihood of future changes (Islam et al., 2012, Guhathakurta & Rajeevan 2008, Srivastava et al., 2016, Swain et al., 2015) [9, 8, 20, 21] .With proper management of water resources, policymakers may develop efficient hydrological policies to combat drought and lower the risk of flood by using trend analysis of historical rainfall data to understand local rainfall features at the regional level. In order to quantify changes of hydro-meteorological variables viz., temperature and rainfall, trend analysis can be employed (Cengiz et al., 2020, Ay & Kisi 2015) [4,2] . As a result, the state is more susceptible to droughts of various severity and magnitude. The southern region is more vulnerable to drought conditions, particularly during the North East Monsoon Seasons (Ramaraj et al., 2015, Kokilavani et al., 2021) [16,11] www.extensionjournal.com Taking all into consideration, a study was carried out to evaluate the frequency and severity of drought as well as spatial and temporal changes in Ramanathapuram district of Tamil Nadu, with the objective of defining drought.

Materials and Methods

Study area

Tamil Nadu is divided into eight agroclimatic zones, with the North Eastern and South Zones holding the top two positions with 24% and 20% of the total area, respectively, according to a report by the Indian Meteorological Department (IMD). Next behind are the Western Zone (12%), North West Zone (14%), Southern Zone (12%), and Cauvery Delta Zone (15%). Thus, the current study was carried out in Tamil Nadu's Southern Zone. The study area is situated between latitudes 8° 9' and 10° 50' North and longitudes 77° 10' and 79° 25' East. The region stretches from the coastal areas in the east to the high mountain regions in the west. Fig. 1 shows the map of the research area. The elevation diverges from the average sea level of 100 meters

Mann-Kendall (MK) test

As one of the most widely used global techniques for trend detection in hydrology, climatology, and meteorology, the non-parametric Mann-Kendall test was used in this work to identify the trend in rainfall. A time series' trend analysis includes both the trend's statistical significance and magnitude. This statistical technique is employed to investigate the temporal trends and spatial variation of hydroclimatic series(John,2018) [10] .

where this MK test is applied to two time series, xk which is ranked from k=1, 2, …, n-1, and xj which is ranked from j=k+1, 2, …, n. Every data point xk is used as a reference and compared to other data points. sgn(𝜃)={1, 𝜃>0, 0, 𝜃 =0, -1, 𝜃} where the notation t indicates the extent of every specific tie, and t represents the sum of all ties. Z statistics is computed using below equation, where the sample size n should be more than 10 The variance of MK statistic (S) is calculated using below equation.

where positive and negative Z numbers denote the increasing and decreasing trends, respectively.

Standardized precipitation index (SPI)

Standardized precipitation index (SPI): The SPI was designed by transforming the probability of observed into an index (McKee et al., 1993) [13] to quantify the precipitation deficit for multiple time scales. SPI = (Xik-Xi) / Ai; Where, Ai = Standardized deviation for the year; Xik = Precipitation for the year and kth observation; Xi = mean precipitation. For calculating SPI, 33 years or more of continuous monthly precipitation data is needed. Positive SPI values indicate greater than median precipitation and Negative SPI values indicate less than median precipitation. Based on the SPI values, conditions are classified as Extremely wet (SPI > 2.0), Very wet (1.50 to 1.99), Moderately wet (1.00 to 1.49), Mildly wet (0 to 0.99), Mild drought (0 to -0.99), Moderate drought (-1 to -1.49), Severe drought (-1.50 to -1.99) and Extreme drought (Less than -2.00).

Results and Discussion

Basic characteristics of monthly, seasonal and annual rainfall data

For the period 1990-2022, statistical rainfall characteristics of Ramanathapuram district were evaluated and given in Table 1 andFig The Mann-Kendall trend, its statistical significance, for rainfall data spanning the years 1990 to 2022. Table 2 demonstrates the trend in total yearly rainfall over 33 years.

There is decreasing trend in the month of January, June October, December. The month of August is significant at 0.05 level of significance. The months showed the trends with a significance level of 0.05, which means there is a 95% probability of not making a mistake in trend hypothesis.

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