Madras Agric. J., 105 (4-6): 182-185, June 2018 Trend Analysis of Rainfall Intensity in Tiruchirappalli District of Tamil Nadu A. Indhuja1* and U. Arulanandu2 1Department of Physical Science and Information Technology, Tamil Nadu Agricultural University, Coimbatore. 2Department of Social Sciences, ADAC and RI, Tiruchirappalli. Rainfall is the dynamic weather parameter having a significant role in the agriculture livelihood. Growth in agriculture and other related sectors depends mainly on the adequate amount and timely availability of rainfall. Variability in precipitation exerts a huge impact on human beings and agriculture. This variation gives the necessity to study the regular pattern of rainfall. The present study aims at analysing the trends in rainfall intensity across various blocks of Tiruchirappalli district using daily rainfall data for the period 1990 to 2017. Non-parametric tests such as Mann- Kendall test and Sen’s slope estimator were employed for this purpose. Results revealed that two blocks showed statistically significant increasing trends (95% confidence level) and one block showed significant decreasing trend (95% confidence level) and the remaining eleven blocks showed no significant trends. Key words: Rainfall, Trend, Mann-Kendall, Sen’s slope. Rainfall is one of the important weather parameters (MK) test and Sen’s slope estimator. They observed that having greater effect on the livelihood of majority a decreasing trend in some of the months and an of individuals in all over the world. Growth in increasing trend in few other months. The study agriculture and other related sectors depends on also revealed an overall change in precipitation adequate amount and timely availability of rainfall. Of trend during South-west monsoon. (Rai et al., 2014) all the climatic factors, rainfall is of greatest concern conducted a study on climate change, variability to the farmers in rainfed agriculture. The variation of and rainfall probability for crop planning in a few annual and monsoonal rainfall in space and time are districts of central India. They obtained initial and well known and this variability of monsoonal rainfall conditional rainfall probability of getting 10 mm and has considerable impact on agricultural production. 20 mm rainfall per week and concluded that 25th The term variability refers to the deviation from the Standard Meteorological Week (SMW) in Damoh long-term average. In the context of rainfall, variability district is suitable for seed bed preparation and 27th is the extent to which rainfall amounts vary across an SMW (2-7 July) in Sagar district is most suitable for area and over time. sowing operation. With this background the current study is concerned with trend analysis of rainfall in Monitoring of real time rainfall distributions on Tiruchirappalli district of Tamil Nadu. daily basis is required to estimate the progress and status of monsoon and to commence necessary Material and Methods action to control flood/drought situation. This uplifts a Study area question that whether the variability is purely random or is there any identifiable pattern in these variations. Tiruchirappalli district is situated in central south- Information on temporal and spatial variations is eastern India, almost at the geographic centre of the very essential for understanding the hydrological Tamil Nadu surrounded by a Perambalur district in balance on a regional/global scale. The distribution the north, Pudukkotai district in the south, Karur and of rainfall is also significant for water management Dindigul districts in the west and Thanjavur district in in agriculture and monitoring of drought. (Kwarteng the east. It lies between the coordinates 10o47’40.56” et al., 2009) analysed 27 year rainfall data in the N latitude and 78o41’6”E longitude. The topology of Sultanate of Oman using Mann-Kendall test and Tiruchirappalli is almost flat, with an altitude of 78 reported that the yearly rainfall over Oman was quite metres above mean sea level. The district has an variable and irregular. (Kumar et al., 2010) observed area of about 4,404 sq.km. It belongs to Cauvery long term rainfall trends in India using non-parametric delta zone, which receives an average annual rainfall Mann-Kendall test and concluded that no significant of about 842.6 mm. trend was detected in the whole of India in annual, Data collection seasonal or monthly rainfall. (Babar and Ramesh, 2014) analysed the trends in south west monsoon Daily rainfall data for the period from 1990 to rainfall over Nethravathi basin using Mann-Kendall 2017 was obtained from the Disaster Management and Mitigation Department, Revenue Administration, *Corresponding author’s email: [email protected] 183 Government of Tamil Nadu. This consisted of If, Z is positive and p < 0.05, then it is said to be secondary data on daily rainfall of 14 blocks in in increasing trend; Tiruchirappalli district. If, computed probability p > 0.05, then there is Tools of analysis no trend. Mann-Kendall trend test Sen’s slope estimator The non-parametric Mann-Kendall test (Mann The magnitude of the trend in the seasonal and 1945, Kendall 1975 and Gilbert 1987) is commonly annual( data− 1) series was estimated using a non- > 0 parametric √() method known as Sen’s estimator (Theil, used to identify monotonic trends in climate data or = 0 = 0 ( + 1) hydrological data. The null and alternative hypothesis 1950). This method < 0 can be used when the trend is is an indicator function that results{ in√ the() values -1, 0, or 1. Based on the sign are given by If, Z is negative andassumed p < 0.05, then it is saidto to be in decreasing linear, trend ;that is: If, Z is positive and p < 0.05, then it is said to be in increasing trend; H : There( is no− trend ) in the series. If, computed probability p > 0.05, then there f(t) is no trend.= Qt + B 0 of where j >k, the function is calculated as follows. Sen’s slope estimator Where, Q - slope, H1: There is a negative or positive trend. ( − ) The magnitude of the trend in the seasonal and annual data series was estimated using Temporal variation of rainfall across 14 Blocksa non of-parametric method known as Sen’s estimator (Theil, 1950).B This - method constant can be used and the district would be analysed by using Mann-Kendallwhen the trend is assumed to be linear, that is: t - time. test. The is anpositive indicator sign function indicates that results a constant in the values increase -1, 0, or 1. Based on the sign 1 () = +− > 0 in trend over time and the negative value indicatesWhere, Q - slope, To get the slope Q in the above equation, we of ( − where) j >k, the function is calculated as follows. a constant decline in trend. The larger the( Mann-− B -) constant= and[ first 0 calculate − the= slope0] of all data value pairs using t - time. ( Kendall− ) is anstatistic, indicator function stronger that results the in the trend values -1,(magnitude 0, or 1. Based on isthe sign −the1 formula: − < 0 To get the slope Q in the above equation, we first calculate the slope of all data value pairs (proportional − ) Test tostatistic strength).: The first step is to find the of where j >k, the function is calculated as follows. using the formula: where i=1,2,…k ; j>k sign of difference between consecutive 1 − data > 0points. ( − ) X and X are the data values at time j and k 0 − = 0 j k is an indicator function( that− results ) = in [the values -1, 0, or 1. Based] on the sign − = respectively. − − 1 − < 0 where i=1,2,…k ; j>k ( − ) j >k 1 − > 0 Testof statistic :where , the function is calculated as follows. j k ( − ) = [ 0 − = 0] −1and are the data values at time and respectively. If there are ‘n’ values Xj in the time series, we ( − ) −1 − < 0 is an indicator function that results in the values -1, 0, or 1. Based on the sign is an indicator function that results in the valuesIf there - 1,are ‘0,n’ valuesor 1. Basedin the time on series the, we signget as many as N = slope estimates . Test statistic : is an indicator function that results get as many as slope estimates Q. The Sen’s (−1) i ( − ) of where j >k , the function is calculated as follows.2 in the values( − -1,) 0, or 1. Based− 1 1 on − the > 0sign of = The∑ Sen’s slope∑ estimatorslope is the median (estimator of these− N values) ofis . theThe N valuesmedian of are of these N values of of where j >k, the function is calculated as follows. =1 =+1 where j >k, the function( − ) = is[ calculated0 − = as0] follows.( −ranked) in ascending orderQ and .the The Sen’s estimator N values is given by, of Q are ranked in ascending order −1 i i = ∑−1 ∑− (<0− ) (where− ) j = 1,2,3,…,=1 = n+-11 and k = j+1, j+2, j+3, ……………..and the Sen’s estimator n. is given by, Test statistic: Test statistic: = ∑ ∑ ( − ) 1 − > 0 where j = 1,2,3,…, n-1 and k = j+=11,= j++12, j+3, …………….. n. To obtain the 0 constant − = 0 B in the equation, N values where j = 1,2,3,…, n-1 and k = j+1, j+2, j+3, …………….. n. 1 − > 0 ( − ) = [ ] −1 − < 0 −1 of differences X - Qt are found. The median of these ( − ) = [ 0 Test− statistic = 0: ] j k, j > k i i where and where are the annual and values in are years the j and annual k, j > k, valuesrespectively in years and , respectively where and are the annual values in years j and k, j > k, respectively−1 − < 0 = ∑ ∑ ( − ) values gives an estimated of B. The Mann Kendall Zc Test statistic: =1 =+1 and Sen’s slope estimation were done using XLSTAT where j = 1,2,3,…, n-1 and k = j+1, j+2, j+3, …………….