The global climate system has undergone unprecedented changes due to global warming since the 1950s, and continuous climate change will affect many countries, increasing the risk of flood and drought and other natural disasters, which will finally adversely affect the agricultural economy [1
]. Climate change studies have become an essential part of understanding and predicting climate change as it exacerbates the effects of natural disasters such as floods, droughts, heavy rainfall, and temperature [5
Numerous studies conducted in the recent past have shown that there is a growing rainfall variability globally, regionally, and sub-regionally [6
]. North and Central Asia, the eastern regions of North and South America, and northern Europe are particularly prone to increased rainfall [12
], while Northern and Southern Africa, the Mediterranean, and some other regions receive less rainfall. Although a significant increase in rainfall has been observed in Brazil’s northern Amazon region, it has been shown to show a tendency to decrease rainfall as it extends to the southern regions [15
]. Considering the context of India, it seems that for different states, the rainfall trend can be identified as both positive and negative [15
]. In addition, some studies have shown that urban temperature is rising in Sri Lanka [20
]. Analysis of rainfall trends has become a research field that has attracted great interest and enthusiasm in recent times [21
]. However, as the global or regional scale declines to the national or sub-national level, further localized variations can be observed [22
]. Moreover, rainfall analysis provides essential information for decision-makers on activities such as water resource management, development, policy planning, and disaster preparedness [23
]. The same scenario also reported that there has been a significant change in rainfall trend in Sri Lanka over the last few decades [24
]. Due to the geographical context of Sri Lanka, the Indian Ocean (IO) monsoon system influences the systematic migration of rainfall over the country’s various geographical areas throughout the year [25
El Niño and La Niña significantly affect the Indian Ocean monsoon system, changing the country’s rainfall and temperature. In the event of El Niño, Walker circulation weakens as the eastern Pacific warms abnormally, and sinks in the western Pacific, extending into the mid-Indian Ocean region during the summer [26
]. Thus, in general, the rainfall in Sri Lanka decreases from July to August and from January to March, while the northeastern monsoon receives more rainfall during the period from October to December due to the movement of the Indian Ocean Walker cell to the east [32
On the other hand, in Sri Lanka, like many other South and Southeast Asian countries, paddy is grown as a major crop all over the country [33
]. Compared to the last few decades, the area used for paddy cultivation and production in Sri Lanka has increased steadily and this has been influenced by various socio-economic, political, cultural, and technological methods [35
]. However, there are two main crop seasons in Sri Lanka, called Yala and Maha, and crop failures in the dry zone have been reported for many years (2001, 2004, 2016–2018) due to unprecedented floods and droughts [36
]. Early or late onset of rainfall should determine the strategies to be adopted for the commencement of cultivation. In addition, rainfall is the primary source of water for each field, and its quantitative value determines whether an area is normal or whether there will be a drought or flood in that area. Therefore, the study of rainfall trends helps to identify the prevalence of floods and drought in a particular area [5
As an example, a large number of studies on rainfall trends in Sri Lanka have been conducted over the past three decades and identified different localized variabilities in the country [21
]. A recent study [21
] showed that the eastern, southeastern, northern, and north-central parts of Sri Lanka have been experiencing an increase in rainfall over the past 31 years (1987–2017), and that there has been a decrease in the trend of rainfall in the western, northwestern, and central parts of the country.
Although many studies have been conducted to understand the rainfall trends in Sri Lanka, most of those studies focused only on data gathered from a limited number of rainfall stations [21
]. Therefore, spatial variability was not captured in those studies. Such studies’ main disadvantage is that they are not appropriate to represent trends at the district or climatic zone level, as the calculated values are limited to a small area. As reported in previous studies, the best way to avoid the above limitations is to use satellite precipitation estimates that, calibrated with stations data, accurately represent the spatial variability of rainfall events [44
In recent times, satellite-based and reanalyzed rainfall observations (raster data) have become a better solution to gauge precipitation data with greater accuracy and higher spatial and temporal resolution [48
]. Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Climatology Center (GPCC), Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Global Precipitation Measurement (GPM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Climate Hazards Group InfraRed Precipitation with Stations data (CHIRPS) are some of the well-known major rainfall products. Furthermore, out of the above rainfall estimates, CHIRPS data have been widely used for rainfall tendency analysis, and many of those studies emphasized the suitability of CHIRPS [49
] data for identifying precipitation trends. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with Stations data (CHIRPS) have been used for this study. Conversely, because CHRPS data are a global product, it is important to understand the validity of data using local rainfall measurements when using it for a specific area. In this study, the determination of the validity of CHRPS data as a primary requirement is also introduced.
The study used statistical methods such as the Mann–Kendall (M–K) test and Sen’s slope estimator to analyze the rainfall trend at the district and climatic zone level in Sri Lanka [8
]. Even though the validity of CHIRPS precipitation data has already been established by many researchers in the global context, which is also applied for the countries in the tropics [49
], an additional cross validation process was perforemed using location-specific rainfall data through the linear regression method.
This section mainly discusses the trend of seasonal rainfall over the past 30 years in Sri Lanka. Analysis of the seasonal rainfall trend helps farmers to manage their cultivation practices better and plan the crops. Furthermore, these analyses are of great help in managing long-term hazards such as floods and drought. The climate of Sri Lanka can be divided into two monsoons and two inter-monsoon seasons, namely, the southwestern monsoon (SWM), the northeastern monsoon (NEM), and the first and second inter-monsoon (FIM, SIM), respectively.
The two-tailed Mann–Kendall trend test was also employed to identify seasonal rainfall trends with 5% significant and 95% confidence levels. The variation of the values determined by the M–K test for the four seasons of rainfall is graphically illustrated in Figure 6
. For the Kalutara and Hambantota districts, the variation in annual, SWM, NEM, FIM, and SIM rainfall is illustrated in Figure 7
, respectively, and the Sen’s slope is shown together with the rainfall variation. This gives an obvious idea of the direction and magnitude of the rainfall trend.
However, the results of the M–K trend test show that there is an increase in rainfall in all districts of Sri Lanka during the SWM, but only seven districts show a significant trend. All these districts fall in the country’s wet zone, namely Colombo, Gampaha, Galle, Kalutara, Ratnapura, Matara, and Kegalle, respectively. Similar to the annual rainfall trend, the highest trend was recorded in SWM from Kalutara (21.943 mm/year) district and the lowest from Kilinochchi (0.978 mm/year) district (Table A3
An important point that emerges from the analysis of M–K values in NEM is that no district shows a statistically significant trend in rainfall. The most important thing to note here is that about 40% of the districts represent a decreasing trend. The districts showing these negative values belong to all four climatic zones—wet, dry, intermediate, and semi-arid—namely Ampara, Badulla, Batticaloa, Colombo, Galle, Hambantota, Kalutara, Matale, Matara, and Moneragala, respectively. The districts of Ampara, Moneragala, Batticaloa, and Badulla show a negative trend despite the fact that NEM is expected to receive more rainfall. Ultimately, this indicates that these districts are more prone to drought during the “Maha” season. Sri Lankan farmers had to experience this phenomenon in 2014, 2016, and 2017 [56
When further interpreting the results of the M–K test, as shown in Figure 6
and Table A3
, there is an increased tendency for precipitation to increase for all districts during the FIM season. However, 17 districts (68%) out of the total districts show a statistically significant increasing trend (at 0.05 significant level). The highest trend of rainfall of 9.39 mm/year is recorded in the Kegalle district and the lowest, 1.27 mm/year, is in the Jaffna district. Batticaloa, Galle, Hambantota, Jaffna, Kilinochchi, Mannar, and Matara are the seven districts which do not show a statistically significant rainfall trend.
During the SIM, only Galle and Matara districts show a statistically significant rainfall trend of 6.28 and 6.09 mm/year, respectively. This shows that there has been no significant change in the intensity of rainfall in both the NEM and SIM seasons in the last 30 years.
shows the statistical parameters such as average, maximum, minimum, standard deviation, mean, and variance coefficients of long-term (1989–2019) annual rainfall based on different climatic zones. Average precipitation values in the wet, dry, and intermediate zones are still well within their classification ranges, but the average value in the semi-arid zone is higher than the maximum in its range. Furthermore, analysis of the coefficient of variance demonstrates that greater inter-annual variability cannot be detected in any climate zone.
shows non-parametric M–K test results and the Sen’s slope conducted with a 0.05 significance level for wet, dry, intermediate, and semi-arid climate zones of Sri Lanka. It is noteworthy that all of these climatic zones show a statistically significant trend. The highest trend (31.301 mm/year) is in the wet zone and the lowest (11.549 mm/year) is in the semi-arid zone. Increases in rainfall of 14.521 mm/year in the dry zone and 17.27 mm/year in the inter-zone are also shown (Table A2
). From the above calculations, it can be concluded that there is a significant increase in rainfall from 1989 to 2019 in all climatic zones of Sri Lanka. Maps of annual rainfall trends of the district and climatic zones are shown in Figure 9
Although the districts of Jaffna and Kilinochchi were included in the dry zone, the annual average precipitation of the two was found to be less than the rainfall margin (1250–1750 mm) in the dry zone. These two districts seem to be moving out of the dry zone and into the semi-arid zone. Further study of the intermediate zone and its distribution in the districts shows that although the Kurunegala District represents about 70% of the intermediate zone’s land area, the average annual rainfall of the district is less as 1762 mm. A similar situation is observed in the Monaragala district as well (Table 1
). That is, this value is best suited to represent the dry zone. However, in Badulla, Matale, and Kandy districts, the average rainfall is well within the intermediate-zone class margin. Considering all these factors, the main point to be concluded is that the margin separating the dry zone and the intermediate-zone has changed slightly.
This study suggests that the methodology followed in this study could be adopted for developing countries in tropical and subtropical regions that suffer from a lack of local rainfall measurements to analyze rainfall variability over time. Moreover, rainfall station data do not show a good spatial variability of rainfall in terms of the distribution of rainfall stations. This study emphasizes that monthly CHIRPS data can be used as a suitable replacement for station rainfall for precipitation trend analysis to represent the effect of climate variability in Sri Lanka. The findings of this study have the potential to be used as an indication of climate change in Sri Lanka and to provide guidance for decision-makers on disaster risk management and mitigation processes.
For the past 31 years, from 1989 to 2019, each district’s rainfall trends covering 25 districts of Sri Lanka have been studied using the M–K test and Sen’s slope estimator. The results of the M–K non-parametric statistics test show an increase in annual rainfall for every district in the country. However, the annual rainfall in all districts except four in the dry zone increased significantly during the study period, and Jaffna, Batticaloa, Kilinochchi, and Ampara can be identified as the districts which did not show such an increase. Seasonal precipitation analysis shows that only the wet zone districts show a significant increase in SWM rainfall. However, 40% of the districts in the NEM show a negative trend and the other 60% show a positive trend, but no statistically significant trend in any district. Districts showing negative trends are spread over all climatological zones in Sri Lanka. Considering the trends in rainfall over the past 31 years in the climatic zones of Sri Lanka, it can be concluded that there is a significant tendency for precipitation to increase in all climatic zones (wet, dry, intermediate, and semi-arid) of Sri Lanka. Here, the maximum increase is recorded in the wet zone and the minimum increase is recorded in the semi-arid zone. A good example to prove this is the impact on the salt pans in the Hambantota district. That is to say, the salt production decreases as the district receives rainfall throughout the year. Further confirming these trends, it has been pointed out that the incidence of lightning in Sri Lanka has also increased from 1998 to 2014 [62
]. Considering all these factors, the main point to be concluded is that the margin separating the dry zone and the intermediate-zone has changed slightly.
However, some studies [21
] have shown that there is a decrease in annual rainfall trends in some districts. Nevertheless, this study seems to have generated a slightly opposite opinion. The main reason for this is that the study used raster data (CHIRPS data) generated by taking into account the spatial variability of rainfall, but previous studies used data provided by precipitation stations that did not consider spatial variability. Using one or two rainfall stations for one province or district, it is not very successful to apply those values to the whole district or province. Based on the results of this study, it can be concluded that there is a tendency for an increase in annual rainfall trends in all four climate zones.
With increasing rainfall at both the annual and seasonal level, it is likely that there will be an increased risk of floods in the southern and western provinces in the future. Finally, with the results of this study, the main point that should be brought to the attention of decision-makers is that the eastern and southeastern districts may face severe droughts in the future due to the declining rainfall trend in NEM. Therefore, it is advisable to introduce effective drought and flood management and preparedness measures with special attention to these areas. However, the findings from rainfall trend analysis through CHIRPS data can be used effectively to capture the effect of rainfall on climate change in Sri Lanka.