Can innovative trend analysis identify trend change points?

Spatiotemporal analysis of precipitation variability in annual, seasonal and extreme values over upper Indus River basin

Exploring recent groundwater level changes using Innovative Trend Analysis (ITA) technique over three districts of Jharkhand, India

Droughts as destructive climatic extreme events affect natural environment of an area. Identifying droughts has a vital importance in the planning and management of water resource systems of a river basin. This study investigates the trends of maximum hydrologic drought variables, annual maximum duration (AMD), and annual maximum severity (AMS), by using Mann–Kendall, modified Mann–Kendall, and recently developed Şen's innovative trend analysis (ITA) methods. These methods are applied to the AMD and AMS of nine different stations located in Coruh River Basin, Turkey, in which numerous highly critical power plants have recently been constructed, under construction, or planned. Basic Mann–Kendall test indicated no trend in the investigated stations while the modified Mann–Kendall gave significantly decreasing trend for AMS series of station 2304 and for AMD series of station 2321 at 10% significance level. Modified Mann–Kendall and ITA approaches indicate that the AMS of station 2304 show significantly decreasing trend. According to the ITA method, the peak AMS values of the stations 2315 and 2322 have also significantly decreasing trend after 1986. Both modified MK and ITA methods provide increasing trends in drought severities of the stations 2316 and 2323. It should be noted that some droughts or water stress may be occurred in these stations in the future. Modified Mann–Kendall test provides no significant trend for the seven stations while ITA results indicated some positive or negative trends at these stations. The primary points of interest of Şen's ITA method are that it is not subject to any assumption such as serial relationship, non‐normality, sample size, and trends of low, medium, and high data can be seen by this method easily. The study indicates that the ITA method could be simply and successfully used by hydrologist or water resources decision makers or in identifying droughts to prepare efficient management plans. Copyright © 2016 John Wiley & Sons, Ltd.

Aims: Most socio-economic activities depend on the climate. In the context of global climate change, it is crucial to understand how the climate is changing in a country like Benin in order to design effective adaptation responses. This study focused on analyzing the trend of annual precipitation totals in southern Benin.Study Design: Graphical study.Place and Duration of Study: Data for this study was collected by M´et´eo-B´enin agency, from 1922 to 2016 across six stations in southern Benin. The selected stations are those with less than ten percent missing data.Methodology: The innovative trend analysis method (ITA) and the non-parametric Mann-Kendall test were applied to the data.Results: The Mann-Kendall test shows that rainfall is stationary in all stations, while the ITA indicates that Adjohoun (slope = 0.792), Bopa (slope = 1.181), and Grand-Popo (slope = 0.734) are experiencing a relatively increasing trend, whereas Pobe (slope = -1.590) and Sakete (slope = -1.156) show a decreasing trend. By category, low totals have not shown any significant trend across the stations, while medium totals are relatively increasing in Adjohoun. As for high totals, they are decreasing at the stations of Abomey, Adjohoun, Grand-Popo, and Sakete, but increasing at Bopa.Conclusion: The hidden trends revealed by the ITA are important for decision-making, particularly in agriculture and fishing, which are the main activities in the study area.

Understanding the variability in extreme meteorological events due to climate change and anthropogenic activities is crucial to ensure sustainable development. In this paper, the variation in precipitation and temperature in the Upper Narmada Basin (UNB), a humid subtropical region of central India, during 1901–2002, was analyzed using the Mann-Kendall (MK) test with the Sen’s slope (SS) estimator and innovative trend analysis (ITA). As a result, a significant negative trend in the annual precipitation occurred at two stations (12.5%) in the UNB, whereas no well-defined significant seasonal trends were detected. Moreover, in the annual mean temperature, a significant increasing trend occurred in the basin, with the highest and lowest rates of 0.470 °C/10 year and 0.287 °C/10 year, respectively. The seasonal temperature exhibited a significant increasing trend in the spring and autumn seasons. The trends in the extreme values were investigated using the ITA method. Furthermore, a quantitative study was carried out to measure the suitability of the ITA by comparing it with nonparametric methods (the MK test and SS estimator). The results endorse the reliability of the ITA method and show strong agreement between the trends and statistics of the parametric (ITA) and nonparametric approaches. To visualize the extreme events in meteorological series, a discrete wavelet transform (DWT) was employed with the Daubechies (db3) mother wavelet. In addition, change points were detected using the sequential Mann-Kendall (SQMK) and cumulative sum (CUSUM) tests. Significant change points in the annual precipitation were detected at nine stations (56.25%) during 1955–1958, while only three stations (18.75%) exhibited the annual mean temperature during 1960. The findings of this study could provide support to understand the variability in the meteorological trend over the basin and can help with water resource planning in future development.

Spatiotemporal climate variability and trends in the Upper Gelana Watershed, northeastern highlands of Ethiopia

Effective drought and water-resource management is a fundamental challenge worldwide. In recent decades, the intensification of drought has become a serious challenge in northwestern Iran, particularly in the Lake Urmia basin, where rising temperatures and declining heavy rainfall have accelerated water scarcity. Therefore, monitoring drought and studying its trends is crucial.This study evaluates drought patterns at seven meteorological stations using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at 3, 12, and 24-month time scales. The Innovative Trend Analysis (ITA) method, supported by the Seasonal Kendall test, was used to identify and assess drought behavior.The ITA method clearly showed drought trends, whereas the Seasonal Kendall test often failed to detect any trends in short-term data. The results showed that the stations of Tabriz and Urmia have more dry and normal periods, while wet periods have reduced, indicating a reduction in overall moisture. Mahabad, Saqqez, Maragheh, and Sarab had a decrease in all categories (dry, normal, and wet), which demonstrates severe and persistent drought. SPEI also identified short-term droughts in Mahabad and Tekab, which SPI was unable to capture.Frequency analysis using McKee’s classification showed that most months fall within the normal range; however, ITA trends indicated that the intensity and persistence of normal periods are decreasing in many stations. These results indicate that ITA trends can identify which stations enter drought rapidly, retain moisture stability, and is critical for water storage planning and early warning systems.Overall, the integration of SPI and SPEI with statistical and trend methods provides a comprehensive framework for drought monitoring in semi-arid regions. The findings suggest that the use of ITA is highly effective for water resource management, long-term change prediction, and strengthening adaptation strategies in the sensitive and critical Lake Urmia basin.

Gaining insights into the patterns of hydroclimatic elements such as inflows to dams is essential to adeptly strategize and oversee water resource planning. For this study, we focused on Karuppanadhi and Gundar dams within the Chittar River Basin in Tamil Nadu. We employed various time series trend assessment methods – Mann–Kendall (MK), modified Mann–Kendall (MMK), Sen slope estimator, and innovative trend analysis (ITA). Furthermore, we conducted change point detection analysis using homogeneity tests, namely Pettitt's test, standard normal homogeneity test (SNHT), and Buishand test. The analysis was carried out across three-time scales: monthly, seasonal, and annual for 30 years (1991–2020) span. Results revealed declining trends significantly across all three timescales for the Karuppanadhi dam. Whereas for the Gundar dam, notable trends included increased patterns in January, March, December, and the winter season, while other months/seasons showed statistically decreasing trends. ITA exhibited greater sensitivity in identifying trends at monthly and seasonal scales, indicating its superior trend detection over MK and MMK methods. Change point analysis of trends identified a rising trend in August post-2017 for both dams. Other change points indicated decreasing inflow trends thereafter. Analysing trends and change points in dam inflows aid decisions on water resources management.

This study investigated trends in 35 years (1979–2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen’s slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year−1. The sequential significance of linear trend in MK test-statistics is very strong (R2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced metabolic-activities and shortened crop-duration. Likewise, increased Tmin may result in lesser crop and biomass yields owing to the increased respiration.

This study investigates the impact of climate change on river systems within the Eastern Mediterranean Basin (EMB), utilizing the Mann-Kendall (MK) test, enhanced by Sen’s slope estimator (SSE) and Şen’s Innovative Trend Analysis (ITA) methods. The research focuses on hydrological changes,, particularly in streamflow trends, and examines their implications in the context of climate change and anthropogenic activities. The methodology involves a detailed analysis of hydro-meteorological series, including streamflow data from different observation stations. The research enhances the robustness of trend detection by applying advanced methodologies such as trend-preserving pre-whitening, which satisfies the serial independence requirement of the MK test. The study area comprises 10 sub-basins in the EMB, with a particular attention to the Göksu River and its tributaries. The results reveal significant declines in the annual streamflow values at several stations, demonstrating the considerable influence of climate and environmental changes on the basin's hydrology. These findings are further evaluated using ITA graphs, which offer a detailed analysis of the spatial and temporal variability in streamflow patterns. This research contributes to a better understanding of hydrological responses to climatic variability, providing vital information for water resource management and policies in regions undergoing significant environmental changes.

This study investigates the spatio-temporal distribution and trends of seasonal rainfall for different meteorological sub-divisions (MSDs) of India using statistical analysis and the innovative trend analysis (ITA) method. The gridded dataset of daily rainfall for 120 years from 1901 to 2020 was obtained from the India Meteorological Department (IMD) and analysed using statistical results of mean rainfall, standard deviation, coefficient of variation, skewness, kurtosis, maximum seasonal rainfall, percent deviation of rainfall, number of rainy days, rainfall intensity, rainfall categorization, trend detection, and cross-correlation coefficients. The period was divided into three quad-decadal times (QDT) of 40 years each (i.e., 1901–1940: QDT1, 1941–1980: QDT2, and 1981–2020: QDT3). A general decrease in the number of rainfall events was observed in all the seasons except for a few MSDs of northwest India showing a rise throughout the pre-monsoon season in recent times (QDT3). Significant trends were detected using the ITA method in seasonal rainfall in nearly all the MSDs of India. Our findings are highlighting the qualitative and quantitative characteristics of seasonal rainfall dynamics at the MSDs level which will be useful for comprehending the rainfall dynamics as impacted by climate change and climate variability in India, and may further lead the policymakers and stakeholders for making the best use of available water resources.


 This study examined and compared the new innovative trend analysis (ITA) of monthly, seasonal and annual rainfall with traditional trend analysis methods in relation to soybean productivity in western Maharashtra. Spearman’s rank correlation, Mann-Kendall and its 6 different modifications were used to analyze the trends of rainfall, whereas Spearman’s rho, simple linear regression and Sen’s slope with two different modifications were employed to quantify the magnitude of trends at 1%, 5% and 10% level of significance. Autocorrelation coefficient was calculated at lag-1 and tested at 5% level of significance. Rainfall variability of the region is very high (CV>30) in all the months and seasons with positively skewed rainfall distribution. Our results revealed that out of 34-time series data analyzed, ITA was able to ide ntify all the significant trends (11 -time series) that can be detected by traditional methods. Meanwhile, ITA also identified trends in 17-time series which cannot be detected by any of the traditional methods. The study revealed significant increase in monsoon and annual rainfall values, which is helpful in sustaining soybean productivity in the western parts of the Maharashtra.

Long-term spatiotemporal variability in occurrences of wet and dry days across South Mongolian Plateau

The increase in greenhouse gases in the atmosphere has worsened global warming, and marked changes have been observed in meteorological and climatic events, especially since the early 2000s. Trend analysis studies are important for determining changes in meteorological and climatic events over time. This study investigated the trends of maximum precipitation and minimum temperature in the Aegean Region and Eastern Anatolia Region of Türkiye by conducting an innovative trend analysis (ITA), the Mann–Kendall (MK) test, and linear regression analysis (LRA). As a method, ITA has been used together with traditional methods in the last decade, and its advantages have been demonstrated in comparative trend studies. An important contribution of ITA is that it can categorize datasets according to their size (low, medium, and high). The classification technique of the ITA method includes dividing the sorted dataset into three equal parts and separately examining the trends of low, medium, and high data values. This approach is reasonable for datasets with low skewness (or normally distributed series). However, the normal distribution acceptance of ITA data classification is insufficient for trend analysis of data series with extreme values. Therefore, we propose a modified data classification method to rationally examine skewed datasets with the use of quartiles. Our study was performed for the trend analysis of maximum rainfall and minimum temperature data in two regions located in the west and east of Türkiye showing different climatic characteristics. In the first part of the study in which the numerical trend analysis of ITA was evaluated, the MK and LRA methods showed similar results, whereas the ITA detected trends at a greater number of stations owing to its sensitivity feature in detecting trends. In the second part, which included data classification in trend analysis, the equal split data classification used in the ITA and the modified data classification proposed in the study were compared. The comparative results of the trend analysis of the maximum rainfall and minimum temperature data showed the superiority of the proposed data classification in examining the trend of extreme values, especially for maximum rainfall data with relatively high skewness.

The present investigation emphasizes on the meteorological drought characteristics of the Marathwada region using the Standardized Precipitation Index (SPI) method. Rainfall data of eight districts in the region from 1901 to 2021 have been investigated. The analysis revealed that the region experienced a significant 49 per cent drought with some districts, such as Hingoli and Nanded, facing more frequent droughts than precipitation events. The longest drought, spanning from 1918 to 1927, and the most severe drought years, including 1918, 1920, 1929, 1972 and 2015, underscore the severity of the situation. Notably, extreme drought (ED) and severe drought (SD) events were experienced between 2 per cent and 5 per cent, with mild drought (MD) and mild wet (MW) classes being the dominant classes. Spatial analysis using the Kriging method revealed that the southern and eastern parts of the region are at higher risk of drought. Trend analysis using Mann‐Kendall (MK) and Spearman Rho (SR) tests showed an increasing drought trend. In contrast, there is a significant increase in the extreme drought class using the Innovative Trend Analysis (ITA) method. The spatial occurrence rates of extreme and severe droughts have increased since 2010, highlighting the urgent need for improved water resource management and climate adaptation strategies to reduce future drought risks.