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In Taiwan, rivers have steep slopes and short lengths, making it difficult to retain water in the rivers. Therefore, understanding the flow characteristics is essential. This study analyzes data from 65 flow stations with over 30 years of records to characterize the annual mean number of low-flow days, flow variability, and the seasonality of low-flow occurrences. The analysis uses indices such as the intermittency ratio, Richards–Baker flashiness index, and six-month seasonality of the dry period (SD6) and evaluates trends in these indices using the Mann–Kendall test. The results show that nearly 70% of the stations have an intermittency ratio of less than 0.1, although the number of low-flow days has significantly increased over time. Stations in the southwestern watersheds exhibit higher flow variability; however, the trends in flow variability are not statistically significant. Low-flow events predominantly occur during the dry season, with 68% of the stations experiencing them between January and March. The findings on flow characteristics and their long-term trends provide references for river management and water resource planning in the future. [ABSTRACT FROM AUTHOR]

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ABSTRACT The Brazil current (BC) is a westerly current that flows south along the Brazilian coast, being part of the Southern Brazilian Continental Shelf (SBCS). Recent studies have indicated a trend towards intensification and a shift to the south of the region where this current predominates. We analysed the seasonality of the relationship between atmospheric variables and sea surface temperature (SST) with potential trends and changes in the spatio‐temporal pattern of these variables from 1980 to 2020 over the BCs area in the South Atlantic Ocean. For this purpose, monthly data on SST, air temperature at 2 m above the surface (T2M), mean sea level pressure (MSLP), zonal wind (U10) and meridional wind (V10), obtained from ERA5 reanalysis, were used. Descriptive statistical analyses, trends using the Mann‐Kendall test, correlation matrices and Pettitt's test revealed a significant spatial correlation between the variables, with temporal trends of variation, especially over the BCs area. The meridional (zonal) wind predominantly exhibited a north–south (west–east) direction, supporting the hypothesis that the study region was displaced. Additionally, statistically significant positive trends were observed for SST (0.02°C ∙ dec−1 in austral autumn, winter and spring and 0.01°C ∙ dec−1 in austral summer), T2M (0.02°C ∙ dec−1 in austral winter and spring), MSLP (0.05°C ∙ dec−1 in austral autumn) and negative for U10 (−0.01°C ∙ dec−1 in austral spring). Pettitt's test results confirm significant changes in the behaviour of most analysed variables from the late 1990s to the early 2000s. The post‐breakpoint periods of the variables consistently showed above‐average values compared to the pre‐breakpoint periods, supporting positive upward trends consistent with literature findings. In particular, they highlight the notable upward slope in SST in the BC region. [ABSTRACT FROM AUTHOR]

In this study, an analysis of hourly air temperatures in four groups of 32 stations from the UK highland (5 stations), UK lowland (4 stations), Italian highland (11 stations), and Italian lowland (12 stations) at different altitudes was carried out over the period from 2002 to 2021. The study aimed to examine the trends of each hour of the day during this period, over different averaging time windows (10‐day, 30‐day, and 60‐day). The trends were computed using the Mann–Kendall trend test and Sen's slope estimator. The similarity of trends within and across the groups of stations was assessed using the hierarchical clustering with dynamic time warping technique. An additional analysis was conducted to show the correlation of trends among the group of stations using the correlation distance matrix. Hierarchical clustering and distance correlation analysis show trend similarities and correlations, also indicating dissimilarities among different groups. Using 30‐day averages, significant warming trends in specific months at the Italian stations are evident, especially in February, July, August, and December. The UK highland stations did not show statistically significant trends, but clear pattern similarities were found within the groups, especially in certain months. The ultimate goal of this article is to provide insights into temperature dynamics and climate change characteristics on regional and diurnal scales. [ABSTRACT FROM AUTHOR]

ABSTRACT The main purpose of this paper was to identify significant changes in air moisture conditions in Poland, which accompany climate warming. Meteorological data used in the research included the relative humidity (RH) values from 48 stations obtained from the Institute of Meteorology and Water Management—National Research Institute from 1966 to 2020. The monthly mean, standard deviation (SD) and coefficient of variation of RH from 12 PM for all months (with particular reference to the middle months of seasons—January, April, July and October) were used. Additionally, the dry weather (RH < 30%) frequency in the warm half of the year was observed. Long‐term changes were found by comparing relative humidity values in three 15‐year subperiods (1966–1980, 1986–2000 and 2006–2020) and the statistical significance was estimated using the Mann‐Kendall test. The most considerable long‐term changes were noticed in April and July, especially in the last 15‐year subperiod. The statistical significance was higher, mostly in warmer months. The SD was also higher in April and July than in January and October. Hence the humidity conditions in the warmer half of the year fluctuated more and more widely. A significant decrease in the RH mean values and an increase in SDs in spring and summer impact the increasing frequency of dry weather. Relations between meteorological characteristics suggest the warming climate contributes to drying the near‐surface atmosphere but also impacts intensive precipitation events or snow cover parameters. The decreasing trend of long‐term relative humidity may negatively impact the environment, human health and well‐being and cause serious economic losses. [ABSTRACT FROM AUTHOR]

Copyright of Al-Adab / Al-ādāb is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the Wadi Cheliff basin (Algeria), a 48-year (1971–2018) time series of annual maximum daily rainfall was studied to identify and quantify trends observed at 150 rain gauges. Initial trends in annual maximum daily rainfall were determined using the Mann–Kendall test, with a significance level of 95%. The slope or increase/decrease in the annual maximum daily precipitation was assessed using the Theil–Sen estimator. A running trend analysis was then performed to quantify the effects of different time windows on trend detection. Finally, to assess the different spatial distribution of annual maximum daily precipitation during the observation period, spatial analysis was performed using a geo-statistical approach for the whole observation period and at different decades. The results showed a predominant negative trend in annual maximum daily rainfall (about 11% of rain gauges at a 95% significance level), mainly affecting the north-eastern area of the catchment. The spatial distribution of annual maximum daily rainfall showed high rainfall variability in the period of 1970–1980, with a decrease in the decades of 1980–1990 and 2010–2017 when the maximum values were more evenly distributed across the region. [ABSTRACT FROM AUTHOR]

The study of the statistical trends on rainfall and temperature is much more efficient for hydrological design and planning for scarce water availability zones. In the present study, the sequential Mann–Kendall test (SqMKT) on the Mat-Lab platform is used to study the pattern of rainfall series and temperature series data of the Tikamgarh area of India, surrounded by five stations (nearby) from 2000 to 2020. The SqMKT is mainly used to perform non-linear trends on the rainfall and temperature series. In the SqMKT analysis on rainfall series projects, there was no significant trend in all months, except in the month of June. These months have intersecting points, and each point has Z values in the range of –0.5 < Z < 1.5. The SqMKT analysis on the temperature series shows a significant trend in the months of April, June, July and December, respectively, whereas the remaining months do not have any pattern or trend, similar to the rainfall series and temperature series have u values in the range of –0.5 < u < 1.5. The global climatic pattern is somewhat directly or indirectly connected to the Indian climate pattern, which results in variations in rainfall and temperature patterns from year to year. The indefinite variation in rainfall and temperature results in a direct impact on crop yield and crop water demand or total water availability. [ABSTRACT FROM AUTHOR]

In the current study, the impacts of climate change on precipitation to the Amaravati city of Andhra Pradesh, India, are assessed. Trends and variability of precipitation changes for the historical period 1951–2014 and various Shared Socioeconomic Pathways (SSP), SSP scenarios of the 2015–2100 period are determined by considering daily precipitation time series from bias-corrected climate projected data of precipitation from CMIP6 GCM, ACCESS CM2. Mann–Kendall (M–K) test and Sen's slope estimator are used to perform trend and variability analysis of precipitation attributed to climate change. No magnitude of trend is found for precipitation both for observed and under SSP scenarios. However, there are increasing and decreasing trends observed season-wise and annual precipitation datasets for both observed and under SSP scenarios within and around the study area. Also, the urban land proportion projections indicate that the total area becomes urbanized even at the end of the year 2060. The findings of this study may assist in predicting the impacts of climate change on precipitation to a city. [ABSTRACT FROM AUTHOR]

In recent years, the effects and consequences of climate change have shown themselves by creating irregularities and trends in the essential climatic variables. In most cases, the trend of climatic variables is associated with periodicity. In this study, the trends and periodicity of these data (precipitation, temperature, evapotranspiration, and net available water (NWA) have been investigated in a period of 60 years in Iran. The Mann–Kendall trend test and Sen's slope estimator are applied for analyzing the trend and its magnitude. Wavelet transform is used to detect the periodicity of time series and to determine the correlation between NWA and temperature, precipitation, and evapotranspiration in common periodicity. The results show that the stations located in eastern and western Iran have more significant increasing/decreasing trends. Evapotranspiration shows the highest increasing trend in most stations, followed by temperature, while NWA and precipitation have trends at lower significance levels and decreasing direction. The examination of periodicity in time series showed that, among all the studied stations, evapotranspiration has the most extended periodicity with an average length of 8.3 years, followed by NWA, temperature, and precipitation with 7.3 years, 5.8 years, and 5.5 years. The results of the correlations investigation showed that in about 80% of the stations, there is a high correlation between precipitation and NWA in the short-term periodicity and at the end of the studied period. The evapotranspiration variable in most stations has a high correlation in different periodicities with the amount of NWA. [ABSTRACT FROM AUTHOR]

Water quality is vital for human health and the protection of natural ecosystems, and demand for quality water is increasing day by day. It is known that changes in precipitation and temperature patterns due to climate change directly or indirectly affect water quantity and quality. In order to understand the potential effects of climate change on water resources, it is very important to know the changes in flow and water quality data over time. Trend analysis methods are the most used methods for this purpose. In this study, monthly, seasonal, and annual changes of dissolved oxygen (DO), water temperature (WT), discharge (Q), and specific conductance (SC) parameters, which are measured and recorded daily between 1987 and 2022 at four monitoring stations in the Broad River Basin (South Carolina, USA), were investigated using the Mann-Kendall test and innovative trend analysis (ITA) methods. Electrical conductivity (EC) values, calculated by considering SC and WT data, were considered. The Mann-Kendall test and ITA identified significant trends in 32.4 and 64.6% of the 272-time series analysed, respectively. It was determined that ITA was more sensitive in identifying decreasing trends. While the spatially and temporally varying trends in the river DO concentration and EC values were associated with human activities, it was concluded that the increasing trends in WT values and decreasing trends in Q values may be due to climate change on precipitation and air temperature parameters. This study, based on long-term data sets, illuminates the global concerns about the impacts of climate change on water quality and provides important findings that will guide sustainable management of water resources and measures to be taken against climate change. It is the first study to examine long-term trends of water quality parameters for the basin. [ABSTRACT FROM AUTHOR]

Global food production and water distribution are at risk due to increasing temperatures and changing precipitation trends. The main objective of the study was to analyze the climate trend and future projections in seven stations in southern Iraq. The period (1981-2020) was designated as a base period. The periods (2021-2040) and (2041-2060) were defined as the future two periods. The Mann-Kendall trend test was employed to assess trends utilizing XLSTAT. The study employed the most recent version of the LARS-WG 8 model to forecast climate change by using three GCMs (ACCES-ESM1-5, HadGEM3-GC31-LL, and MRI-ESM2-0). These simulations are based on two scenarios (SSP-245 and SSP-585). The statistical indicators provided support for the outcomes of model calibration and validation, demonstrating its competence and reliability. The results of this analysis indicate that there is a non-significant increase in precipitation and a considerable increase in both maximum and minimum temperatures during the period (1981-2060). The downscaled result reveals an increase in monsoon precipitation in the range of 2.233-2.831 mm under SSP-245 and SSP-585, respectively, compared with the base periods 1981-2020 during the Near Future and 1.988-2.543 mm during the mid-future. Also, annual maximum/minimum temperature increases in the range of (1.156-1.549 °C) and (1.486-1.770 °C) during the Near Future. (2.095-2.892 °C) and (1.486-1.770 °C) during the mid-future, respectively, for SSP-245 and SSP-585. These outcomes can enhance understanding to develop strategies for mitigating and adapting to these impacts. [ABSTRACT FROM AUTHOR]

This research aimed to identify the most appropriate probability distribution for modeling average monthly rainfall in the agro-climatic zones of West Bengal and to detect any trends in this data. The study utilized historical rainfall data spanning 51 years (1970-2020) obtained from the IMD in Pune. To determine the best-fitting distribution and assess trends, 23 different probability distributions were employed, with the Mann-Kendall test and Sen's slope estimator used for trend analysis. Goodness-of-fit tests, including the Kolmogorov-Smirnov, Anderson-Darling, and Chi-square tests, were employed to determine the most suitable distribution. The findings indicated that the Generalized Extreme Value, Gamma, and Lognormal (3-parameter) distributions were the best fits for two specific districts. The monthly rainfall distributions can be effectively used for predicting future monthly rainfall events in the region. The Mann-Kendall test revealed an increasing trend in rainfall for Kalimpong and Nadia Districts and a decreasing trend for Malda District. [ABSTRACT FROM AUTHOR]

This study identified the trends in monthly temperature, precipitation, and evaporation for Astore, Darosh, Gilgit, Gupis and Skardu and trends in inflow, outflow and reservoir level for Tarbela reservoir. Two non-parametric tests i.e. Man-Kendall and Sen's Slope and Innovative Trend Analysis (ITA) were used to determine the trend. The first Mann-Kendall test with a significance level 5% was applied to 33-year data of five selected areas from 1990-2022. The results showed an increasing trend in temperature in March for all selected areas. No significant trend was observed in precipitation except negative trends for Darosh in March, May and December and positive trend for Gilgit in January and September. It has been observed that the trend direction given by ITA and Mann-Kendall is similar. Inflows to reservoir were found directly related to the temperature because of glacier melt in rising temperature, thus increasing the inflow, although the precipitation was found decreasing with increase in temperature. Altered snowmelt patterns can influence weather systems, potentially contributing to more extreme weather events. [ABSTRACT FROM AUTHOR]

In East Africa, agricultural production is predominantly rain-fed. The El Niño Southern Oscillation (ENSO) is the driver of climate variability, which affects rainfall amount that leads to humanitarian impact. This paper aims to study the impacts of El Niño Southern Oscillation (ENSO) on rainfall amount and anticipated humanitarian impact. The study was carried out in Western Amhara in Amhara National Regional State of Ethiopia, which features a variety of seasons that characterize the nation and Eastern Africa. Monthly rainfall data were collected from fifteen meteorological stations of Western Amhara service center. Selected El Niño and La Niña years were also extracted from the National Oceanic and Atmospheric Administration (NOAA) from 1986 to 2015. Once the data quality was checked and inspected, the monthly rainfall data of the selected stations was arranged in a Microsoft Excel spreadsheet and analyzed using XLSTAT software. The coefficient of variation and the Mann–Kendall nonparametric statistical test were employed to analyze trends and variability of rainfall and temperature. The long-term recorded annual rainfall data indicated that there was an increasing trend from 1986 to 2015 insignificantly Western Amhara. El Nio's effects are predicted to lead to more severe and violent heatwaves, wildfires, floods, droughts, and diseases in East African countries like Ethiopia, Sudan, and Somalia, which are already dealing with humanitarian challenges. The rainfall variability was less (Coefficient of Variation, CV = 8.6%); also, the mean monthly rainfall of Western Amhara decreased during El Niño years and increased during La Niña years especially in the rainy season (June, July, August and September) over 30 years. This finding will be useful to suggest possible adaptation strategies and efficient use of resources during planning and implementation. [ABSTRACT FROM AUTHOR]

The hydrological regulation function of glaciers in different watersheds is different. This study took the Yanggong River Basin (YRB) and Urumqi River Basin (URB) as two typical cases, to explore the runoff change differences and their responses to climate factors from 1979 to 2017. In the past 39 years, the YRB's annual runoff showed an insignificant trend of increasing first and then decreasing, while the URB's increasing trend was significant. From the 1980s to the 2010s, the YRB's monthly runoff extremum occurred earlier than before, and the peak value decreased. The time of monthly runoff extremum in the URB has not changed, but the peak value is increasing. Both basins experienced an increase in annual temperatures from 1979 to 2017, with the rate of warming being more pronounced in the URB. The precipitation in the YRB had no significant trend from 1979 to 2017, and the significant increasing trend in annual precipitation extended in the URB from 1998 to 2010. The YRB's runoff change was mainly influenced by the flood season precipitation, while the URB's runoff increase was due to the temperature rise causing faster glacier and snow melt, and the summer precipitation change. In continental glacier basins with many glaciers, the regulation function of glaciers on total runoff is more significant. [ABSTRACT FROM AUTHOR]

The present study offers a comprehensive evaluation of the monthly rainfall and temperature patterns across nine stations and fifty-nine points in North-Eastern Nigeria using NASA's Prediction of Worldwide Energy Resources data, spanning four decades (1981–2021). By employing the Mann–Kendall (MK) test and inverse distance weighting (IDW) interpolation, the researchers effectively detected and visualized trends in climate variables. The MK test results indicate contrasting rainfall trends, with notable decreases in Akko, Billiri, Maiduguri, Numan, and Yola, and increases in Gombe, Abadam, Biu, and Mubi. The trends in the maximum temperature were found to be statistically significant across all stations, showing a consistent increase, whereas the minimum temperature trends exhibited a slight but insignificant decrease. The application of the Theil–Sen slope estimator quantified these trends, providing nuanced insights into the magnitudes of changes in climate variables. The IDW results further corroborate the general trend of decreasing rainfall (z = −0.442), modest increases in the maximum temperature (z = 0.046), and a marginal decline in the minimum temperature (z = −0.005). This study makes an important contribution by advocating for the proactive dissemination of climate information. Given the evident climate shifts, particularly the increasing temperatures and fluctuating rainfall patterns, timely access to such information is crucial to enhancing climate resilience in the region. The rigorous statistical methods applied and the detailed spatial analysis strengthen the validity of these findings, making this study a valuable resource for both researchers and policymakers aiming to address climate variability in North-Eastern Nigeria. These research results may also be useful for understanding the climate variabilities in different parts of the world. [ABSTRACT FROM AUTHOR]

Abstract This study examines the multi-decadal variability and trends of surface air temperature and precipitation in the Indian Cardamom Hills (ICH), a degraded tropical rainforest area unique for cardamom cultivation. Utilizing observed long-term climatic data (1958–2017), statistical methods such as the Mann–Kendall test (MKT), Sen’s Slope Estimator (SSE), and Incremental Trend Analysis (ITA) were applied to assess the impact of surface air temperature, rainfall, and the number of rainy days on cardamom yield. The analysis revealed a significant decline in annual rainfall by approximately 13.62 mm per year, with pronounced seasonal declines 0.87 mm for winter, 12.33 mm for pre-monsoon, 24.93 mm for southwest monsoon, and 18.10 mm for post-monsoon. Simultaneously, the number of rainy days dropped by nearly 19.75 days over the 40-year period. A noticeable increase in decadal minimum and average temperatures was observed, highlighting potential adverse effects on cardamom yield and irrigation water resources. The findings suggest that excessive rainfall during the southwest monsoon negatively correlates with cardamom yield, while slightly warmer temperatures show a weak positive correlation. The study also emphasizes the need for adaptive agricultural practices and climate-resilient policies to mitigate the effects of changing climatic conditions on cardamom production. This research contributes valuable insights for farmers and other stakeholders as well as policymakers aiming to ensure sustainable cardamom cultivation amidst climate change.

This study examines the multi-decadal variability and trends of surface air temperature and precipitation in the Indian Cardamom Hills (ICH), a degraded tropical rainforest area unique for cardamom cultivation. Utilizing observed long-term climatic data (1958–2017), statistical methods such as the Mann–Kendall test (MKT), Sen’s Slope Estimator (SSE), and Incremental Trend Analysis (ITA) were applied to assess the impact of surface air temperature, rainfall, and the number of rainy days on cardamom yield. The analysis revealed a significant decline in annual rainfall by approximately 13.62 mm per year, with pronounced seasonal declines 0.87 mm for winter, 12.33 mm for pre-monsoon, 24.93 mm for southwest monsoon, and 18.10 mm for post-monsoon. Simultaneously, the number of rainy days dropped by nearly 19.75 days over the 40-year period. A noticeable increase in decadal minimum and average temperatures was observed, highlighting potential adverse effects on cardamom yield and irrigation water resources. The findings suggest that excessive rainfall during the southwest monsoon negatively correlates with cardamom yield, while slightly warmer temperatures show a weak positive correlation. The study also emphasizes the need for adaptive agricultural practices and climate-resilient policies to mitigate the effects of changing climatic conditions on cardamom production. This research contributes valuable insights for farmers and other stakeholders as well as policymakers aiming to ensure sustainable cardamom cultivation amidst climate change. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive analysis of rainfall trends in the middle Euphrates region of Iraq, extending from 1980 to 2018, including wide region between the stations of Samawa, Al-Najaf, Karbala, Hilla, and Diwaniya. The research aims to fill a critical gap in the understanding of regional hydrological patterns and provide essential insights for sustainable water resource management. Using advanced statistical methods, such as the MannKendall test and Sen’s slope estimator, along with autocorrelation and cross-correlation analyses, we detected slight trends that were not previously reported. Principally, the Mann-Kendall test indicated no significant overall trends, while Sen’s slope estimator identified slight positive and negative trends at specific stations, highlighting local climatic variations. the findings reveal that all stations, except Samawa, indicated stationarity and homogeneity, with a particularly strong positive mutual correlation between Karbala and Hilla stations (0.7693 at lag 0). This research contributes new insights into rainfall variability in the Middle Euphrates, in Iraq, which presents significant data to improve water resource management strategies and inform future hydrological studies in the region. [ABSTRACT FROM AUTHOR]

Against the backdrop of intensified global climate change, the frequency and intensity of extreme weather events in mainland China continue to rise due to its unique topography and complex climate types. In-depth research on the trends and impacts of climate extremes can help develop effective adaptation and mitigation strategies to protect the environment and enhance social resilience. In this research, temperature data from 2029 meteorological stations for the period 1961–2021 were used to study 15 extreme temperature indices and 3 extreme composite temperature indices. Linear propensity estimation and the Mann–Kendall test were applied to analyze the spatial and temporal variations in extreme temperatures in China, and Pearson's correlation analysis was used to reveal the relationship between these indices and atmospheric circulation. The results show that in the past 60 years, the extreme temperature index in China has shown a trend of decreasing low-temperature events and increasing high-temperature events; in particular, the increase in warm nights is significantly higher than that of warm days. In terms of spatial distribution, daily maximum temperature less than the 10th percentile (TX10P) and daily minimum temperature greater than the 90th percentile (TN90P) increased significantly in the warm temperate sub-humid (WTSH) region, north subtropical humid (NSH) region, and marginal tropical humid (MTH) region, whereas frost days (FD0) and diurnal temperature range (DTR) decreased significantly. In the extreme composite temperature index, extreme temperature range (ETR) showed a downward trend, while compound heatwave (CHW) and compound heatwave and relative humidity (CHW-RH20) increased, with the latter mainly concentrated in the WTSH and NSH regions. Correlation analysis with climate oscillation shows that Arctic Oscillation (AO), Atlantic Multiannual Oscillation (AMO), and El Niño–Southern Oscillation (ENSO) are positively correlated with extremely high temperatures, whereas North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) are negatively correlated. [ABSTRACT FROM AUTHOR]

One of the main global concerns of the twenty-first century is climate change, which is causing patterns of precipitation and temperature to shift, as well as a rise in the frequency of extreme occurrences. In order to evaluate the effects of climate change on the Himalayan State, the study examines the long-term changes in temperature and precipitation in Sikkim, India, over a period of 121 years (1901–2021). The study uses the "Mann-Kendall Trend Test" and "Sen's Slope Estimator" to analyse the monthly temperature and precipitation data across Sikkim's districts: East, West, North, and South. The paper shows that the state has a significant increase in average temperatures across all districts, with an upward trend and p-values <0.01. The study also shows that the precipitation trends are less uniform, with South Sikkim being the only district exhibiting a significantly decreasing rainfall trend. The rising temperatures and variable precipitation patterns highlight the region's vulnerability to climate change, with potential implications for water resources, agriculture, and ecological balance. This research points towards the need for urgency in incorporating climate understandings into the policy frameworks to mitigate the adverse effects of climate change and promote sustainability in Sikkim. [ABSTRACT FROM AUTHOR]

The study assessed the radiological impact of the Kaiga Generating Station (KGS) on the surrounding environment and the safety of the nearby population. Over a period of 15 years (2005–2020), the radiological monitoring detected only trace levels of 3H and 137Cs (attributed to fallout) in the surrounding environment. The study utilized the non-parametric Mann–Kendall test to analyze the long-term trends, identifying either decreasing or no trend in the radioactivity levels across various environmental matrices such as air, water, biota, and dietary items. These findings indicate no significant accumulation of radioactivity, confirming the minimal environmental impact of the KGS operations. [ABSTRACT FROM AUTHOR]

This article presents an analysis of monthly precipitation totals based on data from the Global Precipitation Climatology Centre and monthly mean temperatures from the National Oceanic and Atmospheric Administration for 377 catchments located worldwide. The data sequences, spanning 110 years from 1901 to 2010, are analysed. These long-term precipitation and temperature sequences are used to assess the variability in climate characteristics, referred to here as polarisation. This article discusses the measures of polarisation used in the natural sciences. This study adopts two measures to evaluate the phenomenon of polarisation. The first measure is defined based on a stationary time series, calculated as the ratio of the amplitude of values to the standard deviation. The second measure is proposed as the difference in trends of these values. Based on the analysis of monthly precipitation data in the studied catchments, polarisation components are confirmed in 25% of the cases, while in the remaining 75%, they are not. For temperature data, polarisation is confirmed in 12.2% of the cases and not in the remaining 88.8%. The trend analysis employs Mann–Kendall tests at a 5% significance level. The Pettitt test is used to determine the point of trend change for precipitation and temperature data. This article underscores the complex relationship between climate polarisation and sustainable development, reaffirming that sustainable development cannot be pursued in isolation from the challenges posed by climate change. It emphasises the importance of integrating environmental, social, and economic strategies to adapt to extreme climatic events and mitigate their effects. This research is supported by detailed graphical analyses, with the results presented in tabular form. [ABSTRACT FROM AUTHOR]

In recent years, the escalating effects of climate change on surface water bodies have underscored the critical importance of analyzing streamflow trends for effective water resource planning and management. This study conducts a comprehensive regional investigation into the streamflow rate trends of 18 rivers across the United Kingdom (UK). An enhanced Mann–Kendall (MK) test was employed to meticulously analyze both rainfall and streamflow trends on monthly and annual scales. Additionally, the Innovative Trend Analysis (ITA) method was applied to elucidate the variability of streamflow rates, providing a more nuanced understanding of hydrological changes in response to climatic shifts. MK test reveals statistically significant positive trends in streamflow rates, particularly for rivers in south-central Scotland and northern England. Specifically, in January, rivers such as the Tay at Ballathie, Tweed at Peebles, and Teviot at Ormiston showed Z-scores above 2. Annually, similar positive trends were observed, with the Tay at Ballathie (Z = 3.42) and Nith at Friars Carse (Z = 3.35) exhibiting the highest increases in streamflow rates. The ITA method showed no relevant trends for the lowest values of streamflow, except for the Thames at Kingston, while considerable variability was observed for the highest streamflow rates, with several rivers showing positive trends and, however, some England rivers, like Bure at Ingworth, Test at Broadlands, and Trent at Colwick, showing negative trends. From this perspective, a more in-depth analysis of the extreme streamflow trends was carried out. In particular, the flood frequency of the maximum annual streamflow was assessed, based on the fitting of the Generalized Extreme Value (GEV) distribution on the annual maxima. Increasing location parameter (μ) and return period trends were observed for several rivers across the UK. In particular, the Tay at Ballathie (Scotland) showed the most marked increase, with μ that ranged from about 730 m3/s to more than 900 m3/s. At the same time, slight decreasing trends were observed for the Trent River (μ from 378 m3/s to 341 m3/s). The critical comparison of the MK test, ITA, and GEV distribution fitting revealed both agreements and discrepancies among the methods. While the analyses generally aligned in detecting significant trends in streamflow rates, notable discrepancies were observed, particularly in rivers with negligible trends. These inconsistencies highlight the complexity of hydrological responses and the limitations of individual methods. Overall, the study provides a comprehensive view of how streamflow dynamics are evolving in UK rivers, highlighting regional variations in the impact of climate change. This understanding can improve water resource management strategies by integrating diverse analytical approaches. [ABSTRACT FROM AUTHOR]

This study used 18 years (2001–2018) of Moderate Resolution Imaging Spectroradiometer-based Enhanced Vegetation Index products over Jharkhand state to extract phenology metrics based on Harmonic Analysis of the Time-Series algorithm. Results revealed that majorly Start of Season (SoS) occurred during April to June, End of Season (EoS) during December to February, and Peak of Season (PoS) during August to September in the forested areas. Trend analysis of SoS, PoS and EoS revealed advancement in 3891 Km2, 2627 Km2, and 3486 Km2 and delay in 5447 Km2, 5953 Km2, and 8265 Km2 of the study area. [ABSTRACT FROM AUTHOR]

As governments continue to address climate change when formulating policy, there remains a need to determine if such a change exists in the historical record to inform clear indices for monitoring the present climate for site-specific interventions. This study characterised trends and anomalies in rainfall and dry spells, providing local information often projected from satellites or regional data in data-scarce regions. From 1961 to 2007, daily rainfall records in Central Malawi were used to calculate indices for low-(Balaka), medium-(Bunda, Chitedze, KIA), and high-altitude (Dedza) sites, which were then subjected to Mann–Kendall's, Cramer's, and Spearman-Rho's trend tests. Significant decreasing trends in terms of wet days and growing season length were evident across locations. Seasonal and extreme rainfall, dry spells, and inter-seasonal and near-decadal anomalies were not consistently or inevitably significant. Unexpectedly, rainfall anomalies were largest in Bunda and KIA, which have mild climatic regimes, while the lowest were in Balaka, a rainfall-averse zone. The relationship between El Niño-Southern Oscillation (ENSO) and extreme rainfall and dry spell events did not reach statistical significance. In conclusion, extreme precipitation and dry spell events show varied intensities and proportions rather than increased frequency. The disparate results largely justify the need for in-depth local-scale assessments for agroclimatic applications. [ABSTRACT FROM AUTHOR]

This study aims to provide a comprehensive analysis of the impacts of high-intensity coal mining on vegetation in Liangbei Town, a typical deep coal mining area in central of China. Using Landsat remote sensing data from 2000 to 2023, processed by the Google Earth Engine (GEE) platform, the study calculates the Normalized Difference Vegetation Index (NDVI). Temporal and spatial distribution patterns of vegetation were assessed using LandTrendr algorithm, Sen's slope estimation, the Mann–Kendall test, the coefficient of variation, and the Hurst index. Vegetation growth dynamics were further analyzed through transfer matrix and intensity analysis frameworks. Driving factors influencing vegetation trends were evaluated using local climate data and surface deformation variables from SAR imagery. Temporal Dimension: From 2000 to 2023, the annual NDVI in Liangbei Township showed an upward trend with a growth rate of 0.0894 (10a)−1, peaking at 0.51 in 2020. Spatial Dimension: The NDVI distribution in Liangbei Township displayed a pattern of being lower in the center and higher around the edges, with values concentrated between 0.4 and 0.51, covering 50.34% of the total area. Trend of Change: Between 2000 and 2023, 83.28% of the area in Liangbei Township experienced significant improvement in the NDVI, with vegetation growth trends shifting primarily from slight to significant improvement, encompassing a total area of 10.98 km². This shift exhibited a marked tendency. Driving Factors: Deep mining in Liangbei Township is concentrated in the eastern part, with SAR imagery indicating a maximum surface subsidence of 0.26 m. As surface subsidence increases, the NDVI significantly decreases. The findings suggest that in the future, 91.13% of the vegetation in Liangbei Township will display an antipersistent change trend. The study offers critical insights into the interaction between mining activities and vegetation cover can serve as a reference for environmental evolution and management in similar mining areas. [ABSTRACT FROM AUTHOR]

Climate change is expected to significantly impact temperature and precipitation, as well as snow accumulations and melt in mid-latitudes, including in the Baltic region, ultimately affecting the quantity and seasonal distribution of streamflow. This study aims to investigate the changes in the magnitude and timing of annual maximum discharge for 30 hydrological monitoring stations across Latvia from 1950/51 to 2021/22. Circular statistics and linear mixed effects models were applied to identify the strength of seasonality and timing. Trend analysis of the magnitude and timing of flood peaks were performed by using the Theil–Sen method and Mann–Kendall test. We analyzed regional significance of trends across different hydrological regions and country using the Walker test. Results indicate strong seasonality in annual flood peaks in catchments, with a single peak occurring in spring in the study sub-period of 1950/51–1986/87. Flood seasonality has changed over recent decades (i.e., 1987/88–2021/22) and is seen as a decrease in spring maximum discharge and increase in winter flood peaks. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt dominated to mixed snow–rainfall dominated, with consistent changes towards the earlier timing of the flood peak, with a more or less pronounced gradation from west to east. Analysis shows that a significant trend of decrease in the magnitude and timing of annual maximum discharge was detected. [ABSTRACT FROM AUTHOR]

To properly manage the terrestrial ecosystem, it is essential to understand the vegetation sensitivity to climate variations and human actions. The main target of this survey was to evaluate the spatiotemporal variation in vegetation cover, and its relationship with climate variations and to calculate the contributions of driving factors in Namak Lake basin, Iran, during 2001–2019. To this end, Vegetation Health Index (VHI) and Standardized Precipitation Evapotranspiration Index (SPEI) in 3, 6, 9, and 12-month time scales were used to assess vegetation dynamics and its reactions to climate variations based on coefficient of determination (R2) and Linear Regression (LR). The results presented that vegetation cover had an improving trend in 87.78% and a decreasing trend in 12.19% of the basin, while it was stable in 0.03% of areas. The correlation between VHI and different time scales of SPEI indicated that coverage was mainly affected by 3-month SPEI in more than half of the basin (53.74%). High correlations between VHI and SPEI were found in upland areas in the northeast and some areas in the east of the basin. These areas also had the highest slope of VHI changes in relation to climate factors. Climate variability affected about four-fifths (79.22%) of coverage, while 16.36% was influenced by human actions, and 4.42% by both factors. Moreover, more than 99% of the significant improvements and degradations in coverage were related to climate variations and mankind's actions, respectively. The outcomes can serve as a foundation for initiating vegetation growth and protection in the Namak Lake basin. [ABSTRACT FROM AUTHOR]

The principal goal of this study is to analyze the evolution of topics and trends in emerging research fields by a combination of entity linking, Mann–Kendall test, and burst detection techniques. Multiple methods are applied here in the emerging field of cloud computing by focusing on the frequency of critical topics from 2004 to 2021. Statistical analysis reveals that the Internet of Things exhibits a significant scientific growth compared to other subject areas within the research field of cloud computing. Other emerging topics with rapid growth are computer networks, encryption, big data, distributed computing, and interaction of cloud computing with virtual machine research. The combination of different techniques can better show the complex dynamics and complementary aspects of scientific topics and trends underlying evolutionary pathways in emerging fields, such as the science and technology advances of architecture, hardware, and software components in the field of cloud computing. In scientometrics, the analysis with multiple techniques provides comprehensive scientific and technological information driving new directions in the evolution of research fields to guide R&D investments towards growing topics and technologies having the potential of supporting fruitful scientific and technological change. [ABSTRACT FROM AUTHOR]

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Climate change and anthropogenic activities (changes in rainfall and temperature pattern) activities have significantly affected agricultural activity and crop production. So, studying cropland greenness and crop yield trends is essential to understand their impacts and to ensure food security. The present study attempted to depict the cropland greenness and wheat yield trends in Uttar Pradesh (UP) state, India, during 2001–2019. The Moderate Resolution Imaging Spectroradiometer (MODIS) based Normalised Difference Vegetation Index (NDVI) dataset was used to decipher the cropland greenness trends through the Mann-Kendall (MK) test. Furthermore, the wheat yield dataset from Baghel and Sharma (2022) was used to depict the wheat yield trends using the Thiel-Sen slope test from 2001 to 2019. The study's results showed that ~ 37.3% (82,041 km2) area of the total agricultural land was with positive cropland greenness (NDVI) trend, and 1.67% (3673 km2) area was under a negative cropland greenness trend. On the other hand, ~ 8463 km2 (at 99% significance level) and 160,557 km2 (90% significance level) area corresponding to the ~ 4% and 73%, respectively, of the total agricultural land has shown positive (increasing) wheat yield trends during 2001–2019. In conclusion, the findings of this study emphasize the need for ongoing monitoring and a comprehensive understanding of cropland greenness and wheat yield trends over different agroclimatic zones. By gaining insights into these trends, policymakers and stakeholders can develop and implement effective mitigation and adaptation strategies to minimize the adverse effects of climate change and anthropogenic activities on agricultural systems. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change has essentially affected the characteristics of the thermal seasons, hence the overall ecosystems, and human health. The characteristics of the thermal seasons in Iraq, and how they change are still unclear. This research has been conducted to: (1) evaluate the spatial characteristics of summer season in Iraq over the period (1960-2021). (2) Estimating changes in the length and timing (onset and end) of summer in Iraq using the Mann-Kendall test (MK) and Sen's slope estimator. The findings indicated that there are significant spatial differences in the average length of the summer season in Iraq. The difference reaching more than 30 days between northern and southern Iraq, It is longer in the south. Results of trend analysis showed that summer season length significantly increases by 3.33 and 6.67 days/decade respectively. Our results reveal that, all over Iraq, the onset of thermal summer season occurs earlier by more than 17 days during (1960-2021). The biggest statistically significant changes in summer advancing were observed in northern and western Iraq. However, the results revealed that the only western Iraq has been recorded advancing at the end of the summer, while the end of the summer at all other parts occurred later.

This study identified the trends in monthly temperature, precipitation, & evaporation for Astore, Darosh, Gilgit, Gupis and Skardu and trends in inflow, outflow and reservoir level for Tarbela reservoir. Two non-parametric tests i.e. Man-Kendall and Sen’s Slope and Innovative Trend Analysis (ITA) were used to determine the trend. The first Mann-Kendall test with a significance level 5% was applied to 33-year data of five selected areas from 1990-2022. The results showed an increasing trend in temperature in March for all selected areas. No significant trend was observed in precipitation except negative trends for Darosh in March, May and December and positive trend for Gilgit in January and September. It has been observed that the trend direction given by ITA and Mann-Kendall is similar. Inflows to reservoir were found directly related to the temperature because of glacier melt in rising temperature, thus increasing the inflow, although the precipitation was found decreasing with increase in temperature. Altered snowmelt patterns can influence weather systems, potentially contributing to more extreme weather events.

The hydrological regulation function of glaciers in different watersheds is different. This study took the Yanggong River Basin (YRB) and Urumqi River Basin (URB) as two typical cases, to explore the runoff change differences and their responses to climate factors from 1979 to 2017. In the past 39 years, the YRB’s annual runoff showed an insignificant trend of increasing first and then decreasing, while the URB’s increasing trend was significant. From the 1980s to the 2010s, the YRB’s monthly runoff extremum occurred earlier than before, and the peak value decreased. The time of monthly runoff extremum in the URB has not changed, but the peak value is increasing. Both basins experienced an increase in annual temperatures from 1979 to 2017, with the rate of warming being more pronounced in the URB. The precipitation in the YRB had no significant trend from 1979 to 2017, and the significant increasing trend in annual precipitation extended in the URB from 1998 to 2010. The YRB’s runoff change was mainly influenced by the flood season precipitation, while the URB’s runoff increase was due to the temperature rise causing faster glacier and snow melt, and the summer precipitation change. In continental glacier basins with many glaciers, the regulation function of glaciers on total runoff is more significant.