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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]

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]

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]

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 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]

[Objective] Rainfall erosivity serves as an indicator to assess the potential impact of rainfall on soil erosion, playing a crucial role in evaluating regional soil erosion risk. Therefore, analyzing the temporal and spatial variations of rainfall erosivity in Beijing from 1981 to 2020 holds significant importance for scientifically assessing and preventing regional soil erosion risks. [Methods This study employed Kriging interpolation, Mann-Kendall non-parametric test and wavelet analysis based on daily precipitation data collected from 119 rainfall stations in Beijing and its surrounding areas between 1981 and 2020. These methods were utilized to analyze the spatial distribution, trend changes, and periodic fluctuations of annual rainfall erosivity as well as erosivity associated with moderate rain (10~25mm), heavy rain (25~50mm), and extreme rain ≥50 mm) in Beijing. [Results] The annual rainfall erosivity in Beijing ranged from 1 691.51 to 3 914.89 (MJ ·mm)/(hm²·h·a) during the period from 1991 to 2020. The spatial distribution characteristics of annual rainfall erosivity exhibited similarities with heavy rain and rainstorm but differed from moderate rain patterns. Overall, there was a decreasing trend observed from northeast regions towards the surrounding areas. Over the past four decades, moderate rainfall erosivity demonstrated a significant increasing trend in Beijing; however, no significant mutations or trends were observed for annual rainfall erosivity, heavy rain events, rainstorms or July-August summer precipitation erosivity. Notably large decreasing trends were identified for annual rainfall erosivity within local areas such as Miyun and Pinggu districts. The main cycle for both annual rainfall erosivity and medium-to-heavy intensity precipitation lasted approximately twenty-five years with two to three alternating "low-high" changes. [Conclusion] The study can offer a scientific foundation for soil and water conservation, agricultural practices, and ecological preservation in Beijing. [ABSTRACT FROM AUTHOR]

This research aims to assess the climatic temporal suitability over the year and identify the appropriate season for open-air tourism in ten Romanian cities. It was evaluated using the Enhanced Tourism Climatic Index on a temporal scale of one day and then aggregated to 10 days over 61 years (1961–2021). Daily mean and maximum temperature, mean and minimum relative humidity, wind speed, precipitation, and sunshine hours were employed in the investigation. The Mann–Kendall test and Sen's slope were used for trend detection in the frequency, season duration, and first/last suitable day during the year for outdoor tourism. Acceptable or better weather conditions usually begin in the last part of April and end in mid-October, with Good or better conditions lasting between 260 and 310 days/year. The trend shows a shift of Good conditions earlier in the year (0.3–9.0 days/decade), resulting in a longer season duration (0.8–13.0 days/decade) for open-air activities. The trend is statistically significant mainly for the extra-Carpathian regions. Big differences in open-air events number during the climatically suitable season have been identified among the cities considered (2–19 events/year). This study is useful for better planning open-air events and activities for tourism and recreation. [ABSTRACT FROM AUTHOR]

This study delves into the application of Shannon entropy to analyze the long-term variability in climate data, specifically focusing on precipitation and temperature. By employing data from 1901 to 2010 across 377 catchments worldwide, we investigated the dynamics of climate variables using the generalized extreme value (GEV) distribution and Shannon entropy measures. The methodology hinged on the robust bootstrap technique to accommodate the inherent uncertainties in climatic data, enhancing the reliability of our entropy estimates. Our analysis revealed significant trends in entropy values, suggesting variations in the unpredictability and complexity of climate behavior over the past century. These trends were critically assessed using non-parametric tests to discern the underlying patterns and potential shifts in climate extremes. The results underscore the profound implications of entropy trends in understanding climate variability and aiding the prediction of future climatic conditions. This research not only confirms the utility of Shannon entropy in climatological studies but also highlights its potential in enhancing our understanding of complex and chaotic climate systems. The study's findings are vital for developing adaptive strategies in response to the evolving nature of climate extremes, thus contributing to more informed decision-making in environmental management and policy formulation. [ABSTRACT FROM AUTHOR]

Preserving the quality of groundwater has become Bangladesh's primary challenge in recent years. This study explores temporal trend variations in groundwater quality on a broader scale across 18 stations within the Dhaka division over 35 years. The data set encompasses an analysis of 15 distinct water quality parameters. Modified Mann-Kendal, Sens Slope and Mann-Kendal tests were performed to determine the trend's variation and slope. In addition, the spatial–temporal changes in the quality of groundwater are studied through Geographic Information System (GIS) mapping and Piper diagram was applied to identify the unique hydrochemical properties. This is the first study conducted on this area using various trends analysis and no in-depth study is available highlighting the trends analysis of groundwater quality on a larger magnitude. In contrast, the correlation matrix reveals a high association between Mg2+ and SO42−, Na+ and Cl− that affects salinity and overall hardness at the majority of sites. The Piper diagram also demonstrates that the groundwater in Madaripur Sadar has major salinity issues. The analysis reveals a distinctive dominance of bicarbonate (HCO3−) ions across all sampling stations, with (HCO3−) equivalent fractions consistently ranging from 0.70 to 0.99 which can cause a significant impact on groundwater uses. This extensive analysis of long-term groundwater quality trends in the Dhaka Division enables researchers to comprehend the overall transition of groundwater quality for hardness related complications in future. Moreover, it can be a baseline study considering the valuable implications and future steps for sustainable water resource management in this region. [ABSTRACT FROM AUTHOR]

Daily maximum, TX, and minimum, TN, temperatures recorded at Fabra Observatory, for the period 1914–2020 (from June to September), have permitted to identify the daytime and night time heatwaves, HWs, at the Barcelona Metropolitan Region, BMR, along 107 years. Four heatwaves indices have been computed both for maximum and minimum temperatures: the number of events per season, HWN; their maximum duration, HWD; their frequency of occurrence, HWF; and the amplitude of the hottest day event, HWA. Trends in these indices have been obtained and their statistical significance quantified by means of the Mann-Kendall test. For the whole period (1914–2020), positive significant trends have been detected for the four indices, with a marked positive trend since year 2000 for TX, and since 1985 for TN. Nevertheless, when 31-year moving windows have been analysed, both positive and negative significant trends are obtained, being remarkable the change in trend signs around 1960s. The convenience of using the four HW indices is evaluated applying a Principal Component Analysis, PCA, obtaining two principal components. Additionally, the spatial distributions of the MODIS land surface temperatures, LST, corresponding to some extreme heatwaves, permits the detection of two hotspots in the BMR, one for TX and the other for TN. It is also worth mentioning that correlations between the Western Mediterranean Oscillation index, WeMOi, and HW episodes are detected, being notable that, at the beginning of these episodes, WEMOi values are usually lower. These correlations could improve the HWs forecasting. [ABSTRACT FROM AUTHOR]

Human activities, particularly the regulation of hydropower stations, have profoundly altered river flow patterns. While studies have extensively assessed the impact of large or multi-year regulated hydropower stations on hydrological regimes using indicators of hydrological alteration (IHA) and range of variability approach (RVA), the impact of daily regulation hydropower stations has received comparatively less attention. This study aims to evaluate the influence of daily regulation hydropower stations on hydrological regime changes, focusing on the upper Yellow River region in China. Using daily runoff data from 1954 to 2020 at the Guide station, the study compares the impacts of multi-year regulated (Longyangxia) and daily regulation (Laxiwa and Nina) hydropower stations. The Mann-Kendall test showed that 27 out of 32 Indicators of Hydrological Alteration (IHAs) had significant trends under Longyangxia operation, which reduced to 18 IHAs with the inclusion of daily regulation stations. The Range of Variability Approach (RVA) revealed that only 46.87% of IHAs exhibited high alteration from the natural regime when daily regulation was considered, down from 75.00% with Longyangxia alone. This suggests that daily regulation can mitigate the negative impacts of multi-year regulation, potentially enhancing the river's eco-hydrological health. [ABSTRACT FROM AUTHOR]

The natural fluctuation of hydrological regime is the key to maintaining the functionality and hydrological health of river ecosystems. Aiming at the change of hydrological regime in the Yellow River Basin caused by climate change and human activities, we selected daily runoff data from Lanzhou, Longmen and Huanyuankou stations (1956-2020), the representative hydrological stations in the Yellow River Basin and used the Mann-Kendall and Pettitt test methods to comprehensively evaluate the hydrological regime in the Yellow River Basin. The Mann-Kendall and Pettitt tests were used to quantitatively evaluate the extent of hydrological changes in the Yellow River Basin by using the eco-hydrological index range of change (IHA-RVA) method. The results show that a) the abrupt changes in runoff at Lanzhou, Longmen and Huayuankou stations occurred in 1984, 1987 and 1986 respectively, and that the average annual flow in the control basin at Longmen and Huayuankou stations showed a significant decrease. b) The variation of the minimum annual discharge in Lanzhou Station during 90 days is the highest, reaching 83%. The average discharge of Longmen Station in April is the highest, reaching -100%. The average increase (decrease) rate of discharge at Huayuankou Station has the highest variation, reaching -92%. c) The overall hydrological alterations at Lanzhou, Longmen, and Huayuankou stations are 34%, 37% and 51% respectively, which are all moderate. [ABSTRACT FROM AUTHOR]

Accurate and in-depth rainfall studies are crucial for understanding and assessing precipitation events' patterns, intensities, and impacts, enabling effective planning and management of water resources, agriculture, and disaster preparedness. Despite many rainfall studies in Bangladesh at the national and regional scales, study on the spatiotemporal rainfall variability is still rare at the local scale. The current study aims to apply Mann–Kendall (MK), Modified Mann–Kendall (MMK), and Innovative Trend Analysis (ITA) techniques to assess the long-term annual and seasonal rainfall trends and variability over the southeast region of Bangladesh. Monthly rainfall data from ten Bangladesh Meteorological Department climate stations between 1981 and 2022 was used for the analysis on annual and four seasonal scales. The precipitation concentration index results showed significant variations in annual rainfall across the study area, whereas seasonal PCIs were consistent with moderate rainfall. According to standardized rainfall anomaly findings, each station experienced at least one severe to extremely severe drought episode during the 42-year study period. Homogeneity tests revealed significant breakpoints in some rainfall datasets, while 78% were declared homogeneous. MK, MMK, and ITA techniques revealed similar increasing and decreasing trend patterns throughout the study area. Annual rainfall showed an upward trend in the coastal part and a downward trend in the northern part of the study area, with monsoon rainfall exhibiting a similar trend pattern. The ITA technique outperformed the MK and MMK techniques in detecting trends, identifying significant increasing and decreasing trends in 76% (38 out of 50) of the observations, while the MK and MMK techniques detected trends in only 8% and 44% of the total observations, respectively. The outcome of the current study is expected to be helpful for the sustainable planning and management of water resources in the southeast region of Bangladesh. [ABSTRACT FROM AUTHOR]

Using the daily 2-minute average wind speed data from 1961 to 2020 in Yichang City, the climate tendency method, Mann-Kendall test method and wavelet analysis method were used to analyze the change trend, mutation, and periodic characteristics of average wind speed at different time scales, revealing the long-term wind speed variation patterns in the local area of the Three Gorges area. The results showed that the annual mean wind speed in Yichang City had increased in recent 60 years with a decreasing rate of 0. 084 m/ (s·10 a), and the four seasons mean wind speed had a slightly increasing trend with a similar climate tendency rate. The increase of average wind speed was the fastest in August and the slowest in June. The Mann-Kendall mutation test showed that the annual mean wind speed in Yichang City had a sudden change in 1971,1996 and 2013. Wavelet analysis showed that the annual mean wind speed changes periodically, and the first main period of the annual mean wind speed change was 32 years. [ABSTRACT FROM AUTHOR]

[Objective] The purposes of this study are to elucidate the long-term trends and periodic characteristics of runoff in the Dagu River Basin, and to offer the theoretical insights to guide water resource management and promote sustainable development in the Dagu River Basin. [Methods] The measured runoff data from the Nancun Hydrological Station（1956—2020） and the Zhazi Hydrological Station（1956—2016） were used to analyze the trend of annual runoff changes and abrupt change times using the Mann-Kendall test and sliding t-test. The Morlet continuous complex wavelet method was used to analyze the periodic characteristics of multi-year runoff in the basin. [Results] The annual runoff in the Dagu River Basin was generally declining, and there was a characteristic of more flow during the flood season（June—September） and less flow during the non-flood season. The peak flow usually occurred in August. The runoff of Nancun Station was abrupt in 1976, and the runoff of Zhazi station was abrupt in 1979. The runoff of the Dagu River Basin exhibited significant periodic variations at multiple time scales, with a dominant period of around 20 years, and significant oscillations before the 1980s. [Conclusion] The long-term series runoff of Dagu River Basin showed a trend of significant decline, and the basin runoff suddenly changed in the 1970s, and there were periodic changes in different time scales. In the future, the research on the mechanism of runoff change should be strengthened. [ABSTRACT FROM AUTHOR]

This study was aimed to investigate the trends in (11) thermal bioclimatic indicators throughout Iraq's various climates to better understand their spatiotemporal variations in different climates. All bioclimatic indicators have been calculated from daily ERA5 datasets of temperature extracted from 361 grid points covering Iraq. This data set covers global coverage of monthly temperatures from 1980 to 2022, with a spatial resolution of (0.25°x0.25°). Eleven thermal bioclimatic indicators were subjected to the Mann-Kendall (MK) test in order to measure trends in a single direction, without taking into account the influence of natural cycles. The findings showed that the majority of Iraq's thermal bioclimate indicators had changed. implying that rising temperatures have had a significant influence on the country's bioclimate. The annual mean temperature data revealed that Iraq had a considerable increase in Bio1 of (0.28 to 0.48) °C/decade, which is more than the )0.15( °C/decade worldwide average. The rise was found to be significantly greater in Iraq's northern and eastern regions. The analysis suggested that the diurnal temperature range decreased in most regions of Iraq, especially in the southern and northeastern sections. The maximum temperature increased most dramatically in the warmest quarter, whereas the changes in the coldest quarter were less noticeable, showing an increase in climatic extremes in Iraq. The study unequivocally shows that climate change is leading to an increase in the mean temperature, specifically during the warmest months of the year. [ABSTRACT FROM AUTHOR]

The objective of this study was to propose bioclimatic zoning to classify human thermal comfort and discomfort in the state of Minas Gerais, Brazil; both historical and future scenarios are considered. Thus, historical series (1961 to 2017) of the effective temperature index as a function of the wind (ETW) were obtained as a function of the monthly average values of the minimum, mean, and maximum dry-bulb air temperatures (tdb,min, tdb,mean, and tdb,max, respectively), in addition to the mean relative humidity (RH , %) and mean wind speed (V , m s −1). The data were obtained from 34 weather stations and subjected to trend analysis by using the nonparametric Mann–Kendall test, thus enabling the simulation of future scenarios (for 2028 and 2038). Then, to define the thermal ranges of the bioclimatic zoning, maps of ETWmin, ETWmean, and ETWmax were created from geostatistical analysis. Overall, the results show warming trends for the upcoming years in Minas Gerais municipalities. All climatic seasons showed an increase in the frequency of new classifications in the upper adjacent classes, which indicates climate warming. Therefore, when considering future scenarios for the autumn and winter seasons, attention should be given to changes in predicted thermal sensation, especially in the Central Minas Gerais, Belo Horizonte Metropolitan, South/Southwest Minas, Campo das Vertentes, and Zona da Mata. [ABSTRACT FROM AUTHOR]

This study examines the changing rainfall patterns in the Vietnamese Mekong Delta (VMD) utilizing observational data spanning from 1978 to 2022. We employ the Mann–Kendall test, the sequential Mann–Kendall test, and innovative trend analysis to investigate trends in annual, wet, and dry season rainfall, as well as daily rainfall events. Our results show significant spatial variations. Ca Mau, a coastal province, consistently showed higher mean annual and seasonal rainfall compared to the further inland stations of Can Tho and Moc Hoa. Interestingly, Ca Mau experienced a notable decrease in annual rainfall. Conversely, Can Tho, showed an overall decrease in some months of the wet season and an increase in dry season rainfall. Furthermore, Moc Hoa showed an increase in the number of rainy days, especially during the dry season. Principal component analysis (PCA) further revealed strong correlations between annual rainfall and extreme weather events, particularly for Ca Mau, emphasizing the complex interplay of geographic and climatic factors within the region. Our findings offer insights for policymakers and planners, thus aiding the development of targeted interventions to manage water resources and prepare for changing climate conditions. [ABSTRACT FROM AUTHOR]

Estimation of baseflow is a complex hydrographic task. Baseflow techniques and coefficients vary from basin to basin, stream to stream, and year to year. In this study, meta-heuristic optimization is used to automatically identify baseflow. The Particle Swarm Optimization (PSO), a meta-heuristic optimization approach, is chosen. The constraint and cost functions were determined using the PSO algorithm, Lyne and Hollick techniques, and a computer application. Over the period 1980–2015, the data were collected at the Kale station in the Yesilirmak River basin to validate the study model. The results show that the hydrographs and baseflow dividing line were separated effectively. It has also been revealed that the PSO has a high speed as well as a high level of precision. In the research, in addition to the baseflow separation, the hydrograph, baseflow, and ratio of the baseflow to the streamflow at the station No. 1402 were assessed using the Mann–Kendall test and Innovative Trend Test (ITA), and as a result, their trends have been found. By the use of both of these methods, it has been shown that all parameters have an unfavorable trend. In addition, the research came to some other significant conclusions, such as the fact that the baseflow declines in tandem with the flow values and that the baseflow rates are low in years with high peak values of the hydrograph. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to explore the variation law of the long-term measured runoff and sediment load series, and to provide scientific support for the implementation of the western ecological security strategy by the country. [Methods] The linear trend estimation and moving average, Mann Kendall nonparametric test method, wavelet analysis method, were applied to analyze the measured data of annual runoff and sediment load series at Changmapu, Panjiazhuang, and Dangchengwan stations in the Shule River Basin. [Results](1) Both the annual runoff and sediment discharge of Shule River basin was increasing, however, the increasing trend of runoff was more significant than sediment discharge. The annual runoff of Changmapu, Panjiazhuang, and Dangchengwan stations had an obvious turning point in 1999, 2016 and 1982, respectively. The annual sediment discharge of Dangchengwan did not have sudden changes, and the sudden changes in the annual sediment discharge of Changmapu and Panjiazhuang all occurred in 1998.(2) The runoff and sediment discharge of the three representative stations in the Shule River basin all showed the evolution characteristics of multiple time scales. Wavelet analysis indicated periodicities of 58 years, 31 years, 14 years, 9 years and 5 years for annual runoff and periodicities of 48 years, 23 years, 14 years, 7 years and 5 years for annual sediment load in Changmapu. There were periodicities of 59 years, 32 years and 14 years for annual runoff and periodicities of 37 years, 14 years, 8 years and 5 years for annual sediment load in Panjiazhuang station. There were periodicities of 42 years and 5 years for annual runoff and periodicities of 16 years and 8 years for annual sediment load in Dangcheng station. [Conclusion] The overall trend of water and sediment in the Shule River Basin is increasing, and there is a significant periodic change. Except for the sediment transport in Dangchengwan, all other stations have sudden changes in water and sediment transport. Moreover, the sudden change in sediment transport at the same hydrological station lags behind the sudden change in runoff. [ABSTRACT FROM AUTHOR]

The main elements that define the climate of a place are air temperature and atmospheric precipitation. Through this study, we aim to highlight the significance and extent of the trends of the two climatic elements for the interval 1961- 2020 at the Cotnari meteorological station compared to those at the territorially neighboring stations Botoşani, Iaşi and Roman. For this purpose, we identified the basic thermo-pluviometric peculiarities at the Cotnari meteorological station for the period 1961-2020 and analyzed the evolution of the thermo-pluviometric parameters on interdecadal and interannual periods. We then applied the Mann-Kendall test combined with Sen's slope to estimate the trend over the reference period. Following these analyses, in Cotnari, taking as a reference the average annual temperature of 9.6°C and the average annual amount of precipitation of 543.8 mm, we found that after the year 2000, the trend of these two elements was positive, which shows an increase in air temperature and quantitative atmospheric precipitation. In total, the annual thermal averages increased statistically significantly by 0.33°C/decade. Annual precipitation increased during 1961–2020 by 2.2 mm/decade and showed modest statistical significance. [ABSTRACT FROM AUTHOR]

The present study analyzes trends of extreme flows for the Krishna river at the Prakasam barrage, Vijayawada of Andhra Pradesh state, India. Annual maximum and minimum flows are considered using available data from the CWC (Central Water Commission) portal from 1965–1966 to 2019–2020. The trend analysis of extreme flows is carried out using the Mann-Kendall trend test, Sen's slope, and modified Mann-Kendall test, that is, bootstrapped Mann-Kendall trend test with optional bias-corrected pre-whitening. Also, R programming is applied for the trend analysis of extreme flows. Extreme annual flows are in decreasing trend. Annual maximum flow has significant decreasing trend with Sen's slope of 105.52 cumecs per year. Annual minimum flow has insignificant decreasing trend at a magnitude of 0.0002 cumecs per year. Trend results of the present study are useful for the trend analysis of extreme river flows. [ABSTRACT FROM AUTHOR]

The article provides a long-term trend analysis of the Kesinga catchment daily gridded rainfall at a (0.25° × 0.25°) high spatial resolution from 1901 to 2020 (120 years). The trend in seasonal and annual rainfall was detected using rank-based nonparametric statistical tests, namely Spearman's rho and Mann-Kendall test, which are used for detecting monotonic trends in time series data at the 5% significant level, smoothing curve, Sen's slope test, and a plot of innovative trend analysis. The results showed that statistically significant trends had a pattern with both positive (increasing) and negative (decreasing) trends, with positive and negative trends evident in the winter and negative trends shown in the monsoon, PREMON, and annual seasons. The middle of the study area revealed the highest negative trend, and the lower Kesinga catchment showed the lowest negative annual rainfall trend. In the entire Kesinga catchment, the seasonal data and annual rainfall both showed statistically significant and non-significant patterns. Consistently, the MK and SR tests were both conducted at the validated significance level. In various contexts, the statistically significant massive trend that has occurred was negative (70%). If the current pattern continues in the future, there will be a scarcity of water and more strain on the control of water resources at the given grids in corresponding temporal scales. [ABSTRACT FROM AUTHOR]

As a climate-sensitive and fragile region, how the Tibetan Plateau (TP) responds to global warming would have significant implications for its ecological environment and sustainable socio-economic development. A crucial tool for assessing fine-scale climate impacts is the NEX-GDDP-CMIP6 dataset. This study utilized the NEX-GDDP-CMIP6 dataset to determine changes in extreme temperature and precipitation indices under different Shared Socioeconomic Pathways (SSP) relative to the baseline warming by 1.5 °C, 2 °C, and 3 °C. By using the Theil-Sen median trend and Mann-Kendall test methods, the research concluded that warming trends and increased humidity were on an upward trend. These changes led to amplified fluctuations in the frequency, intensity, and duration of multiple extreme indices. [ABSTRACT FROM AUTHOR]

Aridity is a climatic phenomenon characterized by shortage of water availability in a given time and space resulting in low moisture and reduced carrying capacity of ecosystems. It is represented by a numerical indicator known as Aridity Index (AI), a function of rainfall and temperature. Aridification is a slow and steady effect of climate change and assessing its spread and change is vital in context of global climatic variations. Aridity is predominantly significant for agrarian countries like India, where a slight rise in drylands area can have a significant impact on the economy and community sustenance. AI is an inclusive indicator of climatic conditions in most arid and semi-arid regions. It helps in identifying and interpreting large scale trend in temperature and precipitation; and thus, classifying region into different climatic classes. The present study assessed long-term AI based on precipitation and temperature data obtained from the India Meteorological Department at the resolution of 1 × 1 degree for years 1969–2017. AI is estimated as a ratio of mean precipitation to mean potential evapotranspiration, calculated using Thornthwaite method. The results highlight the trend of aridity over pan-India with Innovative Trend Analysis and Mann–Kendall test. The study concludes that there is a relatively slow, however steadily progressive drier conditions being established in most of the regions. A shift from 'Semi-arid' towards 'Arid' class appeared in central mainland. The north-eastern Himalaya showed decrease in humid conditions ('Humid' to 'Sub-humid'). The study implies that there is a rising aridity trend over the years due to changing climatic conditions. The shifts in aridity can have serious implications on agriculture, long-term water resource utilization and land use management plans. Our results have scope for future landscape management studies in drylands and better adaptation methods in arid regions. [ABSTRACT FROM AUTHOR]

As vegetation plays a critical role in terrestrial ecosystems, understanding its status and variation is vital for preserving the stability of an ecosystem. Central Asia serves as a representative example of an arid and semi-arid region characterized by sparse vegetation and poor soils, making its vegetation particularly fragile and sensitive. To investigate the vegetation condition in the region, this study examined the spatial and temporal characteristics of vegetation variation from 2001 to 2020, utilizing the normalized difference vegetation index (NDVI) as an indicator. Meanwhile, trend analysis, Mann–Kendall abrupt change point test, geodetector, and correlation analysis were used to quantitatively analyze the natural and anthropogenic drivers of these variations over the past two decades. The results suggest that vegetation coverage in Central Asia was relatively low, with an annual average NDVI of 0.16 over the past 20 years. Moreover, the spatial distribution of NDVI in Central Asia exhibited significant spatial heterogeneity, with vegetation coverage declining from north to south and from east to west. Furthermore, the NDVI exhibited a slightly increasing trend during the period of 2001 to 2020 with an increased rate of 0.00025/yr. However, we detected an abrupt change point in vegetation dynamics in Central Asia around 2010, which indicated a significant shift in vegetation variation in the region. Land-use type has a great influence on the spatial heterogeneity of NDVI in Central Asia, which can explain 46% of the vegetation distribution in this region. Moisture factors such as precipitation and soil water content followed with 35% and 32% contributions, respectively. Regarding the temporal variation of NDVI, it is mainly driven by the fluctuation in precipitation, with the degree of influence of precipitation on NDVI varying for different regions in various geographical conditions. This study offers a more comprehensive insight into the spatial and temporal dynamics of NDVI in Central Asia and indicates that precipitation plays a significant role in driving the spatial heterogeneity and temporal variation of NDVI. These findings are essential for predicting vegetation changes in arid regions under future environmental conditions and formulating effective strategies to prevent and alleviate vegetation degradation. [ABSTRACT FROM AUTHOR]

The emission, transport, and deposition of desert dust are influenced by environmental factors evaluated mainly as a function of precipitation, air temperature, and wind. The present study estimates the desert dust balance and its relationship with environmental factors for the period 1981–2020 in the Baja California Sur region, Mexico. Monthly data on wind, air temperature, precipitation, dust emission and deposition from in situ measurements, reanalysis, satellite estimates and a numerical parameterization scheme are used. First, the in-situ time series were reconstructed with a non-linear principal component analysis based on an autoassociative neural network. We then evaluated the performance of the satellite estimates and the reanalysis data using the matching technique, after which we quantified the dust emission in three source zones. To estimate the state of the climate, we obtained the annual cycle of monthly climatologies, and yearly averages. The effect of climate on the dust budget is estimated by means of non-parametric associations between the variables of interest. Finally, we estimate climate trends using Pettitt, Modified Man-Kendall and Theil-Sen tests. The results show that the data sets used represent the mean and variability of in situ measurements. There are three seasons with transitional periods for precipitation and air temperature. The wind shows a longitudinal west–east gradient. Its maximum intensity is from April to September. Northern zone was dominated by highest emissions. Dry deposition mechanism was the most representative. Emissions and dry deposition are controlled by wind intensity and precipitation, while precipitation controls wet deposition. The Pettitt test showed that abrupt changes in the time series coincide with periods where positive sunspot anomalies converge with negative PDO and SOI anomalies. Finally, trend analyses identified a temporal broadening of the dry season, warmer winters, and summers with increases of ~ 0.02 °C, predominantly increasing trends in dust emissions and wind intensity, and a progressive decrease in dust deposition mechanisms. [ABSTRACT FROM AUTHOR]

This paper analyzed the variations of two air temperature indices, diurnal temperature range (DTR) and annual temperature range (ATR), calculated based on observations at the Zagreb Grič Observatory over a period of 133 years (1887–2019). In intense climate changes strongly manifested by the increased air temperature, these two climate indices were determined to significantly impact human health and the environment. This effect is especially evident in urban areas. The Zagreb Grič Observatory is located in the center of Zagreb and has not changed its location during the observed period. It has a long homogeneous series of climatological observations, enabling a detailed study of climate variation in the city, which is strongly influenced by various urbanization processes. In 133 years, both of the analyzed indicators showed a statistically insignificant downward trend. The Rescaled Adjusted Partial Sums (RAPS) method revealed statistically significant differences in DTR's time series between three sub-periods: 1887–1953, 1954–1989, and 1990–2019. The time series of ATR during 133 years behaved statistically differently in four sub-periods: 1887–1905; 1906–1926; 1927–1964; and 1965–2019. The analysis of monthly values of DTR showed that the DTR values are the highest in the warm part of the year, from May to August, when they are twice as high as those during the cold period from November to December. With an increase in precipitation, the DTR values decrease, while they increase as the mean annual temperature increases. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid advancement of China's urbanization, the contradiction between urban development and the ecological environment has become increasingly prominent, and the urban ecological system now faces severe challenges. In this study, we proposed an ecological index-based approach to monitor and evaluate the ecological environment using a Google Earth Engine cloud-based platform and Landsat time series. Firstly, a long-term series of Landsat images was obtained to construct and calculate the remote sensing-based ecological index (RSEI). Then, the Theil–Sen median estimation and the Mann–Kendall test were used to evaluate the trend and significance of the RSEI time series and combined with the Hurst index to predict the future development trend of the ecological environment in the study area. Finally, the coefficient of variation method was used to determine the temporal stability of the ecological environment. Taking Zhoushan Archipelago, China, as the study area, we mapped the distribution of the ecological environment using a spatial resolution of 30 m and evaluated the ecological environment from 1985 to 2020. The results show that (1) from 1985 to 2020, the average RSEI in the Zhoushan Archipelago decreased from 0.7719 to 0.5817, increasing at a rate of −24.64%. (2) The changes in the areas of each level of ecological environmental quality show that the ecological environment in the Zhoushan Archipelago generally exhibited a decreasing trend. During the study period, the proportion of the areas with excellent ecological environmental quality decreased by 38.83%, while the proportion of areas with poor and relatively poor ecological environmental quality increased by 20.03%. (3) Based on the overall change trend, the degradation in the ecological environment in the Zhoushan Archipelago was greater than the improvement, with the degradation area accounting for 84.35% of the total area, the improvement area accounting for 12.61% of the total area, and the stable area accounting for 3.05% of the total area. (4) From the perspective of the sustainability of the changes, in 86.61% of the study area, the RSEI exhibited positive sustainability, indicating that the sustainability of the RSEI was relatively strong. (5) The coefficient of variation in the RSEI was concentrated in the range of 0–0.40, having an average value of 0.1627 and a standard deviation of 0.1467, indicating that the RSEI values in the Zhoushan Archipelago during the study period were concentrated, the interannual fluctuations of the data were small, and the time series was relatively stable. The results of this study provide theoretical methods and a decision-making basis for the dynamic monitoring and regional governance of the ecological environment in island areas. [ABSTRACT FROM AUTHOR]

Interactions between land use and cover and a basin hydrological regime are complex and dynamics. The identification of trends and changes in rainfall and flow regimes in a region is relevant in water resources planning and management so that environmental, economic and social adversities are avoided. Thus, this study aims to identify possible trends in the historical series of rainfall and fluviometric stations in Rio das Mortes basin, Minas Gerais, Brazil, as well as to relate the modifications in the flow rate behaviour due to changes in land use and cover in the basin between the years of 1985 and 2017. For that, hydrological data were used from the Ibituruna-MG river station and 12 rainfall stations and orbital images from Landsat-5 and Sentinel satellites. Flow rate and precipitation behavior were performed using the nonparametric Mann-Kendall test and the Pettitt's test, while the land use and cover classification was performed in an eCognition Developer® 64 environment. Significant trends were observed in the average of total annual rainfall series and decreasing trends in the average of monthly flow rate series of lowest runoff over the years 1925 to 2014. There were changes in land use and cover in the studied region, however, these were not significant enough to modify the hydrological regime of Rio das Mortes basin during the analysed period. [ABSTRACT FROM AUTHOR]

Climate change is a pressing issue that is affecting the lives and livelihoods of millions of people across the world. This study investigates the trend analysis and spatial-temporal variations of temperature and precipitation on a monthly, seasonal, and annual basis in Rajasthan state, India, over the past 40 years (1981-2020). The trend analysis of temperature and precipitation were analysed using the Mann-Kendall test at the confidence level of 95%. The magnitude (slope) was determined by using Theil-Sen's slope test. The results of the analysis revealed significant positive and negative trends of temperature and precipitation observed on a monthly, seasonal, and annual basis in all the 33 districts of Rajasthan state. The summer season experienced the maximum average temperature, while the winter season had the minimum. The study also found that the northern and western parts of Rajasthan experience "Mawat" rain during the winter due to cyclones happening in the Mediterranean Sea during that season. The annual average temperature and precipitation were observed to be maximum in the southern part and minimum in the northern and western parts of the state. The findings of this study provide valuable information for the future management of water resources and the likely impact of activities on the hydrologic cycle and natural resources in Rajasthan state. [ABSTRACT FROM AUTHOR]

Climate variability has significant implications for human health, necessitating a comprehensive understanding of the relationship between the two. The present study examines the trend analysis of climatic variables, and their possible impacts on health and identifies specific challenges faced by the people of Himachal Pradesh, India. The Mann-Kendall test, a non-parametric test, was used to examine temperature and rainfall trends. A survey was conducted to gauge public awareness regarding climate change and its health risks in the region. The study analysed weather patterns over 10 years, revealing fluctuating temperatures with the hottest years being 2012, 2015-17. Rainfall exhibited irregular patterns with less rainfall in 2012, 2014, 2017 and 2019. Trend analysis showed significant temperature trends in Dharamshala and Kangra. Weather-related incidents and fatalities peaked during 2012-14, while diseases, such as acute respiratory infections (ARI), asthma, cardiovascular diseases, diabetes, hypertension, and vector and water-borne diseases saw an increase over the decade. The survey results showed that the people of this region suffered mostly from respiratory problems, water-borne diseases and mental health issues. This study contributes to the existing knowledge by establishing a possible relationship between climate variability and the health of the people. Furthermore, it also provides a health database, facilitating the formulation of targeted interventions to address health-related challenges arising from the observed changes in weather patterns. [ABSTRACT FROM AUTHOR]

Based on GIMMS NDVI3g data from 1982 to 2015, by trend analysis, Mann-Kendall test and R/ S analysis, the temporal and spatial variation and future trend research of vegetation cover in the southwest karst area of China was studied. The results could provide a basis for ecology in this area. (1)In term of temporal variation of NDVI, annual and seasonal NDVI increased in fluctuant trends from 1982 to 2015. The annual and seasonal NDVI showed an overall trend of fluctuation and increase from 1982 to 2015, and the seasonal NDVI significantly increased. (2)In terms of the spatial distribution of NDVI, the vegetation cover was relatively better during the study period. The vegetation cover showed obvious spatial heterogeneity on the seasonal scale. The areas of NDVI≥0. 8 changed with the seasons in a trend of transferring from the western mountains of Hubei to Lincang of Yunnan. (3)The annual NDVI showed an increasing trend during the study period, up to 80. 31% and mainly in the vicinity of Yunnan-Guizhou Plateau. The variation of NDVI had significantly heterogeneity on the seasonal scale. The degradation of vegetation area changed along the Hengduan Mountains-Sichuan Basin, Guizhou-Hunan and Guangdong-Yunnan-Guizhou plateau. (4)In the future, the vegetation cover will show a continuous change. Vegetation area improvement will be 73. 30% on the annual and seasonal scales. [ABSTRACT FROM AUTHOR]

The most significant effects of climate change are related to temperature and precipitation. Changes in precipitation and temperature patterns affect water resource capacity, agricultural activities, global biodiversity and emergency management. In this study, using two statistical models (Mann-Kendall and Pettit’s test), climate data for the territory of Belgrade in the time interval 1961-2020 were processed. Trends were analyzed: average annual temperatures, average monthly temperatures, annual and monthly precipitation amounts. The aim of the research is to determine the statistical significance of the increasing/decreasing temperature and precipitation trends on a monthly and annual basis. Based on the obtained results, it was determined that the changing point of the annual temperature is in 1997, while a statistically significant increasing trend was observed in all months except November. The increasing trend recorded by the precipitation amount is 0.345 mm/year, but without statistical significance. The most significant results corresponding to July and October. [ABSTRACT FROM AUTHOR]

Mann–Kendall trend test and Sen's slope estimator method were used to find out significant changes in extreme climate indices for daily temperature and precipitation in Cherrapunji over the period from 1979 to 2020. In this study, 21 precipitation and temperature-based extreme climate indices were calculated using RClimDex v 1.9-3, among which six were derived from the number of days above nn mm rainfall (Rnn) according to India Meteorological Department (IMD) convention and the rest 15, in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). It was observed that, among all the indices, consecutive dry days (CDD), summer days (SU25) and very light rainfall (VLR) days increased significantly with 0.54, 1.58 and 0.14 days/yr, respectively, while only consecutive wet days (CWD) decreased significantly with 0.36 days/yr. A slight negative trend was observed in the case of tropical nights (TR20) and among the other precipitation indices as well. Again, the indices associated with daily maximum temperature increased significantly with 0.06–0.07°C/yr. For the indices associated with daily minimum temperature, almost no change or a slight negative change was observed, except a significant positive trend in February and significant negative trend in November for monthly minimum of daily minimum temperature (TNN) only. The analysis revealed that some of the extreme climate indices which explain the climatic conditions of Cherrapunji have shown statistically significant change over the period of 42 years and if this trend continues, then Cherrapunji will be under threat when it comes to climate change. [ABSTRACT FROM AUTHOR]

The Mann–Kendall test for trend has gained a lot of attention in a range of disciplines, especially in the environmental sciences. One of the drawbacks of the Mann–Kendall test when applied to real data is that no distinction can be made between meaningful and non-meaningful differences in subsequent observations. We introduce the concept of partial ties, which allows inferences while accounting for (non)meaningful difference. We introduce the modified statistic that accounts for such a concept and derive its variance estimator. We also present analytical results for the behaviour of the test in a class of contiguous alternatives. Simulation results which illustrate the added value of the test are presented. We apply our extended version of the test to some real data concerning blood donation in Europe. [ABSTRACT FROM AUTHOR]

Hydrological conditions are strongly regulated by monsoon systems in the Mekong River Basin (MRB), while relevant studies investigating the intensity of the rainy season are still insufficient. This study employed the Mann-Kendall (M-K) test, Sen's slope estimator, and innovation trend analysis to detect the variation of summer discharge in the MRB. Wavelet analysis is used to investigate the correlation between discharge and two South Asian summer monsoon subsystems (SAMI1 and SAMI2). Results show that the summer discharge in the MRB generally shows significant downward trends during 1970–2016 with a Z value range of −3.59–−1.63, while the high discharge at Vientiane, Mukdahan, and Pakse increases after 1970. The mutation years of the summer discharge series are around 2010 for Chiang Sean and Vientiane, and in 2015 for Luang Prabang, which resulted from the newly built large dams, Xiaowan and Nuozhadu. The wavelet analysis shows that the SAMI1 can be used to predict the summer discharge at Chiang Sean at a ~8-year timescale, while the SAMI2 correlates with the summer discharge well at a 1–8-year scale, especially at Mukdahan and Kratie during 1980–2016. [ABSTRACT FROM AUTHOR]

[Objective] The spatio-temporal distribution. abrupt change and periodic characteristics of rainfall erosivity and wind erosion climate erosivity in different regions of Shaanxi Province were studied > so as to provide scientific basis for soil erosion control and ecological construction in Shaanxi. Methods] The daily meteorological data of 96 stations in Shaanxi Province from 1981 to 2020 were used to calculate the rainfall erosivity and wind erosion climatic erosivity to analyze the change of water-wind erosion climate erosivity using methods such as climate trend analysis, spatial interpolation, Mann-kendall trend test and wavelet analysis. [Results] (1) The rainfall erosivity in Shaanxi from 1 981 to 2020 was 2 71 9.6 MJ * mm/(hm' • h). with large spatial differences, showing a spatial distribution of high in the south and low in the north. The wind erosion climatic erosivity froni 1981 to 2020 was 3.18, with a decreasing trend froni north to south. (2) Tn the past 4() years, the rainfall erosivity in Shaanxi showed an evident inter-annual variation with general upward but not passing a significant test. The rainfall erosion experienced a variation trend of first increasing and then decreasing, and it was stronger in the current era. The wind erosion climatic erosivity also showed an evident inter-annual variation, but the change trend was not significant. It experienced a variation trend of first decreasing and then increasing. Tt was strongest in the 1 990s and weakest in the current era. The rainfall erosivity was mainly larger from June to September, and the maximum value appeared in July. The wind erosion climatic erosivity was larger in winter and spring, and the maximum value was in April. The two erosivities were obviously asynchronous. (4) There were three oscillation periods of rainfall erosivity in Shaanxi Province, which was 2〜4 years, 8 years and 31 〜32 years. There were two oscillation periods of wind erosion climatic erosivity, which were 5〜1() years and 31 〜32 years. The abrupt change of rainfall erosivity occurred significantly in 2009, since then the rainfall erosivity increased gradually. Conclusion] At present, the rainfall erosivity in most areas of Shaanxi Province is strong, especially in northern Shaanxi with the strongest wind erosion climate erosivity. The wind erosion climate erosivity in eastern Yulin also showed an upward trend in recent 4() years. Therefore, more attention should be paid to the increase of wind erosion and water erosion climate erosivity in these areas. [ABSTRACT FROM AUTHOR]