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Understanding the long-term trends in temperature is crucial for assessing the impacts of climate change on agriculture, human and animal health, and natural habitats. An in-depth analysis of long-term spatio-temporal trends of monthly maximum and minimum temperatures along with Diurnal Temperature Range (DTR) from 1951 to 2022 in various Agro-Climatic Zones (ACZs) of India was performed using newly introduced Innovative Polygonal Trend Analysis (IPTA) and Innovative Trend Analysis (ITA) along with traditional Mann-Kendall (MK) or modified Mann-Kendall (m-MK) tests. The MK/m-MK and IPTA assessments detected significant trends in 44.6% and 86% of the time series data, respectively, while the ITA method detected significant trends in every time series data. The southern, western, and central parts of India are consistently experiencing rising monthly maximum and minimum temperatures. The western dry region, Central Plateau & Hills, East Coast Plains & Hills, Gujarat Plains & Hills, West Coast Plains & Hills, Southern Plateau & Hills, Western Plateau & Hills and Eastern Himalayan Region predominantly show increasing trends in both maximum and minimum temperatures in all months. The Indo-Gangetic Plains (Middle, Trans, Upper and Lower) exhibit decreasing trends in maximum temperatures during January, February, May, and June. The DTR showed increasing trends in the northern and western parts, while it has increasing trends in the central and southern parts of the country. The results of this study provide valuable information to assist in precise and informed decision-making on agricultural resource management and socio-economic policies. [ABSTRACT FROM AUTHOR]

Anthropogenic-induced climate change triggered increased extreme precipitation events, posing a significant threat to vulnerable regions like Pakistan. However, the lack of reliable long-term in-situ records hampers the monitoring of climatic extremes in the country. This study assessed the skill of four daily gridded precipitation datasets (APHRODITE, CHIRPS, CPC, and PGF) in tracking changes in precipitation extremes from 1985 to 2016 at 42 meteorological stations across Pakistan. This study employed Sen slope estimator in determining the change and the Mann–Kendall (MK) and its modified version (mMK) to test the significance of the changes. Spatial analysis of trends based on in-situ and gridded datasets revealed substantial increases in most precipitation extremes. However, there were large variations in the skill of gridded products in estimating precipitation extremes. The APHRODITE and PGF overestimated or underestimated trend significance, respectively. The CPC outperformed the others, exhibiting an RMSE of 3.96, Pbias of 18.5, NSE of 0.23, md 0.53, and a correlation coefficient of 0.6 in estimating changes at a 95% confidence level. Moreover, CPC also demonstrated superior performance in estimating trends at a 99% confidence level. It also performed best in estimating mMK trend significance at a 99% confidence level. Therefore, the study recommends CPC for tracking extreme precipitation trends in the region. [ABSTRACT FROM AUTHOR]

In recent years, climate change has significantly impacted European river systems, reshaping streamflow patterns with far-reaching consequences for ecosystems and water resources. This study investigates hydrological variability across 16 major European rivers. Cross-correlation analysis reveals strong climatic influences, with the Danube showing robust positive correlations with rivers such as the Elbe, Oder, Rhine, and Vistula, suggesting shared climatic drivers. In contrast, negative correlations between Central European rivers, like the Danube and Drava, and Southern European and UK rivers highlight the influence of distinct climatic regimes and geographical factors. To assess trends and identify abrupt changes in streamflow, the study applies the Mann-Kendall (MK), Seasonal Kendall (SK), and Regional Kendall (RK) tests, along with the Bayesian Estimator of Abrupt Change, Seasonal Change, and Trend (BEAST) algorithm. Hierarchical clustering analysis identifies four distinct groups: one cluster dominated by a strong negative trend in the Ebro River, another with a positive trend in the Thames, and two additional clusters representing Eastern and Western European rivers, with a few exceptions. The findings from the MK and SK tests reveal declining trends in rivers such as the Danube, Drava, and Nemunas, likely driven by long-term climatic shifts. In contrast, the Thames exhibits significant increases in streamflow, likely reflecting unique climatic conditions in Southern UK. The RK test further corroborates these observations, showing an overall pattern of declining streamflow across the studied rivers. BEAST analysis uncovers historical variability by identifying important transitions on long-term trends and abrupt changes in streamflow. Rivers like Danube, Loire, Drava, Nemunas and Vistula transitioned from positive to negative trends starting in the 1970s to 1990s. BEAST reveals also more complex dynamics in rivers like Rio Ebro and Thames, where both upward and downward abrupt changes reflect the impact of extreme weather events. [ABSTRACT FROM AUTHOR]

Trend analysis of meteorological variables is important in the determination of climate change. Precision is an important component of the hydraulic cycle and changes in temperature and precipitation affect agriculture, living ecosystems and water resources management. This study analyses Innovative Trend Analysis (ITA), Mann-Kendall, Sen slope and Innovative Polygon Trend Analysis (IPTA) to determine the trends of temperature and precipitation variables between 1980 and 2023 in Siirt province and climate change indicators were determined. Meteorological variables were evaluated separately on monthly, seasonal and annual scales. The results obtained from Mann-Kendall, ITA, IPTA and Sen trend analyses for precipitation and temperature variables were compared against each other. The results of all trend analyses for precipitation show a decreasing slope, while an increasing trend is detected in temperature values. The trend values are larger at monthly and seasonal scales. The trend results obtained in the present study indicate that more attention should be paid to drought risk management and water resources management in Siirt province. [ABSTRACT FROM AUTHOR]

The severe lockdown imposed to prevent the spread of COVID-19 decreased the emissions of air pollutants in large cities. A comparative approach was adopted to analyze the effect of the COVID-19 lockdown on ambient air pollution concentrations and the impacts of meteorological parameters on them using data from air quality monitoring stations (AQMS) in Tabriz, Iran. Air quality improvement was significant for all pollutants, except for O3, in the first phase of the lockdown compared to other phases. The lockdown (restricted social contact, closing of shops, schools, universities, restaurants, and many administrative centers and companies, etc.) temporarily reduced air pollutants. Comparing meteorological parameters between lockdown periods and the same period in previous years showed no statistically significant variations (P-value < 0.05). Therefore, the meteorological parameters did not intervene in reducing air pollutants during the lockdown. The effects of lockdown on the concentration of air pollutants could provide a special way to understand the extent of quarantine compliance by citizens, evaluate additional air quality policies, and assess the impacts of reducing various emission sources.Highlights: A comparative approach to analyze the effect of the COVID-19 lockdown on air pollutants concentrations and the impacts of meteorological parameters on them. Reductions in air pollutants concentrations during COVID-19 lockdown periods compared to the same intervals in the previous years. Lack intervene the meteorological parameters in reducing air pollutants, and mainly due to reduction emissions during COVID-19 lockdown periods. [ABSTRACT FROM AUTHOR]

This study examines the spatiotemporal variability and trends of rainfall in the central highlands of Abbay Basin using the Integrated Multi-satellite Retrievals for GPM (IMERG-06) dataset. Parameters on onset and cessation dates, dry spells, Coefficient of Variation (CV%), and Standardized Rainfall Anomalies were utilized to evaluate rainfall variability and seasonality. Trend analysis was carried out using Mann-Kendall test and Sen's slope estimator. The results highlighted a consistent pattern of late onset and early cessation of rainfall. The CV values for annual (10.7%), kiremt (11.7%), and belg (10.6%) seasons rainfall indicate moderate variability, while bega (22.6%) rainfall showed higher variability. SRA findings reveal episodic fluctuations between wet and dry years. The trend analysis demonstrates a statistically significant increasing trend in annual (9.14 mm/year) and belg seasons (6.94 mm/year) rainfall. However, kiremt season exhibited statistically non-significant (p > 0.05) decreasing trend. The temporal variability in rainfall onset, cessation dates and duration significantly impacts agricultural processes such as tillage and planting operations, affecting crop production. While the study area holds potential for agricultural activities, climate variability may reduce productivity. Therefore, the study findings are valuable for agricultural developers, planners and water resource managers. Including additional weather elements is crucial to enhance the precision and reliability of these findings for practical applications. [ABSTRACT FROM AUTHOR]

This current research analyzed the spatio-temporal trends and variability of monsoon season and month-wise rainfall for 26 tehsils in the upper Godavari basin (UGB) of Maharashtra, India. An attempt has been evaluated on rainfall data (1998–2023) obtained from the Department of Agriculture, Maharashtra. To assess the basic trends of the rainfall data statistical techniques, i.e., mean monthly and monsoonal rainfall, standard deviation (SD), and non-parametric method such as Mann–Kendall (MK) trend test, furthermore, simple linear regression (SLR) equation has been applied. Rainfall variability has been examined using the coefficient of variation (CV), and analyzed data has been incorporated into the GIS environment to prepare various maps. The MK analysis revealed an insignificant decreasing trend, especially in June, which suggests a declining trend in rainfall quantity. In contrast, an insignificant increasing trend has been noticed in September which interprets that maximum rainfall occurred in this month in the UGB. In the monsoon season, most of the places denoted no trend, while Dindori (Z = 2.51) and Akole (Z = 1.76) tehsils show significant increasing trends but a drastic decline in the Igatpuri tehsil (Z = − 2.65) The rainfall has been seen to increase towards the west due to the block posed by the Western Ghat to the east-flowing monsoon wind. This study also revealed the monsoon rainfall varied between 93% (Ahmednagar tehsil) and 25% (Aurangabad tehsil) and monsoon month-wise maximum variability (154%) at Ahmednagar in September and minimum (29%) at Igatpuri in July. The approach adopted in this paper identified the micro-level rainfall distribution, trend, and variability which will be greatly advantageous for sustainable water resource management. [ABSTRACT FROM AUTHOR]

De acuerdo con diversas instituciones nacionales e internacionales, México es uno de los países más vulnerables a los efectos de la variabilidad climática, como eventos hidrometeorológicos extremos y de cambio climático. La presente investigación se desarrolló con el propósito de conocer cómo se han comportado la temperatura y precipitación en un periodo de 60 años (1956-2015), a partir del análisis de los datos mensuales de las estaciones meteorológicas, mediante la automatización de procesos (para estructurar datos geoespaciales, hacer interpolaciones y clasificar el clima según Köppen-Geiger), y el uso de herramientas geoespaciales, en una de las subcuencas más importantes como fuente de abastecimiento de agua potable tanto para la región como para la Ciudad de México, y una de las principales zonas agrícolas del Estado de México. Los resultados de los tres análisis realizados en este estudio demuestran que aunque se han presentado algunos cambios en los valores de precipitación y temperatura, dichas variaciones no han implicado un cambio en el tipo de clima presente. Sin embargo, no se descarta que esta situación pueda verse modificada por cambios a nivel cuenca, como aseguran otros autores, quienes mencionan que la precipitación está disminuyendo mientras que la temperatura está aumentando para todo el centro del país. Por lo tanto, se hacen necesarias acciones integradas de conservación ambiental dentro de la subcuenca del río Sila, que permitan mantener las condiciones climáticas actuales, salvaguardando así el bienestar de las futuras generaciones.

Abstract As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

Abstract With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China.

Extended Abstract Background: Vegetation is one of the main components of biosphere preservation that acts as a link between soil, water, and atmosphere. It is crucial in providing organic matter, regulating the carbon cycle, and exchanging energy on the surface of the earth. In recent years, climate change and global warming have caused frequent events, such as floods, heat waves, and droughts, which can damage terrestrial ecosystems. Climate change directly affects the growth of vegetation; on the other hand, changes in vegetation cover give feedback to climate change by regulating water, energy exchange, and carbon dioxide concentration. Methods: The research was carried out in Mazandaran province to analyze vegetation trend in the study area during the 2001-2020 period. The 16-day composite MODIS-NDVI time series data, named MOD13Q1, with a spatial resolution of 250 meters (920 NDVI images) were used for this purpose. The non-parametric Mann-Kendall method was employed to investigate changes in vegetation activity and trend significance. The overlying vegetation trend map and the location of big cities and main roads of the province were also investigated in this research. Results: A decreasing trend of vegetation cover was observed in 16% of the total studied area, and the rest showed an increasing trend, although the significant decrease and increase of vegetation cover occurred in 5% and 65% of the area, respectively, with a 95% confidence level. The vegetation trend map showed that the most significant reduction of vegetation in the last 20 years occurred in coastal areas and low-altitude regions, especially around big cities and main roads entering the province. Decreased vegetation around the metropolises is expected due to the increase in population and the need for urban development. However, the results showed that the most significant decrease in vegetation occurred in the cities of Mahmudabad (19%), Babolsar (17%), Ghaemshahr (10%), and Jouybar (9%). Unlike the big cities of Sari and Ghaemshahr, the cities of Sorkhrood, Mahmudabad, and Babolsar are at the top of the cities with reductions in vegetation cover in the last 20 years. Unfortunately, this is not due to urban development and increasing population, but drastic changes in the use of agricultural land and citrus orchards and turning them into private villas are the main factor in the reduction of vegetation. Comparing the vegetation trend map with the main roads of the province reveals that a significant reduction of vegetation has occurred around the main roads entering Mazandaran province, especially on the Haraz, Firouzkouh, and Farim roads. In contrast, smaller areas of vegetation cover reduction were observed around the Chalus road. The investigation of the areas with positive vegetation cover trends showed that the highlands of the province, especially the eastern highlands, experienced a significant increase in vegetation cover. However, a less significant positive trend of vegetation was observed in the western highlands. Rather, most of these areas have experienced no trend conditions in the past 20 years, which could be due to the recent global warming and the higher temperature in the east of the province than in the western regions, which generally has caused suitable temperature conditions for the growth of vegetation in the eastern highlands of the province. It seems that the western highlands still do not have suitable temperature conditions for the growth of vegetation. Conclusion: The results of this research show that the changes in vegetation in Mazandaran province are under the control of two natural and human factors, and the former (climate) has caused an increase in vegetation in 65% of the area of the province, especially in the highlands, probably caused by the increase in temperature. The recent global warming has made it possible to provide living conditions for plants in the highlands of the province, especially the eastern highlands. Nevertheless, the human factor has been destroying vegetation throughout the province, especially in tourist areas and those with easy access. As such, a significant trend of vegetation reduction was observed both on the coasts, around metropolises, in the heart of the Hyrkan forests, and in the heights near the main roads. A significant decrease in vegetation cover has occurred in 5% of the area of the province, and these decreases were observed mostly in the plains, coastal strip, low altitudes with low slopes, outskirts of cities, and roads of the studied area. Vegetation is also being destroyed in the marginal areas of the roads from Ramsar to the neighboring western province, Gorgan Sari, Tehran, Chalus, Haraz, and Firuzkouh, which can be the main reason for the increase in traffic load, changes in land use, and the construction of recreational facilities and villas. Based on the results of this research, extreme changes in land use in the last 20 years are very evident, and if the human process of land use change continues along with the loss of water and soil resources, we may see irreparable blows to the ecosystem of the Caspian systems in the near future.

This study aimed to analyze trends in the amount of rainfall and temperature during the period 1978-2015 at the Aqaba and Tabuk stations to infer them as an indicator of climate change. The study relied on the inductive approach based on analyzing the statistical characteristics of the distribution of rainfall and temperature, in addition to examining the homogeneity of variance. The study concluded that there is a great similarity in the annual rainfall regime and an increase in the average annual rainfall of the Tabuk by 13.7% and there is an increase in the maximum annual rainfall amount and range by 12.6% and 12.8%, respectively at Aqaba. The value of t-statistical test, the value of the absolute difference between the two halfmeans, and twice the value of the standard error indicated the presence of non-significant trends in the general change in annual rainfall at the Tabuk and Aqaba. The standard deviation also showed the extent of dispersion of seasonal rainfall amounts around the average and an increase in the average annual temperature observed at the Aqaba station by about 2.4°C over the Tabuk station.Calculating the general temperature change indicates that there is an increasing trend at the two stations. The t-test values also showed increasing and significant trends in temperature during the summer and winter seasons, and non-increasing and non-significant trends during the fall and spring seasons at Aqaba. While the results of this test revealed increasing and significant trends in temperature during all seasons at Tabuk station.The study recommends applying detailed studies for all stations and for the longest period to determine general trends in the characteristics of rainfall and temperature. [ABSTRACT FROM AUTHOR]

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen's slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area. [ABSTRACT FROM AUTHOR]

With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China. [ABSTRACT FROM AUTHOR]

Recognizing the impact of climate change on the temporal and spatial variations in forests is crucial for sustaining them in the face of climate change. Here, we aimed to: (1) analyses the greening and browning trends in HFs based on time-series VIs, focusing on foliage trends observable through remote sensing; (2) explore the temporal and spatial trends of climatic factors; and (3) identify the relationship between the greening and browning of the forests and climate change. In this regard, we generated an 18-year (2003–2020) time series with an 8-day temporal resolution, encompassing MODIS vegetation indices (EVI and NDVI) and four climatic and hydrological factors: day and night temperature (LSTd, LSTn), precipitation (PRE), and actual evapotranspiration (ET). Subsequently, we used spatial statistical methods for analysis. EVI and NDVI trend analyses over the study period revealed greening in 77.02% and 92.32% of the study area, respectively. The statistical test confirmed significance (p < 0.05) for this greening in around 41.59% (EVI trend) and 75.11% (NDVI trend). Regarding the climatic and hydrological factors, PRE exhibited a declining trend, whereas LSTd, LSTn, and ET showed an increasing trend. Conclusively, the results reveal a positive correlation, ranging between 0.7 and 0.9, between temperature (LSTd and LSTn) and vegetation indices, indicating a close association between the greening process in HFs and rising temperatures (LSTd and LSTn). These results contribute to the understanding of the ecological resilience of HFs, aiding in the development of strategies to enhance ecosystems' resilience in the face of climate change. [ABSTRACT FROM AUTHOR]

Nonparametric trend detection tests like the Mann–Kendall (MK) test require independent observations, but serial autocorrelation in the datasets inflates/deflates the variance and alters the Type-I and Type-II errors. Prewhitening (PW) techniques help address this issue by removing autocorrelation prior to applying MK. We evaluate several PW schemes—von Storch (PW-S), Slope-corrected PW (PW-Cor), trend-free prewhitening (TFPW) proposed by Yue (TFPW-Y), iterative TFPW (TFPW-WS), variance-corrected TFPW (VCTFPW), and newly proposed detrended prewhitened with modified trend added (DPWMT). Through Monte Carlo simulations, we constructed a lag-1 autoregressive (AR(1)) time series and systematically assessed the performance of different PW methods relative to sample size, autocorrelation, and trend slope. Results indicate that all methods tend to overestimate weak trends in small samples (n < 40). For moderate/high trends, the slopes estimated from the VCTFPW and DPWMT series close (within a ± 20% range) to the actual trend. VCTFPW shows slightly lower RMSE than DPWMT at mid-range lag-1 autocorrelation (ρ1 = 0.3 to 0.6) but fluctuates for ρ1 ≥ 0.7. Original series and TFPW-Y fail to control Type-I error with increasing ρ1, while VCTFPW and DPWMT maintained Type-I errors below the significance level (α = 0.05) for large samples. Apart from TFPW-Y, all PW methods resulted in weak power of the test for weak trends and small samples. TFPW-WS showed high power of the test but only for strong autocorrelated data combined with strong trends. In contrast, VCTFPW failed to preserve the power of the test at high autocorrelation (≥0.7) due to slope underestimation. DPWMT restores the power of the test for 0.1 ≤ ρ1 ≤ 0.9 for moderate/strong trends. Overall, the proposed DPWMT approach demonstrates clear advantages, providing unbiased slope estimates, reasonable Type-I error control, and sufficient power in detecting linear trends in the AR(1) series. [ABSTRACT FROM AUTHOR]

In this study, spatiotemporal analysis of forest fires in Turkiye was undertaken, with a specific focus on the large-scale atmospheric systems responsible for causing these fires. For this purpose, long-term variations in forest fires were classified based on the occurrence types (i.e. natural/lightning, negligence/inattention, arson, accident, unknown). The role of large-scale atmospheric circulations causing natural originated forest fires was investigated using NCEP/NCAR Reanalysis sea level pressure, and surface wind products for the selected episodes. According to the main results, Mediterranean (MeR), Aegean (AR), and Marmara (MR) regions of Turkiye are highly susceptible to forest fires. Statistically significant number of forest fires in the MeR and MR regions are associated with global warming trend of the Eastern Mediterranean Basin. In monthly distribution, forest fires frequently occur in the MeR part of Turkiye during September, August, and June months, respectively, and heat waves are responsible for forest fires in 2021. As a consequence of the extending summer Asiatic monsoon to the inner parts of Turkiye and the location of Azores surface high over Balkan Peninsula result in atmospheric blocking and associated calm weather conditions in the MeR (e.g. Mugla and Antalya provinces). When this blocking continues for a long time, southerly winds on the back slopes of the Taurus Mountains create a foehn effect, calm weather conditions and lack of moisture in the soil of Antalya and Mugla settlements trigger the formation of forest fires. [ABSTRACT FROM AUTHOR]

Net Primary Productivity (NPP) is a crucial indicator of ecological environment quality. To better understand the carbon absorption and carbon cycling capabilities of Henan Province, this study investigates the trends and driving factors of NPP across different climatic zones and land use types. The Theil–Sen Median trend analysis method and the Mann–Kendall trend test are employed to monitor NPP changes from 2001 to 2020. The average annual NPP in Henan Province during this period was 414.61 gC·m−2·year−1, showing a significant increasing trend with a growth rate of 3.73 gC·m−2·year−1. Spatially, both the annual average NPP and its increase rate were higher in the western part of Henan compared to the eastern part, and NPP variability was more stable in the southern region than in the northern region. By classifying climatic zones and using the Geodetector method to assess NPP sensitivity to natural factors, the results show that climate and vegetation factors jointly influence NPP variations, with annual precipitation being the primary natural factor affecting NPP trends in Henan Province from 2001 to 2020. By analyzing the NPP gain and loss matrix, the impact of land use changes on NPP was evaluated. Forests had the highest average annual NPP at 483.52 gC·m−2·year−1, and the conversion of arable land to urban areas was identified as the primary land change type leading to NPP reductions. In the subtropical zone of Henan, forests, croplands, and grasslands exhibited higher NPP values and increase rates compared to those in the warm belt. This study provides new insights into the spatial variation of NPP caused by changes in climatic zones and land use types. [ABSTRACT FROM AUTHOR]

1-Introduction Dust aerosols have adverse effects on public health, air quality, and the environment; therefore, continuous monitoring of their spatio-temporal changes in different regions, especially arid and semi-arid regions, is very important. Considering the vast spatial extent of Kerman province, the inappropriate distribution of air pollutant measurement stations, a number of synoptic stations, as well as the large area of the province and the different climatic and biological diversity; the use of remote sensing techniques and especially the use of Aerosol optical depth (AOD) index of the MODIS sensor can be one of the appropriate tools to analyze and investigate the trend of temporal changes and the pattern of spatial distribution of dust particles in different regions of this province. This study has been carried out with the main purpose of analyzing the changes in dust aerosols based on the average monthly, seasonal and annual values of aerosol optical depth in different regions of Kerman province during the period from 2000 to 2022, so that while knowing the state of these changes, the high-risk areas of dust production in recent decades should also be identified. 2-Methodology In the present study, the MODIS sensor aerosol optical depth index product (MCD19A2) was used to analyze the trend of changes in dust aerosols in different regions of Kerman province. In order to validate this product, the average daily horizontal visibility recorded on the days of dust events was used. The data related to the MCD19A2 satellite product was downloaded through programming in the Google Earth Engine environment for different cities of Kerman province in the period from 2000 to 2022. After filtering the dusty days (AOD>0.5), the average values of the mentioned index on monthly, seasonal and annual time scales were calculated separately for each region. The Mann-Kendall test was then used to analyze the temporal changes of the optical depth of dust aerosols in different regions of Kerman province. 3-Results Based on the spatial distribution pattern of the air quality, it was found that the air quality of the eastern half in March and April was lower than other areas of the province, while in the central areas, the air pollution was less and the air quality was more favorable. The results of the Mann-Kendall test showed that in June and December, the trend of changes in the dust aerosols optical depth in more than two thirds of Kerman province had a non-significant decrease (Z>-1.96). This is why in November and May, half of the province and in other months more than two-thirds of the province have experienced incremental changes over the last 23 years. The pattern of long-term average spatial changes of the optical depth of aerosols on a seasonal scale showed that Kerman province was more affected by aerosols in the spring and summer seasons. Maximum dust pollution has occurred from Raver to Rigan, Jiroft to Manojan, Sirjan and Anar cities. The mentioned areas in the cold seasons of the year have also experienced the worst conditions in terms of the presence of aerosols, but their concentration has been significantly lower compared to the warm seasons of the year. The results of the Mann-Kendall test showed that 75% of the cities of Kerman province have faced an increasing-insignificant trend of spring dust events, which has led to an increase in the concentration of aerosols. In summer, these changes were increased in more than 95% of the province's regions, and the most changes were observed in Anar, Baft, Fahraj, Kohnouj, Kohbanan, Orzuiyeh and Rafsanjan. Although in the fall season, about 25% of the regions of the province had a decreasing trend and about 4% had no particular trend, but in more than 70% of the regions of Kerman province, the trend of changes in dust aerosols was an increase, and among the regions with a positive trend, the cities Baft and Jiraft had the worst conditions (Z>1.96). The remarkable result is the rising trend of dust and dust aerosols in all regions of Kerman province during winter, particularly in the cities of Anar, Anbarabad, Baft, Faryab, Ghaleganj, Manojan and Rabor. Although Anbarabad, Baft, Orzuiyeh, Shahrbabak and Sirjan exhibit a stronger annual increase compared to other areas, the rise in AOD changes is evident throughout the province. This 23-year trend indicates that Kerman has not experienced favorable conditions, highlighting the increasing frequency of dust events in this desert region. 4-Discussion & Conclusions Based on the findings of the analysis of the temporal changes of dust aerosols; the western cities of the province have become more sensitive to the phenomenon of wind erosion compared to the past. This can be a serious threat to the residents of these areas. On the other hand, the increasing trend in the southern and eastern regions highlights the intensification of dust events, contributing to the decline in air quality in the province over recent decades. Considering the intensification of the phenomenon of wind erosion and dust storms in many areas of Kerman province, it is necessary to control this phenomenon in order to increase the health security of the residents of the affected areas. Although the awareness of the spatial and temporal changes of dust aerosols has led to an increase in our understanding of the phenomenon of wind and dust erosion in the province, but in order to prevent, control and reduce the risks caused by the occurrence of this destructive environmental phenomenon, it is necessary to identify the main driving factors of these changes that are suggested to be investigated separately for each city in future researches. [ABSTRACT FROM AUTHOR]

This study examines the spatiotemporal variability and trends of rainfall in the central highlands of Abbay Basin using the Integrated Multi-satellite Retrievals for GPM (IMERG-06) dataset. Parameters on onset and cessation dates, dry spells, Coefficient of Variation (CV%), and Standardized Rainfall Anomalies were utilized to evaluate rainfall variability and seasonality. Trend analysis was carried out using Mann-Kendall test and Sen’s slope estimator. The results highlighted a consistent pattern of late onset and early cessation of rainfall. The CV values for annual (10.7%), kiremt (11.7%), and belg (10.6%) seasons rainfall indicate moderate variability, while bega (22.6%) rainfall showed higher variability. SRA findings reveal episodic fluctuations between wet and dry years. The trend analysis demonstrates a statistically significant increasing trend in annual (9.14 mm/year) and belg seasons (6.94 mm/year) rainfall. However, kiremt season exhibited statistically non-significant (p > 0.05) decreasing trend. The temporal variability in rainfall onset, cessation dates and duration significantly impacts agricultural processes such as tillage and planting operations, affecting crop production. While the study area holds potential for agricultural activities, climate variability may reduce productivity. Therefore, the study findings are valuable for agricultural developers, planners and water resource managers. Including additional weather elements is crucial to enhance the precision and reliability of these findings for practical applications.

The Black Sea region is the region with the highest rainfall in Türkiye. However, precipitation in the Black Sea region varies considerably both between years and within the region. This situation causes droughts in the region, with dry and wet periods following each other. This study aimed to determine the drought and wet periods in the Black Sea region according to the annual and 12-month SPI values. Standardized Precipitation Index (SPI) values were calculated according to the average precipitation data of 26 meteorology stations selected from the region between 1960 and 2020. The trends of the identified drought and wet periods were determined using Mann-Kendall trend analysis. In addition, using the heat map, the drought and wet periods of the Black Sea Region were determined by dividing coastal and inland areas. The analysis results determined that 1966, 1969, 1974-1977, 1984-1986, 1993-1994, 2006-2007, and 2019-2020 received less rainfall than normal and many stations had severe drought. It shows that 1967, 1988, 1996-1997, 1999, 2009, and 2016 received more precipitation than normal, that is, it has a humid character. According to the Mann-Kendall trend analysis results, it was not found that there was a decreasing trend in the coastal areas of the Western Black Sea Region. However, there was no significance in the decrease. Although there is an increasing trend in the Central and Eastern Black Sea region, this trend was found to be significant in some stations. Due to the landforms of the region, it was determined that there was not a general dry period or a general wet period and that the drought and wet periods differed in the east-west direction and the coastal-inland areas.

Abstract Dam construction has some qualitative and quantitative effects on groundwater resources. This effect may be in the form of an increasing groundwater table or a changing groundwater system. In this paper, the effect of the Rodbal dam construction on the Darab aquifer was investigated. For this paper water table levels from observation wells and precipitation data was used. The study aims to analyse the behaviour of the water table during precipitation by employing a combination of the standardisation process, Fuzzy Inference System (FIS), and Root Mean Square Error (RMSE) calculations. Fuzzy logic involves the fuzzification of input data, transforming precise values into fuzzy sets. The effectiveness of the FIS is highlighted, particularly in determining the number of membership functions for inputs. The performance of the results is assessed using indicators such as RMSE and Coefficient of Determination (R2). The FIS showed a high level of effectiveness in performance assessment, exhibiting a 70% similarity between the fuzzy and Mann–Kendall methods. Nonetheless, the Fuzzy Purpose Method corresponded more closely with the observed data, indicating a more accurate reflection of reality. The findings indicate that for P3, P7, and P8, the results from the Mann–Kendall method do not show a discernible trend. Conversely, the proposed Fuzzy method accounts for changes in the behaviour of these piezometers.

Understanding farmers' perceptions, attitudes, and adaptation strategies toward climate change is important for developing effective policies that support agricultural development and food security in rural communities. This study aimed to understand climatic trends over the past two decades (2003–2022), farmers' perceptions, and adaptation strategies regarding climate change in Dera Ghazi Khan, Pakistan. The Mann–Kendall trend test identified a significant decrease in average minimum temperature (τ = −0.357, p < 0.05) and an increase in rainfall patterns (τ = 0.337, p < 0.05). A mixed-method approach is employed, utilizing a survey of 180 randomly selected farmers, focus group discussions, and climate data analysis. Ordinal and binary logistic regression models were used to analyze the influence of sociodemographic factors on farmers' perceptions of climate change and their choice of adaptation strategies. The results indicate that farmers primarily rely on religious beliefs/prayers (65.6%) to cope with climate change, followed by seeking off-farm jobs (50%) and changing fertilizer use (42.2%). The result of the binary logistic regression indicates that among the different demographic characteristics, education, and land size significantly influence farmers' decisions in taking adaptation measures against climate change. This study emphasizes the need for climate policies that integrate farmer knowledge with meteorological data and sociodemographic analysis to ensure a sustainable agricultural sector in Pakistan. Further research is necessary to explore more effective adaptation methods. [ABSTRACT FROM AUTHOR]

This paper presents a statistical analysis of rainfall data through a practical application of statistical tests, with the aim of highlighting climatic variability in the Kébir Rhumel watershed. This analysis uses rainfall data from 1901 to 2021 collected in the Kébir Rhumel watershed (North–East Algeria). The use of the Mann–Kendall and Pettitt tests has allowed us to confirm the existence of a break in 2013 for all stations except Ain Smara and Gerrah, where it was detected in 2020. The SPI (Standardised Precipitation Index) defines five climatic periods that have alternated on the Kébir Rhumel, the wet condition being the most representative with 44% of the series analysed, and the least present is the severe drought (> 1%). The TIA (Trend Innovative Analysis) shows a positive trend for the El Milia, Tadjenant, Grarem Gouga, Guerrah and Ain Smara stations and a negative trend for the Chebabta and Tiberguent stations. Finally, the graph of the climate index of L. Emberger clearly shows the shift of the stations after the break of the sub-humid stage towards the semiarid stage. [ABSTRACT FROM AUTHOR]

This study examines trends in minimum and maximum temperatures at various climate stations located in different regions of Morocco for a period of five decades (1970 to 2019). Mann–Kendall, Sen's estimator, Innovative Trend Analysis (ITA) and Innovative Polygon Trend Analysis (IPTA) were used in the analysis. The results show significant fluctuations, at different time scales, between minimum and maximum temperatures at all stations. In coastal areas, such as Rabat Sale, minimum temperatures fell during January and February while other months saw increases. Average minimum temperatures in Rabat Sale tend to fall by 0.5 °C. On the other hand, maximum temperatures in Rabat Sale rose by 0.2 °C. A decrease of 0.4 °C for Tmin and 1.6 °C for Tmax were observed in higher continental regions, such as Meknes. Other stations, such as Fez Sais (0.6 °C Tmin and 2.6 °C Tmax) and Taza (1.1 °C Tmin and 2.6 °C Tmax) showed an upward trend. Trends also vary, with notable increases in minimum and maximum temperatures, indicating different climatic dynamics according to altitude and locality. In particular, the ITA highlights a significant increase in annual maximum temperatures, with a P-value < 0.05 and trend slopes ranging from 0.0015 °C per year in Rabat Sale to 0.0076 °C per year in Taza. In addition, the IPTA results confirm diversity of upward and downward trends on monthly and seasonal scales, highlighting impact of geographical factors such as proximity to sea, topography, and continentality that contribute to formation of regional microclimates. The results highlight significant impact of climate change in Morocco. [ABSTRACT FROM AUTHOR]

Groundwater represents one of the largest resources of freshwater in the world. Thus, investigations of groundwater level variations due to climate change and increasing human activities are of great importance, especially in resource scarce regions. Our research aimed to understand the long‐term effects of climate events and water use on groundwater levels over the study area via Mann‐Kendall, Sen's Slope, Innovative Polygon Trend Analysis (IPTA), and Innovative Trend Analysis (ITA) analyses. Although several studies are available in relation to GWL trend analysis via ITA, Mann‐Kendall and Sen slope in the literature, there are few IPTA studies conducted. The focus of the study was seven wells across Türkiye over the period 1987–2022. Results demonstrate that there was a downward trend in GWL in all stations annually, regardless of the method. At monthly scale, a decrease was noted, especially in June, August, and September, while seasonally, decreases were seen in autumn and winter. Moreover, it was evident the results of the Sen slope and ITA were compatible, while the IPTA was a useful tool in detecting GWL trends. Identifying and understanding GWL trends is highly valuable in informing groundwater resource managers of critical areas of overuse and other factors affecting groundwater, resulting in preventive interventions to overcome such problems and protect this critical resource. [ABSTRACT FROM AUTHOR]

Rainfall is a crucial climate variable, shows irregular spatial and temporal variations. Significant spatial variability and persistent changes in land use intensify the complexity of urban weather systems. Therefore, climatological rainfall variables deserve attention from both a scientific and technological perspective. The rapid urban expansion of Hyderabad city, coupled with extreme weather variations, has led to increased environmental vulnerability. The present study aims to assess the spatiotemporal trends of annual rainfall and rainfall extremes in Hyderabad city from 1990 to 2020. This study employed the RClimDex model and daily gridded rainfall data to analyze annual rainfall and rainfall extreme indices, focusing on Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), Total Precipitation (PRCPTOT), Rainfall Events Exceeding 10 mm (R10MM), 20 mm (R20MM), Total Precipitation from Very Wet Days (R95PTOT), Maximum 1-Day Precipitation (RX1DAY), and Maximum 5-Day Precipitation (RX5DAY). The trends in annual rainfall and rainfall extremes were assessed using the Mann-Kendall (MK) test, and spatial distribution variations for the identified trends were evaluated with the Inverse Distance Weighting (IDW) interpolation technique. The results of the study showed that no significant annual rainfall trends from 1990 to 2020, indicating natural variability rather than consistent long-term changes. However, extreme Consecutive Dry Days and Maximum Wet Spell trends show increasing trends. The PRCPTOT pattern remains almost stable, and R10MM rainfall events exhibit an increasing trend at a few locations, suggesting potential shifts in precipitation patterns. Conversely, a decreasing trend for rainfall extremes R20MM, R95PTOT, RX1DAY, and RX5DAY indicate a general reduction in extreme rainfall events and very wet days in GHMC suggesting localized reductions in extreme events and varied impacts of prolonged rainfall reductions at annual scale. The study reveals Hyderabad's high spatial variability in annual rainfall distribution and rainfall extremes, emphasizing the importance of analyzing high resolution gridded rainfall data for effective decision-making and efficient water resource management. [ABSTRACT FROM AUTHOR]

There has been significant variation in precipitation in different parts of the world, and increasingly this has been attributed to climate change. Despite reliance on rain-fed agriculture, detailed analysis of regional precipitation trends within specific sub-national areas, such as the Niger Delta, remains scant. This study examines annual rainfall trends over 51 years (1972-2022) across seven stations in the Niger Delta using different statistical methods. Descriptive statistics show different patterns among stations, some showing upward trends, others declines. Mean annual rainfall ranges from 1,969.05 mm in Akure to 2385.04 mm in Port Harcourt, showing significant regional variability. Linear regression and LOWESS analysis show mixed trends; Mann-Kendall and Spearman's Rho tests showed significant increase in Owerri, while Sen's slope analysis confirms varying trends across the region. Pettitt test results confirms Owerri's significant increase in precipitation. This study contributes to a greater understanding of precipitation trends in the Niger Delta. [ABSTRACT FROM AUTHOR]

Albedo is one of the key parameters in climatic studies. Investigating its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor continuously produces the land surface albedo on a global scale and with the appropriate spatial resolution and makes it available to researchers. In this study, to analyze Iran's surface albedo trend, first, the daily albedo data of the MODIS on Iran in the period from January 1, 2001 to December 30, 2021 with a spatial resolution of 500 m were prepared from the NASA website. After the necessary pre‐processing, the long‐term seasonal and annual trend of Iran's albedo was calculated at the 90% confidence level using the non‐parametric Mann–Kendall test. The findings showed that the albedo trend is positive in the lowland interior areas of Iran and negative in the highland areas. Since the decreasing trend of albedo in highland areas indicates the reduction of snow cover in these areas, this issue can challenge the life and water resources of these areas that rely on the accumulation of snow. [ABSTRACT FROM AUTHOR]

The present study examines long-term annual, seasonal and monthly changes and short-term fluctuations in monsoonal rainfall and temperature over plain and hill zones of Uttarakhand. Both rainfall and temperature data for period of 1981-2020 were analyzed in this study. Statistical trend analysis techniques namely Mann-Kendall test and Sen's slope estimator were used to examine and analyze the problems. The detailed analysis of the data for 40 years indicates that the annual range of temperature is increasing in the hill zone. In the context of agriculture, the observed trends in temperature and rainfall patterns pose significant implications for farming practices and crop yields in Uttarakhand. The increasing annual range of temperature, particularly in the hill zone, suggests a heightened risk of temperature extremes such as heat waves and cold spells. During the monsoon season, while rainfall levels may remain relatively stable or exhibit minor fluctuations, the variability highlighted by the box and whisker plots underscores the importance of preparedness for both excess and deficit rainfall scenarios. [ABSTRACT FROM AUTHOR]

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This study examines the Riparian Buffer Zones (RBZs) in Türkiye, analyzing land cover changes from 2017 to 2023 to assess their effectiveness in ecological conservation and water resource management. The research employs Esri-Sentinel land cover data, Shuttle Radar Topography Mission digital elevation models, and RiverATLAS data to identify and delineate RBZs, classify land cover types, and evaluate trends and changes over seven years. The findings indicate that 44.8% of RBZs are covered by 'Rangelands', 32.2% by 'Crops', and 16.1% by 'Trees' classes. The study notes a considerable increase in built areas and agricultural fields, which may indicate ongoing urban expansion and its potential impact on the effectiveness of RBZs. Despite regulatory efforts, the substantial presence of agriculture within RBZs indicates a need for more robust environmental protection policies. The results indicate a pressing need for a policy reassessment to enhance forest cover within RBZs and reduce agricultural encroachment. This would improve water quality and facilitate the achievement of sustainability goals numbered 2, 3, 6, 11, 14 and 15. The findings thus call for a strategic enhancement of RBZ management to better protect water resources against the adverse effects of agricultural and urban activities. [ABSTRACT FROM AUTHOR]

Dam construction has some qualitative and quantitative effects on groundwater resources. This effect may be in the form of an increasing groundwater table or a changing groundwater system. In this paper, the effect of the Rodbal dam construction on the Darab aquifer was investigated. For this paper water table levels from observation wells and precipitation data was used. The study aims to analyse the behaviour of the water table during precipitation by employing a combination of the standardisation process, Fuzzy Inference System (FIS), and Root Mean Square Error (RMSE) calculations. Fuzzy logic involves the fuzzification of input data, transforming precise values into fuzzy sets. The effectiveness of the FIS is highlighted, particularly in determining the number of membership functions for inputs. The performance of the results is assessed using indicators such as RMSE and Coefficient of Determination (R2). The FIS showed a high level of effectiveness in performance assessment, exhibiting a 70% similarity between the fuzzy and Mann–Kendall methods. Nonetheless, the Fuzzy Purpose Method corresponded more closely with the observed data, indicating a more accurate reflection of reality. The findings indicate that for P3, P7, and P8, the results from the Mann–Kendall method do not show a discernible trend. Conversely, the proposed Fuzzy method accounts for changes in the behaviour of these piezometers. [ABSTRACT FROM AUTHOR]

Groundwater is a precious natural element which ensures global water, food, and environmental security in the twenty-first century. Systematic monitoring, sustainable utilization, preservation and remediation are critical aspects of efficient groundwater resource management. This study deals with the analysis of spatial variability and trend in groundwater chemistry as well as identification of possible contamination sources in a coastal alluvial basin of eastern India. Pre-monsoon season data of 14 groundwater-quality variables measured in 'leaky confined' and 'confined' aquifers were analyzed for ten years (2012–2021). Mann–Kendall (M–K) test with the Sen's Slope Estimator, Spearman Rank Order Correlation (SROC) and Innovative Trend Analysis (ITA) tests were employed to assess decadal (2012–2021) trends. The analysis of the results indicated that the 'critical' water-quality parameters exceeding the acceptable limits for drinking are TDS, EC, TH, pH, Mg2+, Na+, K+, Fe2+, HCO3ˉ, Clˉ and NO3ˉ. Weak negative correlations between rainfall and groundwater elevation for both the aquifers reveal poor rainfall recharge into the aquifers. Therefore, a reduction in groundwater abstraction and augmentation of groundwater recharge is recommended. Trend analysis results indicated that the concentrations of TH, Mg2+ and Fe2+ exhibit significant increasing trends in the 'leaky confined aquifer'. In contrast, significant rising trends in TH, Mg2+, Na+, Fe2+, HCO3ˉ and NO3ˉ concentrations are identified in the 'confined aquifer'. Further, the SROC test could not detect the trends in groundwater quality in most blocks and for many parameters. On the other hand, the ITA test revealed significant trends in most of the parameters of the two aquifers in almost all the blocks. Trend magnitudes of the groundwater-quality parameters based on the Sen's Slope Estimator and the ITA test vary from –63.7 to 58.65 mg/L/year for TDS, –14 to 39.07 mg/L/year for TH, –1.49 to 4.83 mg/L/year for Mg2+, –7.14 to 22.96 mg/L/year for Na+, –0.32 to 0.44 mg/L/year for Fe2+, –8.33 to 20.75 mg/L/year for HCO3ˉ, –26.52 to 31.01 mg/L/year for Clˉ and 1.29 to 3.76 mg/L/year for NO3ˉ over the study area. The results of M–K and ITA tests were found in agreement in all the blocks for both the aquifers. Groundwater contamination in both the aquifers can be attributed to weathering, geogenic processes, mineral dissolution, seawater intrusion, poor recharge pattern and injudicious anthropogenic activities. It is strongly recommended that concerned authorities urgently formulate efficient strategies for managing groundwater quality in the 'leaky confined' and 'confined' aquifers which serve as vital sources of drinking and irrigation water supplies in the study area. [ABSTRACT FROM AUTHOR]

Introduction Global warming threatens human survival in today's scenario; and has become an environmental challenge. The climate data shows the warming trend in many parts of the world, which has led to a wide range of climate effects such as reduced precipitation, drought, and the occurrence of extreme events. The increasing vulnerability of many urban areas, especially in developing countries, has been one of the main concerns of life. Therefore, examining the risk of risks caused by global warming on a national and local scale is a fundamental step to increase the readiness of urban areas to reduce current and future risks caused by climate change. Droughts have effects on vegetation, soil and freshwater quality, and etc., and are a serious ecological problem around the world, its impact on crops and water availability for humans can jeopardize human life. Although drought has always been common, the drought risk has become increasingly prominent because of the climatic warming that has occurred during the past century. Therefore, these effects of are noticeable in all climates, and Iran, having a dry and semi-arid climate, is one of the countries that is always at risk of drought, and this causes great economic damage to the country every year. in addition to this, the review of the history and climatic texts shows that the importance of the effects of climatic elements (rainfall and temperature) on the drought situation of the region in the coming period is essential. Until now, the study of global warming in terms of increasing the risk of drought using the sixth report and new climate data has not been studied in Tehran province. So this study aims to investigate the effects of climate change on increasing the risk of drought in Tehran province. Materials and Methods This research, First, the parameters (temperature and precipitation) for the synoptic stations (Abali, Shemiran, Mehrabad) for the period (1988-2020) were received from the Tehran Meteorological Organization. To projection in the future, down-scaling methods (SDSM-DC model) and The Mann-Kendall test were used to investigate the changes in temperature and precipitation. Climatic parameters change in space and time scale for many reasons. that these changes should be checked based on observations and statistical methods. Rainfall is one of those climate parameters that is not normal, and methods such as Menn-Kendall should be used to deal with such conditions; For this purpose, using Macro Excel, the value of age slope and Z statistic was calculated in the period (1988-2020) for the stations (Mehrabad, Shemiran and Abali) to investigate the trend of precipitation and temperature from the past to the present at a confidence level of 95-99% computed. In the following NetCDF data together with CanESM5 predictors from the base period (1979-2014) according to the most recent SSP release scenarios of the IPCC 6th Report were obtained from the Canadian Climate Change website. Among them, only Mehrabad station had a complete basic period compared to other stations, it was chosen as the selected station in Tehran. Drought indices are used as an index to track and quantify drought, this research is SPI index with DIC software has been used to evaluate the drought. in this index Precipitation, which has been one of its main components, whose output and results are more consistent with reality. Results and Discussion The results using the Mann-Kendall test showed that the examination of temperature changes in the stations (Mehrabad, Shemiran, Abali) was an increasing trend. Rainfall in most months of the year is a stable trend, only jumps are observed which can be justified by the increase in the frequency of rainfall. In the simulation with the CanESM5 model under the SSP5 scenario at Mehrabad station, the highest temperature was assigned to July and the highest rainfall will be in March. in this research, The drought survey showed that Mehrabad station experienced severe drought only during 1989-1993, while the duration of the drought period was longer in Abali and Shemiran stations and both of them faced very severe drought in 2014. in addition, this Investigation of three stations with a common period of 32 years in Tehran shows that Tehran has overcome the drought situation in recent years; But most of the time, the region may be in close to normal climatic conditions. But the risk of dry to very dry conditions will be very close. On the other, the results confirmed that drought depends on both rainfall and temperature. Conclusion As drought depends on both precipitation and temperature, The more the drought is accompanied by the trend of increasing temperature, decreasing precipitation, and the prediction of climate models, the more likely it is that climate change will occur due to global warming. As a result, the temperature of Tehran will increase. And while the rainfall is decreasing, it will be fluctuating and torrential. so In the future, Tehran's climate will have more fluctuations in rainfall and will be warmer than the current conditions. In addition, rains will occur more randomly but with more intensity. Tehran has had a drought in recent years, but most of the time the region has been in near-normal climatic conditions, but is the risk of dry and very dry conditions. This factor will create environmental challenges in the future. In addition to this, it is necessary to have a plan for climate risk management in the future due to the new climate of Tehran, which is prone to drought. [ABSTRACT FROM AUTHOR]

The study of drought, one of the many problems caused by climate change, enables the planning of water use and water resources. The increase or decrease in drought severity, which is one of the drought parameters, is an important source of information in terms of predetermining the consequences that may arise due to drought. In this study, drought analysis was conducted for 1-, 3-, 6-, 9- and 12-month time periods with the Standard Precipitation Index (SPI) using long-term precipitation data of four stations in the Tigris River basin from 1960 to 2022. Drought duration and severity series were obtained from drought index values, and the trends of drought severity series were calculated with Mann-Kendall (MK) and Innovative Trend Analysis (ITA) tests. According to the results, the ITA test was found to be more sensitive in detecting trends in drought severity series compared to the MK test. According to the MK test, drought did not show a significant increase or decrease. On the other hand, according to the ITA test, drought increased at 1- and 12-month scales at Siirt and Batman stations, respectively, and at 1- and 12-month scales at Diyarbakır station. Drought increased in all time periods at Mardin station. [ABSTRACT FROM AUTHOR]

Rising temperatures due to global warming necessitate immediate evaluation of heatwave patterns in Peninsular Malaysia (PM). For this purpose, this study utilized a locally developed heatwave index and a gridded daily maximum temperature (Tmax) dataset from ERA5 (1950–2022). During validation, the ERA5 dataset accurately represented the spatial pattern of Level 1 heatwaves, showing widespread occurrence. Historically, Level 1 heatwaves prevailed at 63.0%, followed by Level 2 at 27.7%, concentrated in northwestern states and the enclave between the Tahan and Titiwangsa mountain ranges. During very strong El Niño events in 1982/83, 1997/98, and 2015/16, Level 2 heatwave distributions were 10.4%, 26.8%, and 15.0%, respectively. For future projection, the model ensemble was created by selecting top-performing Global Climate Models (GCMs) using Kling-Gupta efficiency (KGE), ranked re-aggregation with compromise programming index (CPI), and GCM subset selection via Fisher-Jenks. The linear scaling bias-corrected GCMs (BC-GCMs), NorESM2-LM, ACCESS-CM2, MPI-ESM1-2-LR, ACCESS-ESM1-5, and FGOALS-g3, were found to exhibit better performance, and then ensemble. March to May show the highest increase in all scenarios, ranging from 3.3 °C to 4.4 °C for Level 1 heatwaves and 4.1 °C to 10.7 °C for Level 2 heatwaves. In the near future, SSP5-8.5 projects up to a 40.5% spatial increase for Level 1 heatwaves and a 2.3% increase for Level 2 heatwaves, affecting 97.1% and 57.2% of the area, respectively. In the far future, under SSP2-4.5 and SSP5-8.5, Tmax is projected to rise rapidly (1.5–4.5 °C) in the northern, western, and central regions, with increasing population exposure anticipated in the northern and western regions. [ABSTRACT FROM AUTHOR]

Rainfall is the most important fundamental physical parameter among the climate, as this parameter determines the environmental condition of the particular region, which affects the agricultural productivity. Global warming or climate change, is one of the most important worldwide issues discussed among scientists and researchers. One of the consequences of climate change is the alteration of rainfall patterns and an increase in temperature. The drastic changes in rainfall pattern showed a significant impact on society, and therefore its up-to-date information is needed to estimate the spatial distribution and variability at all points of the territory. In this paper, a study on trend analysis of rainfall data observed at Anasi, Haliyal, Kadra, and Supa rain gauge stations in Karnataka, India, was carried out. For this purpose, the annual 1-day maximum rainfall (AMR) and annual total rainfall (ATR) series were generated from the daily rainfall data and used in trend analysis. A non-parametric Mann-Kendall (MK) test was applied to evaluate the presence of significant trend in AMR and ATR, while the rate of significant trend was computed by Sen's slope estimator (SSE). The MK test results indicated that there is a decreasing trend in AMR series of Anasi, Haliyal, Kadra, and Supa. The study showed that the rate of decreasing trend in the AMR series of Anasi, Haliyal, Kadra, and Supa is computed as 1.4 mm/year, 0.1 mm/year, 0.6 mm/year, and 0.2 mm/year, respectively. For the ATR series, the rate of decreasing trend for Anasi was computed as 23.8 mm/year, whereas 11.2 mm/year for Supa, whereas the rate of increasing trend was 4.3 mm/year for Haliyal and 2.2 mm/year for Supa. This paper illustrated the application of the MK test and SSE for analyzing the trend in AMR and ATR of Anasi, Haliyal, Kadra, with Supa and the results obtained from the study. [ABSTRACT FROM AUTHOR]