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We perceived a trend in the study and practice of petroleum-contaminate sites. Monitored natural attenuation (MNA) can reduce the contaminant concentrations in the soil and groundwater, and it is a method that can remediate the petroleum-contaminated site effectively. MNA is becoming a research focus. This study evaluated MNA using a series of lab-based bench-scale experiments and a large amount of monitoring data from field samplings. Based on the in-site total petroleum hydrocarbon (TPH) results, we used statistical methods, the Mann-Kendall test, and mass fluxes in order to evaluate the MNA of petroleum-contaminated sites in groundwater. The results showed that the TPH concentrations were decreasing, and the plume became smaller. The attenuation rate was from 0.00876 mg/d to 0.10095 mg/d; remediating the petroleum contamination site would cost 1.3 years to 10.6 years. The plume reached a quasi-steady state, and mass flux declined. The most essential process of MNA was biodegradation, and the second was sorption. During the monitoring period, 393 g of TPH was attenuated, including 355 g of TPH gradated by microbes. Biodegradation upstream of the plume was more serious. Iron(Ⅲ) and manganese were the main electron acceptors utilized by microbes during the monitored period. MNA was in progress, and it can be an effective method to remediate the petroleum-contaminated site. Lab-based bench-scale experiments were performed with much monitoring data from the field samplings in order to understand the fate and transport mechanism of the petroleum contamination from the land surface to shallow groundwater according to site conditions. [ABSTRACT FROM AUTHOR]

The consensus of the scientific community across the globe showed that the planet's annual average temperature is likely to be 2 °C above pre-industrial levels of 2050 standards. It is believed that warming the globe by 2 °C due to greenhouse effect and/or climate change will result in severe rainfall amount and more frequent and intense droughts, floods, heat waves, and other extreme weather events. Gondar City of the Amhara Region will not be exceptional from this scenario. The objective of the study was to assess UHI caused by climate change in Gondar City of the Amhara Region, Ethiopia. Thirty temperature and thirty rainfall observations were taken from the Meteorological Agency. It was analyzed using Mann–Kendall trend test and homogeneity test using XLSTAT software. Analysis of the historical climate data in Gondar City revealed that there has been an increasing trend of maximum temperature and a decreasing trend in minimum temperature and a general tendency of decreasing rainfall. The results of Mann–Kendall trend test and homogeneity test also showed that the average amount of annual rainfall and maximum temperature change were significant at p < 0.05. The result also noted that there was a constant increase in maximum temperature, while high variability in rainfall from 2010 to 2020. However, there is a constant increase in rainfall from 1990 to 2020 in the study area. The increasing in temperature and the variability and increasing rainfall are evidences for the existence of climate change. The finding of Landsat temperature measurement indicates the rising temperature in Gondar City as compared to the surrounding rural areas. In conclusion, the test result and the Landsat measurement showed the presence of urban warming an indicator of UHI in the city of Gondar. [ABSTRACT FROM AUTHOR]

This research paper presents an analysis of temperature variables over the West Banas basin in order to detect the presence of underlying trends employing historical temperature data for three points viz., Abu Road, Mount Abu and Pindwara obtained for a period of 40 years (1981 -- 2020) from MERRA-2 database. The study aims to investigate the long-term changes in temperature trends and identify any significant patterns or anomalies in mean, maximum and minimum temperatures at monthly, seasonal and annual timescales at the three locations amounting to a total of 162 series. The trends were evaluated using the Mann-Kendall test, a popular and powerful statistical technique formulated for analysing abnormal distributions. Prior to the application of the trend test, autocorrelated time series were identified and the trend test was modified using a variance correction approach to incorporate the influence of autocorrelations upon the resultant trends. The findings of autocorrelation analysis revealed that 11 of the 162 series were autocorrelated, a majority of which were associated with the temperature series at Abu Road. The results of the trend test showed that 27 out of the 162 series possessed significant trends with the mean and maximum monsoon temperatures in most of the series exhibiting a reducing trend while the minimum temperature appeared to be rising. Overall, the research highlights the importance of monitoring temperature trends, particularly in regions that may be more vulnerable to the impacts of climate change. The findings of this study can inform future climate adaptation strategies and support decision-making processes aimed at mitigating the effects of global warming on the natural and built environment. [ABSTRACT FROM AUTHOR]

Extended abstract 1-Introduction Soil and air are two essential elements in the life of creatures on the earth. Their interaction in certain conditions can cause many risks; among these dangers, dust storms can be mentioned. Under the conditions of dust storms, a large amount of dust is emitted in the air and the horizontal visibility is reduced to less than 1000 meters. Therefore, due to the important role of the dust phenomenon, it is highly necessary to understand the spatial-temporal changes and to analyze their longterm variations. Jazmurian region, located in the southeast of Iran, between the two provinces of Kerman and Sistan and Baluchistan, has become completely dry and turned into a desert due to drought and construction of numerous dams, and has turned this region into one of the key areas of dust production in the country. Therefore, the purpose of this study is to investigate the temporal-spatial changes of dust storms in relation to climatic parameters in Jazmurian wetland, which is of particular importance in order to properly manage this area to face the problems caused by dust storms. 2-Methodology In order to carry out the present research, the meteorological data related to the synoptic stations located in the Jazmurian wetland area for a period of 20 years (2000-2020) were received from the Iranian Meteorological Organization. Climatic data used in this research include temperature, precipitation, relative humidity, wind speed and direction, horizontal visibility, and remote sensing data including Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI). The research method uses a combination of statistical analysis, observation and remote sensing. In order to check the AOD and NDVI, the monthly data of MODIS sensor was used. In this study, 12 synoptic stations that had the longest and most complete statistical periods were used in order to identify the temporal-spatial changes of dust occurrence in Jazmurian wetlat. The Mann-Kendall test was used to examine the trend of time changes. The slope of the Sen estimator was used to check and confirm the accuracy of the trend changes. In order to better understand the spatial distribution pattern of dust events in the Jazmurian wetland basin, the inverse distance interpolation method (IDW) was used. Also, Pearson's spatial correlation analysis was used to investigate the mutual effects between the indicators. 3- Results The 20-year average review of the indicators showed that the maximum value of aerosol optical depth in the studied area was 0.3, which is seen in the central part of the wetland. The vegetation index also showed that the maximum value of this index was 0.2, which covers most of the northern, northwestern and western parts. Examining the average rainfall trend showed that the maximum and minimum rainfall in this period are about 219 and 85 mm, respectively. Meanwhile, the 20-year average temperature survey showed that the maximum and minimum temperatures were 28.7 and 17.2 degrees Celsius, respectively. The fact that the maximum rainfall is in the northern and western part is in harmony with the minimum temperatures in these areas. The examination of the average wind speed showed that the maximum speed was 3.6 m/s, which was mostly in the central, west and northwest, south and southwest parts. The results of the wind direction index showed that the lowest wind direction is in the northern parts of the region and the highest wind direction is in other parts of the Jazmurian wetland basin. The maximum humidity in the studied area is 43.73%, which is mostly seen in the north, northwest, west, south, and southwest parts. Examination of the horizontal visibility index showed that the maximum amount of horizontal visibility was in the northeastern and northwestern parts of the region. Also, the process of changes in the MannKendall test showed that the annual averages of the indicators of wind direction, wind speed and horizontal visibility have been increasing with a positive slope, and the trend of changes in the relative humidity index has a negative slope and indicates a decrease in the period of 20 years. The results of the correlation analysis (at a significance level of 5%) showed that the highest correlation of the optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index. 4- Discussion & Conclusions The growing trend of the emission of dust particles caused by the phenomenon of wind erosion in recent decades has caused major concerns at different regional, national and global levels. Therefore, it is necessary to understand the temporal-spatial changes of the dust caused by these events in order to reduce their adverse consequences in different regions. Accordingly, in this research, with the help of this knowledge, information related to the optical depth of particles in the air (AOD) and the vegetation cover index (NDVI) were investigated using the MODIS sensor satellite data. Using the meteorological data received from the website of the National Meteorological Organization, the climatic data of rainfall, temperature, relative humidity, horizontal visibility, wind direction and wind speed were evaluated in the period of 2000-2020 and finally the correlation between the AOD index and other climate parameters was evaluated. The results of the optical depth investigation showed that the maximum optical depth is located in the central parts of Jazmurian wetland. The trend of changes in rainfall and temperature indicators also showed that the trend of these two parameters was increasing; this increase in temperature is more noticeable. Correlation investigation between optical depth and other parameters showed that the highest correlation of optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index. In general, we can conclude that the optical depth of airborne particles is highly dependent on environmental factors, which is more evident in arid and semi-arid areas, especially in Iran and the Jazmurian wetland area. In recent years, the area of the wetland has acted as a source of dust. Therefore, by using the remote sensing data obtained from the MODIS sensor and the climate data, it is possible to examine and analyze the trend of dust changes in the units of time and space. [ABSTRACT FROM AUTHOR]

Introduction: In recent decades, along with the physical development of cities and population increase due to immigration, heat islands, which are mainly the result of human made activities, have gained significant importance. So, the reduction of vegetation cover, the high consumption of fossil fuels, the emission of greenhouse gases and the use of inappropriate materials in urban construction have created the microclimate of a heat island above the metropolis of the world. Finally, it causes an increase in the land surface temperature, atmospheric stability, persistence and stabilization of pollutants and an increase in respiratory diseases. Today, by using remote sensing methods and using digital satellite images, it is possible to examine the land surface temperature with high accuracy and in a short period using MODIS sensors and Terra satellite images. Therefore, the main objective of the current research was to analyze the temporal and spatial variations of heat islands of Isfahan using the principal component analysis method. With this technique, it is possible to identify the seasons and months when the land surface temperature and the heat island increased. Material and Methods: In this regard, the present research considered analyzing the temporal and spatial variations of this phenomenon in Isfahan during a period of 20 years (from 2000 to 2020 AD). To achieve this purpose, the land surface temperature (LST) data extracted by MODIS sensor and Terra satellite was used. These data are available for the whole world with a time resolution of 8 days and a spatial resolution of 1x1 km in a sinusoidal grid with dimensions of 1200x1200 km. Therefore, for Isfahan, 913 images were extracted from the MODIS sensor. Then, with the principal component analysis (PCA) method, the seasons and months that have the most influence on the occurrence of heat islands were identified and in order to analyze the trend of this phenomenon, the Mann-Kendall and the Kolmogorov-Smirnov tests were used. Results and Discussion: The findings of the research indicated that the land surface temperature in the last 20 years in Isfahan had an increasing trend with a rate of 4%. However, this trend in the population and urban centers has been completely different from the surrounding areas of Isfahan. In terms of spatial distribution, the highest occurrence of heat islands has been registered in the eastern and southeastern parts (including Hassan Abad and Jolgeh) due to proximity to the hot deserts of Kavir-Lout, proximity to Sepiddasht, Varzaneh, Shahrak Ramsheh industrial towns and changes in the land use of agricultural to industrial and residential. also in the North-West region (including Mahmudabad and Isfahan city) due to the increase in man-made heating caused by the increase in the consumption of fossil fuels, the growth of residential, industrial and commercial units, temperature has risen. In addition, the results showed that the intensity of the heat island in winter is higher than in summer, and the most intense time of its occurrence was recorded in January and the least in November. Conclusion: Isfahan is integrally affected by global climate conditions, but depending on the geographical location of each part of this province, the land surface temperature and the occurrence of heat islands are different, so that, eastern and central parts, adjacent to Kavir-Lout and close to industrial towns, have an increasing trend. Moreover, the southern parts have a decreasing rate of temperature and heat islands due to less urban population, larger agricultural lands and more vegetation. The increase in urbanization, migration, and the increase in fossil fuel consumption, the decrease in vegetation, the aggravation of drought, and the change in land use have a fundamental role in increasing the occurrence of this phenomenon. [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.

South Asia has been experiencing recurring severe air pollution episodes in recent years. While many previous studies investigated such episodes focusing on individual cities and specific events, limited information exists on episode characteristics across multiple cities in this region. This study presents a comparative analysis of the characteristics of ambient PM2.5 pollution episodes in 12 South Asian cities across five countries during 2019−2023. Daily mean PM2.5 mass concentrations were decomposed into trend, seasonal, and residual components, and episodes were identified through anomalies in residuals. Furthermore, pollution episodes were characterized using magnitude, frequency, duration, and a relative severity index. The cities exhibited annual mean PM2.5 mass concentrations ranging from 20.6 ± 2.5 μg m−3 (Colombo) to 116.6 ± 9.3 μg m−3 (Lahore), with six out of 12 cities having annual mean PM2.5 mass concentrations > 50 μg m−3. Additionally, significant increasing trends (p < 0.05) in PM2.5 levels were observed for Dhaka, Chennai, Hyderabad, Kolkata, Islamabad, and Lahore (Sen's slope: 1.00−4.33 μg m−3 y−1), whereas decreasing trends (p < 0.05) were observed for Mumbai (−0.74 μg m−3 y−1) and New Delhi (−2.00 μg m−3 y−1). Mean PM2.5 episode magnitudes varied in a wide range from 49.9 ± 6.1 μg m−3 (Colombo) to 367.1 ± 17.9 μg m−3 (Lahore) across the cities. Likewise, the mean episode frequency ranged from 1.6 y−1 (Kathmandu) to 5.2 y−1 (Dhaka), whereas duration ranged from 1.2 (Mumbai) to 2.6 (Kathmandu) days per episode. Based on the relative index of episode severity, Lahore, Dhaka, and New Delhi exhibited high episode severity, as well as high baseline PM2.5 levels. In contrast, Karachi, Islamabad, Hyderabad, and Kathmandu showed moderate episode severity and moderate baseline PM2.5 levels, whereas Colombo and Mumbai showed low episode severity with low to moderate baseline PM2.5 levels. Moreover, annual PM2.5 episode severity ranks among the cities changed dramatically during 2019−2023. The relative severity of baseline and episodic pollution levels presented in this study may help policymakers prioritize the control strategies targeting pollution episodes, long-term trends, or both, as well as protecting human health through mitigation, preparedness, and forecasting. The findings will also provide insights for formulating regional policies aimed at transboundary cooperation and collaboration to deal with air pollution challenges across South Asia.

This paper presents an in-depth analysis of the variability and trend detection of water discharge in the Hieu River Basin over the period from 1/1/1961 to 31/12/2020. Firstly, the wavelet analysis is implemented to investigate the flow variability at different time scales. Using time series of daily flow at Quy Chau and Nghia Khanh, the periodicities of flow are examined, showing that periodic oscillations in flow mainly occurred at 1 year, from 2 to 4 years, and from 4 to 8 years. Secondly, discharge variability is investigated, revealing an increase from January to September (excluding June) and a decrease from October to December. At Quy Chau, flow increased seasonally and annually by 0.19 and 0.06 m3/s, respectively, while its values at Nghia Khanh decreased of up to −0.50 m3/s. Thirdly, temporal trends of flow are assessed using Mann–Kendall and Sen's slope estimator, and sequential Mann–Kendall test. Results show flow decreases during 1961–1969, 1973–1976, and 1996–2020 and increases in 1969–1973 and 1976–1996. Temporal patterns of flow at Quy Chau and Nghia Khanh demonstrated synchronization across different time scales. Relationship between flow and rainfall is discussed to investigate insights into their relationship. HIGHLIGHTS Wavelet analysis is applied to examine wavelet power spectrum of flow at different time scales.; Flow increases from January to September (excluding June) and a decrease from October to December at the Quy Chau station.; Water discharge decreases during 1961–1969, 1973–1976, and 1996–2020 and increases in 1969–1973 and 1976–1996.; Flow at Nghia Khanh has a stronger relationship with rainfall than those at Quy Chau.;

IntroductionThe temperature of the earth has been rising by about 0.74 degrees Celsius over the past century. A gradual increase in the average annual temperature has been reported by many researchers worldwide, while other reports suggest a decrease in this parameter. The assumption is that there will be more areas of the world experiencing higher temperatures. The climate changes are effectively represented by temperature changes, which is considered one of the main indicators in climate studies. The chemical composition of the atmosphere has changed because of the increase in human industrial activities, so it is responsible for unprecedented changes in the global climate in the past century. The increase in greenhouse gas concentration is the cause of this change. The evidence indicates that the increase in atmospheric gas concentration has caused a significant increase in global temperature. The use of thermal data from sensors is widely used in the study of terrestrial phenomena, as indicated by many studies. The temperature of the earth's surface is directly and indirectly linked to all human activities. It is still not possible to calculate the temperature of the earth's surface with perfect and accurate methods, but some sensors with suitable temporal, spectral, and spatial performance are able to take photos of the entire surface of the Earth. The study is more important due to the fact that various species of animals, such as Jebeer (belonging to the Bovidae), are exposed to climate changes in arid and desert areas. Due to its impact on humans, other creatures, and the entire environment, it is imperative to pay attention to climate change nowadays. In this regard, the main aim of the current study is to evaluate the LST (Land Surface Temperature) trends, changes, and temperature threats of the land surface in the Central Plateau of Iran. Time series remote sensing data of the MODIS (MOD11A2) sensor and Terra satellite, in 8 days with spatial resolution of 1km from 2002 to 2018 have been used. Material and Methods The current study has been focused on the central plateau of Iran. The central plateau of Iran lies within the arid lands belt of the northern hemisphere. The current study has been attempting to extract exact information from the images by employing specific techniques. To achieve this goal, the MOD11A2 product of Terra satellite MODIS sensor, the trend of temperature changes and time series construction of the significance of Man Kendall methods and linear correlation parameters such as maximum monthly temperature, maximum annually temperature based on maximum monthly temperature, median monthly temperature, maximum annually temperature based on median monthly temperature, minimum monthly temperature, minimum annually temperature for daily and nightly temperature were used in TerrSet software and Earth Trends Modeler section to extract significant increasing and decreasing areas. After identifying some parts of provinces with significant temperatures based on analysis and results, we can identify the vital numerical value of the temperature in each pixel of those significant parts in the next stage. This can be achieved by utilizing the difference between the final temperature and the initial temperature. Trend analysis was used to simulate daily and nightly temperature changes for parameters of maximum monthly temperature, maximum annually temperature based on maximum monthly temperature, median monthly temperature, maximum annually temperature based on median monthly temperature, minimum monthly temperature and minimum annual temperature. Results and DiscussionDaily temperature data in the Central Plateau of Iran, which includes monthly minimum temperature, annual minimum temperature, monthly maximum temperature, annual maximum temperature based on monthly maximum temperature, monthly median temperature and annual maximum temperature based on monthly median temperature, common in Semnan and Isfahan provinces, showed a significant increase in linear correlation according to the results. In Isfahan province, the linear correlation decreased significantly between the maximum annual temperature based on the maximum monthly temperature and the median monthly temperature. There was no significant trend in other provinces. The linear correlation between temperature data in Isfahan and Semnan provinces, including the minimum monthly, minimum annual, maximum annual, and median monthly temperature, decreased significantly. The linear correlation between average annual temperature, average monthly temperature, maximum annual temperature determined by maximum monthly temperature, average monthly temperature, and maximum annual temperature determined by median monthly temperature increased significantly in Yazd and Isfahan provinces. No significant trends were observed in other provinces. To estimate the amount and approximate number of significant increases and decreases, simulations of temperature changes were conducted. The range and approximate range of numbers for significant increase and decrease in temperature were calculated in degrees Celsius. In all analyses, the parts with higher temperatures had a reddish color. The intensity of the red color increased as the temperature increased, and as the temperature decreased, the red color became fainter and turned blue. The central plateau of Iran recorded a maximum temperature of 44C°and a minimum temperature of -7C°according to this study. The central plateau of Iran has three main provinces, which include Isfahan, Semnan, and Yazd. Considering the temperatures mentioned for these three provinces, the temperatures obtained from this study are very similar, which means that the conducted study is approved to a large extent. Animals are considered to be at risk due to temperature changes. Future research should emphasize the impact of climate change and temperature increase on the living conditions of various animals, particularly those found on the central plateau of Iran.

[Objective] Climate change directly affects global wind speed changes and the efficiency of wind energy resource utilization. Analyzing wind speed historical changes is one of the important topics for climate change response, efficient resource utilization, ecological security management, and sustainable social development. [Methods] Using the ERA5-Land grid reanalysis wind speed dataset at the 0.1° resolution from the European Center for Medium Range Weather Forecasts (ECMWF) and methods such as least squares, Theil-Sen slope estimation, and MK trend test to study the annual, seasonal, and monthly average wind speed trends and the evolution of suitable wind power areas over the past 72 years from 1950 to 2021 worldwide. [Results] (1) The global mean land surface wind speed increases slightly at an overall rate of 0.020 m/(s·10a) from 1950 to 2021. (2) The surface wind speed changes on a global scale exhibit significant spatial differences, especially remarkable in Africa and Antarctica in comparison with other continents. (3) As the seasonal changes, the land surface wind speed in winter season shows the significant changes, with a changing rate of 0.033 m/(s·10a). As the months changes, December, January and June exhibit particularly noticeable variations of surface wind speed. The global mean land surface wind speed has a mean rate of change of 0.073 m/(s·10a) and -0.066 m/(s·10a) for significant increases and decreases, respectively, in the regions passing the 95% significance test; and it has the mean rate of change of 0.080 m/(s·10a) and -0.071 m/(s·10a) for extremely significant increases and decreases, respectively, for the region passing the 99% highly significant test. The monthly average wind speed change rate and range in Antarctica are relatively large, affecting significantly the global average wind speed change rate and area assessment. (4) The global wind power energy density has slightly increased, with an average growth rate of 3.017 W/(m2·10a). The increase was most significant in January and December of the year, reaching 7.086 W/(m2·10a) and 6.660 W/(m2·10a), respectively. Antarctica and Africa lead in increasing wind power density for electricity generation, at 14.107 W/(m2·10a) and 4.652 W/(m2·10a) respectively. Asia stands out as the only continent with an overall decrease, while the remaining four continents show minor changes. [Conclusion] There were significant regional, seasonal, and monthly differences in global land surface wind speed changes. In order to accurately support climate change response, resources and ecological protection, and efficient development, dynamic monitoring and detailed analysis of changes in land surface wind speed and wind energy density in each region is still needed.

Groundwater is the primary water resource used for domestic, industrial, and agricultural needs for the community in the Yogyakarta-Sleman Groundwater Basin area. The urbanization rate has increased since the 1970s and has made massive use of groundwater, causing environmental problems, including the quality and quantity of groundwater. Therefore, this study aimed to investigate the spatiotemporal groundwater fluctuation trends based on the non-parametric Mann-Kendall test and recharge rate estimation using the water table fluctuation (WTF) method. The groundwater level data were collected from monitoring wells across the study area during 2018-2022, particularly emphasizing 8 wells representing recharge, transition, and discharge areas. The results showed that the groundwater fluctuation pattern generally followed the season. During the rainy season from January to April, groundwater reached the shallowest level and began to decline gradually when it entered the dry season from May to October. Groundwater recharge rate was estimated to vary from 171.49 to 1,505.56 mm/year. Meanwhile, the Mann-Kendall test showed that most of the Yogyakarta-Sleman Groundwater Basin area did not experience significant fluctuation trends, except for two monitoring wells in the center of Yogyakarta City which had increasing groundwater level trends. The rising groundwater levels were expected to be caused by urban wastewater recharge. This study has provided a new description and insights into spatiotemporal changes in the groundwater table and the quantification of groundwater recharge.

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.

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.

The emerging global environmental crisis, intensified by global warming, necessitates a deeper understanding of climate variations, especially in critical geographical divisions like the Qinling-Huaihe demarcation zone, which acts as a natural division between northern and southern mainland China. This study investigates the spatial–temporal differentiation of climatic elements within the Qinling-Huaihe demarcation zone from 1961 to 2018, employing data accumulated from 144 meteorological stations. Utilizing methodologies including the univariate linear regression, the Mann-Kendall test, and the Kriging interpolation, this investigation unveils the spatial–temporal variation characteristics of precipitation, relative humidity, and temperature. Temporally, the climatic alterations in the zone are predominantly marked by warming trends, significantly pronounced since the 1990s, with the elevation in minimum temperature being the most notable. Both precipitation and relative humidity exhibit a fluctuating ascending trend. Spatial analysis reveals a west-to-east increase in precipitation, while relative humidity presents lower values in the central region, escalating towards the eastern and western edges. The spatial distribution patterns for average, maximum, and minimum temperatures align closely, showcasing higher temperatures in the central region, extending to the Huaihe River area, with the Qinling Mountains exhibiting the lowest temperatures, particularly noticeable north of the Qinling Mountains.

Bangladesh is a significant contributor to the global food basket but is also one of the most vulnerable countries to climate change. Understanding regional climatic variability helps reduce climate risks and ensure food security. This research examined monthly, seasonal, and yearly temperature, rainfall, and relative humidity in Bangladesh using data from 35 meteorological stations from 1970–2020. The study utilized the Mann–Kendall method to evaluate trends and employed Sen’s slope to quantify their magnitude. Additionally, quantile regression was applied to analyze the impact of climatic variables on rice yield. The findings revealed that maximum (Tmax) and minimum (Tmin) temperatures were steadily increasing, with the southwest experiencing a more rapid rise compared to other regions in Bangladesh. Seasonal Tmax and Tmin rose in most parts of Bangladesh, particularly during the monsoon. In most areas, there was a significant (p

Study region: This study refers to the Upper Tiber basin at the Ponte Nuovo outlet in central Italy. Study focus: This study aims at analyzing runoff coefficient (Rc) trends and connections with hydroclimatic parameters, namely (temperature (T), precipitation (P), soil water storage (SWS), and LULC (Land Use Land Cover) changes) using Mann-Kendall (MK) test and wavelet coherence analysis (WCA). New hydrological insights for the region: The results show a decreasing Rc over 1927–2020, coupled with increasing T and decreasing SWS based on seasonal MK test, and implications for water resource management in Central Italy. Results underscore the need for sustainable hydrological management paradigms to address challenges posed by scarcity of water resources under unpredictable changing climate. Rc-hydroclimatic parameters correlations through WCA revealed complex hydrological interactions. Precipitation exhibited insignificant and erratic patterns from 1950 to 1978, and while it established more significant correlations with Rc from 1990 to 2020, it remained moderately erratic. Conversely, weak correlation found against LULC changes, concurrently with strong positive but lagged correlation with SWS (1 month), and strong lagged (3–6 months) but negative correlation with T indicate the prevailing significance of hydroclimatic factors over LULC changes. These insights underscore the pivotal role of hydroclimatic factors in shaping regional water resources. Policymakers can harness these insights as a bedrock to develop effective strategies for water resources planning and climate change adaptation.

This study aims to present an overview of incorporating the Water Framework Directive into Italian law through Law 152/06. Subsequently, it will focus on a case study involving 34 rivers in the Salerno Province, utilizing data obtained from ARPA Campania. This work analyses the macro pollution indicators of the observed rivers using two aggregated indexes, namely PLM and PLMeco. These indexes were introduced by Italian legislation in 1999 and 2006, respectively. The results show the quality of the river and the variations observed over the years in the Province of Salerno, utilizing non-parametric tests.

AbstractRecently, extreme climatic events have been a major concern across the world. Assessments on various climates and geographic regions are needed to understand the uncertainties in extreme climate events’ responses to global warming. Developing countries particularly Ethiopia is highly affected by such extreme climate events due to its low adaptive capacity. The aim of this study was to investigate the trends of daily extreme temperatures indices in Ethiopia. The changes and trends in climate extremes of temperature were evaluated based on 14 indices of extreme temperatures over Ethiopia. The Mann-Kendall (MK) trend test is used to investigate the trends in the selected datasets. In the present study, three zones, which represent 34 stations, were selected based of extreme climate indices. The results of 14 extreme temperature indices showed that warm days (TX90p) and nights (TN90p) increased by 2.65 (P

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]

In the context of climate change, where the average temperature has risen in recent decades on the Mediterranean coast of the Iberian Peninsula, bioclimatic indicators show an increase in thermal discomfort. This is especially relevant in regions with a clear focus on mass and seasonal sun and beach tourism, with a large number of tourists experiencing discomfort in hot and humid summer environments. The research analyses the temporal evolution (1967–2022) of the coasts of the provinces of Alicante and Murcia (Spain) using the Climate Comfort Index (CCI), divided into four different regions. Used are 14 coastal meteorological observatories divided into four regions. Trend analysis was performed using the Mann–Kendall (MKT) and Theil–Sen (TSE) tests. The results revealed a loss of climate comfort during the summer season (−0.3 to −0.4/decade), as well as an expansion of the warm period toward June and early September, with an increase of 38.7 days in "hot" thermal comfort. The increase in thermal discomfort in the summer is influenced by an increase in average temperature (0.5 to 0.7 °C/decade) and a reduction in the average relative humidity (−1.0 to −2.1%/decade) and wind speed (−0.2 to −0.9 km/h/decade). In the last 22 years (2000–2022), decreases (p  ≤ 0.05) have been recorded in July and September (−0.2 to −0.4/decade), reaching "excessive heat" climatic comfort thresholds for the first time. Finally, there has been an increase in thermal comfort in winter, especially during December in recent years (2000–2022). [ABSTRACT FROM AUTHOR]

Introduction and Objective: Drought as a climatic phenomenon is considered as one of the most important natural hazards, which is known for its slow onset and may have multiple effects on hydrology, agriculture and socio-economic conditions. Drought monitoring includes its severity, spatial distribution, and duration, and becomes an essential input for establishing drought risk management and mitigation plans. Many drought indicators have been introduced and applied in recent decades in regions with different climatic characteristics. Material and Methods: In this study, the meteorological and hydrological drought of Tajan watershed in Mazandaran province was evaluated and monitored using standardized precipitation index (SPI) and standardized streamflow index (SSI). For this purpose, firstly, the data of six stations Rain gauges and eight hydrometric stations were used in the period of 1990-2020, after removing the statistical deficiencies and completing the data of rainfall, flow rate, homogeneity and normality of the data. Finally, the meteorological and hydrological drought process was analyzed with the mentioned two indicators using Mann-Kendall test and Sen slope estimator in MAKESENS software. Results: The results showed that the SPI index has the highest response to rainfall on a one-month scale, so that its lowest value was at Kordkheil station with a value of -3.31, the most severe drought that occurred in April 2011. On the other hand, droughts have occurred in all rain gauge stations and their intensity has increased over time. According to the SSI index, hydrological drought has also occurred in all hydrometric stations with different intensities. The trend of these indicators also shows the increase in intensity and frequency of drought with the passage of time in the studied watershed. Conclusion: In Darabkola and Kordkheil stations, the SPI index has the highest number of years of occurrence and the highest intensity of drought. In Darabkola station, the frequency of moderate, severe and very severe droughts are relatively high. Very, very severe drought in Edareh Sari station has the highest amount in terms of frequency, which indicates that there is the greatest risk of drought occurrence in the plains and plains of the basin. The results of the trend with the Mann-Kendall test indicate an increase in drought and a decrease in rainfall in the Tajan watershed. Due to climate changes, increase in demand due to increase in population and decrease in rainfall, the occurrence of drought in the future may occur with more frequency and intensity, which can cause great damage to agriculture and other parts of the region. The SSI index in hydrometric stations indicates the decrease in flow and the occurrence of hydrological drought in the basin. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of temperature trends is vital for assessing the impacts of climate change on a regional scale. In this context, the present study focuses on Madhya Pradesh state in Central Indian region to explore the spatial-temporal distribution patterns of temperature changes from 1951 to 2021. Gridded temperature data obtained from the Indian Meteorological Department (IMD) in 1° × 1° across the state are utilised to analyse long-term trends and variations in temperature. The Mann-Kendall (MK) test and Sen’s slope (SS) estimator were used to detect the trends, and Pettitt’s test was utilised for change point detection. The analysis reveals significant warming trends in Madhya Pradesh during the study period during specific time frames. The temperature variables, such as the annual mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin), consistently increase, with the most pronounced warming observed during winter. The trend analysis reveals that the rate of warming has increased in the past few years, particularly since the 1990s. However, Pettitt’s test points out significant changes in the temperature, with Tmean rising from 25.46 °C in 1951–2004 to 25.78 °C in 2005–2021 (+0.33 °C), Tmax shifting from 45.77 °C in 1951–2010 to 46.24 °C in 2011–2021 (+0.47°C), and Tmin increasing from 2.65 °C in 1951–1999 to 3.19 °C in 2000–2021 (+0.46 °C). These results, along with spatial-temporal distribution maps, shed important light on the alterations and variations in monthly Tmean, Tmax, and Tmin across the area, underlining the dynamic character of climate change and highlighting the demand for methods for adaptation and mitigation. [ABSTRACT FROM AUTHOR]

The Three River Headwater Region (TRHR) is an important river source area providing important ecological functions. Decades ago, climate change and human activities severely degraded the ecosystem in the TRHR. To restore vegetation, a series of ecological projects have been implemented since 1989. Using net primary productivity (NPP) data from 1988 to 2012, a sequential Mann-Kendall trend test (SQ-MK) method was applied to identify the turning point of vegetation NPP. This approach was able to represent the critical response time of the vegetation to important disturbances. A 3-year time window was set after the implementation of one ecological project to detect and analyze its short-term effects. The ecological projects included the Yangtze River Basin Shelterbelt System Construction Project (YRCP), the TRHR Nature Reserve Construction Project (TNR), the Returning Grazing Land to Grassland Project (RGLGP), and the first phase of the Ecological Conservation and Restoration Project of the TRHR (ECRP). Our results showed that the vegetation in the TRHR responded positively to restoration: 89% of pixels showed an increasing trend and 54% of pixels underwent an abrupt change. The accelerated growth type accounted for the highest proportion among all types of detected turning points. In the ECRP's window, the positive turns rose rapidly, from 41% in 2005 to 86% in 2008, and it showed the most balanced restoration effects across grasslands. The alpine meadow and montane meadow restoration was largely influenced by the ECRP and the RGLGP (both >40%). The alpine steppe restoration was mainly attributed to the ECRP (68%). On the county scale, the positive turns in Yushu at the source of the Yangtze River mainly benefited from the RGLGP (56%), while the positive turns in Maduo at the source of the Yellow River benefited from the ECRP (77%). Nangqian, Tanggula and Zaduo County were still in need of intervention for restoration (< 3%). The results of the study can enhance our understanding of the spatio-temporal distribution of the short-term ecological benefits of different ecological projects, thus provide a scientific and timely reference for future planning and adjustment of the conservation and restoration projects. [ABSTRACT FROM AUTHOR]

Karnataka state has the second highest rainfed agricultural land in India, where agricultural output relies heavily on rainfall. The Shimsha basin, a sub-basin of Cauvery in the state, comes under a semi-arid region and predominantly consists of rainfed agricultural land. Rainfall patterns have changed dramatically with time resulting in frequent floods and droughts. Understanding the spatiotemporal distribution of rainfall and its change patterns in the area would benefit sustainable agriculture planning and water resources management practices. The current study aims to determine the variability and trend in rainfall. The daily rainfall data of the Shimsha basin from 1989 to 2018 is collected, and the annual, seasonal, and monthly rainfall totals and the number of rainy days are derived. All the time series are subjected to statistical methods to examine rainfall variability and trend. The mean, standard deviation, coefficient of variation (CV), and Standardized Anomaly Index are used for the preliminary and variability analysis, while the coefficient of skewness and kurtosis are used to understand the rainfall distribution characteristics. The homogenous and serially independent series are identified by homogeneity and serial correlation tests. The trend in the homogenous and serially independent series is identified by Mann–Kendall and Spearman's rank correlation tests, while the magnitude of the trend is quantified using the Sen's slope technique, and the trend change point is evaluated using the sequential Mann–Kendall test. Based on the study, the average rainfall in the study area is 801.86 mm, with CV ranging from 43.3 to 22.27%. The southwest monsoon (SWM) season brings the greatest rain to the basin, followed by the post-monsoon (PM), summer, and winter seasons. In the annual time frame, except one station, all other stations have shown significant or insignificant increasing trends. The seasonal rainfall has shown insignificant rising trends during the summer and winter seasons while insignificant increasing and decreasing trends during the PM season. The SWM season has indicated significant increasing trends, insignificant increasing and decreasing trends. Overall, the study area has noticed an increased annual and seasonal rainfall except for the post-monsoon season, during which the rainfall showed a considerable decline. The findings of the study are helpful in water resource management, agricultural planning, and socioeconomic development in the study area. [ABSTRACT FROM AUTHOR]

Protecting the water quality of the Yellow River is of great significance to the ecological protection of the Yellow River Basin. The identification of spatiotemporal variations of the water environment and the implementation of measures to control non-point source (NPS) pollution are both key to improving the water quality. Between 2012 and 2021, we conducted assessments of eight indicators, including water temperature, dissolved oxygen (DO) and pH, chemical oxygen demand (CODMn), five-day biological oxygen demand (BOD5), total phosphorus (TP), NO3-N, and NH3-N at six sites in the main stream of the Yellow River in Henan. We explored the causes of changes in water eutrophication using multivariate statistical analysis and formulated recommendations to improve NPS pollution through adjustments in land use patterns. The results showed that temporal water eutrophication markedly decreased and it was most spatially severe in the east. The most effective control of water eutrophication was observed between 2016 and 2018. As the transition from the flood season to the non-flood season took place, the main source of NPS pollution changed from being primarily influenced by precipitation, to being predominantly attributed to agricultural runoff. We recommend addressing the increased soil erosion in the west and controlling the discharge of agricultural effluent in the east. During the flood season, the ecological interception zones can effectively intercept NPS pollution outputs. These findings offer valuable insights for future scientific management strategies to prevent and control NPS pollution in the river. [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]

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]

The average yield of maize is significantly dependent on the meteorological conditions of the growing year. Both the most favorable weather conditions and the weather anomalies that tend to cause damage depend on the given phenophase. The aim of this research is to analyze the climatic changes that are important in maize production in the Hajdúság region. For the climatological study of the area, homogenized temperature and precipitation data from the Hungarian Meteorological Service was used for the Debrecen region, which are freely available for download from the data repository of the institution. Trend analysis was performed for the last 50-year (1973-2022) and 30-year (1993-2022) periods. In total, 40 meteorological data series matching the study objective were analyzed. Linear regression calculations were performed using the SPSS 27 statistical software. For the non-parametric procedure, the MAKESENS Excel application was used, based on the Mann- Kendall (MK) test and Sen's slope estimation. This research shows that the choice of the length of the study period affects the results of trend analysis. The numerical values of the trend slope for the 30-year vs. 50-year period differ, and for some parameters there are also substantial differences (e.g., trend sign). The results of the parametric and non-parametric trend analyses differed only marginally for the temperature variables included. Also, for precipitation data that do not follow a normal distribution (e.g., monthly), there were only a few significant differences. The trend in mean annual temperature shows an increase of 0.39 and 0.52 °C in 10 years, and an increase of around 2 °C in 50 years and 1.5 °C in 30 years. There is a significant warming in both the summer and winter half-years, with the summer half-year showing a steeper upward trend in the 50-year data series and the winter half-year in the 30-year data series. There is a clear pattern of large, highly significant warming in the summer months and less significant changes in the two spring and two autumn months that were observed. A negative, non-significant trend in annual precipitation is observed. The decreases of 17 mm and 24 mm/10 years obtained for the 50- and 30-year time series are not negligible from a practical point of view. For the summer half-year, the precipitation amount is decreasing, with a slope of -27 mm/10 years for the last 30 years, but even this value is not significant due to the high variability. There is no significant change in the amount of precipitation in the winter half-year over the last decades. Significant trends cannot be detected from monthly or even semi-annual or annual precipitation data. The Mann-Kendall test showed a trend decrease only in the 30-year April data series at the p=0.1 significance level. Overall, the changes are negative for maize production. It should be highlighted that the obvious warming, combined with a slight decrease in precipitation, is leading to a deterioration in crop water availability and a reduction in crop yields. The impact of the identified adverse climatic changes can be compensated to a significant extent by the proposed agrotechnical responses. [ABSTRACT FROM AUTHOR]

The current study primarily sought to select the best index for elaborating on dust activities, analyze the temporal and spatial changes of the index’s trend, and examine the relationship of the index with environmental factors in Iranian dry regions. To this end, the study examined the data collected on dust concentration, dust storm index, the number of dusty days (NDD), the pollution caused by dust storms, and the frequency of all dust events over a period of 18 years (2001-2018) using the MODIS-aerosols optical depth (AOD) product. Moreover, Pearson's correlation coefficient was used to analyze the correlation between the indices and AOD data sets. On the other hand, the trend of the best index annual changes in twenty-eight Iranian urban areas was analyzed using the Mann-Kendall method. Also, the most important environmental factors controlling dust activities in high-risk areas were identified using the random forest model. The results of the study indicated a strong correlation between NDD and AOD in Iranian dry regions (r= 0.7; p-value= 0.001). It was also found that the trend of NDD’s annual changes significantly increased in Torbat Heydarieh, Nehbandan, and Anar (Z>+1.96). However, the trend significantly decreased in Chabahar and Iranshahr (Z>│-1.96│. Generally, the results indicated an insignificant decreasing trend of annual NDD changes across the entire Iranian arid regions from 2001 to 2018 (Z= -0.45). on the other hand, the random forest model suggested that air pressure and wind speed exerted the greatest influence on dust activities that occurred in Iran’s high-risk area throughout the study period. Therefore, it could be argued that the findings of this study can help better monitor dust events and reduce their environmental risks in Iranian dry areas. [ABSTRACT FROM AUTHOR]

The objective was to investigate if changes in annual, monthly, and seasonal precipitation are associated with emergence of declining oak trees in Iran. Daily precipitation data were obtained from 20 synoptic stations distributed over the Zagros area from 1988-2019. Non-parametric Mann-Kendall (MK) test and Sen's Slope estimator (Qmed value) were applied to identify significant trends in the precipitation data. "De Martonne" climate classification (i.e., De Martonne aridity index (IDM) was used for climate classification. Although most stations showed decreasing trends in annual precipitation during the studied period (1988-2019), these trends were statistically significant at only two stations. The mean number of events per year pre- and post-oak decline was not significantly different (68 events before against 71 events after decline). Most of the annual precipitation in the Zagros region falls in winter and spring (80% in total). However, this ratio decreased after the year 2000 by 6% (not significant) compared with before. The difference between the average annual precipitation, before (1988-2000) and after (2000-2019) the emergence of the oak decline phenomenon, were not statistically significant in any of the climate types (semi-arid: 406 mm vs. 378 mm), Mediterranean (530 mm vs. 489 mm), and humid (924 mm vs. 912 mm) as well as in whole Zagros region (537 mm vs. 508 mm). Although our data suggested insignificant trends in precipitation for most stations, future research should investigate if rising temperature in the Zagros area has resulted in higher evaporation and drier soil thereby accelerating the oak tree decline. [ABSTRACT FROM AUTHOR]

G lobal warming is a result of the greenhouse effect caused by the gases released into the atmosphere; It is usually expressed as an increase in the measured average temperatures. In addition to this, extreme weather events such as droughts, floods, and severe hurricanes become more frequent, and the specified extreme events become more severe. The effects of global climate change on hydrological and meteorological variables are increasing day by day. Therefore, hydro-meteorological parameters should be examined carefully. In this study, the effects of global climate change on the Hirfanli Dam Basin temperature series were investigated using the Mann-Kendall Test and Sequential Mann-Kendall Test. The annual mean temperature series of six stations recorded between 1965 and 2017 were analyzed and evaluated. It has been determined that the annual mean temperature has increased throughout the basin and significant increases started since the 1990s. Researches analysing the effects of global climate change on hydro-meteorological parameters related to the Hirfanli Dam Basin should be increased. These studies may be the investigation of the trends of climate parameters with different methods, as well as their relations with global atmospheric indices such as the North Atlantic Oscillation and Southern Oscillation. In the Hirfanlı Dam Basin, which shows semi-arid climate characteristics, especially drought disaster should be investigated. In addition to drought detection, these studies should be conducted with an integrated disaster management perspective in order to prepare for drought disasters. With the perspective of integrated disaster management, it will be more resilience to disasters with plans in which all components in the basin are together and effective against many disasters, especially drought. [ABSTRACT FROM AUTHOR]

Groundwater is the primary water resource used for domestic, industrial, and agricultural needs for the community in the Yogyakarta-Sleman Groundwater Basin area. The urbanization rate has increased since the 1970s and has made massive use of groundwater, causing environmental problems, including the quality and quantity of groundwater. Therefore, this study aimed to investigate the spatiotemporal groundwater fluctuation trends based on the non-parametric Mann-Kendall test and recharge rate estimation using the water table fluctuation (WTF) method. The groundwater level data were collected from monitoring wells across the study area during 2018-2022, particularly emphasizing 8 wells representing recharge, transition, and discharge areas. The results showed that the groundwater fluctuation pattern generally followed the season. During the rainy season from January to April, groundwater reached the shallowest level and began to decline gradually when it entered the dry season from May to October. Groundwater recharge rate was estimated to vary from 171.49 to 1,505.56 mm/year. Meanwhile, the Mann-Kendall test showed that most of the Yogyakarta-Sleman Groundwater Basin area did not experience significant fluctuation trends, except for two monitoring wells in the center of Yogyakarta City which had increasing groundwater level trends. The rising groundwater levels were expected to be caused by urban wastewater recharge. This study has provided a new description and insights into spatiotemporal changes in the groundwater table and the quantification of groundwater recharge. [ABSTRACT FROM AUTHOR]

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