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

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

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

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

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

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

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

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

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

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

Copyright of Turkish Journal of Remote Sensing & GIS is the property of Halil Akinci and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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

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

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

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

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

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

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

Abstract Preserving the quality of groundwater has become Bangladesh’s primary challenge in recent years. This study explores temporal trend variations in groundwater quality on a broader scale across 18 stations within the Dhaka division over 35 years. The data set encompasses an analysis of 15 distinct water quality parameters. Modified Mann-Kendal, Sens Slope and Mann-Kendal tests were performed to determine the trend’s variation and slope. In addition, the spatial–temporal changes in the quality of groundwater are studied through Geographic Information System (GIS) mapping and Piper diagram was applied to identify the unique hydrochemical properties. This is the first study conducted on this area using various trends analysis and no in-depth study is available highlighting the trends analysis of groundwater quality on a larger magnitude. In contrast, the correlation matrix reveals a high association between Mg2+ and SO4 2−, Na+ and Cl− that affects salinity and overall hardness at the majority of sites. The Piper diagram also demonstrates that the groundwater in Madaripur Sadar has major salinity issues. The analysis reveals a distinctive dominance of bicarbonate (HCO3 −) ions across all sampling stations, with (HCO3 −) equivalent fractions consistently ranging from 0.70 to 0.99 which can cause a significant impact on groundwater uses. This extensive analysis of long-term groundwater quality trends in the Dhaka Division enables researchers to comprehend the overall transition of groundwater quality for hardness related complications in future. Moreover, it can be a baseline study considering the valuable implications and future steps for sustainable water resource management in this region.

Abstract This study aimed to derive major pollutants for standard watersheds with relatively high pollution levels and identify their trends. Hence, the water quality index (WQI) and multivariate statistical techniques were used to analyze the water quality evaluation of standard watershed during the total maximum daily load (TMDL) policy period implemented since 2004. The WQI was calculated for 41 standard watersheds, divided into 14 main streams and 27 tributaries. Consequently, in the main stream, WQI decreased as it moved downstream after the MS5 site. In the tributary, WQI values were found to be low at TS11, TS15, TS16, and TS17 sites. However, the Mann–Kendall test results indicated that the overall WQI value was increasing, suggesting that the water quality of the study basin was improving as the TMDL policy phase progressed. Principal component analysis of the group with relatively low WQI among the standard watersheds revealed that water temperature, dissolved oxygen, total phosphorus, chemical oxygen demand, biochemical oxygen demand, and electrical conductivity were the main variables in the main stream cluster. In the tributary stream cluster, total phosphorus, dissolved oxygen, total suspended solids, total nitrogen, and electrical conductivity showed high loading values. This study proposed a series of methods to provide the basic data required for watershed management through detailed water quality assessment methods, statistical techniques for deriving major pollutants, and trend analysis of water quality evaluation.

Human activities, particularly the regulation of hydropower stations, have profoundly altered river flow patterns. While studies have extensively assessed the impact of large or multi-year regulated hydropower stations on hydrological regimes using indicators of hydrological alteration (IHA) and range of variability approach (RVA), the impact of daily regulation hydropower stations has received comparatively less attention. This study aims to evaluate the influence of daily regulation hydropower stations on hydrological regime changes, focusing on the upper Yellow River region in China. Using daily runoff data from 1954 to 2020 at the Guide station, the study compares the impacts of multi-year regulated (Longyangxia) and daily regulation (Laxiwa and Nina) hydropower stations. The Mann-Kendall test showed that 27 out of 32 Indicators of Hydrological Alteration (IHAs) had significant trends under Longyangxia operation, which reduced to 18 IHAs with the inclusion of daily regulation stations. The Range of Variability Approach (RVA) revealed that only 46.87% of IHAs exhibited high alteration from the natural regime when daily regulation was considered, down from 75.00% with Longyangxia alone. This suggests that daily regulation can mitigate the negative impacts of multi-year regulation, potentially enhancing the river's eco-hydrological health. HIGHLIGHTS This study contrasts the impacts from multiyear with daily regulation hydropower stations on hydrological regimes.; The supplementary daily regulation tends to mitigate the alterations by multiyear hydropower station.; The rate and frequency of runoff change increase with the additional daily operations.; Nina and Laxiwa decrease hydrological regime change to 75.24% from 82.29% in the upper Yellow River region.;

Revealing the contribution of each of the climatic and human factors can help the management of water resources. Firstly, trend analysis and change‐point tests were performed to determine the status of the parameters affecting the groundwater resources of the Mahidasht aquifer during the period from 1981 to 2019 by using statistical methods and the Pettitt test. The GMS model was calibrated as a tool to simulate the Mahidasht aquifer system. After determining the change point, modeling of the groundwater level before and after the change point was done using the GMS model. By removing the effect of human factors in the model, the contribution of the effects of climate variability and human activities on groundwater was obtained. The results showed that there was no significant trend in annual rainfall, but the annual runoff has a significantly decreasing trend at the confidence level of 99%, and the trend of the groundwater level is also significantly decreasing at the confidence level of 99%. Pettitt change point test showed precipitation without a change point, but the runoff in 1998 and the groundwater level in 2001 had a change point. Finally, the modeling of the aquifer showed that the contribution of human activities in the reduction of the groundwater level of the Mahidasht aquifer was 78 and climate variability is 22%.

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

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

The Himalaya represents the most fragile ecosystem in the world, signifying its sensitivity towards global climate change. In the current scenario, the Himalaya needs to assess the climatic change trends at the regional level. To investigate climatic trends, we analysed the long-term (1980–2020) climatic data (maximum temperature—TMax and minimum temperature—TMin, precipitation, and relative humidity—RH) collected by the five different meteorological stations from Shiwalik to Pir Panjal mountain range of Jammu province. The nonparametric Mann–Kendall test was used to analyse the significance of climatic change trends for temperature, precipitation, and RH data on seasonal and annual scales, whereas the nonparametric Sen's estimator of the slope was applied to quantify the magnitude of climatic change trends. The results reveal that the Jammu province region received 53% of annual precipitation from Western Disturbances and 47% from Indian Summer Monsoon. The contribution of Western Disturbances was greater towards the northern region of Jammu Province, while the southern lower region was substantially influenced by ISM. With substantial inter-station variations, our results indicated a significant increasing trend of TMax only for Banihal, while all the studied stations except Jammu exhibited a significant increasing trend of TMin. For the entire Jammu province, a significant increasing trend of TMax was observed for the spring season. On an annual scale, the increasing rate of changes was observed more for TMin (0.066 °C) than TMax (0.016 °C) of Jammu province while a nonsignificant declining rate of change was exhibited for precipitation (− 0.098 mm a−1). The shifting pattern in temperature and precipitation could have serious environmental implications that will greatly influence the biodiversity and ecological stability of the region. [ABSTRACT FROM AUTHOR]

Copyright of Arab Journal for Scientific Publishing is the property of Research & Development of Human Recourses Center (REMAH) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The prediction of land use and land cover (LULC) patterns is essential for land use planning, natural resources management, and climate change mitigation. In this study, the artificial neural network (ANN) technique and QGIS software have been proposed to project 5- and 10-year future LULC for the Mahanadi River basin in Chhattisgarh, India. The results reveal that slope, aspect, and hillshade maps have significant effects on LULC. The projection of the future LULC for the years 2027 and 2032 reveals that the grassland and cropland areas would significantly decline and increase, respectively, in the study region. The results from trend analysis show an increasing trend for forests, permanent wetlands, cropland, urban built-up land, waterbodies, and cropland/natural vegetation, while decreasing trends for the remaining classes. The overall finding from this study suggests that remote sensing enabled with the ANN technique has the potential to project the future LULC with high accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

River ecosystems in Central Asia face significant stress from environmental changes and pollution. This study assesses temporal and spatial variations in water quality parameters within the Zarafshan River Basin using retrospective data and field measurements. Water quality indicators, including electrical conductivity (EC), total suspended solids (TSS), ammonium nitrogen (N‐NH4), nitrite nitrogen (N‐NO2), nitrate nitrogen (N‐NO3), temperature (T), chemical oxygen demand (COD), dissolved oxygen (DO), and discharge, were analyzed using the Pearson's correlation coefficient and ANOVA, with the Mann–Kendall (MK) test detecting trends over time. Obtained results indicate significant seasonal effects with elevated TSS during summer, increasing sediment load and changing aquatic habitats. The strong inverse correlation (–0.89) between DO and N‐NH4 signifies ecological challenges particularly in low DO concentrations during summer (3.25 mg L–1). Long‐term analysis identifies Navoiazot chemical factory as a major pollution hotspot. Spatial analyses based on extended sampling have revealed the Siab and Dargom canals and Samarkand City as major pollution sources of elevated N‐NO2 and COD, respectively. Trends at various gauging stations (MK‐test) show increasing EC (τ = 0.72) and N‐NH4 (τ = 0.46) levels, with decreasing TSS, N‐NO3, T, and COD levels over time. Recommendations include targeted measures to reduce pollution at the Navoiazot factory and downstream, introducing sustainable agriculture practices, increasing public awareness for environmental conservation, and improving urban wastewater treatment to meet water quality requirements for different users. [ABSTRACT FROM AUTHOR]

This study aimed to derive major pollutants for standard watersheds with relatively high pollution levels and identify their trends. Hence, the water quality index (WQI) and multivariate statistical techniques were used to analyze the water quality evaluation of standard watershed during the total maximum daily load (TMDL) policy period implemented since 2004. The WQI was calculated for 41 standard watersheds, divided into 14 main streams and 27 tributaries. Consequently, in the main stream, WQI decreased as it moved downstream after the MS5 site. In the tributary, WQI values were found to be low at TS11, TS15, TS16, and TS17 sites. However, the Mann–Kendall test results indicated that the overall WQI value was increasing, suggesting that the water quality of the study basin was improving as the TMDL policy phase progressed. Principal component analysis of the group with relatively low WQI among the standard watersheds revealed that water temperature, dissolved oxygen, total phosphorus, chemical oxygen demand, biochemical oxygen demand, and electrical conductivity were the main variables in the main stream cluster. In the tributary stream cluster, total phosphorus, dissolved oxygen, total suspended solids, total nitrogen, and electrical conductivity showed high loading values. This study proposed a series of methods to provide the basic data required for watershed management through detailed water quality assessment methods, statistical techniques for deriving major pollutants, and trend analysis of water quality evaluation. [ABSTRACT FROM AUTHOR]

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

A population is regarded as the main non-economic driver of carbon emissions, causing the climatic crisis, especially in China experiencing a dramatic demographic transition. In contrast to aging, low fertility, the most remarkable feature of the Chinese population transition, has always been ignored when evaluating carbon emissions, due to the lack of long-run data. To narrow this gap, an integrated framework combining the continuous input–output tables from 1997 to 2018 with the Mann–Kendall test and vector auto-regression was presented to clarify the fluctuating trend of household embedded carbon emissions and the driving pattern of low fertility, aging, and urbanization. Our main findings showed that changes in household embedded carbon emissions have increased sharply in the last two decades. The growth of Chinese household embedded carbon emissions began to accelerate in 2001, which lagged 1 year behind the demographic indicators. Low fertility has a positive impact on households' embedded carbon emissions. More importantly, the impact of low fertility is more significant and far-reaching than that of aging. These suggest that aggressive policies for stimulating fertility and low-carbon lifestyles should be considered by policy makers. [ABSTRACT FROM AUTHOR]

Due to global warming, precipitation regimes are expected to change, and heavy events are expected to occur more frequently. This study investigates the relative share of heavy daily precipitation events to total precipitation for past and current climates. In this regard, daily precipitation data with a spatial resolution of 0.25° x 0.25° from the APHRQDITE and CHIRPS databases are used. We used two nonparametric tests, the Mann-Kendall test and Sen's slope estimator, to identify the trend. The results showed that the frequency of daily heavy precipitation has been increasing in most regions of Iran. The relative share of heavy daily precipitation events to total precipitation has increased over the southwest and central areas of Iran from a case of the past to the current climate. The rise in the share of heavy precipitation of the total precipitation has led to a decrease in the frequency of rainy days (wet days) and an increase in the intensity and concentration of precipitation in Iran. The amount of increase in the share of heavy rainfall to the total precipitation is more prominent in the middle parts of the Zagros Mountains. These conditions lead to heavy floods in the southwestern plains of Iran. [ABSTRACT FROM AUTHOR]

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

Ri Bhoi district, located on the northern slopes of the Meghalaya plateau, has a complex climate ranging from pleasant summers and cold winters in the Highland zone closer to the Shillong plateau to hot and humid summers and cool winters in the Lowland zone, which merges with the Brahmaputra plains. Climate change, which is a reality at present, adversely impacts the marginalised section of the farmers more, especially those in the developing economies who depend on the vagaries of the climatic elements, and their crop production depends on the success or failure of seasonal rains. The present work attempts to analyse the rainfall trend on an average monthly, seasonal, and annual basis for the last 20 years for the Ri Bhoi district. The techniques followed for this analysis are the Mann-Kendall test at a 95% confidence level and Sen's slope estimate. The findings suggest an erratic rainfall pattern in the highland and lowland zones of Ri Bhoi district that could impacts agriculture and agro-based livelihoods. [ABSTRACT FROM AUTHOR]

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen's slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors. [ABSTRACT FROM AUTHOR]

Arunachal Pradesh in one of the largest states in north eastern states of India, having subtropical humid climate influenced by monsoon. An attempt has therefore, been made to understand the climatic conditions of the state and its influence on the reference evapotranspiration (ETo) and crop water requirement (CWR) of rice crop, using 21 years (2001-2021) data of 14 districts of Arunachal Pradesh. The results revealed that the maximum temperature varied from 13°C to 30°C while minimum temperature varied from 3°C to 20°C and annual rainfall varied from 1200 mm to 2700 mm across the state. The maximum temperature was found to decrease while the minimum temperature and rainfall were found to increase with varying significant levels in different districts. The mean annual reference evapotranspiration (ETo) was found to vary between 900 mm and 1400 mm. The crop water requirement of rice estimated using CROPWAT model revealed a large spatial variation from 508 mm to 731 mm in different districts of the state. [ABSTRACT FROM AUTHOR]

Rainfall trend analysis is essential for managing water resources, agriculture, disaster management, and climate change research. The current study aims to examine annual rainfall variability and trend over 38 meteorological stations in Iraq during the period (1980-2021) using three tests: linear regression analysis (LRA), Mann-Kendall (MK), and the innovative trend analysis (ITA). The results of the three different tests showed that most stations recorded a decreasing trend except for four stations in ITA, six stations in MK, and seven stations in the LRA test, which exhibit a positive trend. However, three stations, Emaidyah, Rabiah, and Biji, showed an increasing trend for all three tests. The ITA test recorded more significant results (14 stations) than the other two tests. The larger significant result appeared in the significance level of 95 % (nine in LRA, eight in MK, and five in ITA). The outcomes of the three trend-detection approaches by assessing the statistical significance levels, 90 %, 95 %, and 99 %, revealed no significant trend in 16 stations dispersed throughout the various climatic zones of Iraq. Only Emadiayah station indicated a positive trend at the significance of 99 %. The overall results showed that the ITA test outperformed the MK and LRA tests since it produced more significant results. [ABSTRACT FROM AUTHOR]

Climate change has made weather patterns less predictable, making situations more challenging for farmers throughout the production process. This study investigates the impact of climatic variables (maximum and minimum temperature, rainfall, humidity at 8 AM and 5 PM) and fertilizer application on wheat production in Bahawalnagar district, a major wheat producing region of Punjab, Pakistan. The study utilizes the Mann–Kendall and multiple linear regression analysis to check climatic trends and identify the factors influencing wheat yield from 1991 to 2022. The study utilized a regression model to compare actual and predicted wheat yields. The results showed a decreasing trend in rainfall and an increasing trend in both maximum and minimum temperatures during the wheat growing season. Sen's slope values for maximum temperature (0.037), minimum temperature (0.007), humidity at 8 AM (0.275), and humidity at 5 PM (0.167) indicate the direction and magnitude of trends. The regression model explained about 92% of the variance in the wheat yield. The regression analysis of humidity at both 8 AM (p = 0.001) and 5 PM (p = 0.001) shows a significant positive correlation with wheat yield. Fertilizer use exhibited a significant positive association with wheat yield (β = 9.58). Fertilizer application for wheat crops increased from 112.4 kg/ha in 1991 to 284.3 kg/ha in 2021. The regression model identifies that the average wheat yield loss from 1991 to 2022 is approximately 0.1208 t/ha per year because of the influence of climatic factors. The study findings underscore the importance of the utilization of adaptive agricultural practices that can ensure food security and improve agricultural sustainability in the region. [ABSTRACT FROM AUTHOR]

The surface solar radiation in most parts of the world has undergone a phenomenon known as global dimming and brightening, characterized by an initial decrease followed by an increase. As a result, the sunshine duration (SD) has decreased in the past 60 years. Against the backdrop of global dimming and brightening, SD has decreased to varying degrees in many regions of China. Using the observed data of SD, cloud amount (total cloud amount and low cloud amount, abbreviated as TCA and LCA), precipitation, and relative humidity (RH) from 34 meteorological stations in Chongqing during the period of 1961–2020, along with a digital elevation model (DEM) with a resolution of 90 m, this study analyzed the spatiotemporal variations and influencing factors of SD. The analysis employed methods such as linear regression, Mann-Kendall test, wavelet transformation, and DEM-based possible SD distributed model. The results showed that the annual SD in Chongqing has significantly decreased over the last 60 years, with a decreasing interannual trend rate (ITR) of 40.4 h/10a. Except for no obvious trend in spring, SD decreased significantly in summer, autumn and winter at the ITR of 21.1 h/10a, 8.5 h/10a and 7.5 h/10a, respectively. An abrupt decrease in the annual SD was found in 1979. The difference before and after the abrupt decrease was 177.7 h. The difference before and after the abrupt decrease was 177.7 h. The annual SD possessed the oscillation period of 11a. The spatial heterogeneity of the mean annual SD during the last 60 years was obvious. The distribution of SD in Chongqing is high in the northeast and low in the southeast. In addition, about 73% of the total area in Chongqing showed a significant and very significant decreasing trend. The regions with significant changes are mainly concentrated in the regions with altitudes of 200∼1000 m. The increasing LCA was the main cause of the decrease of the annual SD in the regions with 200–400 m altitude decreased the most and changed the most. Increasing LCA is the primary cause of the reduction in annual SD, showing a strong negative correlation coefficient of −0.7292. In Chongqing, PM2.5 concentration showed a significant decrease trend in annual, spring, autumn and winter during 2000–2020, but the significant correlation between PM2.5 concentration and SD was only in autumn and reached an extremely significant level. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Agricultural productivity is highly correlated with climatic variations, including drought events. This study is aimed at performing a comprehensive assessment of agricultural drought conditions in the Köppen–Geiger climate zones in Bangladesh, based on the temperature condition index (TCI), vegetation condition index (VCI), and vegetation health index (VHI). The zones are classified as follows: temperate dry winter with a hot summer zone, tropical savannah zone, and tropical monsoon zone. The range of VHI is optimized based on its correlation with TCI and VCI. The correlation among the stratified drought indices is also examined to quantify and measure the strength and direction of the linear relationships between them. Moreover, Mann–Kendall test is conducted to assess the statistical trends in the spatiotemporal propagation of droughts across different climate zones. The balanced correlation approach for VHI reveals that vegetation health is governed by the temperature conditions. Certain variations in the drought intensity, frequency, and duration are observed across climatic zones in earlier years while the recent years are noted with less droughts. Normal or no drought conditions are noticed mostly in the tropical monsoon zone through VCI and VHI. The correlations among the drought classes indicate that VHI is more strongly correlated with TCI than with VCI, while NDVI exhibits stronger correlations with VCI than with either VHI or TCI. The Mann-Kendall test revealed that VCI has significant downward trends in drought categories and an upward trend in normal conditions, whereas VHI and TCI displayed inconsistency in statistical trends. By extensively exploring the agricultural drought conditions within specific climate zones, this study offers valuable insights for agronomists and stakeholders involved in climate resilience planning and agricultural development in Bangladesh.