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This study aimed to develop an approach for country-scale domestic grey water footprint (GWFdomestic) accounting and examine spatio-temporal differences using statistical methods. In this scope, the GWFdomestic was calculated as the amount of water required to reduce the total nitrogen concentrations of domestic wastewater released into receiving media from 81 cities in Türkiye. GWFdomestic values were estimated based on the data on wastewater amount and applied wastewater treatment process. GWFdomestic was calculated by dividing the pollutant load of discharged water by the critical concentration in the surface water. The empirical results showed that (a) the produced wastewater amount increased up to 125 m3/year in some cities. (b) GWFdomestic values showed a difference between 330 and 1,900 depending on the level of treatment, and the average value was about 750 m3/ca.year. (c) A total of 81 cities were grouped under four categories, and applied water treatment technology was the main characteristic of this classification. (f) GWFdomestic has not statistically significantly changed over time in a large part of the country. It can be concluded that country-scale GWFdomestic accounting can assist water managers in developing prevention measures by analyzing spatio-temporal differences in the water footprint of domestic discharges. HIGHLIGHTS An approach to account for the country-scale domestic grey water footprint-GWFdomestic was proposed.; GWFdomestic was calculated as the amount of water required to reduce total nitrogen concentrations.; Spatio-temporal differences in GWFdomestic were examined using factor analysis and Mann–Kendall tests.; GWFdomestic values showed a difference between 330 and 1,900 across the country, and the average value was about 750 m3/ca. year.;

Abstract The change of temperature and weather parameters is a major concern affecting sustainable development and impacting various sectors, such as agriculture, tourism, and industry. Changing weather patterns and their impact on water resources are important climatic factors that society is facing. In Thailand, climatological features such as ambient temperature, relative humidity, and precipitation play a substantial role in affecting extreme weather events, which cause damage to the economy, agriculture, tourism, and livelihood of people. To investigate recent serious changes in annual trends of temperature, relative humidity, and precipitation in Thailand, this study used the Mann–Kendall (MK) test and innovative trend analysis (ITA) methods. The MK test showed that all six regions had an upward trend in temperature and humidity index (humidex, how hot the weather feels to the average person), while relative humidity and precipitation showed both upward and downward trends across different regions. The ITA method further confirmed the upward trend in temperature and humidex and showed that most data points fell above the 1:1 line. However, the upward trend in most variables was not significant at the 5% level. The southern and eastern regions showed a significant upward trend in relative humidity and humidex at a 5% level of significance according to the MK test. The output of this study can help in the understanding of weather variations and predict future situations and can be used for adaptation strategies.

[Objective] Clarifying the regional characteristics and variation trends of extreme precipitation events has great significance for ecological security and disaster mitigation under climate change. [Methods] Based on the observation data from 1961-2020, linear trend analysis, M-K test, Morlet wavelet analysis, and correlation analysis were used to analyze the spatiotemporal variation of extreme precipitation events and their sensitivity to climate change from previous period (1961-1990) and recent period (1991-2020) across the upper and middle Yellow River Basin. [Results] (1) Most extreme precipitation indices decreased first and then increased around the 1990s, except the continuously decreasing consecutive dry days (CDD). In the recent period, average daily rainfall intensity (SDII), rainfall on very wet days (R95), and rainstorm days (R50) significantly rose at 0.43 mm/(d·10a), 13.98 mm/10a, and 0.06 d/10a respectively (p < 0.05). (2) In the whole period, the southwestern part of the study region was relatively wet while the Yellow River bend area was the driest, and the extreme heavy precipitation presented more in the southeast and less in the west. In the recent period, the wetting trend in the upper Yellow River Basin gradually increased, and the frequency and intensity of extreme heavy precipitation in the middle Yellow River Basin increased significantly. (3) The average annual temperature in the upper and middle Yellow River Basin rose by about 1.5 ℃ with the acceleration of the warming rate during the past 60 years. The annual precipitation first decreased and then increased, and the upward trend in the recent period reached the extremely significant level (p < 0.01). The climate of the study region was transforming from warm-dry to warm-wet, especially in the upper part of the basin. Extreme precipitation was more sensitive to the annual precipitation amount than average temperature and had significant positive correlations, except for CDD. [Conclusion] The trends and magnitudes of variation of extreme precipitation events in the previous period and the recent period were much larger than that in the whole period. Since the 1990s, distinct warm-wet trend appeared in the upper reaches, while extreme heavy precipitation events increased significantly in the middle Yellow River Basin, requiring special attention to future floods.

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

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

Groundwater is the primary source of water for domestic and irrigation purposes in the peninsular region of the Bhagalpur and Khagaria districts of Bihar. Though this region is bounded by perennial rivers on three sides, the groundwater level is decreasing gradually because of over exploitation and misuse. In this study, spatial and temporal analyses of rainfall and groundwater levels for pre- and post-monsoon seasons from 1996 to 2020 have been carried out using GIS tools, graphical plots, and statistical methods of pattern recognition. The spatial analysis of rainfall shows less rainfall in the western region of the study area, whereas it shows heavy rainfall in the region near the Vikramshila Bridge. The temporal analysis of rainfall shows decreasing trend in the whole study area and the rate of decrease was 25.05 mm/year during 1996–2020. The results of the pre-monsoon groundwater levels analysis show decreasing trend in the majority of wells, and the rate of decrease varies from 0.005 to 0.102 m/year. By contrast, the post-monsoon groundwater levels showed an increasing trend varying from 0.005 to 0.083 m/year at wells located near the River Ganga, except at Maheshkhunt. Thus, there is a need for proper groundwater management for a sustainable future. HIGHLIGHTS The study investigated the change in the patterns of rainfall and groundwater levels in a peninsular region formed by four rivers.; The study used GIS tools and graphical and statistical methods for spatio-temporal analysis.; The results showed a declining trend in rainfall and groundwater levels and their variation in space.; Based on this study, the authorities can initiate steps for groundwater management.;

The paper presents in form of a case study the results of 10-year long hydro-chemical studies on the Korzeń stream on which the “Skrzyszów” small storage reservoir was built. Studies aimed at evaluating the impact of the reservoir on the surface water quality in a Flysch stream. The basis for the analysis was results of 21 hydro-chemical water quality parameters, from the following groups of indicators: physical and acidity, oxygen and organic pollution, biogenic, salinity, metals. Indicators were determined in one-month intervals in two periods: 2005–2009 (before the reservoir was built) and 2015–2019 (after the reservoir was built). Obtained results were subjected to a statistical analysis. The trend analysis of changes was performed using the Mann–Kendall test or the seasonal Kendall test; significance of differences between indicator values from two periods was evaluated using the nonparametric Mann– Whitney U test. Results of analysis showed significant change trends of water quality parameters, in case of total iron concentration the trend was downward in both periods. Statistically significant differences between the values of definite majority of indicators were found in two analysed periods, indicating both favourable and unfavourable impact of the reservoir on water quality in the stream. Construction of the storage reservoir resulted in a significant change of physical and chemical indicators of water flowing in the stream. Random variation dynamics as well as tendencies and trends of changes over time have changed. In addition to modifying the stream hydro-chemical regime, the reservoir also affected the social and natural conditions.

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

The main purpose of this paper was to investigate the monthly, seasonal, and annual rainfall variability in the Mae Klong River Basin in Thailand using the Mann–Kendall (MK) test, Sen's slope method, Spearman's Rho (SR) test, and the innovative trend analysis (ITA) method. The monthly rainfall data of eight stations for the period 1971–2015 were used for trend analysis. Datasets with significant serial correlation were corrected by the trend-free pre-whitening (TFPW) approach for statistical methods. The MK test showed increasing rainfall trends for five out of eight stations in the dry season while 50% of stations indicated increasing trends in the wet season. On an annual scale, 75% of the stations exhibited increasing rainfall trends. The results of the SR test were in line with the MK test for seasonal and annual rainfall. The ITA method showed comparable findings with those of the statistical methods. For the entire basin, trend analysis found increasing rainfall on both seasonal and annual scales by all the tests. The findings of this study could benefit water supply and management, drought monitoring, agricultural production activities, and socioeconomic development in the Mae Klong River Basin in the future. HIGHLIGHTS Statistical methods and graphical methods for rainfall trends are compared.; Datasets with significant serial correlation were corrected by the trend-free pre-whitening (TFPW) approach for statistical methods.; The results of Spearman's Rho test were in line with the Mann–Kendall test for seasonal and annual rainfall.; The innovative trend analysis method showed comparable findings with those of the statistical methods.;

Drought has become one of the most devastating natural risks of agricultural production and the environment in almost all climate regions. Thus, understanding the spatiotemporal characteristics of drought and its associated impacts is crucial in drought early warning management and adaptation efforts. In this study, we used the 3-month Standardized Precipitation Index (SPI-3) obtained from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) to investigate the space–time characteristics of drought conditions. Also, this study examined the impact of the SPI-based drought on vegetation health conditions using the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time-series data from 1981 to 2020. The results revealed that the region experiences drought primarily between July and September, with the most prolonged drought events lasting up to five months. Morocco suffered from more frequent droughts than other countries in the region. The Mann-Kendall test showed that the trend of drought became drier over the last decade, whereas the period from 1981 to 2010 witnessed either wetting or no trends. This study also found that the response of crops and grasslands showed higher correlation with the SPI-3 and that the response of vegetation to droughts was higher during the dry season. The findings of this study provide useful information to support local and regional drought planning and adaptation programs and enhance the understanding of drought development in the region.

ABSTRACT Andit tid watershed is part of Blue Nile basin located in the central highlands of Ethiopia. The lack of data and information at watershed level resulted in different conclusions from trend studies of river flow, sediment yield and crop productivity at a basin scale. There is an opportunity to improve water and land if it can be underpinned by a better scientific understanding of trends of flow, sediment yield and crop production at the basin level. This research is carried out using descriptive statistics, Mann–Kendall (MK) and Pettit’s test to determine the potential trends of river flow, sediment yield and crop productivity using Andit tid watershed case. The result showed that there was high variability of interannual river flow with CV >30%. The Pettitt test showed a significant abrupt change in monthly (March, July, August, September and October) and seasonal (summer and winter) river flow. The Pettitt test result of sediment yield and crop production showed no change. MK test showed a significant (P

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

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

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

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

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

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

The average annual precipitation values in the Cheliff-Zahrez basin range from 80 to 600 mm/an, indicating a semi-arid climate. This work revolves around a new drought exceedance probability index (DEPI), a standardized precipitation index (SPI) and effective drought index (EDI) in different time scales (3, 6, 9, 12 and 24) derived from monthly precipitation series stretching from September 1970 to August 2015. The latter aims to analyze the performance, similarities and differences between the most used drought indices such as SPI and EDI and to compare their results with those obtained using DEPI. The results indicated that the majority of selected stations tend to a decline in annual rainfall, with a dominant break in series between 1970 and 1980. The Mann–Kendall test result showed that the monthly rainfall trend had significantly decreased in the majority of studied stations. Furthermore, the SPI and EDI series showed persistent monthly drought conditions from January 1970 to March 2010 with an extreme drought peak of − 3. However, the DEPI index showed monthly drought events (< 0.5) of different classes beginning from March 1980 to December 2010. In the study area, the coefficient of determination explained a high variation (> 80%) between SPI and EDI at the time scale of 24 months. At the 9- and 12-month scale, the coefficient of determination showed a variance greater than 50% over the entire basin. On the other hand, the coefficients of determination results between SPI and EDI for the time scale of 3 to 6 months are characterized by a gradient from the northeast to southwest or from 10 to 90%. The stations of the Coastline 2 basin have revealed that the relationship between SPI and DEPI as well as EDI and DEPI is not significant, being allowed between 10 and 30% on time scales of 3, 6, 9, 12 and 24 months. The results of this work and information on the severity and persistence of droughts will be essential to enable managers to adopt an integrated and sustainable management of scarce resources and aim at minimizing agricultural production losses in the region. [ABSTRACT FROM AUTHOR]

As a major grain-producing province in China's Central Plains, Henan Province is severely impacted by drought, making the study of agricultural drought characteristics in the region crucial. Theil–Sen (Sen) trend analysis, the Mann–Kendall (M-K) test and the Hurst index method were used to systematically analyze the spatial variation characteristics of agricultural drought based on the Temperature Vegetation Dryness Index (TVDI). The results show that: (1) The drought occurs in central, northwestern and southern Henan on an annual scale. The drought situation will continue to increase in northern, eastern northeastern and central Henan. (2) The drought in spring, summer and winter showed an increasing trend, but the opposite trend was observed in autumn. The increasing trend of drought in each season is mainly distributed in northern, central and eastern Henan. (3) The drought in January, February, April, July, September and December showed an increasing trend, while the drought in the other 6 months showed a decreasing trend. The increase in drought during July and August was not pronounced, while the drought situation in September remained largely unchanged. The distribution of drought across the other months exhibited varying patterns across different regions. Overall, the drought trend in Henan Province is on the rise, displaying distinct seasonal and regional patterns in its temporal and spatial distribution. The results can provide a reference for Henan Province to formulate effective measures of drought resistance and disaster reduction to ensure grain production. [ABSTRACT FROM AUTHOR]

1- Introduction Land subsidence, as one of the environmental hazards, is happening in many countries of the world. This phenomenon, if not properly managed, can cause irreparable damage. In this regard, Iran, as one of the countries that has been facing the risk of land subsidence for several decades, will probably be affected by the damage of this phenomenon in the near future. Damages including; Damage to agricultural lands, buildings, roads, bridges, pipelines, etc. Various activities such as; Mining, excessive extraction of underground water, etc., have intensified the process of land subsidence to the point where it has become one of the most important hazards of geomorphology. Identifying the boundaries, the pattern of land subsidence and estimating its intensity will play a significant role in the management and control of this phenomenon. Therefore, it is necessary to take measures to prevent further problems. Therefore, the important goal of this research is to evaluate the subsidence of the Kashmer plain with the radar interferometry method and its relationship with the groundwater drought. Maybe the results of this research can help the executive managers and planners of land and soil resources in the field of protection and management of water resources to prevent land degradation. 2- Methodology In this research, radar interferometry was used to monitor subsidence, and Kendall and Pettit's time series analysis tests were used to evaluate groundwater drought. Also, to calculate the density of wells, kernel density estimation was used, which transforms and determines the position of points in space in a continuous density function in the studied area. Finally, to determine the correlation coefficient and covariance between the existing rasters, as well as some statistical parameters such as the minimum, maximum, average and standard deviation values for each raster, Band Collection Statistic analyzer, which is considered a part of multi variate analyzers was used. Two SENTINEL satellite images were used to determine the amount of subsidence in the target area: 1- The Master image was taken on 04/04/2017. The variable image of 03/25/2021 Slav was also used with a time span of about 4 years and using Land subsidence was calculated from SNAP software. The PSI index was used to determine the level of groundwater drought. This index can be used for all piezometric levels. 3- Results The results of the radar interferometric analysis showed that the subsidence in the studied area was due to excessive water withdrawal from wells and underground water sources. The cause of subsidence around the wells was due to the lack of equipment and the entry of particles into the well. The results of changes in the time series of the PSI index showed that it is insignificant at the probability level of 5% in Kalate Rahim and Khalil Abad wells and significant in the rest of the wells. In the studied area, the lowest water level drop is related to the wells of Khalil Abad, Kalate Rahim. Khalil Abad well has had a drop in water level from 1996 to 2006, and from 2006 to 2021, the PSI index had an upward trend. The analysis of PSI data up to 2019 showed that the groundwater drought in the Kashmir plain has reached its peak over time, and from 2019 to 2014, the conditions have somewhat returned to normal conditions. In addition, subsidence is developing from the western areas such as Khalilabad, which have been involved in this issue in the past, towards the central areas and the center of Kashmar plain. The highest density of wells in the study area is in the central areas towards the western areas of the plain. The study of the land use map of the region also showed that the majority of the density of wells is related to agriculture and irrigated agriculture, which includes 76% of the exploited wells. 4- Discussion & Conclusions The obtained results showed that in different regions of Kashmir Plain, in the period of 4 years (2017 to 2021), there was about 46 to 84 cm of land subsidence, which means that annually in different areas between 11.5 and 21 cm of subsidence can be observed. On the other hand, the process of subsidence has reached the central areas from the west of the Kashmar plain, and the highest intensity of subsidence can be seen around the city of Kashmar. The time series of PSI groundwater drought index is insignificant in Kalate Rahim and Khalil Abad wells and significant in the rest of the wells. Regarding the relationship between the amount of land subsidence and the severity of groundwater drought, the highest amount of subsidence is located in the areas that are in the minimum historical conditions of the PSI index and include the highest fluctuation of subsidence in the region. As we approach the normal conditions of the region in terms of the PSI index, the amount of subsidence also decreases, which indicates a strong connection between groundwater drought and land subsidence. The future perspective of the dangers caused by this phenomenon is very difficult and even impossible, considering the vast dimensions of the damage it causes to the fields of natural resources. Therefore, the custodian bodies, including the country's natural resources and watershed management organization, the General Directorate of Natural Resources and Watershed Management, the Jihad Agriculture Organization, the Regional Water Company of Khorasan Razavi Province, have a very heavy responsibility in managing the crisis and improving the conditions. [ABSTRACT FROM AUTHOR]

1- Introduction One of the important purposes of flood spreading plans is to feed groundwater tables and increase quality of these resources. One of the most important indicators for evaluation of artificial recharge plans is to examine their impact on quality of groundwater resources. The main aim of current research is to investigate effects of implementation of artificial aquifer recharge plan (Herat flood spreading) on temporal changes of groundwater quality parameters in the region. 2- Methodology Harat watershed area is 1413 square kilometers in south of Yazd province. The location of flood spreading sites implemented at the end of Harat basin outlet and with an area of 490 hectares, which includes four implementation areas. In order to investigate and evaluate the effects of flood spreading projects on groundwater resources, statistics of parameters of 17 wells were used from the area of aquifer of Fathabad affected by these projects, based on available information, parameters of calcium, carbonate, magnesium, sodium, chlorine, and total dissolved solids and salt was extracted. The wells were classified into two groups, control and affected, based on their location relative to sites and the direction of flow in waterways of area. According to length of period, in order to evaluate the impact of water withdrawals and consequently impact of sedimentation on the efficiency of the sites, the entire period was divided into two periods so that 2003-2011 is first period and 2012-2021 is second period. Minitab software was used to check linear trend of average groundwater quality parameters. For this purpose, the average of all types of quality parameters of water resources, first and second periods were entered in software and the change process for each parameter was obtained. In order to investigate temporal trend of groundwater quality parameters, Mann-Kendall test was used at 95% confidence level and Sen's slope by XLSTAT 2019 Software. 3- Results The results related to time trend of water quality factors through Mann-Kendall method and Sen's slope showed that calcium factor among nine wells located downstream of the project, three wells have no trend and the rest have a negative trend. The results of checking trend of control wells showed that calcium had a positive trend in all but one well during statistical period under review. Factors of sodium, bicarbonate and magnesium in the downstream of projects often have a negative trend and also in the control area they often show a positive trend, but factors of salinity, chlorine and total dissolved solids in the control area do not have the same situation as other factors. So that the number of wells without trend in the control range is more than the rest of the factors. This means that the condition of the aquifer in terms of three indicators is neutral and does not have a negative or positive tendency, but the investigation of trend related to affected area showed that flood spreading projects have been able to improve the status of these factors, which are part of the important factors affecting agricultural water. lead to improvement. In order to investigate effects of flood spreading projects, at the beginning and after several years, linear trending of the average factors was done in two time periods. Due to lack of data in the last of years of implementation of flood spreading to evaluate effectiveness of groundwater quality from flood spreading project, the number of available years was divided into two almost equal parts so that impact of these projects can be investigate in the initial period and after a few years. The results of linear trend of the first and second periods showed that total dissolved solids and calcium were decreasing with a high slope in the first period, but in second period and after a few years, effectiveness decreased, but it is still decreasing with a gentle slope. Bicarbonate and magnesium factor have had an increasing trend in first period, and in second period, magnesium has decreased towards a negative slope, but bicarbonate follows an increasing trend with a higher slope than in first period. In the case of other factors such as salinity, chlorine, sodium, trends are almost similar to each other. So, in the first period, they have decreased with a slight slope, but in second period, this slope has increased proportionally. This means that the infiltration of flood water through these projects has been able to improve status of all factors except for bicarbonate, but the passage of time has left different effects on the manner and extent of effect, which requires more detailed investigations. 4- Discussion & Conclusions According to results of investigations of time trend of various factors in this region, flood spreading has been able to have a positive effect on quality of groundwater. So that in determining trends of whole aquifer, except for bicarbonate factor, which had a positive trend, in other factors, there was a decreasing trend and no trend, which indicates positive effect of flood spreading on the control of quality factors. The results of this research showed that state of trend of all factors in some wells of witness area showed an increase and, in some wells, there was no trend, but in the affected area (downstream) all factors had a decreasing trend. The location of wells and distance from the waterways and flood spreading sites have a great impact on the vulnerability of wells. So that B9 well, which is located in the farthest part of the affected aquifer and is far from flood spreading sites, is among wells that had the most negative trend in most factors. Also, B3 and B2 wells are among wells that have the highest decreasing slope. Investigations showed that B9 well was located at a very short distance from the main waterway and B2 and B3 wells are also located near the distribution sites in addition to position relative to waterway and are affected by several flood distribution sites. So, distance of wells from waterway and the location of the sites can be very effective. [ABSTRACT FROM AUTHOR]

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.

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 major grain-producing province in China’s Central Plains, Henan Province is severely impacted by drought, making the study of agricultural drought characteristics in the region crucial. Theil–Sen (Sen) trend analysis, the Mann–Kendall (M-K) test and the Hurst index method were used to systematically analyze the spatial variation characteristics of agricultural drought based on the Temperature Vegetation Dryness Index (TVDI). The results show that: (1) The drought occurs in central, northwestern and southern Henan on an annual scale. The drought situation will continue to increase in northern, eastern northeastern and central Henan. (2) The drought in spring, summer and winter showed an increasing trend, but the opposite trend was observed in autumn. The increasing trend of drought in each season is mainly distributed in northern, central and eastern Henan. (3) The drought in January, February, April, July, September and December showed an increasing trend, while the drought in the other 6 months showed a decreasing trend. The increase in drought during July and August was not pronounced, while the drought situation in September remained largely unchanged. The distribution of drought across the other months exhibited varying patterns across different regions. Overall, the drought trend in Henan Province is on the rise, displaying distinct seasonal and regional patterns in its temporal and spatial distribution. The results can provide a reference for Henan Province to formulate effective measures of drought resistance and disaster reduction to ensure grain production.

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]

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

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