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Climate change has a substantial influence on a range of meteorological factors and the global hydrological cycle. This paper presents an analysis of the annual rainfall (P), temperature (including maximum temperature: T max , minimum temperature: T min , and average temperature: T avg), stream flow (Q) data from 6 gauging sites, and groundwater level (GL) data from 7 groundwater stations in and around the Barak River Basin in India from 1986 to 2020. To identify patterns in the time series, the simple linear regression (SLR) approach, the Mann-Kendall (MK) test, the Hamid Mann-Kendall (HMK) test and the Spearman's Rho (SRO) tests have been employed. Pettit test has been used to identify the change points in the time series. The results indicated an increase in the T max and the T min across the study area, while no clear patterns were found in the T avg time series. Except for the 'Hailakhandi' station, the annual total rainfall series showed an increasing trend. T max and T min showed a directional change point between 1999 and 2005, and between 2001 and 2007, respectively, according to change point analysis. Except for two stations, overall declining trends in the annual stream flow were found. Moreover, a total of five out of seven groundwater stations indicated a rise in groundwater levels. The findings presented here offer valuable insights into the current condition of the Barak basin and emphasize the importance of implementing sustainable water management practices. • Significant impact of climate change on hydro-meteorological parameters in the study area. • A noteworthy increase in both maximum and minimum temperatures. • Overall declining trends in annual stream flow across most stations in the basin. • Groundwater stations demonstrate rising groundwater levels. [ABSTRACT FROM AUTHOR]

The Serra da Mantiqueira Environmental Protection Area is one of the most important Atlantic Forest biodiversity hotspots in the World, and one of the main water sources for the Brazilian Southeast Region. In this study, we analyze the existence and characteristics of streamflow changes in two watersheds (Sapucaí-Mirim and Sapucaí-Guaçu River watersheds) of the Serra da Mantiqueira Range, and if these changes are due to climate change, alterations of land cover and/or external factors. Mann-Kendall and Pettit tests were used to detect changes in streamflow, rainfall and evapotranspiration data series, at different time scales. The characteristics and magnitude of land cover changes were evaluated from multi-temporal maps, produced from satellite images and the supervised classification technique. The results show an increase in winter rainfall at the two watersheds studied. No changes were detected in the streamflows of the Sapucaí-Mirim River Basin. The summer streamflow of Sapucaí-Guaçu River watershed reduced at a rate of −0.035 m³.s−1. year−1. In addition, there were sudden streamflow changes in the summer (from the year 1967) and autumn (from the year 1988) in Sapucaí-Guaçu watershed. Furthermore, the reference summer evapotranspiration of the Sapucaí-Guaçu watershed showed an increasing trend and an abrupt increase (in 1988), besides a sudden reduction of actual evapotranspiration in 2006. The integrated analysis of these results, together with the changes in land cover and population, allow us to conclude that the reductions in summer and autumn streamflows at the Sapucaí-Guaçu watershed were probably due to the increase in the water withdrawal for public supply, added to the effects of urbanization on the hydrology of the watershed. • We studied two watersheds within Serra da Mantiqueira Range. • Changes in streamflow, rainfall and evapotranspiration were analyzed. • Streamflow reduction is not related to rainfall changes, but with water withdrawal. [ABSTRACT FROM AUTHOR]

The Elevation Dependent Warming (EDW) in the mountain regions have wider implications to its cryosphere, hydrological, and ecological systems. This paper explores an EDW in the Indus River Basin, considering Jhelum, Kabul, and Indus sub-basins to improve the accuracy and understanding of cryospheric and hydrological changes in the basin. We use the maximum (Tmax), minimum (Tmin), and mean (Tmean) near surface atmospheric temperature data from 21 ground stations for the 1988–2021 period and applied the Mann-Kendall (MK) trend tests for exploring the trends in the data. The results show that Tmax and Tmin has significant (p < 0.001) warming trends in the Upper Indus Basin (UIB) until 2210 mean above sea level (m asl). Tmax has increased with a rate of 0.031 °C yr−1 (p < 0.001) while Tmin increased with a rate of 0.029 °C yr−1 (p < 0.001), hence the "diurnal temperature range (DTR) also increased significantly" (0.015 °C yr−1, p < 0.001). In this study, a symmetric pattern of increasing trends has been observed in Tmax and Tmin. Moreover, Tmax has increasing trends throughout the period in the middle and high-altitude regions, except in Autumn and Monsoon seasons, respectively. While more significant and prominent increasing trend observed in Tmax during the winter season. Thus, this consistent warming trends in all seasons with more prominent trend in the winter season for Tmax can have harmful impact on the cryosphere of the region and ultimately, leading to water scarcity and extreme droughts. • A symmetric rising trend has been observed in Tmax and Tmin. • No prominent and significant relationship observed between stations elevation and temperature. • A significant and prominent trend observed above 700 m for Tmax in winter. [ABSTRACT FROM AUTHOR]

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

Surface water resources have witnessed various challenges namely shortage of water availability, deterioration in water quality and reduction of water bodies due to climate change and anthropogenic activities. Thus, extracting surface water bodies accurately and examining trend in their areal extent assumes greater significance. This study makes a novel attempt to utilize remote sensing derived indices and machine learning algorithms to extract and examine spatio-temporal changes in surface water bodies in the lower Thoubal river watershed. Spectral water indices were derived using Landsat data for the years 1989, 1997, 2005, 2013 and 2020 and were fed into machine learning algorithms for precise extraction of surface water bodies. The random forest model exhibited superior performance in terms of surface water extraction. The Mann-Kendall test was then used to examine the trend of surface water bodies during 1989–2020. The analysis revealed a significant declining trend in water extent over the past three decades. Future simulations using a Markov-Chain model also projected a decreasing trend in water bodies for the years 2030 and 2040 in both wet and dry months. The morphological pattern of the surface water bodies was assessed using morphological spatial pattern analysis (MSPA). It has also shown decrease in area under water bodies. These changes in the dynamics of surface water bodies may be attributed to human encroachment on wetlands for settlement and farming purposes, damming of streamflow, garbage dumping and climate change. Thus, a comprehensive approach encompassing water conservation, demand management, supply augmentation, legislation and long-term planning is essential for fostering sustainable water resource management. The findings of the study may serve as a valuable record for decision-making process and policy responses. We argue that the methodology applied in the study may help in protecting and conserving neglected small surface water bodies in other geographical regions. [Display omitted] • Random forest model exhibited reliable efficacy in surface water bodies extraction. • Mann-Kendall test is also effective in areal trend analysis of surface water bodies. • Future Markov-Chain simulations forecast persistent water body reduction. • Shrinkage of wetlands and other surface water bodies is a cause for concern. • Conversion of wetland into farmland remain the major reason for wetland shrinkage. [ABSTRACT FROM AUTHOR]

Under long-term agricultural water saving strategy implemented in the Yellow River basin (YRB), this study analyzed long-term regional groundwater responses and their ecological impacts in an arid irrigation district (Hetao) in the upper YRB. The Mann-Kendall trend test was adopted to examine the trends of the monitoring data of climatic-anthropogenic factors and groundwater depth-salinity, as well as the modeling and remote-sensing results of natural vegetation growth. Results indicated significant decreasing net water diversion while increasing drainage since agricultural water saving, which is a major cause of groundwater reduction instead of climatic factors. This reduction was further confirmed with significant increasing groundwater depth (GWD) trends found in about 90 out of the total 224 monitoring wells across Hetao during 1970–2015. An overall salt accumulation was recognized for Hetao, but groundwater salinity only significantly changed in a few areas with insignificant trends found for more than 70 out of the total 114 monitoring wells during 1995–2015. Meanwhile, significant large-scale decreasing trends were detected for both simulated natural vegetation biomass and remote-sensing derived vegetation index, and wetland loss problem was also found. Particularly, relatively strong similarities were found among the spatial distributions of significant increasing GWD, decreasing vegetation biomass and index, and losing wetlands. This further suggested that the reduction might have caused negative ecological impacts. Overall, the results provided important information regarding long-term regional groundwater responses and their ecological impacts under agricultural water saving, which is significant for agricultural water management for arid irrigation districts. • Long-term groundwater response to water saving was analyzed in an arid region. • Impact on natural vegetations was analyzed by modelling and remote-sensing methods. • Groundwater showed significant depth increase but insignificant salinity change. • Natural vegetation biomass and index showed significant decreasing trends. • Increased GWD and decreased vegetation biomass and index showed strong relations. [ABSTRACT FROM AUTHOR]

Rainfall is a key factor of hydrological variability in a changing climate. Based on daily precipitation dataset of 50 station records, spatial and temporal variations of annual and seasonal precipitation from 1962 to 2011 in Qinghai Province, China are investigated using four statistical methods. Moreover, rainfall is analyzed for different rainfall intensities using the innovative trend analysis (ITA) method and the double ratio statistic (DRS) method. The results indicate that the reduction of precipitation in the densely populated eastern and southeastern regions is closely related to human activities. And human activities primarily affect extreme precipitation. The decrease in summer and autumn precipitation plays a major role in the decrease in the annual total precipitation. Spring and winter rainfall exhibit significant increasing trends. The inhibition of autumn precipitation caused by human activities is the most obvious, and this inhibitory effect can cause drought. It is hoped that this study can provide support for water resources planning and for dealing with droughts and floods. • The influence of human activities on the spatiotemporal variability of precipitation was revealed. • Variations of annual and seasonal precipitation for different rainfall intensities were detected. • Results varied with regions and seasons. • The findings provide support for water resources planning and for responding to droughts and floods. [ABSTRACT FROM AUTHOR]

Quantifying the impact of urbanization on extreme climate events is significant for ecosystem responses, flood control, and urban planners. This study aimed to examine the urbanization effects on a suite of 36 extreme temperature and precipitation indices for the Beijing-Tianjin-Hebei (BTH) region by classifying the climate observations into three different urbanization levels. A total of 176 meteorological stations were used to identify large cities, small and medium-size cities and rural environments by applying K-means cluster analysis combined with spatial land use, nighttime light remote sensing, socio-economic data and Google Earth. The change trends of the extreme events during 1980–2015 were detected by using Mann-Kendall (MK) statistical test and Sen's slope estimator. Urbanization effects on those extreme events were calculated as well. Results indicated that the cool indices generally showed decreasing trends over the time period 1980–2015, while the warm indices tended to increase. Larger and more significant changes occurred with indices related to the daily minimum temperature. The different change rates of temperature extremes in urban, suburban and rural environments were mainly about the cool and warm night indices. Urbanization in medium-size cities tended to have a negative effect on cool indices, while the urbanization in large cities had a positive effect on warm indices. The significant difference of urbanization effect between large and medium-size cities lay in the daily maximum temperature. Results also demonstrated the scale effect of the urbanization on the extreme temperature events. However, the results showed little evidence of the urban effect on extreme precipitation events in the BTH region. This paper explored the changes in temperature and precipitation extremes and qualified the urbanization effects on those extreme events in the BTH region. The findings of this research can provide new insights into the future urban agglomeration development projects. Unlabelled Image • Urbanization effects on extreme climate events were estimated. • The scale effects of urbanization on extreme events were revealed. • Significant changes occurred with indices related to the daily minimum temperature. • Main difference between urban and suburban areas lay in daily maximum temperature. • Little evidence of the urbanization effect on precipitation extremes was found. [ABSTRACT FROM AUTHOR]

Hourly ground-level ozone (O 3) data from 52 monitoring stations in Poland were analyzed over a ten-year pre-COVID19 period (2010–2019) to map and define areas at risk for human health and vegetation, and to calculate trends over the study period. Annual O 3 metrics (24-h average concentrations, 50th percentiles, and hourly maxima), human health metrics (Sum Of daily maximum 8-h Means Over 35 ppb, SOMO35, summertime average of the daily 8-h maximum O 3 concentrations, O 3 MDA8, and number of daily maximum 8-h values above 60 ppb, EU60) and vegetation exposure metrics (AOT40, i.e., accumulation of hourly O 3 concentrations exceeding 40 ppb during the growing season for agricultural crops AOT40c and forests AOT40f) were investigated. Higher O 3 levels occurred in rural areas than in cities. Between 2010 and 2019, the O 3 levels were rising in both urban and rural areas. Despite the reduction of nitrogen oxides (NO x : - 2.33% year-1) and volatile organic compounds emissions (VOCs: - 0.95% year-1), annual O 3 mean levels (+0.81 and +0.12% year-1), 50th percentiles (+1.06 and ∼0% year-1), hourly maxima (- 0.10 and +0.23% year-1), SOMO35 (+2.86 and +1.50% year-1), summertime O 3 MDA8 (+0.49 and +0.48% year-1), EU60 (+0.09 and +0.15 days year-1), AOT40c (+3.79 and +3.29% year-1) and AOT40f (+4.47 and +4.34% year-1) commonly increased in urban and rural stations. The O 3 levels increased at 75.0% of urban stations and 62.5% of rural stations. A slight decline of the number of O 3 peaks occurred in cities, likely driven by the recent reductions in NO x emissions by on-road transport. For all metrics, the increase can be attributed to higher regional photochemical O 3 formation and rising background O 3 levels likely driven by imported O 3 and its precursors by long-range transport, climate change, and lower O 3 titration by NO x emissions decline. The failure to attain the target value for O 3 for protecting vegetation and human health and vegetation persists. Southeastern Poland, where coal stoves are still used for residential heating, faces the highest O 3 risk. This study reports new information on surface O 3 levels, exceedances, and trends in Poland to develop effective policies to mitigate O 3 effects. [Display omitted] • We calculated human health and vegetation exposure O 3 metrics for Poland. • We calculated short-term trends for O 3 metrics over the pre-COVID19 period (2010–2019). • We used an interpolation approach to map O 3 exposure for risk assessment. • We found that the O3 baseline level is rising in both urban and rural areas. • We discussed spatial distribution of levels and changes in O 3 levels. [ABSTRACT FROM AUTHOR]

Abstract Understanding the spatiotemporal evolution of extreme temperature events is critical to evaluate their influences in nature. Out of 28 general circulation models (GCMs) in the Coupled Model Inter-comparison Project phase 5, eight GCMs were selected to simulate changes of the six extreme temperature indices (ETIs) in China: warmest daily maximum temperature-TXx, warm days-TX90p, tropical days-TD30, coldest daily minimum temperature-TNn, cool nights-TN10p and frost days-FD0. Statistically downscaled daily maximum and minimum temperatures at 552 sites under representative concentration pathway (RCP) 4.5 and 8.5 scenarios were used. The modified Mann-Kendall method was used to detect the trends and their significances in ETIs. The Morlet wavelet basic function was used to investigate the main and quasi periods of the ETIs over the historical (1961–2000) and future (2001−2100) time stages. The results showed that FD0 and TN10p had decreasing trends, and TNn had increasing trends at more sites than decreasing trends. However, TD30, TX90p and TXx showed consistently increasing trends both during historical and future periods under the RCP4.5 and 8.5 scenarios. More sites had significant trends in the 6 ETIs during 2001–2100. The decreases in FD0 and TN10p reached 31.4 and 27.4 days during 2021–2060 and 42.6 and 29.7 days during 2061–2100, respectively. The increases in TNn, TD30, TX90p, and TXx reached 8.7 °C, 45.3 days, 41.6 days and 5.7 °C over 2021–2060 and 7.2 °C, 65.6 days, 62.4 days and 6.4 °C over 2061–2100, respectively. With respect to the averaged values for 552 sites, the primary periods of FD0, TN10p, TNn, TD30, TX90p and TXx were 8, 8, 8, 3, 3 and 10 years from 1961 to 2017 and 4, 4, 4, 2, 2 and 3 years under the RCP4.5 scenario from 2021 to 2100, respectively, whereas only TN10p and TNn had the 2- and 4-year periods under the RCP8.5 scenario. Differently from the averaged ETIs over China, more sites had longer periods from 1961 to 2017 to 2021–2100 under the RCP 4.5 or RCP 8.5 scenarios. This outcome meant that many sites had smaller fluctuations and less periodicity from 2021 to 2100 than from 1961 to 2017. The spatiotemporal changes in the ETIs may lead to the shifting of cultivation, variety adaptability and production for main crops in different sub-regions or climate zones. This research provides projected characteristics of extreme temperature events across China. Graphical abstract Unlabelled Image Highlights • The performance of different GCMs in China are different. • There are more warm days and tropical days, less cold nights and frost days in the future. • More and more sites had longer periods of extreme temperature indices from 1961-2017 to 2021-2100. [ABSTRACT FROM AUTHOR]

Abstract Air pollution has emerged as a key environmental issue of Pakistan as its major cities are ranked among top polluted cities in the South Asian region. Due to lack of adequate ground-based monitoring facilities, satellite observations are the only viable source for long-term assessment of air quality over the region. This study analyses the atmospheric concentrations and decadal changes derived from multiple satellite instruments of four important tropospheric trace gases over Pakistan: surface concentrations of carbon monoxide (CO), tropospheric columns of formaldehyde (HCHO), nitrogen dioxide (NO 2) and ozone (O 3). High levels of all these trace gases were observed over Punjab region, which may be attributed to its metropolitan importance. It is the major agricultural, industrialized and urbanized region of the country. Seasonal Mann-Kendall (SMK) test is used to calculate the statistical significance of temporal trend during the last decade (2005–2014). Surface CO showed a significant decrease of about 13 ± 1% over the decade. Tropospheric column ozone (O 3) exhibited a significant increasing trend with a temporal increase of 10.4 ± 1.2%/decade whereas NO 2 showed a significant temporal increase of about 28 ± 2%/decade. However, an insignificant increase of about 8.3 ± 0.3%/decade is estimated for HCHO over the decade. A distinct seasonal behaviour is observed among trace gases. The long-term relationship among trace gases is further explored by statistical tests. It is found that O 3 , NO 2 and HCHO have a significant impact on the long-term decrease of CO whereas; the trend in O 3 critically depends on NO 2 levels along with CO over the region. A statistical model is developed to estimate the long-term association of trace gases over the region. The model indicates that O 3 production may have major influence on decrease of CO over Pakistan in a (volatile organic compound) VOC-limited regime. Graphical abstract Image 1 Highlights • Large temporal variability of trace gases is observed from the year 2005–2014. • Distinct seasonal variation of trace gases revealed long-term relationship among them. • PMK statistics indicated a long-term impact of O 3 , NO 2 and HCHO on decreasing trend of CO. • Tropospheric chemistry is dominated by the reaction pathways that yield ozone instead of CO. [ABSTRACT FROM AUTHOR]

Evapotranspiration is an important element of the water cycle and possible trends in the evapotranspiration can, among others, influence on the water management and agricultural production. Since actual evapotranspiration values are rare and difficult to estimate, reference evapotranspiration was examined in order to document changes in the climatic conditions that affect evapotranspiration. The daily reference evapotranspiration data calculated using the Penman-Monteith method from 18 meteorological stations located in three different climate types in Slovenia was examined in this study. 55 years of data from 1961 until 2016 was analysed. The Mann-Kendall test was applied in order to detect trends in different samples that were defined based on the daily reference evapotranspiration data. Relationship between the evapotranspiration and influencing factors was also investigated using the generalized boosted regression trees model. The calculated trends for different samples are mostly increasing and statistically significant while no consistent trend could be detected for all 18 stations. The maximum increase in the daily reference evapotranspiration for the observed period was 0.5 mm and the maximum decrease −0.4 mm. Moreover, upward trend was detected for two mountain stations and downward for one sub-Mediterranean station. No uniform trend could be found for the stations located in the temperate continental climate. Furthermore, generalized boosted regression trees model indicated that solar radiation has the largest impact on the reference evapotranspiration values, generally followed by air temperature, saturation vapour pressure deficit and wind speed. [ABSTRACT FROM AUTHOR]

Highlights • The spatial variability of the long-term trends of the SWH in the Black Sea was studied. • Wave fields were hindcasted by Mike21 SW for the last 38 years. • Long-term trends are estimated by the Theil-Sen and line of best-fit estimators. • Severe sea states resulted in more significant and steeper trends than the mean values. • Correlations of SWH to climate oscillation indices were studied. Abstract This study aims to estimate the spatial variability of the long-term trends of Significant Wave Height (SWH) in the Black Sea. A spectral wave model was used to hindcast 38 years of SWH forced by ECMWF ERA Interim wind fields. Long-term trends were estimated from normalized SWH (NSWH) data, for each month separately, by using two non-parametric methodologies; Line of best fit and the Theil-Sen estimator, and then mapped to show their spatial variability. Maps were generated for both mean SWHs and 95th percentile SWHs, the latter is considered to reflect the trends of the severe sea states. The basin-averaged analysis was also carried out to investigate the general tendency of SWHs in the Black Sea. The significance of the trends was evaluated by using Mann-Kendall test. The annual mean SWH is found to be increasing (up to 1.6%/year) in the eastern part of the Black Sea while the western part has a negative trend (down to −1.2%/year). Long-term analysis of the 95th percentile SWHs revealed steeper trend slopes and higher statistical significance compared to the mean SWH trends, showing that storm SWHs have a higher tendency to increase than the mean SWHs. Statistically significant correlations between climate indices; North Atlantic Oscillation (NAO), Arctic Oscillation (AO), Antarctic Oscillation (AAO), Atlantic Multidecadal Oscillation (AMO), Pacific North American (PNA), East Atlantic (EA), East Atlantic/West Russia (EA/WR), Scandinavia (SCAND), Niño3 and the Black Sea wave fields were identified. [ABSTRACT FROM AUTHOR]

Regional spatiotemporal assessments of temperature extremes are essential for accurate forecasting of future climate changes, agricultural production and the regulation of water resources. This study evaluates the characteristics of the spatiotemporal variations in temperature extremes from 1961 to 2016 in the Three River Headwaters (TRH) region and its surroundings in the northeastern portion of the Tibetan Plateau in China. The association of these variations with atmospheric circulation patterns is also investigated. This study selected twenty-six meteorological stations where <2% of the data are missing and where the data pass quality control and homogeneity tests. Following the Expert Team on Climate Change Detection and Indices (ETCCDI), thirteen extreme temperature indices and two mean temperature indices are analyzed using the Mann-Kendall test and Sen's test; the indices examined here include six warm indices, six cold indices, the diurnal temperature range (DTR) and the annual minimum and maximum temperatures. Pearson correlation analysis is also used to analyze the correlations between the temperature extremes and various atmospheric circulation patterns. The results indicate that the annual minimum and maximum temperatures display significant increasing trends, whereas the DTR displays a significant decreasing trend with a rate of −0.11 °C/decade. All of the regional warm indices display significant increasing trends. On the other hand, most of the cold indices show significant decreasing trends, except for the lowest daily minimum temperature (TNn) and the lowest daily maximum temperature (TXn), which show increasing trends. These results are consistent with the trends observed by most global-scale studies. In terms of spatial patterns, most of the stations that display significant trends are located in the central and northwestern portions of the TRH region. On the other hand, all of the extreme indices show weak correlations with altitude, with the exception of the DTR, which displays a significant negative correlation with altitude (P<0.01); moreover, most of the indices are weakly correlated with latitude and longitude. Overall, the winter Arctic Oscillation index (AO), the summer and winter North Atlantic Oscillation index (NAO), and the summer and winter Western Pacific Subtropical High Intensity Index (WPI) display significant relationships with most of the extreme temperature indices, and these circulation patterns contribute to changes in temperature extremes in this region. However, the Southern Oscillation Index (SOI) is not significantly correlated with most of the extreme temperature indices. [ABSTRACT FROM AUTHOR]

The objective on this study is to fully statistically determine and describe the rainfall regime characteristics of the very long precipitation records of 124-year period (1892–2015) in Thessaloniki and moreover to apply extreme value statistical methodologies to extreme daily rainfall information (period, 1931–2015), in order to define the extreme precipitation probability distributions. To meet these objectives, the observed annual, monthly and daily rainfall measurements obtained at the Meteorological Station of the Department of Meteorology and Climatology of the Aristotle University of Thessaloniki are used. The use of both Mann-Kendall test and moving average methods are used to determine the profile of the examined very long-period rainfall regime in Thessaloniki, on annual, seasonal, and monthly basis. Taking into consideration the climatic change effect upon precipitation regimes, the extreme daily rainfall measurements are statistically analyzed with extreme value statistical methodologies, defining thus the extreme precipitation probability distribution functions. The Taylor diagram analysis, through combinations of appropriate correlation coefficients, standard deviations, and root-mean-square differences, are constructed to statistically quantify the degrees of similarity between reference points (mean annual precipitation) and results on seasonal and agricultural ( agro -) seasonal basis. All the above tests are applied to detect possible changes in precipitation characteristics, over the study region, throughout the extreme long period of 124 years. The resulted probability distributions might potentially contribute to the prediction of extreme rainfall events, and be used for future climatic change projections. Moreover, based upon the resulted-adopted probability distributions, emerging from this extreme long study period, return periods for different extreme values of precipitation observed are calculated. [ABSTRACT FROM AUTHOR]

In the present study, we conducted a risk assessment of urban population exposure to ambient particles (PM 2.5 , PM 10), nitrogen dioxides (NO 2), and tropospheric ozone (O 3) in six Polish urban areas over the period 2015–2020. The main goals were to: i) evaluate the number of premature deaths attributed to ambient air pollutants, and to ii) assess the effectiveness of emissions control policies in reducing urban population exposure to air pollution, and thus related health effects. For that, we used air quality data from 15 urban monitoring stations and city-specific health data (relative risk values and baseline incidence). For all cities, the annual PM 2.5 , PM 10 , and NO 2 mean concentrations exceeded the 2021 World Health Organization Air Quality Guidelines in 2015–2020. In all cities, the annual PM 2.5 (- 0.5% to - 6.1% year−1), PM 10 (- 1.6 to - 8.1% year−1), and NO 2 (- 1.3% to - 4.5% year−1) mean concentrations declined over time, while O 3 levels rose (+1.0% to + 4.2% year−1). Exposure to ambient PM 2.5 , PM 10 , NO 2 , and O 3 has substantially contributed to mortality in the six studied cities: a total of 6700 deaths for non-accidental causes, 2310 deaths for cardiovascular diseases, and 500 deaths for respiratory diseases were reported. Between 2015 and 2020, the number of annual PM 2.5 -, PM 10 -, and NO 2 -related premature deaths decreased (respectively, by - 8.4, - 6.7, and - 2.1 deaths per 106 inhabitants) in line with cleaner air. The rising O 3 levels led to an increase in annual O 3 -related premature deaths (+1.3 deaths per 106 inhabitants) over time. A major concern is related to the overrun of exposure metrics compared to the target values for human health. To date, human health is mainly threatened by PM 2.5 and O 3 , particularly in Southern Poland. • Risk assessment of urban population exposure to main air pollutants in Poland in 2015–2020. • PM 2.5 , PM 10 , and NO 2 mean concentrations declined while O 3 levels rose. • About 6700 premature deaths are attributed to air pollution in 2015–2020. • PM 2.5 -, PM 10 -, and NO 2 -related deaths declined: 8.4, - 6.7, - 2.1 deaths per 106 people. • Rising annual O 3 -related number of premature deaths: +1.3 deaths per 106 people. [ABSTRACT FROM AUTHOR]

Severe defoliation of mangrove species is reported in several parts of the world. We analyzed the effect of a severe defoliation event resulting from the attack of a lepidopteran caterpillar (an insect outbreak) on the litterfall production. The attack occurred between 2009 and 2010 in a mangrove in southeastern Brazil. Leaf litter production by different mangrove species between 2008 and 2019, was considered in the analysis. The infestation directly affected the species Avicennia schaueriana Stapf & Leechm in all physiographic types assessed, with a decrease in leaf litter production between 43% and 86% since the monitoring began (2009) until the year when defoliation reached the maximum (2011). A decrease in the impact of defoliation was observed along the tidal flooding gradient, with more pronounced effects in forests located in the transition zone with the salt-flat, and progressive decrease towards fringe forests. In fringe and basin forests, leaf litter production by Laguncularia racemosa (L.) decreased between 52% and 67% between 2009 and 2011, respectively, and increased 30% in transition forests. Contrarily, the contribution of Rhizophora mangle (L.) increased 7% in basin, became noticeable in transition, and decreased by 25% in the fringe forests. The time required for A. schaueriana to recover the level of debris production was 8 years, and still reflect the effect of the severe, selective defoliation process on the dynamics and ecological succession of mangrove forests. A model that determines the stages of defoliation and their direct and indirect impacts on litter was developed. • The Insect infestation directly affected the species Avicennia schaueriana. • Losses varied between 43% and 96% of the leaf litter production. • The level of impact of the infestation was dependent on the physiographic types. • Herbivory may change facilitative or competitive processes in mangrove systems. [ABSTRACT FROM AUTHOR]

This paper aims at providing a descriptive view of the low-frequency sea-level changes around the northern Australian coastline. Twenty years of sea-level observations from multi-mission satellite altimetry and tide gauges are used to characterize sea-level trends and inter-annual variability over the study region. The results show that the interannual sea-level fingerprint in the northern Australian coastline is closely related to El Niño Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO) events, with the greatest influence on the Gulf Carpentaria, Arafura Sea, and the Timor Sea. The basin average of 14 tide-gauge time series is in strong agreement with the basin average of the altimeter data, with a root mean square difference of 18 mm and a correlation coefficient of 0.95. The rate of the sea-level trend over the altimetry period (6.3 ± 1.4 mm/yr) estimated from tide gauges is slightly higher than that (6.1 ± 1.3 mm/yr) from altimetry in the time interval 1993–2013, which can vary with the length of the time interval. Here we provide new insights into examining the significance of sea-level trends by applying the non-parametric Mann-Kendall test. This test is applied to assess if the trends are significant (upward or downward). Apart from a positive rate of sea-level trends are not statistically significant in this region due to the effects of natural variability. The findings suggest that altimetric trends are not significant along the coasts and some parts of the Gulf Carpentaria (14°S-8°S), where geophysical corrections (e.g., ocean tides) cannot be estimated accurately and altimeter measurements are contaminated by reflections from the land. [ABSTRACT FROM AUTHOR]

The study on runoff series variation is of great significance for the development and utilization of water resources in a river basin. In this paper, runoff series data from the Three Gorges reservoir and five upstream catchments observed from 1951 to 2013 are used to analyze the changes in the Three Gorges reservoir inflow series via the Mann–Kendall test. Based on the hydro-metrological data (i.e. precipitation, and temperature) and the human activities data (i.e. urbanization percentage, effective irrigation area, afforestation area, population, and gross domestic product (GDP)) during the same period, the back-propagation artificial neutral network (BP-ANN) model is applied to quantify the influence of the driving factors. The results show: (1) During the study period, there is a significant decrease in the Three Gorges reservoir inflow and the reduction rate is 0.73 mm per year; (2) Runoff from all of the five upstream catchments of the Three Gorges reservoir decrease. Specifically, the decreased trends in the runoff from the Mintuo River catchment and the Jialing River catchment are statistical significant; (3) Impacts of climate change and human activities on changes in the Three Gorges reservoir inflow series account for 36% and 64%, respectively. Among all the driving factors, the precipitation is the dominant influencing factor, accounting for the relative contribution of 25%. The temperature, urbanization percentage, effective irrigation area, population and GDP are the minor factors, accounting for the relative contributions of 11%, 17%, 15%, 15% and 14%, respectively. The afforestation area is the least effective factor with a relative contribution of 3%. [ABSTRACT FROM AUTHOR]

As abundant distribution of glaciers and snow, the Tianshan Mountains are highly vulnerable to changes in climate. Based on meteorological station records during 1960–2016, we detected the variations of air temperature and precipitation by using non-parametric method in the different sub-regions and different elevations of the Tianshan Mountains. The mutations of climate were investigated by Mann-Kendall abrupt change test in the sub-regions. The periodicity is examined by wavelet analysis employing a chi-square test and detecting significant time sections. The results show that the Tianshan Mountains experienced an overall rapid warming and wetting during study period, with average warming rate of 0.32 °C/10a and wet rate of 5.82 mm/10a, respectively. The annual and seasonal spatial variation of temperature showed different scales in different regions. The annual precipitation showed non-significant upward trend in 20 stations, and 6 stations showed a significant upward trend. The temperatures in the East Tianshan increased most rapidly at rates of 0.41 °C/10a. The increasing magnitudes of annual precipitation were highest in the Boertala Vally (8.07 mm/10a) and lowest in the East Tianshan (2.64 mm/10a). The greatest and weakest warming was below 500 m (0.42 °C/10a) and elevation of 1000–1500 m (0.23 °C/10a), respectively. The increasing magnitudes of annual precipitation were highest in the elevation of 1500 m–2000 m (9.22 mm/10a) and lowest in the elevation of below 500 m (3.45 mm/10a). The mutations of annual air temperature and precipitation occurred in 1995 and 1990, respectively. The large atmospheric circulation influenced on the mutations of climate. The significant periods of air temperature were 2.4–4.1 years, and annual precipitation was 2.5–7.4 years. Elevation dependency of temperature trend magnitude was not evidently in the Tianshan Mountains. The annual precipitation wetting trend was amplified with elevation in summer and autumn. The strong elevation dependence of precipitation increasing trend appeared in summer. [ABSTRACT FROM AUTHOR]

The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916–2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear. [ABSTRACT FROM AUTHOR]

In this study, the long-term variability and trends of the annual and seasonal numbers of summer and tropical days of the Adana Sub-region were investigated using nonlinear and linear trend detection tests for the period 1960–2014 at 14 meteorological stations. The results suggest that the annual number of summer and tropical days was generally below the long-term average through to the end of the 1980s. In particular, positive anomaly values could be observed at all stations between the years 1993–2014. With respect to the Kruskal-Wallis homogeneity test, the significant breaking date was 1993. The rapid rise of the annual number of summer (tropical) days after this year led to the inversion of the negative trends observed from 1987 to 1992 into positive ones. The increasing trend is statistically significance at 0.01 level in Yumurtalık, Mersin and Antakya for the annual number of summer and tropical days. Dörtyol, İskenderun and Elbistan were significance at 0.01 level for tropical days. The largest positive anomalies of the summer of 2010 are observed in coastal vicinity (Mersin, Yumurtalık and İskenderun). This indicates that these settlements underwent a long-term warm period and thermal conditions due to increasing temperatures in the spring and summer months. The same conditions are found in high inner areas (Göksun and Elbistan) for tropical days. It is noticed that a tendency for greater warming occurred at stations located above 1000 m in the sub-region. The average number of warm days will increase 2-days per 100-years in southern part of the sub-region. The increasing trend in summer temperatures can be considered a potential risk, notably for human health and for economic and crop losses in the Adana Sub-region, including Çukurova, one of the most important agriculture areas of Turkey. [ABSTRACT FROM AUTHOR]

The main source of electricity in Brazil is from hydro, which has about 65.2% share of the country’s electric energy matrix. However, over the last decade the wind energy increased from 19 MW to 2.2 GW. Since wind is an intermittent energy source, heavily determined by the weather and climatic conditions, and important effects on wind power generation can be expected in the mid and long term, in particular related to the impacts of extreme winds. The IPCC AR5 (Intergovernmental Panel on Climate Change) indicates changes in wind speed at the surface in some regions of the world, and increased wind strength in mid-latitude regions. This study scrutinizes future scenarios of extreme winds in Brazil by applying trend analysis techniques on a 50-year historical series of observational wind speed and meteorological parameters at 10 m height in Brazil. Embracing techniques of cluster analysis it was possible to characterize six main regions with macro climatic similarities. To assess the goodness fit distribution, we designate two stations per homogenous region, taking as criteria the stations with better performance in the qualification process to determine the wind distribution pattern in each region applying the Kolmogorov-Smirnov test (KS) and the lowest standard error (SE). After evaluating the frequency distribution of wind speed, the best fit result for the frequency distribution of maximum wind speed is the Gumbel model. The analysis of climatic trends performed by Mann-Kendall test revealed that in minimum wind speed series is not conclusive because it shows disparate results between homogeneous regions. On the other hand, the analysis of climatic trends of maximum wind speed presents 100% positive trends in Group#1, an equal number of stations with not significant trends and positive trends for Group#2, 36.8% more stations with positive trends than negative trends for Group#3 and 20% of stations with more negative trends than stations with positive trends for Group#4. This way, based in these results, is possible assert that there are an increase in the maximum extreme wind in Brazil, mainly in mid-latitudes. [ABSTRACT FROM AUTHOR]

A bibliometric analysis of low carbon related publications is reported in this study in order to depict existing research activities and to identify future directions in this research field. These publications were retrieved from various databases such as: Science Citation Index (SCI), Social Science Citation Index (SSCI), Conference proceedings Citation Index-Science (CPCI-S) and Conference Proceedings Citation Index-Social Science & Humanities (CPCI-SSH). There is a notable growth associated with the body of knowledge on low carbon research. A total of 5445 records were obtained from these four major academic databases. Journal articles and proceedings papers are two frequently used document types representing 93.24% (5077 records) of the records and English is the dominant language with 5250 records (96.42%). The most productive subject is Energy & Fuels (1282 records) and the most productive journal is Energy Policy (313 records). China has largest number of publications related to low carbon. However, the USA accounts for the highest H-index (50). The Chinese Academic of Science is the organization with the most records (100 records) and the highest H-index (15). Four clusters are identified according to the analysis of co-occurrence keywords. Topics from Cluster (I) (central nodes as “climate change” and “renewable energy”) are still vital to the low carbon research. However, their relative popularities declined over the past decade compared to other topics. This indicates more diverse topics from Cluster (II) (central nodes as “low carbon economy”), Clusters (III) (central nodes focusing on “low carbon”, “energy” and “sustainability”), and Cluster (IV) (central node as “smart grid” interrelate with Cluster (I)) will be foci of future research endeavor in the coming decade. [ABSTRACT FROM AUTHOR]

In this study, seasonal trends as well as dominant and significant periods of variability of drought variables were analyzed for 30 rainfall subdivisions in India over 141 years (1871–2012). Standardized precipitation index (SPI) was used as a meteorological drought indicator, and various drought variables (monsoon SPI, non-monsoon SPI, yearly SPI, annual drought duration, annual drought severity and annual drought peak) were analyzed. Discrete wavelet transform was used in conjunction with the Mann-Kendall test to analyze trends and dominant periodicities associated with the drought variables. Furthermore, continuous wavelet transform (CWT) based global wavelet spectrum was used to analyze significant periods of variability associated with the drought variables. From the trend analysis, we observed that over the second half of the 20th century, drought occurrences increased significantly in subdivisions of Northeast and Central India. In both short-term (2–8 years) and decadal (16–32 years) periodicities, the drought variables were found to influence the trend. However, CWT analysis indicated that the dominant periodic components were not significant for most of the geographical subdivisions. Although inter-annual and inter-decadal periodic components play an important role, they may not completely explain the variability associated with the drought variables across the country. [ABSTRACT FROM AUTHOR]

The long-distance effect of atmospheric pollution on ecosystems has led to the conclusion of international agreements to regulate atmospheric emissions and monitor their impact. This study investigated variations in atmospheric deposition chemistry in France using data gathered from three different monitoring networks (37 stations) over the period from 1995 to 2007. Despite some methodological differences ( e.g. type of collector, frequency of sampling and analysis), converging results were found in spatial variations, seasonal patterns and temporal trends. With regard to spatial variations, the mean annual pH in particular ranged from 4.9 in the north-east to 5.8 in the south-east. This gradient was related to the concentration of NO 3 − and non-sea-salt SO 4 2− (maximum volume-weighted mean of 38 and 31 μeq l −1 respectively) and of acid-neutralising compounds such as non-sea-salt Ca 2+ and NH 4 + . In terms of seasonal variations, winter and autumn pH were linked to lower acidity neutralisation than during the warm season. The temporal trends in atmospheric deposition varied depending on the chemical species and site location. The most significant and widespread trend was the decrease in non-sea-salt SO 4 2− concentrations (significant at 65% of the stations). At the same time, many stations showed an increasing trend in annual pH (+0.3 on average for 16 stations). These two trends are probably due to the reduction in SO 2 emissions that has been imposed in Europe since the 1980s. Temporal trends in inorganic N concentrations were rather moderate and not consistent with the trends reported in emission estimates. Despite the reduction in NOx emissions, NO 3 − concentrations in atmospheric deposition remained mostly unchanged or even increased at three stations (+0.43 μeq l −1 yr −1 on average). In contrast NH 4 + concentrations in atmospheric deposition decreased at several stations located in western and northern areas, while the estimates of NH 3 emissions remained fairly stable. The decrease in non-sea-salt SO 4 2− and NH 4 + concentrations was mainly due to a decrease in summer values and can in part be related to a dilution process since the precipitation amount showed an increasing trend during the summer. Furthermore, increasing trends in NO 3 − concentrations in the spring and, to a lesser extent, in NH 4 + concentrations suggested that other atmospheric physicochemical processes should also be taken into account. [ABSTRACT FROM AUTHOR]

With the ensemble Empirical Mode Decomposition Method (EEMD) and the non-parametric Mann-Kendall Test, the quasi-periodic and abrupt changes of sedimentation rate at multiple time scales, and their relations to climate changes and human activities from 1951 to 2010 in Meiliang Bay of Lake Taihu (China) were studied. The results showed the following. (1) The change in sedimentation rate can be completely decomposed into three quasi-periodic changes on 3.7, 6.4, and 24-yr time scales, and a long-term trend. (2) The quasi-periodic changes in sedimentation rate are significantly and positively related to changes in annual average temperature at 6.4 and 24-yr time scales and human activities at 3.7-yr time scales, and not significantly related to precipitation at these time scales. The trend of sedimentation rate has a negative relation with temperature, but positive relations with precipitation and human activities. As a whole, the total variance contribution of climate changes to the quasi-periodic changes of sedimentation rate is close to that of human activities; (3) Temperature and precipitation are possibly related to the abrupt change of sedimentation rate as a whole. Floods have significant impacts on abrupt changes in the sedimentation rate at 3.7, 6.4 and 24-yr time scales. Moreover, some abrupt changes of sedimentation rate at 3.7- and 6.4-yr time scales are partly related to the changes of precipitation at 3.1-yr time scale and temperature at 5-yr time scale. The results of this study will help identify the impacts of climate change and human activities on lake sedimentation at different time scales, and will be available for use as a guide for reasonable development and effective protection of lake resources. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate 50 years (1964–2013) of seasonal and annual rainfall trends and their fluctuation over time in northern Bangladesh. After testing the autocorrelation, non-parametric Mann–Kendall test along with Sen Slope estimator was used to examine rainfall trends and their magnitudes. The sequential Mann–Kendall test was used to identify any fluctuations in the trends over time and to detect the possible points of change in the rainfall series. We found that pre-monsoon and post-monsoon rainfall is increasing in most of the rainfall stations. The only decrement in pre-monsoon rainfall was found for Ishurdi (1.28 mm/year). However, the sequential Mann–Kendall test detected decreasing pre-monsoon rainfall trend after early the 1990s. Monsoon rainfall showed a decreasing trend in the majority of the area studied. The maximum decrement in monsoon rainfall was found for Sylhet station (8.10 mm/year) and minimum in Mymensingh (1.53 mm/year). An upward monsoon rainfall trend was found for Rangpur (2.02 mm/year). Annual rainfall followed the monsoon rainfall trend. However, all of the positive and negative trends were found statistically non-significant at 95% confidence limit with the only exception for monsoon and annual rainfall at Rajshahi station. Rajshahi station was the only region where the monsoon and annual rainfall has a significant negative trend at 95% confidence limit. The sequential Mann–Kendall test detected several non-significant points of change for seasonal and annual rainfall at most of the stations. Periodic fluctuations were also detected. We observed that there were decreasing seasonal rainfall trend after early the 1990s for the majority of the stations. [ABSTRACT FROM AUTHOR]

[Display omitted] • The measurement errors in long-time series remote sensing images are corrected by statistical and spatio-temporal prediction model. • The ecological degradation of the Miyun Reservoir basin from 1985 to 2021 is mainly caused by anthropogenic factors. • Through statistical theory, the ecological development trend in the experimental area is analyzed, and the conclusion is verified by land use evolution. Miyun Reservoir, located in the Miyun District, Beijing, China, is the largest comprehensive water conservancy project and is an important ecological protection area in the North China region. Changes within the basin are the driving factors affecting the ecosystem in the watershed; therefore, it is important to analyze the changes in the ecological environment of Miyun Reservoir. For the analysis of a long time series of image data remotely sensed by satellite, the outliers caused by atmospheric, lighting, and sensor measurement errors are significant, and it is difficult for traditional algorithms to effectively recover the true image value. To address this, this paper proposes a theoretical model for predicting spatio-temporal variation based on deep learning to identify and correct invalid and anomalous values in extended time series data. This study corrected and analyzed the results of Remote Sensing based Ecological Index inversion of Landsat data of the Miyun Reservoir watershed from 1985 to 2021. The findings and conclusions of this study are important for the analysis of long time series image data from satellite remote sensing and for improving regional ecological evaluation and sustainable development planning. [ABSTRACT FROM AUTHOR]

Forest canopy structural complexity (CSC) describes the three-dimensional (3D) arrangement of canopy elements, and has become an emergent forest attribute mediating forest ecosystem functioning along with species diversity. Light detection and ranging (lidar), especially the emerging near-surface lidar platforms (e.g., terrestrial laser scanning/TLS, backpack laser scanning/BLS, unmanned aerial vehicle laser scanning/ULS), can depict 3D canopy information with high efficiency and accuracy, providing an ideal data source for forest CSC quantification. However, current existing lidar-based CSC quantification indices may share common limitations of getting saturated in structurally complex forest stands and not fully capturing within-canopy structural variations. In this study, we introduced the concept of entropy into forest CSC quantification, and proposed a new forest CSC index, namely canopy entropy (CE). Two major bottlenecks were addressed in the CE calculation procedure, including (1) using a Mann-Kendall (MK) test-based resampling strategy to address the issue of incongruent sampling chances of canopy elements at different locations from different lidar systems, and (2) using a kernel density estimation (KDE)-based method to reduce its dependence on point density. The effectiveness and generality of CE were evaluated by simulating TLS and ULS point clouds from nine forest stands and collecting TLS, BLS, and ULS point clouds from 110 field plots distributed in five forest sites, covering a large variety of forest types and forest CSC conditions. The results showed that CE was an effective forest CSC quantification index that successfully captured CSC variations caused by both tree density and the number of vertical canopy layers. It had significant positive correlations with four widely used CSC indices (i.e., canopy cover, foliage height diversity, canopy top rugosity, and fractal dimension; R 2: 0.32 to 0.67), but outperformed them by overcoming their common limitations. CE estimates from multiplatform lidar point clouds agreed well with each other (R 2 ≥ 0.70, RMSE ≤0.10), indicating it has generality in cross-platform forest CSC quantification practices. We believe the proposed CE index has great potential to help us unravel the correlations among forest CSC, species diversity, and forest ecosystem functions, and therefore improve our understanding on forest ecosystem processes. • Proposed a novel canopy structural complexity (CSC) index, canopy entropy (CE). • Collected multiplatform lidar point clouds in 110 plots with large CSC variations. • CE captured forest CSC changes caused by tree density and vertical canopy layering. • CE outperformed four widely used existing indices in forest CSC quantification. • CE estimates from multiplatform lidar point clouds were comparable to each other. [ABSTRACT FROM AUTHOR]

• Two annual PC indices, CID year and CIM year , have an obviously positive correlation. • Downward trend of CID year / CIM year becomes more distinct from southwest to northeast. • Winter/autumn PC is higher and more variable than spring/summer PC in the HRB. • PC of the HRB is negatively affected by ENSO/PDO with distinct spatial patterns. • ENSO has more pronounced negative effects on seasonal PCs of the HRB compared to PDO. Investigating precipitation concentration (PC) is significant for a deeper understanding of the formation of floods and droughts. Taking a Chinese region, Huaihe River basin (HRB), as the study area, this study analyzed the spatial and temporal variations of annual/seasonal PCs and their teleconnections with El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Specifically, the daily and monthly precipitation data are employed to build two annual indices (CID year and CIM year) and four seasonal PC indices. The modified Mann-Kendall test is used to identify the significant trends of PC indices. Besides, the correlation test and cross wavelet transform are used to examine the relationship between CID year and CIM year , the spatiotemporal characteristics of PC indices, and the teleconnections of PC indices with ENSO and PDO. The results show that (1) CID year has a significantly positive correlation with CIM year , and shows a dominate downward trend across the HRB; (2) the precipitation temporal distribution in winter and autumn is more variable and more irregular than that in spring and summer at the HRB; (3) the annual and seasonal precipitation temporal distribution of the HRB become more variable and more irregular with increasing latitude, and the downward trends of CID year and CIM year tend to be more significant with increasing latitude and longitude; (4) ENSO and PDO have potentially negative effects on the annual and seasonal PCs of HRB, and their negative impacts on the annual PC significantly strengthen from south to north in the HRB; and (5) Compared with PDO, ENSO has more pronounced negative impacts on seasonal PCs of the HRB, and its negative impacts on summer PC and winter PC decrease and increase from west to east of HRB, respectively. These findings could provide a new perspective for understanding regional precipitation temporal distribution. [ABSTRACT FROM AUTHOR]

The Regional Comprehensive Economic Partnership (RCEP) agreement signed in November 2020 is the world's largest and greatest potential free trade area. It was officially enforced on January 1, 2022, which attracted great worldwide attention. The RCEP advocates for the development of the low-carbon economy but lacks effective monitoring methods for socioeconomic conditions and carbon emissions. Nighttime light (NTL) images can objectively reflect socioeconomic status and carbon emission potential. However, most studies focused only on consistency correction for multi-source NTL data without deeply analyzing NTL dynamics. An in-depth analysis of the NTL change in the RCEP region is necessary and will strongly facilitate the strategic deployment of a low-carbon economy in RCEP countries. Sen's slope estimator, the Mann-Kendall trend test, the Mann-Kendall mutation test, and Hurst analysis were adopted to analyze the spatiotemporal changes of NTL in the past and future, and gray relational analysis was applied to explore driving factors. The results showed that (1) RCEP's NTL became brighter from 2000 to 2018, and the total NTL amount in 2018 was 3.27 times that in 2000. NTL in all countries except Japan showed an increasing trend to varying degrees, and this trend was more pronounced in developing countries. The maximum increase amount and growth rate were in China and Vietnam, respectively. (2) Areas where NTL showed an increasing trend in the past accounted for 76.67% of the NTL zones, and the areas where predicted to be brighter in the future accounted for 63.87%. These regions were generally clustered in developed urban zones. However, most Japanese cities have observed darkening trends. (3) The relational grade between NTL and all socioeconomic factors in the RECP region was greater than 0.6, and construction land expansion was the most direct and profound driver. Compared with that in developed countries, NTL in developing countries was more closely related to socioeconomic factors. Spatiotemporal Changes and Driving Factors in Nighttime Light for the RCEP Region. [Display omitted] • Nighttime light (NTL) in the RCEP region became brighter from 2000 to 2018. • NTL in developed cities increased significantly and is expected to be brighter. • China led the lighting trend, while Japan's NTL declined. • Construction land expansion was the dominant driver of NTL changes in RCEP region. • Socioeconomic factors in developing countries more strongly promoted NTL increases. [ABSTRACT FROM AUTHOR]

Summary The variation characteristics of precipitation and temperature in the three major Chinese river basins (Yellow River, Yangtze River and Pearl River) in the period of 1957–2013 were analyzed on an annual and seasonal basis, as well as their links to sea surface temperature (SST) variations in the tropical Pacific and Indian Ocean on both interannual and decadal time scales. Annual mean temperature of the three river basins increased significantly overall since 1957, with an average warming rate of about 0.19 °C/10a, but the warming was characterized by a staircase form with steps around 1987 and 1998. The significant increase of annual mean temperature could mostly be attributed to the remarkable warming trend in spring, autumn and winter. Warming rates in the northern basins were generally much higher than in the southern basins. However, both the annual precipitation and seasonal mean precipitation of the three river basins showed little change in the study area average, but distinct interannual variations since 1957 and clear regional differences. An overall warming–wetting tendency was found in the northwestern and southeastern river basins in 1957–2013, while the central regions tended to become warmer and drier. Results from a Maximum Covariance Analysis (MCA) showed that the interannual variations of seasonal mean precipitation and surface air temperature over the three river basins were both associated with the El Niño-Southern Oscillation (ENSO) since 1957. ENSO SST patterns affected precipitation and surface air temperature variability throughout the year, but with very different response patterns in the different seasons. For instance, temperature in most of the river basins was positively correlated with central-eastern equatorial Pacific SST in winter and spring, but negatively correlated in summer and autumn. On the decadal time scale, the seasonal mean precipitation and surface air temperature variations were strongly associated with the Pacific Quasi-Decadal Oscillation. [ABSTRACT FROM AUTHOR]

The aim of software reliability prediction is to estimate future occurrences of software failures to aid in maintenance and replacement. Relevance vector machines (RVMs) are kernel-based learning methods that have been successfully adopted for regression problems. However, they have not been widely explored for use in reliability applications. This study employs a RVM-based model for software reliability prediction so as to capture the inner correlation between software failure time data and the nearest m failure time data. We present a comparative analysis in order to evaluate the RVMs effectiveness in forecasting time-to-failure for software products. In addition, we use the Mann-Kendall test method to explore the trend of predictive accuracy as m varies. The reasonable value range of m is achieved through paired T -tests in 10 frequently used failure datasets from real software projects. [ABSTRACT FROM AUTHOR]

Summary This paper, the second of a two-part paper, investigates the nonstationary behaviour of flood peaks in Quebec (Canada) by analyzing the annual maximum flow series (AMS) available for the common 1966–2001 period from a network of 32 watersheds. Temporal trends in the mean of flood peaks were examined by the nonparametric Mann–Kendall test. The significance of the detected trends over the whole province is also assessed by a bootstrap test that preserves the cross-correlation structure of the network. Furthermore, The LM–NS method (introduced in the first part) is used to parametrically model the AMS, investigating its applicability to real data, to account for temporal trends in the moments of the time series. In this study two probability distributions (GEV & Gumbel) were selected to model four different types of time-varying moments of the historical time series considered, comprising eight competing models. The selected models are: two stationary models (GEV0 & Gumbel0), two nonstationary models in the mean as a linear function of time (GEV1 & Gumbel1), two nonstationary models in the mean as a parabolic function of time (GEV2 & Gumbel2), and two nonstationary models in the mean and the log standard deviation as linear functions of time (GEV11 & Gumbel11). The eight models were applied to flood data available for each watershed and their performance was compared to identify the best model for each location. The comparative methodology involves two phases: (1) a descriptive ability based on likelihood-based optimality criteria such as the Bayesian Information Criterion (BIC) and the deviance statistic; and (2) a predictive ability based on the residual bootstrap. According to the Mann–Kendall test and the LM–NS method, a quarter of the analyzed stations show significant trends in the AMS. All of the significant trends are negative, indicating decreasing flood magnitudes in Quebec. It was found that the LM–NS method could provide accurate flood estimates in the context of nonstationarity. The results have indicated the importance of taking into consideration the nonstationary behaviour of the flood series in order to improve the quality of flood estimation. The results also provided a general impression on the possible impacts of climate change on flood estimation in the Quebec province. [ABSTRACT FROM AUTHOR]

Summary Cold region hydrological systems exhibit complex interactions with both climate and the cryosphere. Improving knowledge on that complexity is essential to determine drivers of extreme events and to predict changes under altered climate conditions. This is particularly true for cold region flooding where independent shifts in both precipitation and temperature can have significant influence on high flows. This study explores changes in the magnitude and the timing of streamflow in 18 Swedish Sub-Arctic catchments over their full record periods available and a common period (1990–2013). The Mann–Kendall trend test was used to estimate changes in several hydrological signatures (e.g. annual maximum daily flow, mean summer flow, snowmelt onset). Further, trends in the flood frequency were determined by fitting an extreme value type I (Gumbel) distribution to test selected flood percentiles for stationarity using a generalized least squares regression approach. Results highlight shifts from snowmelt-dominated to rainfall-dominated flow regimes with all significant trends (at the 5% significance level) pointing toward (1) lower magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest widespread permafrost thawing and are supported by increasing trends in annual minimum daily flows. Trends in selected flood percentiles showed an increase in extreme events over the full periods of record (significant for only four catchments), while trends were variable over the common period of data among the catchments. An uncertainty analysis emphasizes that the observed trends are highly sensitive to the period of record considered. As such, no clear overall regional hydrological response pattern could be determined suggesting that catchment response to regionally consistent changes in climatic drivers is strongly influenced by their physical characteristics. [ABSTRACT FROM AUTHOR]

The principle of maximum entropy can provide consistent basis to analyze water resources and geophysical processes in general. In this paper, we propose to assess the space-time variability of rainfall and streamflow in northeastern region of Brazil using the Shannon entropy. Mean values of marginal and relative entropies were computed for a 10-year period from 189 stations in the study area and entropy maps were then constructed for delineating annual and seasonal characteristics of rainfall and streamflow. The Mann–Kendall test was used to evaluate the long-term trend in marginal entropy as well as relative entropy for two sample stations. High degree of similarity was found between rainfall and streamflow, particularly during dry season. Both rainfall and streamflow variability can satisfactorily be obtained in terms of marginal entropy as a comprehensive measure of the regional uncertainty of these hydrological events. The Shannon entropy produced spatial patterns which led to a better understanding of rainfall and streamflow characteristics throughout the northeastern region of Brazil. The total relative entropy indicated that rainfall and streamflow carried the same information content at annual and rainy season time scales. [ABSTRACT FROM AUTHOR]

In this paper, the Mann–Kendall test and F-test were combined to analyze the annual and seasonal streamflow variations and aberrance points for the twin rivers from 1963 to 2011. The Tennant method was subsequently used to evaluate the ecological flow assurance and deficit. Finally, the Double Mass Curve method was applied to identifying the human activities affecting the streamflow variations. The results were as follows: (1) Three similar stages of the streamflow variations were found for the twin rivers: fluctuations before 1980, the tiny downward trends from the 1980s to the 1990s, and the notably downward trends in the 2000s. (2) The seasonal streamflow also decreased continuously and dramatically, especially in summer, by 80.9% for the Chaohe River and 86.0% for the Baihe River. (3) During the spawning season, 83.3% and 73.1% of streamflow was not at the appropriate level for the Chaohe and Baihe Rivers, respectively, which indicated that the ecological environment was not optimal for the reproduction and breeding of aquatic organisms. While in other periods, the ecological flow assurance was better than that in spawning seasons for the Chaohe and Baihe Rivers, respectively. This indicated that the streamflow regimes of the twin rivers were not always optimal and conducive to the development of the aquatic ecosystem. (4) The streamflow variations of the twin rivers were influenced by increasingly intensive human activities such as changes of land use and land cover, and excessive exploitation and utilization of water resources. These influences were cumulative and showed a gradually increasing tendency. This research is helpful for understanding the streamflow regime and for forecasting of the regional extreme climate, such as drought and floods, and can provide a basis for decision making and formulating adaptive ecological security countermeasures in response to climate changes and human activities. [ABSTRACT FROM AUTHOR]

During the pre-monsoon season in the Eastern and North-eastern Indian regions, thunderstorms are the primary source of precipitation. The intensity and frequency of these thunderstorms are changing over time in these areas. The knowledge of atmospheric instability associated with these pre-monsoon thunderstorms can be aptly collected using thermodynamic indices. Thermodynamic indices integrate the comprehending convective atmosphere's geographical and temporal interpretation and are crucial in thunderstorm nowcasting. The present work investigated the spatial variation of thermodynamic indices for 1987–2016 over two tropical north-eastern states of India (Assam and Tripura) using the ERA-5 reanalysis data with 0.25° × 0.25° (31 km) resolution. The analysis incorporated information on thunderstorm days (TD) and non-thunderstorm days (NTD) provided by the India Meteorological Department (IMD) for differentiating the spatial variations of thermodynamic indices. The thermodynamic indices used in this work are categorised as conditional, potential, and convective instabilities. The results reveal that indices associated with convective and potential instabilities perform better for differentiating thunderstorms. We have incorporated the Man-Kendall trend analysis to investigate the trends in the spatial variation of thermodynamic indices. The results indicate that the region is showing higher instability for thunderstorm occurrences on TD, and there is higher moisture availability for the area during the whole pre-monsoon season. The inhibition is higher over NTD days, limiting the convective activity occurrence on certain days. The severity of thunderstorms as analysed with the help of thermodynamic indices are not changing over the region. • Thermodynamic indices maps have been generated over Tripura and Assam, India, for pre-monsoon. • The difference has been observed in thermodynamical variations during thunderstorms for 1987–2016. • The conditional/convective instability indices differentiate thunderstorms and clear days. • Climate change impact is visible as the threshold values are changing over the years for the study. [ABSTRACT FROM AUTHOR]

Summary Understanding the variation regularity of water level and the potential drivers can provide insights into lake conservation and management. In this study, inter- and inner-annual variations of water level in Dongting Lake during the period of 1961–2010 were analyzed to determine whether anthropogenic or climatic factor should be responsible for the variations. The results showed that water level decreased significantly during the period of 1961–1980, while increased significantly during the period of 1981–2002 at the 5% significance level. However, the variation trend of water level after 2002 did not reach a significant level. The variation in the dry season was more obviously than that in the wet season. The date when water level was firstly below 24 m during the period of 2003–2010 appeared about 27 days earlier than usual, and the date was even advanced to mid-September in 2006. As for the duration, water level was below 24 m for about 185 days in the period of 2003–2010 and 20–30 days longer than the other two periods. In conclusion, water level might be influenced by a combination of anthropogenic and climatic factors, with rainfall probably as the main driver responsible for hydrological alteration during the period of 1961–1980 and 1981–2002 while dam construction as the main driver during the period of 2003–2010. Under the circumstance of uncontrollable climate change, effective measures for reservoir operation should be put forward to maintain the ecological integrity and ensure water release and storage capacity of aquatic ecosystems. [ABSTRACT FROM AUTHOR]

The radiological environment around Wolsong NPP site has been monitored since Wolsong Unit 1 started commercial operation in 1983, as required by regulations in Korea. As a result of the periodic safety review on Wolsong Unit 3 & 4 in 2011, the regulator recommended that an assessment on the long-term accumulation trend of environmental radioactivity around Wolsong Unit 3 & 4 should be performed. In response to this, the assessment was performed based on environmental monitoring data and non-parametric statistical tool (i.e., Mann–Kendall Test). The environmental monitoring data included indicator organisms, soil and marine deposit which were usually monitored for verification of the typical radioactivity level. Most results of the assessment showed no trend and only a few results showed a slight increase. It was concluded that the radioactivity accumulation due to the operation of the plant was insignificant and thus no concern has been raised regarding any effect on the safety and health of the residents around Wolsong NPP site. It is expected that the result of this study could be utilized to establish the plan and policy for environmental monitoring at other NPP sites. [ABSTRACT FROM AUTHOR]

Several studies have shown that the stream water quality in agricultural catchments could vary according to the changes in land use, production intensities and implemented agri-environmental measures. In present study we investigated the nitrogen content and temporal dynamics in concentration and loss in small streams and catchments in Estonia for the period 1992–2011. The studied catchments represent various agricultural production areas, management practices, soil types, geology and size. A statistical analysis using the Mann Kendall (MK) test was undertaken to discern monotone trends in time series of total nitrogen (TN) and nitrate nitrogen (NO 3 –N) concentrations for 8 sampling sites and TN loss for five sites, for which at least a data set of 10 years was available. Additionally the partial Mann–Kendall (PMK) test has been adapted to account for the influence of water discharge to the temporal trends in TN loss in five catchments. The MK trend test revealed one statistically significant ( p < 0.05; two-sided test) upward trend in TN concentrations and two upward trends in NO 3 –N concentrations. Less significant ( p < 0.08) upward trend in TN content was also noted in two streams. Overall, the TN concentrations were rather high and it ranged with 90% probability from 2.3 to 8.9 mg l −1 in the studied streams. The MK test revealed the statistically significant upward trend in TN loss only at the Räpu ( p < 0.001) and Jänijõgi ( p < 0.05) catchments (one-sided test). After conditioning on trends in water discharge there was only one (Räpu) statistically significant temporal upward trend in TN loss. Elevated nitrogen concentrations in three other catchments (Rägina, Vodja, Porijõgi) explain only part of the upward trend in nitrogen losses and increasing tendencies in losses could mainly be associated with upward tendency in discharge. The direct (not flow-normalised) unit-area loss of nitrogen from agricultural land reached to 63.1 and 82.5 kg N ha −1 yr −1 in the Räpu and Jänijõgi catchments, respectively, which is higher than seen at the Rägina basin (25 kg ha −1 yr −1 ) and the River Vodja catchment (21.9 kg ha −1 yr −1 ). Elevated losses are typical for recent years, particularly after 2007. [ABSTRACT FROM AUTHOR]

Summary The magnitude and timing of peak streamflow events may be affected by land-use changes along with climate change, thus leading to nonstationarity in the records. Temporal trend, along with change-points, in peak flow records can affect the accuracy of quantile estimates; therefore, these issues should not be disregarded. Commonly used techniques for pooled flood frequency analysis do not account for nonstationarity found in the data recorded for members of a region. To overcome this shortcoming, the objective of this research is to introduce a trend centered pooling approach for regionalization in which pooling groups are created based on the form of trend found in the at-site data. The approach involves the formation of regions comprised entirely of sites exhibiting either statistically significant increasing or decreasing trends. Regional parameter estimates are determined using a maximum likelihood approach, which is carried out with the assumption of second-order nonstationarity. The technique was applied to four homogenous regions all located in differing hydroclimatological Canadian regions. The uncertainty of quantile estimates calculated through the implementation of this technique was established using a balanced regional vector resampling approach. The results indicate that there is less uncertainty in quantile estimates found through the application of the trend centered pooling approach when compared to a regional stationary analysis of the same regions. The potential for overestimation/underestimation of design quantiles in the presence of significant regional nonstationarity (i.e. decreasing/increasing trends) was elucidated. [ABSTRACT FROM AUTHOR]

Summary Changes in lake hydrological regimes and the associated impacts on water supplies and ecosystems are internationally recognized issues. During the past decade, the persistent dryness of Poyang Lake (the largest freshwater lake in China) has caused water supply and irrigation crises for the 12.4 million inhabitants of the region. There is conjecture as to whether this dryness is caused by climate variability and/or human activities. This study examines long-term datasets of catchment inflow and Lake outflow, and employs a physically-based hydrodynamic model to explore catchment and Yangtze River controls on the Lake’s hydrology. Lake water levels fell to their lowest during 2001–2010 relative to previous decades. The average Lake size and volume reduced by 154 km 2 and 11 × 10 8 m 3 during the same period, compared to those for the preceding period (1970–2000). Model simulations demonstrated that the drainage effect of the Yangtze River was the primary causal factor. Modeling also revealed that, compared to climate variability impacts on the Lake catchment, modifications to Yangtze River flows from the Three Gorges Dam have had a much greater impact on the seasonal (September–October) dryness of the Lake. Yangtze River effects are attenuated in the Lake with distance from the River, but nonetheless propagate some 100 km to the Lake’s upstream limit. Proposals to build additional dams in the upper Yangtze River and its tributaries are expected to impose significant challenges for the management of Poyang Lake. Hydraulic engineering to modify the flow regime between the Lake and the Yangtze River would somewhat resolve the seasonal dryness of the Lake, but will likely introduce other issues in terms of water quality and aquatic ecosystem health, requiring considerable further research. [ABSTRACT FROM AUTHOR]

Summary The Mahanadi river basin, a major river basin in eastern India, is expected to be the worst affected river basins in India in terms of the increase in intensity of floods due to climate change. The last decade has already seen five high floods occurring in the Mahanadi basin. Are these recent high floods an indication that Mahanadi floods are already getting worse? If so, is it due to an increase in extreme rainfalls over the basin? To answer these, we analyse the trends of peak discharge at the mouth of the delta at Naraj gauging site (the flow which is responsible for floods in the delta of Mahanadi basin) and peak releases from Hirakud dam in Mahanadi basin. Subsequently, grid based analysis of extreme rainfall is carried out for the entire Mahanadi basin to analyse the spatially varied extreme rainfall trends. Also, a region based (upper and middle regions of Mahanadi basin) analysis of extreme rainfall is carried out using daily mean areal rainfall. The trends of extreme rainfalls are analysed in relation to the trends of peak floods. The entire analysis pertains to post-Hirakud dam construction period. The analysis reveals that the recent incidences of high floods in Mahanadi basin is due to an increase in extreme rainfall in the middle reaches of the basin. [ABSTRACT FROM AUTHOR]

• Temperature gradients were divided by the soil temperature from 2009 to 2019. • Increasing temperature advanced the flowering phenology of Stipa breviflora. • Not always advanced, a temporary delay occurs in average temperature gradient. • The Mann-Kendall tests the cumulative effect of long-term phenological break point. The sensitivity of plant phenology to climate change can be used as the basis for predicting change in plant species' growth and development period as they adapt to gradual increase in atmospheric temperature. However, it is not clear how the reproductive phenology of plants will respond to a continuous increase in temperature gradient, especially when the time series has break points due to interannual change. In this experiment, the flowering phenology of Stipa breviflora , an established species in the desert steppe of Siziwang Banner in northern China, was observed from 2009 to 2019. A no warming treatment and warming treatment (1.3 °C higher than no warming) were applied. Three temperature gradients were defined: the annual average temperature of the 0–10 cm soil layer in the no warming treatment plot from 2009 to 2019 was taken as the average temperature gradient (C2, 5.63 °C ± 1.09); a higher-than-average temperature gradient (C3, 6.93 °C ± 1.34), and a lower than the average temperature gradient (C1, 4.33 °C ± 1.87). The results showed that increasing temperature was an important driving factor that advanced the flowering phenology of S. breviflora. When high temperatures exceed plants' physiological thresholds (5.63 °C ± 1.09), plants exhibit a temporary delay. Based on a Mann-Kendall test, we found that reproductive phenology was advanced from 2009 to 2015, and delayed by a time break point from 2015 to 2018. After 2018, reproductive phenology continued to be advanced, which once again verified that reproductive phenology would not continue to be advanced in the process of climate warming, but would be temporarily delayed. Therefore, our study reveals the response strategy of S. breviflora to a continuous increase in global atmospheric temperature, and provides a theoretical basis for studying the response mechanism of the desert steppe ecosystem to climate warming. [ABSTRACT FROM AUTHOR]

• Climate variables play a primary role in the tree ring width changes. • The ANN method has the potential to be highly useful for TRW studies. • The Mann-Kendall test was run to detect the trends of the climate and TRSGI data. • There is not a good agreement between the drought indicators and TRSGI. • We obtained the high performance of AI approaches for modelling TRW data. Climate variables play an important role in the increase of tree ring width (TRW), which is one of the primary paleoclimate signals. In this study, we apply new methods for understanding tree growth responses to climate variables under anthropogenic climate change. This study uses regression and artificial intelligence (AI) modelling techniques to develop a model describing the relationships between climate variables and the tree ring standardised growth index (TRSGI) in northeast South Korea. We examined data from 1901 to 1998, and then used data from 1999 to 2019 to reconstruct the TRSGI. This study comprised four major steps. In the first step, we evaluated the performance of the Climate Reach Unit (CRU) TS4.03 in comparison to synoptic station in situ data by using three well-known bias correction methods, namely delta, quantile mapping, and empirical quantile mapping. CRU TS4.03 obtained the highest cross-correlation coefficients (r 2 > 0.90) within the synoptic station data. In the second step, different temperatures, precipitation, vapour pressure, and two drought indices were analysed using TRSGI. In the third step, the Mann-Kendall test was run to detect climate and TRSGI data trends, and it showed that all variables had increasing trends at a significance level of 0.05 during 1901–1998. Finally, in the fourth and final step, by selecting the most significant factors from the statistical tests, four models were developed: multiple linear regression (MLR), stepwise regression (SR), nonlinear autoregressive with exogenous input (NARX), and NARX de-noised wavelet, the last of which was a model we developed by combining NARX and de-noised wavelet models. The results indicated that MLR with r = 0.44 (p < 0.003) and SR with r = 0.27 (p < 0.001) were not strong enough to reconstruct TRSGI. In contrast, the NARX de-noised model (r = 0.80) performed better than the NARX model (r = 0.78), showing highly similar trends to the observed TRSGI in the case study area. This research highlights the high performance of AI approaches for modelling TRW data in comparison to regression models. AI techniques may improve the accuracy of climate variable estimations and reconstructions that use TRW data. The presented artificial neural network method has the potential to be a highly effective method for TRW studies. [ABSTRACT FROM AUTHOR]

Highlights: [•] Pre-whitening cannot really improve trend identification when using the MK test. [•] Series’ trend magnitudes greatly influence trend identification of series. [•] EMD method can be an effective alternative for trend identification of series. [•] EMD method can identify the specific shape of the analyzed series’ trend. [ABSTRACT FROM AUTHOR]

Abstract: Trend analysis of the mean (monsoon season, non-monsoon season and annual) and extreme annual daily rainfall and temperature at the spatial and temporal scales was carried out for all the 33 urban centers of the arid and semi-arid state of Rajasthan, India. Statistical trend analysis techniques, namely the Mann–Kendall test and Sen's slope estimator, were used to examine trends (1971–2005) at the 10% level of significance. Both positive and negative trends were observed in mean and extreme events of rainfall and temperature in the urban centers of Rajasthan State. The magnitude of the significant trend of monsoon rainfall varied from (−) 6.00mm/hydrologic year at Nagaur to (−) 8.56mm/hydrologic year at Tonk. However, the magnitude of the significant negative trends of non-monsoon rainfall varied from (−) 0.66mm/hydrologic year at Dungarpur to (−) 1.27mm/hydrologic year at Chittorgarh. The magnitude of positive trends of non-monsoon rainfall varied from 0.93mm/hydrologic year at Churu to 1.70mm/hydrologic year at Hanumangarh. The magnitude of the significant negative trends of annual rainfall varied from (−) 6.47mm/year at Nagaur to (−) 10.0mm/year at Tonk. The minimum, average and maximum temperature showed significant increasing warming trends on an annual and seasonal scale in most of the urban centers in Rajasthan State. The magnitude of statistically significant annual extreme daily rainfall varied from 2.00mm at Jhalawar to (−) 1.64mm at Tonk, while the magnitude of statistically significant extreme annual daily minimum and maximum temperature varied from 0.03°C at Ganganagar to 0.05°C at Jhalawar, respectively. The spatial variations of the trends in mean (monsoon season, non-monsoon season and annual) and extreme annual daily rainfall and temperature were also determined using the inverse-distance-weighted (IDW) interpolation technique. IDW results are helpful to identify trends and variability in mean and extreme rainfall and temperature in space and time for the study locations where the data is not available and the quality of data is not good. These spatial maps of temperature and rainfall can help local stakeholders and water managers to understand the risks and vulnerabilities related to climate change in terms of mean and extreme events in the region. [Copyright &y& Elsevier]