Search

The issue of detection of hydrometeorological trends remains relevant because of the importance of climate change in design, operation, and management studies related to water resources. This study examines the effects of changes in climate and land use on monthly flows (1962–2018) in the Eastern Black Sea basin, Turkey, using innovative trend analysis methods. In this context, innovative polygon trend analysis (IPTA) and innovative trend significance test (ITST) were used to detect the trends and compared with Mann-Kendall test. Only stations with homogeneous data that did not experience non-climatic changes are used in the analysis. IPTA and ITST approaches are much more sensitive than Mann-Kendall in detecting trends. Although the innovative methods are mostly compatible with each other (90%), IPTA presents additional information about trend transitions between successive parts of time series. Results indicate significant decreasing trends in summer months, likely due to diminishing precipitation and effective evaporation. © 2022 IAHS

Identifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near- and long-term timescales. HIGHLIGHTS The need to perform homogeneity tests to avoid erroneous conclusions is emphasised.; The study cautions the direct use of stream discharge data for climate analyses in urban areas.; Long-term data show no significant changes in rainfall while temperature is rising.; Findings will improve the understanding of hydro-meteorological trends specific to the Rietspruit sub-basin mainly due to temperature spatial variability.

The availability of water resources is under stress due to its unsustainable exploitation. The Chambal basin is located in the water-scarce region in India with average annual rainfall varying between 687.1 mm in the Rajasthan (RJ) region and 938.2 mm in the Madhya Pradesh (MP) region. On average, there are 48 rainy days in the MP region and 39 rainy days in the RJ region of the Chambal basin. Fourteen drought years have been identified during the period spanning 34 years (1985–2018). 44% of basin area located in the MP region and 54% of basin area located in the RJ are found to be drought-prone. The Standardized Precipitation Index-based evaluation of drought characteristics indicated higher drought frequency in the RJ region varying between 1 in 3 years and 1 in 4 years and between 1 in 3 years and 1 in 5 years in the MP region, which has also been substantiated by the Relative Departure Index (RDI), namely average RDI for RJ (0.69) and MP (0.58). The understanding of the contrasts in rainfall and drought characteristics in upper reaches (MP region) and lower reaches (RJ region) of the Chambal basin will help in holistic management and sharing of water resources based on these contrasts and constraints. HIGHLIGHTS Drought indicator-based investigation of drought characteristics in a major tributary of the Ganga river system.; Evaluation of the contrasts in the two different regions (Madhya Pradesh and Rajasthan) of the Chambal basin.; Standardized Precipitation Index-based evaluation of meteorological droughts.; Prioritization of drought-prone districts for effecting mitigation activities during periods of drought.

Collisions with vehicles can be a major threat to wildlife populations, so wildlife mitigation structures, including exclusionary fencing and wildlife crossings, are often constructed. To assess mitigation structure effectiveness, it is useful to compare wildlife road mortalities (WRMs) before, during, and after mitigation structure construction; however, differences in survey methodologies may make comparisons of counts impractical. Location‐based cluster analyses provide a means to assess how WRM spatial patterns have changed over time. We collected WRM data between 2015 and 2019 on State Highway 100 in Texas, USA. Five wildlife crossings and exclusionary fencing were installed in this area between September 2016 and May 2018 for the endangered ocelot (Leopardus pardalis) and other similarly sized mammals. Roads intersecting State Highway 100 were mitigated by gates, wildlife guards, and wing walls. However, these structures may have provided wildlife access to the highway. We combined local hot spot analysis and time series analysis to assess how WRM cluster intensity changed after mitigation structure construction at fine spatial and temporal scales and generalized linear regression to assess how gaps in fencing and land cover were related to WRM cluster intensity in the before, during, and after construction periods. Overall, WRMs/survey day decreased after mitigation structure construction and most hot spots occurred where there were more fence gaps, and, while cluster intensity increased in a few locations, these were not at fence gaps. Cluster intensity of WRMs increased when nearer to fence gaps in naturally vegetated areas, especially forested areas, and decreased nearer to fence gaps in areas with less natural vegetation. We recommend that if fence gaps are necessary in forested areas, less permeable mitigation structures, such as gates, should be used. Local hot spot analysis, coupled with time series and regression techniques, can effectively assess how WRM clustering changes over time., Wildlife mitigation structures are often constructed to reduce wildlife road mortalities; however, gaps in the fence may reduce the effectiveness of these structures. We assessed how hot spots of wildlife road mortality changed with construction of mitigation structures using emerging hot spot analysis and generalized linear regression. We found that hot spot intensity has not changed after 1 year postconstruction of mitigation structures and that resulting spatial patterns of wildlife road mortalities were not associated with the locations of mitigation structures.

Extreme climate and weather events have direct impacts on human life, the environment, and resources. The Diyala River basin is shared between Iraq and Iran, which makes it vulnerable not only to climate change effects but also to upstream control. Therefore, understanding and predicting extreme events is an essential step to help decision-makers make proactive plans to reduce expected damages. The pattern of extreme events has been identified using climate extreme indices developed by the World Meteorological Organization and Expert Team on Climate Change Detection Indices using ClimPACT2 software. Data were obtained from three meteorological stations in Iraq (Sulaymania, Khanakin, and Baghdad) and one in Iran (Sanandaj) over a period of 20 years (2000–2020). Results for temperature showed seven statistically significant positive trends for only three indices (annual number of days with daily maximum temperature of >35°, difference between daily maximum and daily minimum temperatures, and percentage of days with maximum temperature of >90th percentile, indicating an increase in that temperature). Baghdad station had positive temperature trends for all indices. Trends for precipitation were nearly all nonsignificant and difficult to anticipate compared with those for temperature. Percentile-based indices showed more dry and warm events than wet and cold. HIGHLIGHTS Statistical analysis was performed for the Diyala River basin to obtain information about extreme climate indices during the last 20 years.; The nonparametric Mann–Kendall test was used to detect trends at annual, seasonal, and monthly scales.; The Weibull formula was used to predict the occurrence of extreme precipitation events.; Temperature showed a more significant trend than precipitation.

The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020. HIGHLIGHTS Temporal and spatial variation characteristics of total precipitation on the Huang-Huai-Hai Plain.; Two typical distribution fields on the Huang-Huai-Hai Plain.; The shifts of precipitation barycentres on the Huang-Huai-Hai Plain.

Precipitation variations mostly affect the water resource planning in semi-arid regions of northwest China. The objective of this study is to quantitatively explore the spatial and temporal variations of precipitation in different time scales in Xi'an city area. The Mann–Kendall test and wavelet analysis methods were applied to analyze the precipitation variability. In terms of temporal variation of precipitation, the results indicated that the annual precipitation exhibited a significant decreasing trend during 1951–2018. Except for summer precipitation representing a slightly increasing trend, the other seasonal precipitations had a similar decreasing trend to annual precipitation throughout 1951–2018. The monthly precipitation had different change trends, showing the precipitation from June to September could account for 58.4% of the total annual precipitation. In addition, it was clear that annual precipitation had a significant periodic change, with the periods of 6, 13, 19, and 27 years. For the spatial variation of precipitation during 1961–2018, the results showed that annual and seasonal precipitation exhibited obvious spatial differences, indicating an increasing spatial trend from north to south. Thus, understanding the precipitation variation in Xi'an city can provide a theoretical foundation of future water resources management for other cities in semi-arid regions of northwest China. HIGHLIGHTS There were different variation trends in annual, seasonal and monthly precipitation at a temporal scale.; The annual precipitation in Xi'an city had a significantly increasing trend during 1951–2018.; The annual and seasonal precipitation exhibited obvious spatial differences during 1961–2018.; Findings could guide future water resource management and allocation of other cities in semiarid regions of northwest China.

This paper examines monthly, seasonal, and annual trends in temperature and precipitation time series in Osijek during the period between 1900 and 2018. Two new methods, innovative trend analysis (ITA) and successive average methodology (SAM), together with the classic Mann–Kendall (M–K) and Sen’s slope methods, have been applied to determine potential trends in the variables at different time scales. Moreover, time series decomposition using locally estimated scatterplot smoothing (STL) was conducted to determine trend, seasonality, and the relationship between the components of each variable. Regarding the air temperature, ITA showed a monotonic positive trend at relatively low (T ≤ 10 °C) and high (T ≥ 13 °C) temperature ranges in all seasons, excluding spring. A positive trend was also found in the medium temperature range in this season, which agrees with the results of M–K test. The highest Sen’s slope was obtained in January, with the second highest in April. According to the results acquired for the observed precipitation time series, it was discovered that Osijek has experienced a decreasing trend in spring precipitation. However, there is no trend in annual precipitation at a 5% significance level. Differing from the M–K results, the ITA shows a decreasing trend in both spring and autumn seasons. Summer precipitation increases with a significant change in the high precipitating levels (p ≥ 100 mm). Comparing successive pairs of partial trends in both historical temperature and precipitation, our results show that trends in peak and trough change-points are very close to each other, indicating a slight positive trend in temperature and a negative change in precipitation over the past century.

This study analyzed the trends and spatio-temporal variability in rainfall and temperature, and the length of the rainy season (LRS) in the Lake Manyara catchment, Tanzania, covering a period between 1988 and 2018 using stations and satellite climate product. The Mann-Kendall statistical test, Sen's slope estimator, and inverse distance weighting interpolation techniques were used to detect the trends, magnitude of trends and spatial distribution of rainfall and temperature. A modified Stern's method and water balance concept were used for rainfall onset, cessation and LRS analysis, while a standardized precipitation index (SPI) was used to investigate the wetness or dryness of the area. The results showed high variability and decreasing trend (4 mm/y) in annual rainfall, and non-significant increasing trend for minimum and maximum temperature. Rainfall increased from the western to the northern part of the catchment whereas a reversal pattern was noticed for temperature. The SPI shows a signal of normal condition (about 65%) for all stations – with few years showing evidence of wetter and drier conditions. The LRS showed a decreasing trend indicating a potential negative influence on rain-dependent activities. There is a need, therefore, for adaptation measures such as improving water productivity and irrigation at the farm and catchment level.

This study aims to investigate the spatio-temporal variability and trends in climate and its implications for rainfed agriculture in the Rib watershed, north-western highland Ethiopia from 1986 to 2050. The daily rainfall and temperature records for the period 1986–2017 were used to detect the variability and trends of the current climate using the coefficient of variation, precipitation concentration index, Mann–Kendall test, and Sen's slope estimator. On the other hand, future climate changes (2018–2050) were analyzed based on the Coupled Model Intercomparison Project version 5 (CMIP5) model outputs under under two representative concentration pathway (RCP) scenarios, RCP 4.5 and 8.5. The results showed high inter-seasonal and inter-annual variability of rainfall and temperature in the studied watershed over the last four decades. The annual and Kiremt (June–September) rainfall showed a generally increasing trend, while the Belg (March–May) rainfall exhibited a decreasing trend between 1986 and 2017. Conversely, the minimum, maximum and mean temperature demonstrated increasing trends over the study period although most of the detected trends were statistically insignificant at 5 and 10% level of significance. Future climate analysis results showed an increase in future temperature and annual and Kiremt rainfall while Belg rainfall declined. HIGHLIGHTS Both the current and future rainfall and temperature changes and variability were analysed.; Five CMIP5 model outputs and two emission scenarios were considered for analysis of future climate.; Mapping the spatial distribution of rainfall and PCI is essential for water use planning and policy making.; Evaluation of seasonal climate variability and change is vital for rain-fed agriculture, particularly in developing countries like Ethiopia.; Mann-Kendall test and coefficient of variation were found to be important techniques for analysis of climate variability and trends.

Climate change and human activities have changed a number of characteristics of river flow in the Taihu Basin. Based on long-term time series of hydrological data from 1986 to 2015, we analyzed variability in precipitation, water stage, water diversion from the Yangtze River, and net inflow into Taihu Lake with the Mann-Kendall test. The non-stationary relationship between precipitation and water stage was first analyzed for the Taihu Basin and the Wuchengxiyu (WCXY) sub-region. The optimized regional and urban regulation schemes were explored to tackle high water stage problems through the hydrodynamic model. The results showed the following: (1) The highest, lowest, and average Taihu Lake water stages of all months had increasing trends. The total net inflow into Taihu Lake from the Huxi (HX) sub-region and the Wangting Sluice increased significantly. (2) The Taihu Lake water stage decreased much more slowly after 2002; it was steadier and higher after 2002. After the construction of Wuxi urban flood control projects, the average water stage of the inner city was 0.16 m to 0.40 m lower than that of suburbs in the flood season, leading to the transfer of flooding in inner cities to suburbs and increasing inflow from HX into Taihu Lake. (3) The regional optimized schemes were more satisfactory in not increasing the inner city flood control burden, thereby decreasing the average water stage by 0.04 m to 0.13 m, and the highest water stage by 0.04 m to 0.09 m for Taihu Lake and the sub-region in the flood season. Future flood control research should set the basin as the basic unit, and decreasing diversion and drainage lines along the Yangtze River can take an active role in flood control.

The identification of trends in hydrological data is crucial for sustainable planning and management of water resources under the climate-change scenario. This research, identify the long-term temporal trend and magnitude (m3/s/time scale) in monthly, seasonal, and annual streamflow by employing three non-parametric approaches conventional Mann-Kendall (MK), Innovative-Sen trend (IST), and Sen-slope (SS) on 5% level of significance. The monthly streamflow data of 32-years (1976–2007) were recorded at Naula and Kedar stations positioned in the upper Ramganga River catchment (RRC), Uttarakhand State (India). Results of scrutiny reveal a significant negative trend in 17 time-series was detected by conventional MK test, and significant positive/negative trend in 1/30 time-series was inspected by the IST method with changing magnitude over monthly, seasonal, and annual scales at both stations, respectively. Furthermore, a comparison among results of the MK and IST showed that the IST method examined the unseen trend that cannot be detected by the MK technique at the Naula watershed. The pattern of trend detected on annual, seasonal, and monthly time-scales by three non-parametric approaches can help the water resources management authorities and hydrologists to comprehend the hazard and vulnerability under climate-change scenario over the study catchment area.

Background Africa is the most vulnerable continent in the world; which recurrent droughts, extreme temperature and rainfall affects agriculture and food security. The aim of this study was to analyze the trends in extreme temperature and rainfall in major sesame producing areas in western Tigray using RClimDex software. We selected eight temperature and nine rainfall indices from 27 extreme temperature and rainfall indices, which are recommended by joint CCL/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI). A non-parametric Mann–Kendall test and Sen’s slope estimates were used to test the statistical significance and trend of each of the extreme temperature and rainfall indices, respectively. Results Number of heavy rainy days, number of very heavy rainy days, very wet days, extremely wet days, and maximum 5 days precipitation showed a negative trend, with significant (p Conclusions Increase in temperature and decrease in amount of rainfall may have a negative impact on crop transpiration, photosynthetic rate and soil water balance; exacerbating distribution and infestation of malaria and leishmaniasis. The results in this study could have an important role in identifying possible present and future production strategies on sesame, cotton, and sorghum crops, which are essential cash crops produced by farmers and investors.

An accurate quantification in the separation of the relative contributions of climate change and human activities on grassland dynamics is crucial for controlling grassland degradation. Here, we investigated grassland dynamics in China by using net primary productivity (NPP) as an evaluation indicator from 1982 to 2016. We calculated the human-induced grassland NPP (HNPP) by subtracting the potential NPP (PNPP) from the actual NPP (ANPP) to distinguish the climatic and anthropogenic effects on grassland NPP changes across different time scales. Results indicated that the change in grassland ANPP resulted from different dominated factors in the two periods of 1982–1999 and 2000–2016. An obvious increase of grassland ANPP was observed from 1982 to 1999, which mainly due to a slight increasing trend in grassland PNPP driven by a humid-warm climate and a slight decrease in grassland HNPP from weak human activities. An overall increase in ANPP (69.576%) over its decrease portion (30.424%) was observed from 1982 to 1999. Human activities-induced ANPP increase mainly occurred in Shaanxi, Qinghai and Gansu Provinces and Tibet Autonomous Region for the grassland types of Alpine subalpine meadow, Meadow and Slope grassland. Climate-dominated decrease mainly occurred in Shanxi, Shaanxi and Heilongjiang, especially for Plain and Slope grassland. However, an overall decreasing trend of grassland ANPP was observed from 2000 to 2016, mainly attributed to a decreasing trend in grassland HNPP by human intervention and a warm-dry climate-induced negative effect on grassland growth. Overall, the grassland underwent a decrease than increase in ANPP (58.826% vs 41.174%) during 2000–2016; the contributions of climate factors to grassland ANPP increase was relatively greater than that of human factors in Xinjiang, Qinghai and Inner Mongolia. Human activities-dominated ANPP decrease occupied 23.913%, obviously higher than the decrease dominated by climate change (9.248%), which mainly occurred in Alpine subalpine meadow, Desert grassland and Alpine subalpine grassland. Overall, these findings seem to demonstrate that there are great differences in the temporal and spatial effects of climate change and human activities on different regions and different grassland types in China before and after 1999, and contribute to providing location guidance for future grassland restoration. Meanwhile, this study is expected to improve the understanding of the driving mechanisms of grassland dynamics, and provide support for scientifically evaluating and adjusting ecological restoration policies in China.

Spatiotemporal water quality tendencies before and after total maximum daily load (TMDL) implementation in the Hangang basin were analyzed to determine the water quality improvement resulting from the TMDL policy. The periodicities of water quality indicators were also analyzed and water quality characteristics corresponding to different unit watershed units were identified in terms of pollution source. Considering five water quality indicators, including biochemical oxygen demand and total phosphorus, it was observed that water quality indicator concentrations were low in the upstream areas of the Bukhangang and Namhangang watersheds. However, they were high between the downstream areas of the Namhangang watershed and the Imjingang watershed and in the Hangang downstream and Jinwicheon watersheds. Additionally, the concentrations of water quality indicators in most of the unit watersheds where TMDL had been implemented decreased after TMDL implementation. However, increasing tendencies in the concentrations of water quality indicators continued to be observed in some of the watershed units in the upstream areas of the Bukhangang and Namhangang watersheds, possibly because these watersheds are affected by nonpoint source pollution owing to rainfall. Therefore, in the future, it would be necessary to implement policies that take these findings into consideration.

The Himalayas, especially the Everest region, are highly sensitive to climate change. Although there are research works on this region related to cryospheric work, the ecological understandings of the alpine zone and climate impacts are limited. This study aimed to assess the changes in surface water including glacier lake and streamflow and the spatial and temporal changes in alpine vegetation and examine their relationships with climatic factors (temperature and precipitation) during 1995–2019 in the Everest region and the Dudh Koshi river basin. In this study, Landsat time-series data, European Commission’s Joint Research Center (JRC) surface water data, ECMWF Reanalysis 5th Generation (ERA5) reanalysis temperature data, and meteorological station data were used. It was found that the glacial lake area and volume are expanding at the rates of 0.0676 and 0.0198 km3/year, respectively, the average annual streamflow is decreasing at the rate of 2.73 m3/s/year. Similarly, the alpine vegetation greening as indicated by normalized difference vegetation index (NDVI) is increasing at the rate of 0.00352 units/year. On the other hand, the annual mean temperature shows an increasing trend of 0.0329 °C/year, and the annual precipitation also shows a significant negative monotonic trend. It was also found that annual NDVI is significantly correlated with annual temperature. Likewise, the glacial lake area expansion is strongly correlated with annual minimum temperature and annual precipitation. Overall, we found a significant alteration in the alpine ecosystem of the Everest region that could impact on the water–energy–food nexus of the Dudh Koshi river basin.

Background Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann–Kendall test and Sen’s slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool sub-humid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r2 = 0.62) and negatively correlated to the minimum (r2 = 0.58) and maximum (r2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale.

One of the adverse impacts of climate change is drought, and the complex nature of droughts makes them one of the most important climate hazards. Drought indices are generally used as a tool for monitoring changes in meteorological, hydrological, agricultural and economic conditions. In this study, we focused on meteorological drought events in the High Ziz river Basin, central High Atlas, Morocco. The application of drought index analysis is useful for drought assessment and to consider methods of adaptation and mitigation to deal with climate change. In order to analyze drought in the study area, we used two different approaches for addressing the change in climate and particularly in precipitation, i) to assess the climate variability and change over the year, and ii) to assess the change within the year timescale (monthly, seasonally and annually) from 1971 to 2017. In first approach, precipitation data were used in a long time scale e.g. annual and more than one-year period. For this purpose, the Standardized Precipitation Index (SPI) was considered to quantify the rainfall deficit for multiple timescales. For the second approach, trend analysis (using the Mann-Kendall (M-K) test) was applied to precipitation in different time scales within the year. The results showed that the study area has no significant trend in annual rainfall, but in terms of seasonal rainfall, the magnitude of rainfall during summer revealed a positive significant trend in three stations. A significant negative and positive trend in monthly rainfall was observed only in April and August, respectively.

A study has been carried out to analyse the temporal and seasonal patterns in the trends of diurnal air temperature range (DTR) and its components in Shaheed Benazir Abad for the time period 1996–2014.The magnitude, the slope and the significance of trends were investigated by using the linear regression method, the trend magnitude, the Mann-Kendall test and the Sen’s estimator of slope. The Mann-Kendall test and Sen's estimator of slope were calculated by using Addinsoft's XLSTAT 2015 software. The hypothesis of Mann-Kendall test was investigated at 95% confidence level for all variables. The result shows that minimum temperature of Shaheed Benazir Abad has increased at the rate of 0.063°C per year during study period while the maximum temperature for all months exhibits no change. This increase of minimum temperature contributed to the decreasing trend of diurnal temperature range. The DTR decreased at the rate of 0.057°C /year in Shaheed Benazir Abad. The investigation of seasonal DTR trends revealed that Summer and Spring seasons also witnessed a decreasing trends at the rate of 0.26 °C/year and 0.047°C/year respectively. Winter and aseasons, on the other hand, have experienced the increasing trends of DTR at the rate of 0.136 °C/year and 0.115 °C/year respectively. It is found by MK test that Tmax (winter), Tmax (Spring) and Tmin (Spring) exhibited the significant positive trends at the rate of 0.21°C/year, 0.368 °C/year and 0.421°C/year respectively. The increasing trends of Tmax of winter and spring indicate that winter and spring are warmer now.

In the present study, time series for annual, monthly rainfall and number of rainy days per year were analysed to quantify spatial variability and temporal trends for 22 rainfall stations distributed in northeastern Algeria for the period 1978–2010. The Mann–Kendall test and the Sen’s slope estimator were applied to assess the significance and magnitude of the trend. The results showed that precipitation decreases spatially from North to South and from East to West. The application of the Mann–Kendall test (for 0.05% threshold) to the time series data showed that for annual precipitation, no station showed statistically significant trends, unlike the number of rainy days, where there was a significant negative trend in four stations (Jijel, Constantine, Oum El Bouaghi and Tébessa). For the monthly time series, significant positive trends were observed during the months of September in the coastal stations and July for the plateaus and southern Saharan Atlas stations, while significant negative trends were recorded during the months of February and March for the stations of the extreme East in the study area. These results revealed that for the period analysed, there was no significant climate change in northeastern Algeria but there is a seasonal delay having important agroecological implications.

The Adriatic Sea and its coastal region have experienced significant environmental changes in recent decades, aggravated by climate change. The most prominent effects of climate change (namely, an increase in sea surface and air temperature together with changes in the precipitation regime) could have an adverse effect on social and environmental processes. In this study, we analyzed the time series of sea surface temperature and air temperature measured at three meteorological stations in the Croatian part of the Adriatic Sea. To assess the trends and variations in the time series of sea surface and air temperature, different statistical methods were employed, i.e., linear and quadratic regressions, Mann–Kendall test, Rescaled Adjusted Partial Sums method, and autocorrelation. The results evidenced increasing trends in the mean annual sea surface temperature and air temperature, furthermore, sudden variations in values were observed in 1998 and 1992, respectively. Increasing trends in the mean monthly sea surface temperature and air temperature occurred in the warmer parts of the year (from March to August). The results of this study could provide a foundation for stakeholders, decision–makers, and other scientists for developing effective measures to mitigate the negative effects of climate change in the scattered environment of the Adriatic islands and coastal region.

Background The paper presents an overview of air quality in the 27 member countries of the European Union (EU) and the United Kingdom (previous EU-28), from 2000 to 2017. We reviewed the progress made towards meeting the air quality standards established by the EU Ambient Air Quality Directives (European Council Directive 2008/50/EC) and the World Health Organization (WHO) Air Quality Guidelines by estimating the trends (Mann-Kendal test) in national emissions of main air pollutants, urban population exposure to air pollution, and in mortality related to exposure to ambient fine particles (PM2.5) and tropospheric ozone (O3). Results Despite significant reductions of emissions (e.g., sulfur oxides: ~ 80%, nitrogen oxides: ~ 46%, non-methane volatile organic compounds: ~ 44%, particulate matters with a diameter lower than 2.5 µm and 10 µm: ~ 30%), the EU-28 urban population was exposed to PM2.5 and O3 levels widely exceeding the WHO limit values for the protection of human health. Between 2000 and 2017, the annual PM2.5-related number of deaths decreased (- 4.85 per 106 inhabitants) in line with a reduction of PM2.5 levels observed at urban air quality monitoring stations. The rising O3 levels became a major public health issue in the EU-28 cities where the annual O3-related number of premature deaths increased (+ 0.55 deaths per 106 inhabitants). Conclusions To achieve the objectives of the Ambient Air Quality Directives and mitigate air pollution impacts, actions need to be urgently taken at all governance levels. In this context, greening and re‐naturing cities and the implementation of fresh air corridors can help meet air quality standards, but also answer to social needs, as recently highlighted by the COVID-19 lockdowns.

Ganga River basin, being the largest river basin in India, adheres with its social and spiritual importance for the country. Although many studies have been conducted on the Ganga basin, however, trend observed in flow and sediment yield in Ganga River has been scarcely studied. Alteration in flow pattern and sediment transport in rivers brings remarkable impact on river geomorphology and entire ecosystem of the region. The present paper attempts to identify trends observed in Ganga River in terms of annual maximum and annual minimum discharges, water and sediment yield during monsoon season. The trend analysis was accomplished by performing the Mann-Kendall (M-K), Sen’s slope, and innovative trend analysis at various gauging sites along the river for the monsoon months. Significance of trend tests were tested at 5% significance level. Innovative trend analysis (ITA) revealed non-monotonicity within the time series and provided more detailed understanding of changes in hydrological changes. While observed annual maximum discharge showed a negative trend at almost all the sites, annual minimum discharge showed positive trend at gauging sites upstream of confluence of Yamuna River. Data of discharge and sediment load for monsoon months also revealed declining trends at most of the gauging sites. Water and sediment yields at all sites except Gandhighat showed a negative trend. Decline in trend of sediment and water yield is more pronounced in Western Ganga Plain (WGP) as compared to Eastern Ganga Plain (EGP). Incorporating these trends can be helpful for various water management projects in the future. Both climatic factors and human intervention appear to be responsible for the alteration in flow pattern of Ganga River.

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the &ldquo, peak&rdquo, values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for &ldquo, low&rdquo, values, and 40 time series (44.94%) showed increasing patterns for &ldquo, medium&rdquo, values. According to the &ldquo, &ldquo, and &ldquo, values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating &ldquo, values.

One of the most relevant and debated topics related to the effects of the climate change is whether intense rainfall events have become more frequent over the last decades. It is a crucial aspect, since an increase in the magnitude and frequency of occurrence of heavy rainfall events could result in a dramatic growth of floods and, in turn, human lives losses and economic damages. Because of its central position in the Mediterranean area, Sicily has been often screened with the aim to capture some trends in precipitation, potentially related to climate change. While Mann-Kendall test has been largely used for the rainfall trend detection, in this work a different procedure is considered. Precipitation trends are here investigated by processing the whole rainfall time-series, provided by the regional agency SIAS at a 10-min resolution, through the quantile regression method by aggregating precipitation across a wide spectrum of durations and considering different quantiles. Results show that many rain gauges are characterized by an increasing trend in sub-hourly precipitation intensity, especially at the highest quantiles, thus suggesting that, from 2002 to 2019, sub-hourly events have become more intense in most of the island. Moreover, by analysing some spatial patterns, it has been revealed that the south and the east of Sicily are more interested in significant increasing rainfall trends, especially at the 10-min duration. Finally, the comparison between the two procedures revealed a stronger reliability of the quantile regression in the trend analysis detection, mainly due to the possibility of investigating the temporal variation of the tails of precipitation distribution.

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann&ndash, Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade&minus, 1, p = 0.81) and SCD (s = &minus, 2.3 d decade&minus, 1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

In Europe, tropospheric ozone pollution appears as a major air quality issue, and ozone concentrations remain potentially harmful to vegetation. In this study we compared the trends of two ozone metrics widely used for forests protection in Europe, the AOT40 (Accumulated Ozone over Threshold of 40 ppb) which only depends on surface air ozone concentrations, and the Phytotoxic Ozone Dose which is the accumulated ozone uptake through stomata over the growing season, and above a threshold Y of uptake (PODY). By using a chemistry transport model, we found that European-averaged ground-level ozone concentrations (− 2%) and AOT40 metric (− 26.5%) significantly declined from 2000 to 2014, due to successful control strategies to reduce the emission of ozone precursors in Europe since the early 1990s. In contrast, the stomatal ozone uptake by forests increased from 17.5 to 26.6 mmol O3 m−2 despite the reduction in ozone concentrations, leading to an increase of potential ozone damage on plants in Europe. In a climate change context, a biologically-sound stomatal flux-based standard (PODY) as new European legislative standard is needed.

The Earth&rsquo, s climate has warmed by approximately 0.6 &deg, C over the last century, but temperature change in the Taihang Mountain region&mdash, an important transition zone in North China which functions as an ecological barrier for Beijing, Tianjin, and other big cities&mdash, is still unknown. In this study, we analyze the spatial and temporal trends in the average annual and seasonal surface air temperature in the Taihang Mountain region from 1968 to 2017. The effect of elevation, longitude, latitude, percent forestland, percent farmland, and gross domestic product (GDP) on temperature was also determined. Our results show that the Taihang Mountain has warmed by 0.3 &deg, C/decade over the past five decades. Partitioned seasonally, average warming was 0.38, 0.14, 0.21, and 0.47 &deg, C/decade in spring, summer, fall, and winter, respectively. Elevation and latitude were significantly negatively correlated with temperature but had no correlation with the temporal warming trend (i.e., the Z value from a Mann&ndash, Kendall test). The Z value was significantly negatively correlated with percent forestland and positively correlated with GDP, indicating that economic development has induced warming, but afforestation may reduce the rate of warming increase. Together, our results provide important insights into the rates and drivers of climate change within mountainous regions.

Air temperature is the main climatic variable for climate change and global warming assessment. In different regions, different climatic features and forcing factors affect air temperature behaviour and development differently. In this paper, time series of monthly and annual absolute minimum, mean and absolute maximum air temperatures measured in the period Jan. 1949–Dec. 2018 at two meteorological stations, Zagreb Gric and Lastovo, were analysed. The stations are situated in distinct climatological areas in geographically and climatologically completely opposite parts of Croatia. The climate of Zagreb Gric station is mild continental. Station Lastovo is located on the small isolated Adriatic Sea island, which has a hot Mediterranean climate. The distance by air between the two analysed meteorological stations is 340 km. In time series of the absolute annual minimum air temperatures measured at both analysed stations, an increasing trend is not statistically significant, while in the time series of mean annual and absolute annual maximum air temperatures, the trends are statistically significant at the level p

Grassland covers 54% of the Tibetan Plateau (TP) and suffered overgrazing and degradation problems during past decades. To alleviate these problems, a series of policy measures have been implemented during recent two decades and inevitably caused changes of the grassland. To this end, this study quantitatively analyzed the grassland changes and the effects of reduced grazing intensity, and identified the hot plots of grassland degradation in the TP during 2000&ndash, 2019. The grassland status was indicated by the Fractional Vegetation Cover in the green grass period (GP), i.e., FVCGP, and its changes and spatial variations were detected by analyzing the FVCGP trends and their distribution, using the Mann&ndash, Kendal, Sen&rsquo, s Slope, and ArcGIS buffering methods, and data of the MOD13Q1 Collection 6 products and other sources. The results showed that 62.12% of the grasslands were significantly increased in the FVCGP, and 28.34% had no apparent changes. The remaining 9.54% of the grassland significantly decreased in the FVCGP, mainly occurring in the areas nearby roads, rivers, and lakes, and distributed mostly in a point pattern. Of the total FVCGP decreased grassland area, 27.03% was clustered and identified as the hot plots of grassland degradation in six main regions. Decreased grazing intensity and increased precipitation contributed to the increase of grassland FVC in the TP, while local overgrazing could be the main cause of the FVC decrease. To strength the grassland restoration in the TP, the government supports and supervision should be enhanced to further mitigate the grassland pressure of animal grazing, particularly in the hot plot areas of degradation.

Climate change and shrinking of the Aral Sea have significantly affected the region&rsquo, s temperature variations. Observed interannual changes in Uzbekistan&rsquo, s air temperature compared to the duration of synoptic weather types (SWT) in Middle Asia were analyzed. Nonparametric Mann&ndash, Kendall statistical test and climate trends coefficients were used to identify trend characteristics of observed temperature from 1961&ndash, 2016 to the baseline period of 1961&ndash, 1990. The results showed increasing temperature trends average to 1 &deg, C in warm and cold half years over Uzbekistan. The 1991&ndash, 2016 decadal temperature trend ranged from 0.25 &deg, C/decade in the northwest to 0.52 &deg, C/decade in the center, especially pronounced in the oasis and Aral Sea zones. There were also significant changes in the structure of regional SWT. The main difference in the structure of SWT in Middle Asia relative to the baseline period was expressed in a decrease of cold mass invasion duration from 113.4 to 76.1 days and an increase in low-gradient baric field duration from 65.8 to 134.6 days. The process of anthropogenic warming, which began in Uzbekistan in the 1960s of the twentieth century, has accelerated from the mid-1970s with a higher mean annual air temperature than the baseline period&rsquo, s climate normals (1961&ndash, 1990) and is associated with changes in the regional SWT over Middle Asia.

The knowledge of intensity and frequency of rainfall allows establishing predictive measures to minimize impacts caused by high volume of rainfall totals in a region. Therefore, the objective is to evaluate daily rainfall for Paraná slope of the Itararé watershed (PSIW) and to verify the spatiotemporal trend of intense and extreme daily rainfall. Rainfall data from 14 stations collected from 1976 to 2012 were used with less than 4% of data faults. Multivariate analysis based on cluster analysis technique (CA) was used applying the Euclidean distance for the identification of homogeneous groups, and the quantiles technique to classify daily rainfall. The Mann-Kendall (MK) test was used to identify trends for annual rainfall totals, annual number of rainy days (ANRD) and for the occurrence of intense (R95p) and extreme (R99p) rainfall. The CA technique identified three rainfall groups (HG I, II and III). Given the latitudinal position of the area, rainfall at the southern sector is characterized by its greater similarities with the subtropical climate, whereas in the North sector there is a consistent reduction of rainfall totals in autumn and, especially, during winter months, which are characteristic of the tropical climate. The MK test identified the downward trend of ANRD, with greater significance for the south-centered sectors of the basin. The observed trends for the intense (R95p) and extreme (R99p) daily rainfall show the predominance of reduction for the Southwest and central sector, followed by a significant increase in the Southeast and North sectors of the PSIW. Resumo O conhecimento da intensidade e a frequência das chuvas permitem estabelecer medidas preditivas para minimizar os impactos causados pelos altos totais de chuvas totais em uma região. Portanto, o objetivo deste trabalho é avaliar a precipitação diária para a vertente paranaense da bacia hidrográfica do rio Itararé (BHI) e verificar a tendência espaço-temporal das chuvas diárias intensas e extremas. Os dados de chuva de 14 estações pluviométricas coletadas de 1976 a 2012 foram usados com menos de 4% de falhas de dados. A análise multivariada baseada na técnica de análise de agrupamentos (AA) foi utilizada aplicando a distância euclidiana para a identificação de grupos homogêneos e a técnica de quantis para classificar as chuvas diárias. O teste de Mann-Kendall (MK) foi utilizado para identificar as tendências dos totais anuais pluviométricos, número anual de dias chuvosos (NADC) e ocorrência de chuvas intensas (R95p) e extremas (R99p). A técnica de CA identificou três grupos pluviométricos (HG I, II e III). Dada a posição latitudinal da área, a chuva no setor sul é caracterizada por suas maiores semelhanças com o clima subtropical, enquanto que no setor Norte há uma redução consistente dos totais de chuva no outono e, especialmente, durante os meses de inverno, que são características do clima tropical. O teste MK identificou a tendência de queda da NADC, com maior significância para os setores sul-centrados da bacia. As tendências observadas para as chuvas diárias intensas (R95p) e extremas (R99p) mostram a predominância de redução para o setor sudoeste e central, seguido por um aumento significativo nos setores sudeste e norte do BHI.

The variation in climate extremes at different spatial and temporal scales can be conceived as an important indicator of climate change. The focus of this study is to reveal linear trends and observe space-time (ST) variation in extreme climate indices over the Euphrates Basin in Turkey. Extreme climate indices are calculated using daily maximum, minimum, and mean temperatures, including observations of daily precipitation measured from 41 meteorological stations from 1970 to 2017. Three precipitation indices, consecutive dry days (CDD), consecutive wet days (CWD), and precipitation intensity (SDII), together with three temperature indices, number of summer days (SU), number of frost days (FD), and growing season length (GSL), are analysed. Linear trends in these extreme indices are examined using the Mann-Kendall test. The ST distribution and variation in climate indices are examined through prediction maps for this study period. Ordinary kriging (OK), which has proven to be accurate and reliable in many studies, is used to obtain prediction maps on ST framework. Results indicated that there is an evident trend in the temperature-related indices. Regarding SU and GSL, about 66% and 34% of all stations, respectively, show a significant increasing trend. The downward trend (negative Z statistic) for the FD is observed at approximately 83% of all meteorological stations, of which 35% show a significant trend. The ST variation in temperature-related extremes is evident from prediction maps; the trend is not as dominant for precipitation-related indices. In terms of ST prediction maps, the most prominent variation is observed in the south and northeast parts of the basin in CDD and CWD prediction maps from 2013 to 2017.

In Siberia, most boreal forests are located in an area with relatively moist forest soils, which makes logging activities possible exclusively during the frost period with a permanent snow cover and stable sub-zero temperatures. As the global climate is experiencing a trend towards warming, it is reasonable to suppose that the duration of the logging season might shorten over time, influencing the economic potential of Siberian forests. To test this hypothesis, we created a concept for calculating the duration of the logging season, taking into account the economic and climatic peculiarities of doing forest business in these territories. Using the long-run daily-observed climatic data, we calculated the duration of the logging season for eight representative stations in Krasnoyarsk Krai (Yeniseysk, Boguchany, Achinsk, and Minusinsk) and Irkutsk Oblast (Bratsk, Kirensk, Tulun, and Yerbogachen) in 1966&ndash, 2018. We found strong evidence of logging season duration shortening for almost all considered stations, with an uneven effect on the start and end boundaries of the season. Climate warming has almost no effect on the start date of the season in winter, but it significantly shifts the boundaries of the season end in spring. Using the autoregressive-integrated-moving average modeling (ARIMA) models, we demonstrated that, in the near future, the trends of the gradual shortening of the logging season will hold for the most part of the considered stations. The most pronounced effect is observed for the Achinsk station, where the logging season will shorten from 148.4 &plusmn, 17.3 days during the historical sample (1966&ndash, 2018) to 136.2 &plusmn, 30 days in 2028, which reflects global warming trend patterns. From an economic perspective, a shorter duration of the logging season means fewer wood stocks available for cutting, which would impact the ability of companies to enact their logging plans and lead them to suffer losses in the future. To avoid losses, Siberian forest firms will have to adapt to these changes by redefining their economic strategies in terms of intensifying logging operations.

Understanding the spatio-temporal distribution of rainfall characteristics has a major role in assessing the availability of water resources over a catchment. Therefore, it is necessary to understand the changes in rainfall characteristics using gridded precipitation data and robust statistical analysis for making decisions. In this study, the trends in rainfall and rainfall extremes over the Nagavali and Vamsadhara river basins are studied at three time steps (long-term-1901-2018, pre-1950, and post-1950) with four different Mann-Kendall (MK) tests using daily gridded rainfall data of 118 years (1901–2018). The spatial patterns of the trends are evaluated with the kriging interpolation method. Magnitude in rainfall and rainfall extremes (CDD, CWD, PRCPTOT, R10MM, R20MM, R40MM, R95PTOT, RX1DAY, and RX5DAY) are analyzed using the Sen’s slope method. Except in the monsoon season, a decreasing trend is observed in all the rainfall extremes in post-1950 compared to pre-1950 period. Whereas, in the monsoon an increasing trend is observed for the extremes in post-1950 period. Overall period (i.e, 1901–2018) an increasing trend is observed for rainfall and rainfall extremes in the pre-monsoon (March–May), monsoon (June–Sep) seasons and a decreasing trend in the winter season (Dec–Feb) for both the basins. No obvious trends are evident in the post-monsoon season (Oct–Nov). At the annual scale, rainfall and rainfall extremes exhibited an increasing trend. Overall, the Nagavali basin experienced more extreme rainfall events indicating the higher vulnerability of floods while the middle and lower portions of the Vamsadhara basin shown increase in extremes. When linked with hydrological analysis, insights gained from this study are useful for flood vulnerability mapping and risk assessment for both the basins. The research described in this paper is carried out with fund by Ministry of Human Resource Development (MHRD), Government of India under Scheme for Promotion of Academic and Research Collaboration (SPARC) through project number P270. The fourth author’s (V. Sridhar) effort was funded in part by the Virginia Agricultural Experiment Station (Blacksburg) and through the Hatch Program of the National Institute of Food and Agriculture at the United States Department of Agriculture (Washington, DC).

In this study, MODIS normalized difference vegetation index (NDVI), TRMM3B43 precipitation, and MOD11A2 land-surface temperature (LST) data were used as data sources in an analysis of temporal and spatial characteristics of vegetation changes and ecological environmental quality in the Huaihe River basin, China, from 2003 to 2018. The Mann&ndash, Kendall (MK) non-parametric test and the Theil&ndash, Sen slope test were combined for this analysis, then, when combined with the results of the MK mutation test and two introduced indexes, the kurtosis coefficient (KU) and skewness (SK) and correlations between NDVI, precipitation (TRMM), and land-surface temperature (LST) in different time scales were revealed. The results illustrate that the mean NDVI in the Huaihe River basin was 0.54. The annual NDVImax curve fluctuations for different land cover types were almost the same. The main reasons for the decrease in or disappearance of vegetation cover in the Huaihe River basin were the expansion of towns and impact of human activities. Furthermore, vegetation cover around water areas was obviously degraded and wetland protections need to be strengthened urgently. On the same time scale, change trends of NDVI, TRMM, and LST after abrupt changes became consistent within a short time period. Vegetation growth was favored when the KU and SK of TRMM had a close to normal distribution within one year. Monthly TRMM and LST can better reflect NDVI fluctuations compared with seasonal and annual scales. When the precipitation (TRMM) is less than 767 mm, the average annual NDVI of different land cover types is not ideal. Compared with other land cover types, dry land has stronger adaptability to changes in the LST when the LST is between 19 and 22.6 &deg, C. These trends can serve as scientific reference for protecting and managing the ecological environment in the Huaihe River basin.

In order to assess the evolution of aerosol parameters affecting climate change, a long-term trend analysis of aerosol optical properties was performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann–Kendall (MK) statistical test associated with several pre-whitening methods and with Sen’s slope was used as the main trend analysis method. Comparisons with general least mean square associated with autoregressive bootstrap (GLS/ARB) and with standard least mean square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficient trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficient time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, eastern/northern Europe and the Arctic, 22 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 26 % of sites have trends which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10-year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10-year trends are primarily found for earlier periods (10-year trends ending in 2010–2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10-year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10-year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10-year trends of the scattering coefficient – there is a shift to statistically significant negative trends in 2009–2012 for all stations in the eastern and central USA. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage provides insight into potential aerosol effects on climate changes., European Union (EU) 654109, ACTRIS PPP project 739530, IMPROVE, Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air pollutants in Europe (EMEP) under UNECE, Korea Meteorological Administration Research and Development Program "Development of Monitoring and Analysis Techniques for Atmospheric Composition in Korea" KMA2018-00522, "Arctic Monitoring and Assessment Programme" (AMAP) under EU action "Black Carbon in the Arctic" 80026, Norwegian Environment Agency, Basic Science Research Program through the National Research Foundation of Korea 2017R1D1A1B06032548, European Union (EU) 262254, European Union's Horizon 2020 research and innovation programme under project ACTRIS-2 654109, European Union's Horizon 2020 research and innovation programme under project iCUPE 689443, Academy of Finland 307331 264242 268004 284536 287440, AEMET, Swiss State Secretariat for Education, Research and Innovation, SERI 15.0159-1, Taiwan Environmental Protection Administration, Ministry of Science and Technology, European Union's Horizon 2020 research and innovation programme 654109, MINECO (Spanish Ministry of Economy, Industry and Competitiveness), FEDER fund under the PRISMA project CGL2012-39623-C02/00, FEDER fund under the HOUSE project CGL2016-78594-R, Generalitat de Catalunya AGAUR 2014 SGR33 AGAUR 2017 SGR41, Business Finland 2634/31/2015, Ramon y Cajal Fellowship - Spanish Ministry of Economy and Competitiveness RYC-2013-14036, Department of Biotechnology (DBT) India 2634/31/2015, Academy of Finland 307331, National Oceanic Atmospheric Admin (NOAA) - USA, ACTRIS-France National Research infrastructure, CNRS-INSU long-term observing program, Spanish Ministry of Economy and Competitiveness CGL2016-81092-R CGL2017-90884-REDT RTI2018-101154-A-I00, National Natural Science Foundation of China (NSFC) 41675129, National Key Project of the Ministry of Science and Technology of the People's Republic of China 2016YFC0203305 2016YFC0203306, Basic Research Project of the Chinese Academy of Meteorological of Sciences 2017Z011, Knut-and-AliceWallenberg Foundation within the ACAS project (Arctic Climate Across Scales) 2016.0024, CPR: Para La Naturaleza and the nature reserve of Cabezas de San Juan and the support of grants AGS 0936879 and EAR1331841.

In the context of climate changes, knowing the low-flow trends is very important for establishing appropriate measures for water resources management, in order to ensure their sustainability. This paper focuses on Romanian rivers and aims to identify the recent trends (during the period 1980-2013) in the low-flow variability. The analysis is based on discharges data series (daily and monthly) recorded at 54 gauging stations, with a quasi-natural flow regime. The significance of trends for annual, monthly and seasonal low-flow in the analyzed period has been established using the nonparametric Mann-Kendall test. The variability of the lowest annual values of the mean daily and monthly discharges showed positive trends at gauging stations located mainly in the Carpathian area, while negative trends were found in lowland regions (plains and tablelands). During the winter there were identified positive low-flow trends, while negative trends were found in summer and spring. Increases in the minimum monthly flow were particularly evident in February, March and December, and negative trends were identified especially in the summer (July, June and August) and the autumn months (September and October).

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.

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.

This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p &lt, 0.05 to be statistically significant. We observed significant (p &lt, 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p &lt, 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p &gt, 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan.

Rising temperature and shifting precipitation patterns due to climate change are likely to intensify droughts throughout the world. Understanding the drought characteristics of possible future scenarios under climate change requires verification of past drought events using appropriate drought indices. Consequently, this study investigates the application of two widely used drought indices, the standardized precipitation index (SPI) and standardized streamflow index (SSI), to characterize historical droughts, drought trends, and their impact on water quality and stream integrity for a selected study basin in New Jersey. Results indicated that both SPI and SSI were able to identify historical drought events, including three drought emergency periods and the most recent drought-watch periods. A significant positive meteorological drought was observed at the western side of the basin, whilst a significant positive hydrological drought was found in the eastern side. The average pollutant concentration of drought periods were lesser than non-drought periods due to reduction of different processes, such as erosion and transport of sediment and nutrients into rivers and streams, during drought periods as opposed to non-drought periods. The findings from this study will serve to bolster the ongoing efforts to formulate better drought management strategies for future climate change in the Raritan Basin.

The article analyses the values of daily, monthly and annual precipitation measured during the period 1948–2019 at the following four stations: (1) Split, (2) Hvar, (3) Lastovo and (4) Zagreb. The first three stations are located in a Mediterranean climate, while the station in Zagreb is located in a continental climate. The aim of the performed analyses is to detect non-stationarity (trends, jumps, and seasonality) in the precipitation regime at three-time scales (day, month, and year) over the period of the last 72 years (1948–2020). Numerous previous analyses at all four stations showed statistically significant increases in air temperature, which were particularly amplified in the late 1980s by the effect of global warming. Expressed as a percentage of the total annual precipitation at all four analysed locations, the presence of an increasing trend was calculated. The analyses carried out in this work showed that there was a redistribution of precipitation during the year, a decrease in the number of days with precipitation and an intensification of precipitation in both climatic regions. Over the past 73 years, the number of days with precipitation per year has slowly decreased. The number of days with intense precipitation, P ≥ 32.0 mm, has become more frequent.

It is important to understand variations in hydro-meteorological variables to provide crucial information for water resource management and agricultural operation. This study aims to provide comprehensive investigations of hydroclimatic variability in the Bilate watershed for the period 1986 to 2015. Coefficient of variation (CV) and the standardized anomaly index (SAI) were used to assess the variability of rainfall, temperature, and streamflow. Changing point detection, the Mann–Kendell test, and the Sen’s slope estimator were employed to detect shifting points and trends, respectively. Rainfall and streamflow exhibited higher variability in the Bega (dry) and Belg (minor rainy) seasons than in the Kiremt (main rainy) season. Temperature showed an upward shift of 0.91 °C in the early 1990s. Reduction in rainfall (−11%) and streamflow (−42%) were found after changing points around late 1990s and 2000s, respectively. The changing points detected were likely related to the ENSO episodes. The trend test indicated a significant rise in temperature with a faster increase in the minimum temperature (0.06 °C/year) than the maximum temperature (0.02 °C/year). Both annual mean rainfall and streamflow showed significant decreasing trends of 8.32 mm/year and 3.64 mm/year, respectively. With significant increase in temperature and reduction in rainfall, the watershed has been experiencing a decline in streamflow and a shortage of available water. Adaptation measures should be developed by taking the increasing temperature and the declining and erratic nature of rainfall into consideration for water management and agricultural activities.

Surface waters, especially rivers are the most important sources of water supply for drinking and agricultural purposes. Water with desirable quality is necessary for human life. Therefore, knowledge of water quality and its temporal changes is of particular importance in sustainable management of water resources. In this study, available data during 20 years from two hydrometry stations located in the way of Horroud River in Lorestan province were used and analyzed using Aq.QA software. Piper, Schoeller, Stiff, and Wilcox diagram were drawn and Mann–Kendal test was used for determining data trend. According to Wilcox diagram, water of this river in both stations is placed in c2s1 class which is good for agricultural purposes, and according to Schoeller diagram, there is no restrict for drinking purposes. Results of Man–Kendal test show increasing trend for colorine, EC, TDS while decreasing trend for potassium in Kakareza station. On the other hand in Dehnu station, positive trend was seen in calcium and colorine while negative trend for sulfate and potassium. For other variables, no specific trend was found.

This paper pursues two objectives: first, to determine the trends of seasonal and annual precipitation in the Canary Islands and, second, to identify trends in the daily precipitation concentration index (CI). For the first objective, we used data from 1970-2013 of 23 rainfall stations located on different islands, after verifying the homogeneity of their series. For the second, the sample was reduced to eleven series since deficiencies in data records of less than 1 mm of daily precipitation were appreciated. We used the nonparametric Mann-Kendall test to determine whether the series showed linear trends in annual and seasonal precipitation and in the values of CI. The seasonal results showed negative trends in spring and winter in almost all the time series considered, especially in the north of Gran Canaria and Tenerife. Conversely, 78% of the series in autumn recorded an increase in the precipitation. The annual balance indicated a decline of rainfall in most of the locations, because of the high concentration of precipitation in winter. Finally, the majority of the time series exhibited a trend toward a greater concentration of daily rainfall, in particular those series located in areas where the main towns are settled, which is an important issue to consider because of severe flooding and other geomorphological processes.

This paper deals with the occurrence of hydroclimatic extremes in the upper Hron River basin in Slovakia in 1951/61–2010. Select trends in hydroclimatic parameters in 1931/61–2010 are also studied. Emphasis is placed on the occurrence, frequency, and seasonality of dry episodes and flood events. The de Martonne index, the relative precipitation index, base flow index, low flow index, linear regression, the Mann-Kendall test and IHA software were used in the analyses. Mann-Kendall test pointed to significant changes in runoff of the upper Hron River basin. The annual runoff has decreased. Changes in minimums and maximums have had a fundamental influence on this decrease, particularly in the cold half year. Major changes occurred in Q1, QMax, Q75pct and 1-day, 3-day and 7-day maximum values. Approximately since the 1980s there has been a decrease in discharge events equal to or greater than one-year flood Q1. Events where discharges were equal or greater than Q5 occurred only in the first period 1951–1980 (in 1954 and 1974). The de Martonne index, the relative precipitation index and the low flow index show similar results, the longest aboveaverage period of annual values reached from 2007 to 2010 and the longest below-average period from 1990 to 1993.

In recent years, the climate in the arid region of Northwest China has become warmer and wetter, however, glaciers in the north slope of the West Kunlun Mountains (NSWKM) show no obvious recession, and river flow is decreasing or stable. This contrasts with the prevalent response of glaciers to climate change, which is recession and initial increase in glacier discharge followed by decline as retreat continues. We comparatively analyzed multi-timescale variation in temperature&ndash, precipitation&ndash, snow cover-runoff in the Yarkant River Basin (YRK), Karakax River Basin (KRK), Yurungkax River Basin (YUK), and Keriya River Basin (KRY) in the NSWKM. The Mann&ndash, Kendall trend and the mutation&ndash, detection method were applied to data obtained from an observation station over the last 60 years (1957&ndash, 2017) and MODIS snow data (2001&ndash, 2016). NSWKM temperature and precipitation have continued to increase for nearly 60 years at a mean rate of 0.26 &deg, C/decade and 5.50 mm/decade, respectively, with the most obvious trend (R2 &gt, 0.82) attributed to the KRK and YUK. Regarding changes in the average snow-cover fraction (SCF): YUK (SCF = 44.14%) &gt, YRK (SCF = 38.73%) &gt, KRY (SCF = 33.42%) &gt, KRK (SCF = 33.40%). Between them, the YRK and YUK had decreasing SCA values (slope &lt, &minus, 15.39), while the KRK and KRY had increasing SCA values (slope &gt, 1.87). In seasonal variation, the SCF of the three of the basins reaches the maximum value in spring, with the most significant performance in YUK (SCF = 26.4%), except for YRK where SCF in spring was lower than that in winter (&minus, 2.6%). The runoff depth of all river basins presented an increasing trend, with the greatest value appearing in the YRK (5.78 mm/decade), and the least value in the YUK (1.58 mm/decade). With the runoff response to climate change, temperature was the main influencing factor of annual and monthly (summer) runoff variations in the YRK, which is consistent with the runoff-generation rule of rivers in arid areas, which mainly rely on ice and snow melt for water supply. However, this rule was not consistent for the YUK and KRK, as it was disturbed by other factors (e.g., slope and slope direction) during runoff generation, resulting in disruptions of their relationship with runoff. This research promotes the study of the response of cold and arid alpine regions to global change and thus better serve regional water resources management.

Assessing forest degradation has been a challenging task due to the generally slow-changing nature of the process, which demands long periods of observation and high frequency of records. This research contributes to efforts aimed at detecting forest degradation by analyzing the trend component of the time series of Leaf Area Index (LAI) collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Central Mexico from 2002 to 2017. The analysis of the trend component is proposed to overcome the challenge of identifying very subtle and gradual changes that can be undetected if only the raw time series is examined. Additionally, the use of LAI as an alternative to other widely used indexes (e.g., Normalize Difference Vegetation Index and Enhanced Vegetation Index) facilitates consideration of the structural changes evident from degradation though not necessarily observable with spectral indices. Overall, results indicate that 52% of the study area has experienced positive trends of vegetation change (i.e., increasing LAI), 37% has remained unchanged, and 11% exhibits some level of forest degradation. Particularly, the algorithm estimated that 0.6% (385 km2) is highly degraded, 5.3% (3406 km2) moderately degraded, and 5.1% (3245 km2) slightly degraded. Most of the moderate and highly degraded areas are distributed over the east side of the study area and evergreen broadleaf appears to be the most affected forest type. Model validation resulted an accuracy of 63%. Some actions to improve this accuracy are suggested, but also a different approach to validate this type of study is suggested as an area of opportunity for future research.

Prolonged and frequent droughts in Southern California present hazards and uncertainty for the region&rsquo, s increasing population, resulting in proactive and aggressive water management strategies. The goal of this study is to present a case study of the San Diego region&rsquo, s rainfall and temperature time series analysis in order to determine annual and seasonal trends and their significance. Rainfall and temperature data from 20 rain-gauged stations were analyzed for the period 1985&ndash, 2017. A project database was set up for data compilation and quality control, and a Mann-Kendall test for trend analysis was used. Results indicated that rainfall in the region decreased both annually and during the rainy season (November&ndash, April) by up to 0.14 mm between 1985 and 2017, although not in a statistically significant manner, except at two rainfall observation stations. Rainfall appears to have increased in many of the stations examined during the dry season (May&ndash, October), with an average magnitude of 0.09 mm. Analysis of daily minimum and maximum temperature reveals overall average annual and seasonal increases of 0.07 &deg, C and 0.04 &deg, C, respectively, with statistically significant increases at 10 of 17 for minimum temperature, and 0.27 &deg, C and &minus, 0.25 &deg, C with statistically significant increases at 9 of 16 for maximum temperature. Temperature tends to have increased more during the dry season compared to the rainy season. This study reveals an overall decreasing tendency in rainfall and an increasing tendency in minimum and maximum temperatures (although not statistically significant) in the San Diego region between 1985 and 2017, which likely contributed to important management implications for the region&rsquo, s water resources.