Mann-Kendall Method Research Articles

Post-fire vegetation dynamic patterns and drivers in Greater Hinggan Mountains: Insights from long-term remote sensing data analysis

Fire has become a major disturbing factor in boreal forests, and giant forest disturbances play a vital role in regulating the climate under global warming. Therefore, it is essential to investigate the spatiotemporal patterns and main drivers of post-fire vegetation recovery for forest ecological research and post-fire recovery management. However, previous studies have focused on the post-fire forest change within the entire fire perimeter, lacking separate analysis and comparison of the burned zone (BZ) and unburned zone (UNBZ). Here, we propose the utilization of Moderate Resolution Imaging Spectroradiometer land cover type and vegetation index data to monitor vegetation dynamics and explore its drivers after the most serious forest fire in the history of P.R. China in the Greater Hinggan Mountains (GHM). The temporal and spatial patterns of vegetation recovery in the BZ/UNBZ in the GHM were analyzed using the Sen & Mann-Kendall method, Hurst index and coefficient of variation, and their driving mechanisms were explored using GeoDetector and geographically weighted regression. The results showed that there were significant differences in the spatial distribution and fluctuation of vegetation between the BZ and UNBZ, and that the BZ exhibited higher productivity and vigor. Vegetation recovery was influenced by different dominant factors and changed over time, in which land surface temperature and precipitation dominated all the time, whereas topographic relief and elevation had a more significant contribution to vegetation recovery in the BZ and UNBZ, respectively. This study provides a scientific basis for the protection and management of vegetation in disturbed forested areas, particularly after fires.

Spatial and Temporal Characteristics of Fractional Vegetation Cover and Its Response to Urbanization in Beijing

Exploration of the spatiotemporal changes in fractional vegetation cover （FVC） and its response characteristics to urbanization is of great significance for urban ecological protection and planning in Beijing. This study analyzed the spatiotemporal characteristics of vegetation cover changes in Beijing from 2000 to 2020 using the Theil-Sen Median and Mann-Kendall methods based on a long-term time series vegetation cover dataset. Then, this study used the urbanization index as a key indicator of spatial urbanization and utilized the transect line and global grid analysis methods to investigate the response characteristics of FVC to different urbanization gradients. The results indicated that： ① FVC changes showed spatial and temporal heterogeneity. From 2000 to 2020, Beijing was predominantly covered by high vegetation, accounting for 65.22% of the total area, which was mainly distributed in ecological conservation areas consistent with the Jundu, Xishan, and Yaji Mountain ranges. The FVC presented an overall positive development trend, with a decreasing trend of areas with low FVC. The increase in FVC was significant （by 28.68%）, mainly distributed in ecological conservation areas and within a range of 10-12 km in concentric circles centered around Tiananmen Square. The urbanization index and FVC change rate were relatively high in Haidian District, Chaoyang District, Fengtai District, Shijingshan District, and Changping District. ② The artificial land surface in 2000, 2010, and 2020 was 9.69%, 13.64%, and 21.19%, respectively, with significant spatial agglomeration and strong spatial heterogeneity. During the urbanization process in Beijing, the increase in artificial land surface reached 11.5%, with the conversion from arable land to artificial land surface accounting for 53.83% of the total land use conversion area. ③ There was a significant negative correlation between FVC and the urbanization index, indicating that urbanization had a negative impact on regional FVC. However, as the urbanization process stabilized, this negative correlation tended to gradually weaken. Although the central urban areas were mainly characterized by low FVC, there was a significant increasing trend in the FVC, indicating a positive development in the FVC and an improvement in regional ecological quality, which was closely related to the governance of the mountain-water-forest-field-lake-grass-sand system. The results of the study can provide a basis for the development of vegetation restoration programs and ecological management measures in Beijing.

Procedure for detecting drought trends using Şen’s innovative trend analysis methodology

The increasing occurrence of drought has negative effects on water resources. To prevent these negative effects, it is of great importance to know drought trends over time. Many methods are used in the literature to determine the severity of drought, one of which is the standard precipitation index (SPI), which is calculated based on precipitation data. The SPI method was chosen in this study because it is widely used in the literature for its simplicity, flexibility and effectiveness in characterising drought duration and intensity. There are different classifications of drought severity in the SPI method, so it is very important to know the individual trends for each classification. Classical trend detection methods (such as the Mann–Kendall method) require a separate analysis for each drought classification. However, using Şen’s innovative trend analysis, it becomes possible to determine the trends for all drought classifications on a single graph. In this way, the change of drought events over time can be easily determined for all drought classifications.

Rainfall analysis in Xingu River Basin based on the 1981-2020 timeframe

It is essential understanding the incidence of hydrometeorological variables in each river basin to help planning actions focused on guaranteeing multiple water uses, environmental preservation and prevention measures taken against extreme events. The aim of the current study is to investigate rainfall trends in Xingu River Hydrographic Basin (XRHB) from 1981 to 2020. Data propensity analysis was carried out based on the Mann-Kendall methods, on five-year moving average graph, as well as on variations in Climatological Normals (CN) recorded from 1981 to 2010 and from 1991 to 2020. Moreover, the Log-Normal theoretical distribution was adjusted to show mean rainfall predictions within 10-to-100-year return time (Rt). It was done by applying the Kolmogorov-Smirnov (KS), Chi-Square (?2), Filliben (Fi) and Anderson-Darling (AD) tests. Results have evidenced historical series with no trend and minimal variation (-0.5%) between the two CN intervals. Estimates within a 10-to-100-year RT scenario have evidenced rainfall rates higher than the historical average (HA) ranging from 10.0% to 20.0%. Thus, XRHB is a promising scenario for water security planning purposes, since it meets the fundamentals of Brazilian environmental and water resources laws, as well as target 6.5 of Sustainable Development Goal 6 (SDG 6 - UN), which deals with implementing integrated water-resources management at global level.

Variations of Terrestrial Net Ecosystem Productivity in China Driven by Climate Change and Human Activity from 2010 to 2020

Net ecosystem productivity (NEP) plays an important role in the quantitative evaluation of carbon source/sinks in terrestrial ecosystems. This study used Theil–Sen median trend analysis, the Mann–Kendall method, and the Geodetector model to analyze the variation patterns and its dominant factors of NEP from 2010 to 2020. The results showed the following: (1) During 2010–2020, the spatial distribution of carbon sinks in China’s terrestrial ecosystems showed a pattern of high in the southeast and low in the northwest. The area with NEP < 0 accounted for 44.74% of the total area, while the area with NEP > 0 accounted for 55.26%. (2) The northwest region belonged to the significant carbon source, while the other regions belonged to significant carbon sinks. (3) The annual average NEP in different sub-regions showed an increasing trend. During 2010–2020, the overall NEP in China showed a trend in shifting from low-level to high-level, indicating that the NEP of terrestrial ecosystems in China increased during the past 11 years. (4) The NEP gravity center in Northeast China showed a trend in moving southward and then northward, while that of the NEP gravity center in East China showed a circular migration trend of ‘northwest-southwest–northeast–southeast’. The gravity center of NEP in Northwest China was moving northeastward. The migration trajectory of the NEP gravity center in Southwest China presented a “Z” shape. The change in the gravity center of NEP in the central and southern regions had a strong circuitous nature, and the overall trend was to migrate southward. (5) The combined actions of climate change and human activities were the main reason for the change in NEP in China’s terrestrial ecosystem from 2010 to 2020. (6) There were obvious differences in the dominant driving factors of NEP evolution in different regions and different periods in the past 40 years.

Analysis of spatial and temporal variation of frost dates in Jilin Province

In order to understand the changing law of frost date (number) in Jilin Province, and to improve the early warning and forecasting ability of frost disaster, Based on the day-by-day minimum temperature data from 47 meteorological observation stations in Jilin region from 1969 to 2020, the spatial and temporal distribution characteristics of frost date (number) were analyzed by using linear propensity ratio, Mann-Kendall method and sliding t-test, as well as REOF. The results show that: the first frost date, the last frost date, and the number of frost-free days follow the general spatial distribution pattern of "early in the northwest and late in the southeast," "late in the southeast and early in the northwest," and "long in the northwest and short in the southeast". The overall trend of frost dates is delayed first frost date, and early final frost date and prolonged frost-free days. The years with abrupt changes in the first frost date, final frost date and number of frost-free days were 2004, 1997 and 1991, respectively. The number of frost-free days in Jilin Province was categorized into 3 regions based on REOF analysis. It can be seen that analyzing the spatio-temporal variation rule of frost can provide theoretical basis for frost prevention and disaster reduction.

Airborne particulate matter integral assessment in Magdalena department, Colombia: Patterns, health impact, and policy management

The relevance of atmospheric particulate matter (PM) to health and the environment is widely known. Long-term studies are necessary for understanding current and future trends in air quality management. This study aimed to assess the long-term PM concentration in the Magdalena department (Colombia). It focused on the following aspects: i) spatiotemporal patterns, ii) correlation with meteorology, iii) compliance with standards, iv) temporal trends over time, v) impact on health, and vi) impact of policy management. Fifteen stations from 2003 to 2021 were analyzed. Spearman-Rho and Mann-Kendall methods were used to correlate concentration with meteorology. The temporal and five-year moving trends were determined, and the trend magnitude was calculated using Teil-Sen. Acute respiratory infection odd ratios and risk of cancer associated with PM concentration were used to assess the impact on health. The study found that the maximum PM10 concentration was 194.5 μg/m3, and the minimum was 3 μg/m3. In all stations, a negative correlation was observed between PM10 and atmospheric water content, while the wind speed and temperature showed a positive correlation. The global trends indicated an increasing value, with five fluctuations in five-year moving trends, consistent with PM sources and socio-economic behavior. PM concentrations were found to comply with national standard; however, the results showed a potential impact on population health. The management regulation had a limited impact on increasing concentration. Considering that national regulations tend to converge towards WHO standards, the study area must create a management program to ensure compliance.

Spatial and Temporal Trends in Precipitation and Temperature and their Influence on Groundwater in Ballia

A study examined the impact of long-term pre- and post-monsoon precipitation and temperature on groundwater level fluctuations in 17 blocks of Ballia District. The study used 100 years of daily precipitation data (1917-2016) and 62 years of daily temperature data (1951-2012) from the Indian Meteorological Department. Seasonal analysis was performed using pre-monsoon, monsoon, post-monsoon, and winter data. The Mann-Kendall method and Sen's slope were applied. The spatial variability of rainfall and temperature was mapped using the IDW technique in ArcGIS. Significant annual precipitation decreases were found in Murlichapra and Sear blocks. Maniar and Pandah blocks showed precipitation increases. An increasing pre-monsoon trend was observed in several blocks, while post-monsoon trends varied. Groundwater levels fluctuated across Ballia, with a notable decrease of 2.1 m in Bairia Block from 2006 to 2016.

In the Qaidam Basin, Soil Nutrients Directly or Indirectly Affect Desert Ecosystem Stability under Drought Stress through Plant Nutrients.

The low nutrient content of soil in desert ecosystems results in unique physiological and ecological characteristics of plants under long-term water and nutrient stress, which is the basis for the productivity and stability maintenance of the desert ecosystem. However, the relationship between the soil and the plant nutrient elements in the desert ecosystem and its mechanism for maintaining ecosystem stability is still unclear. In this study, 35 sampling sites were established in an area with typical desert vegetation in the Qaidam Basin, based on a drought gradient. A total of 90 soil samples and 100 plant samples were collected, and the soil's physico-chemical properties, as well as the nutrient elements in the plant leaves, were measured. Regression analysis, redundancy analysis (RDA), the Theil-Sen Median and Mann-Kendall methods, the structural equation model (SEM), and other methods were employed to analyze the distribution characteristics of the soil and plant nutrient elements along the drought gradient and the relationship between the soil and leaf nutrient elements and its impact on ecosystem stability. The results provided the following conclusions: Compared with the nutrient elements in plant leaves, the soil's nutrient elements had a more obvious regularity of distribution along the drought gradient. A strong correlation was observed between the soil and leaf nutrient elements, with soil organic carbon and alkali-hydrolyzed nitrogen identified as important factors influencing the leaf nutrient content. The SEM showed that the soil's organic carbon had a positive effect on ecosystem stability by influencing the leaf carbon, while the soil's available phosphorus and the mean annual temperature had a direct positive effect on stability, and the soil's total nitrogen had a negative effect on stability. In general, the soil nutrient content was high in areas with a low mean annual temperature and high precipitation, and the ecosystem stability in the area distribution of typical desert vegetation in the Qaidam Basin was low. These findings reveal that soil nutrients affect the stability of desert ecosystems directly or indirectly through plant nutrients in the Qaidam Basin, which is crucial for maintaining the stability of desert ecosystems with the background of climate change.

A new fuzzy method for investigating the effects of dam on aquifer: case study of Rudbal dam, south of Iran

Dam construction has some qualitative and quantitative effects on groundwater resources. This effect may be in the form of an increasing groundwater table or a changing groundwater system. In this paper, the effect of the Rodbal dam construction on the Darab aquifer was investigated. For this paper water table levels from observation wells and precipitation data was used. The study aims to analyse the behaviour of the water table during precipitation by employing a combination of the standardisation process, Fuzzy Inference System (FIS), and Root Mean Square Error (RMSE) calculations. Fuzzy logic involves the fuzzification of input data, transforming precise values into fuzzy sets. The effectiveness of the FIS is highlighted, particularly in determining the number of membership functions for inputs. The performance of the results is assessed using indicators such as RMSE and Coefficient of Determination (R2). The FIS showed a high level of effectiveness in performance assessment, exhibiting a 70% similarity between the fuzzy and Mann–Kendall methods. Nonetheless, the Fuzzy Purpose Method corresponded more closely with the observed data, indicating a more accurate reflection of reality. The findings indicate that for P3, P7, and P8, the results from the Mann–Kendall method do not show a discernible trend. Conversely, the proposed Fuzzy method accounts for changes in the behaviour of these piezometers.

Investigation of the variability applying classical (MK-SR) and modern (ITTA-TPSC) trend methods to meteorological parameters of Marmara Basin in Turkey

Scientific studies for countries experiencing climate change have accelerated recently. Turkey is among the countries experiencing climate change. Studies carried out for this country or its basins are of great importance both for the basin and the country. Therefore, Marmara Basin, where Turkey's population density is highest and industrialization is at the most advanced level, is selected in this study. The length of meteorological data is 45 years. The analysis of these data is made with Mann-Kendall (MK) and Spearman Rho (SR), which are classical trend methods, and Innovative Triangle Trend Analysis (ITTA) and Trend Polygon Star Concept (TPSC), which are modern trend methods. When the studies on Marmara basin are examined, there is no study that includes these four methods. Therefore, this study stands out in this respect. Because these analysis methods will reveal a new idea by applying them to hydro-meteorological data within the basin area. Before applying MK method, serial correlation method is applied to the meteorological parameter data of all stations. When the analysis results are examined; a general increasing trend is observed in precipitation data for ITTA and TPSC methods. No trend is observed in precipitation data for MK and SR methods. A general increasing trend is observed in temperature data for ITTA, MK and SR methods. However, a generally decreasing trend is observed in temperature data for TPSC method. While there is generally no trend in relative humidity data for MK and SR methods, an increasing trend is observed for ITTA and TPSC methods.

Characteristics and causes of water level variations in the Chenglingji–Jiujiang reach of the Yangtze River following the operation of the Three Gorges Dam

ABSTRACT Water level adjustment downstream of dams significantly impacts river regimes and flood control. However, due to constant strong scouring, our quantitative understanding of the characteristics of water level variations and their causes in the Chenglingji–Jiujiang Reach of the Yangtze River remains limited. Here, we analyzed the water level change trend via the Mann–Kendall method and analyzed geomorphic change and river resistance using 406 cross-sectional profiles as well as data on discharge and water levels from 1991 to 2022. Results showed that the critical conversion discharges (CCD) in the Chenglingji-Hankou Reach and the Hankou-Jiujiang Reach were approximately 35,000 and 30,000 m3/s, respectively, after the operation of the Three Gorges Dam. The water level exhibited an overall decline mainly due to river erosion when the discharge was lower than the CCD. The water level exhibited a nonsignificant upward trend mainly due to increased river resistance (7–20%) when the discharge was higher than the CCD. The obvious increase in the floodwater level in individual years was caused by the effect of downstream water level increase. Our findings further the understanding of downstream geomorphic response to dam operation and their impacts on water levels and have important implications for flood management in such rivers worldwide.

Assessment of Deadly Heat Stress and Extreme Cold Events in the Upper Midwestern United States

Understanding and addressing the implications of extreme temperature-related events are critical under climate change, as they directly impact public health and strain energy infrastructure. This study delved into the critical assessment of deadly heat stress and extreme cold events in the Upper Midwestern United States (UMUS), from 1979 to 2021, recognizing the substantial and disparate impact these phenomena have on socially vulnerable communities. In the current study, the modified Mann–Kendall method was applied to understand the temporal trend of extreme heat stress, as well as extreme cold events, from 1979 to 2021 in the UMUS. The results showed that the average annual frequency of daytime extreme heat stress events was comparatively lower in the northern parts of the UMUS compared to the southern parts from 1979 to 2021. Furthermore, a significant increasing trend in daytime extreme heat stress was found in parts of Michigan, Wisconsin (around the lake region), Ohio, and lower parts of Indiana and Kentucky from 1979 to 2021. In contrast, a decreasing trend was noticed in western parts of the UMUS (parts of Minnesota, Iowa, and Missouri). A significant decreasing trend in extreme cold events was found throughout the UMUS from 1979 to 2021. However, an increasing trend was also noticed in Iowa and northern parts of Minnesota, Michigan, and Wisconsin. The results provide important insights for better understanding the unique risks posed by extreme temperature-related events, especially toward socially vulnerable communities in the UMUS, which is crucial for developing targeted interventions and fostering resilience in the face of escalating climate-related threats.

Identification of Key Areas for Ecological Conservation and Restoration based on Multi-source Data and Remote Sensing Time Series Analysis

Abstract. Ecological conservation and restoration of national land space is an important aspect for implementing the national ecological civilization strategy, and an important measure for establishing the national ecological security pattern and coordinating the systematic management of mountains, water, forests, fields, lakes, grass and sand. The identification of key areas for ecological conservation and restoration is a precondition to spatially and temporally laying out ecological conservation and restoration planning, which is crucial for the ecological conservation and restoration of national land space. Therefore, this paper considers Henan Province as the study area and carries the research and practice of identifying key areas for ecological conservation and restoration by integrating multi-source data and remote sensing time series analysis. Firstly, based on the Google Earth Engine (GEE) cloud platform and MOD13A1 data, the Mann-Kendall method is used to analyze the trend of time series NDVI in the study area from 2011 to 2020. Secondly, based on multi-source data such as meteorological, soil, topographic, net primary production (NPP), etc., an ecosystem health analysis and assessment based on ecosystem service trade-off and synergy is used to select ecological source. Finally, based on the results of time series NDVI analysis and ecological source selection, fusion analysis is used to identify key areas for ecological conservation and restoration. The results show that this proposed research framework not only considers the “static” ecosystem services and ecosystem health attributes, but also measures the “dynamic” ecosystem change trends. It can effectively identify key areas for ecological conservation and restoration in national space. The results of the study can provide technical support for the background survey, problem identification, planning and engineering layout of ecological conservation and restoration in the national land space.

Application of Mann Kendal Sen's Slope Estimator in Trend Analysis of Historical And Future Precipitation and Temperature in the Kilombero River Basin

This study examines historical (1981-2020) and future (2020-2070) trends in rainfall and temperature in the Kilombero Basin using the Mann-Kendall method with Sen's slope estimator. Data were obtained from the Tanzania Meteorological Agency and from simulated historical and future climate data sourced from the Coupled Model Intercomparison Project 6 (CMIP6). The CMIP6 datasets were downscaled and bias-corrected using the CMhyd tool. The basin exhibited a bimodal rainfall pattern with an average of 1400 mm, peaking around April. The CMIP6 models successfully simulated monthly rainfall, Tmax, and Tmin at most stations. No definitive trends in rainfall were observed, but Tmax and Tmin showed significant increases under both SSP2-4.5 and SSP5-8.5 scenarios. More warming is predicted under SSP5-8.5 by the mid-21st century, raising Tmax and Tmin at all stations. This rise in temperature could potentially increase evapotranspiration demand, negatively impacting freshwater availability. The average annual rainfall showed a slightly increasing trend post-2000, from 1403.96mm/year (1981-1999) to 1433.38mm/year (2000-2020), an increase of 2.05%. Sen's slope analysis, however, revealed varying trends across stations, with most showing a decreasing trend. Notably, only Ulanga Met Station showed a significant increasing trend with a slope value of 14.70 and a p-value below 0.05. The study concluded that both temperature and precipitation in the Kilombero Basin are on the rise.

Hydrogeological trends in an alluvial valley in the Brazilian semiarid: Impacts of observed climate variables change and exploitation on groundwater availability and salinity

Study regionMimoso Alluvial Valley, Semiarid Brazil. Study focusThis study aims to assess the influence of climate variability and exploitation on groundwater accessibility, quantity and quality, based on a spatiotemporal data analysis from long-term monitoring field campaigns, conducted monthly from 2000 to 2019. This study successfully identified representative stable monitoring points, piezometers and wells, for piezometric and salinity levels employing the technique of relative differences, taking into account aquifer hydraulic properties. Trend analysis was then carried out adopting the Mann-Kendall Method, Sen's Slope test, Pettitt test, and the Seasonal Trend decomposition through the Loess (STL) method. Principal Component Multivariate Analysis (PCA) was also employed to validate long-term analysis of annual groundwater levels, rainfall, evapotranspiration, and pumping rates. New hydrological insights for the regionThe spatial-temporal variability of salinity is closely linked to the salt balance in regions with low hydraulic permeability and groundwater use for irrigation. Groundwater salinity presented a strong link between rainfall and groundwater levels. A temporal rise in evapotranspiration alongside declines in rainfall and groundwater levels was observed, potentially exacerbating groundwater scarcity alongside intensified aquifer exploitation. Furthermore, groundwater salinity presented a decreasing trend for the pumping wells and no trends for piezometers. This could potentially disrupt future irrigation plans and cause long-term water shortages in a region already under severe water scarcity. Hence, groundwater pumping constitutes a positive management alternative for controlling groundwater salinity in the domain.

Study on the Evolvement Trend Process of Hydrological Elements in Luanhe River Basin, China

Over the past 50 years, there have been significant changes in the runoff process in the Luanhe River basin, exacerbating the scarcity of water resources and their spatiotemporal variability. Therefore, conducting research on the characteristics, trends, and cycles of runoff changes in the Luanhe River basin is of great theoretical and practical significance. This study selected rainfall data from the hydrological stations in Weichang, Chengde, and Qinhuangdao in the Luanhe River basin, covering the period from 1985 to 2008, as well as runoff data from the Hanjiaying, Sandaohezi, and Chengde stations. Based on linear trend regression analysis, the Mann–Kendall rank correlation test, Spearman correlation test, Mann–Kendall method, and Mann–Whitney–Pettitt change point analysis method, this study analyzed the trends in water quantity changes and their change points in the Luanhe River basin. The results of the precipitation at the Weichang and Chengde stations show a non-significant rising trend, remaining relatively stable with slightly increases. Conversely, the precipitation of Qinhuangdao Station shows a decreasing trend over time, albeit non-significant. Considering the detailed diagnostic results from both the Mann–Kendall (M-K) and MWP methods, the change point for Weichang precipitation is identified as 2007, while for Chengde, it spans from 1999 to 2002, and for Qinhuangdao, it is around 1997. The trend of the runoff series of three stations shows a significant decreasing trend and strong significance, and the change point for the annual runoff at the Hanjiaying station and the Sandaohezi station is identified as 2006, and for the Chengde station, the primary change point is 2006, with a secondary change point around 2002. The findings of this research can provide scientific references for the rational development and utilization of regional water resources.

ҚЫЗЫЛОРДА ОБЛЫСЫНДАҒЫ АУА ТЕМПЕРАТУРАСЫНЫҢ 1961...2020 ЖЫЛДАР АРАЛЫҒЫНДА ӨЗГЕРУІ

The purpose of the article is to analyze the dynamics of air temperature, one of the most obvious indicators of climate change, and to determine the long-term trends of air temperature change in Kyzylorda region. Kyzylorda region is located in the south-west of Kazakhstan, is characterized by arid climate and belongs to the zone of ecological disaster. In this paper, the authors studied the changes in air temperature in the period from 1961 to 2020 based on the nonparametric statistical method of Mann–Kendall. The Mann-Kendall method is used to determine whether there is a monotonic trend in the studied data. The Mann–Kendall test is aimed at increasing the accuracy of the result of time series estimation and allows to determine the presence of a trend. The obtained results are characterized by a significant change in temperature in time series of Kyzylorda region. It is noted that for the selected period, to assess changes in the criterion Sen, the average annual temperature changes increased by 0.02...0.05°C. Seasonal trends showed an increase in average temperatures during the year, and the summer months significantly contributed to the warming observed in Kyzylorda region. The obtained data can serve as a basis for assessing both regional climate change and for assessing the ecological state, as meteorological parameters, namely air temperature is one of the important indicators in the study of atmospheric air pollution in Kyzylorda region.

Contaminant Trends in Urban Groundwater: Case Study from Ljubljana (Central Slovenia)

Urban areas can significantly alter the quality status of aquifers if appropriate strategies to prevent and detect groundwater contamination are not implemented in time. The prevention of groundwater contamination should be a priority due to its potential long-term impact on the environment and the high cost of remediation. For effective and sustainable groundwater management, it is crucial to proactively monitor a wide range of compounds to prevent their spread, progression and increasing concentrations. This study is one of the few to analyse the trends of various urban groundwater contaminants (nitrate, sulphate, hexavalent chromium, pesticides, PCE and TCE) from a groundwater management perspective. Characteristic trends are assessed using linear regression and the Mann–Kendall method, while significant changes in trends are determined using the Darken and Pettitt tests. The time span of the analysed trends covers the transition period before and after the implementation of the Water Framework Directive (2000/60/EC) and the Groundwater Directive (2000/60/EC). This study confirms the effectiveness of enforcement measures to protect groundwater quality, as evidenced by several statistically significant decreasing trends. On the other hand, this study emphasises the importance of intervention-targeted sampling campaigns and the reporting of raw analytical values according to the ISO 11843 series of standards. This approach is essential to detect upward trends in emerging contaminants at an early stage and prevent them from reaching levels that could negatively impact the economy or even jeopardise the safety of drinking water supplies.

Variations in the streamflow of the Nierji Reservoir Basin and quantification of the influencing factors

Abstract Nierji Reservoir is the largest and most important water conservancy project in the Nenjiang River Basin. A thorough understanding of variations in streamflow and the driving factors of the Nierji Reservoir Basin (NERB) is crucial, but there are still gaps. In this paper, the annual streamflow data of Nierji Reservoir from 1898 to 2013 were applied to detect the changing trend and abruptions using the Mann–Kendall method. Additionally, a Back Propagation-Artificial Neural Network (BP-ANN) model was developed to explore the relationships between the streamflow and its influencing factors and further quantify the relative contribution of each factor to the streamflow change. The results revealed that the annual streamflow of NERB significantly increased from 1898 to 2013 but declined during 1988–2013. Human activities were found to be the primary driver of streamflow decrease during 1988–2013, accounting for nearly 75% of the total change. Specifically, GDP had the largest influence, contributing 32% to the overall variation. Forest area, precipitation, and cultivated area had smaller contributions of 25, 23, and 18%, respectively. Temperature was found to have the least impact, with a relative contribution of 2%. This study provides valuable insights into water resources management in the Nenjiang River Basin, benefiting both agriculture and ecology.