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This study was undertaken to address how near-surface soil water content (SWC) patterns have varied across diverse agroecological regions (AERs) of mainland India from 1979 to 2022 (44 years) and how these variations relate to environmental factors. Grid-wise trend analysis using the Mann–Kendall (MK) trend test and Sen's slope was conducted to determine the trends and their magnitudes. Additionally, we used Spearman's rank correlation (ρ) to explore the relationships of ESA CCI's near-surface SWC data with key environmental variables, including rainfall, temperature, actual evapotranspiration, and the normalized difference vegetation index (NDVI). The results revealed significant variations in SWC patterns and trends across different AERs and months. The MK trend test indicated that 17.96% of the area exhibited a significantly increasing trend (p < 0.1), while7.6% showed a significantly decreasing trend, with an average annual Sen's slope of 0.9 × 10−4 m3 m−3 year−1 for mainland India. Areas with the highest decreasing trends were AER-16 (warm per-humid with brown and red hill soils), AER-15 (hot subhumid to humid with alluvium-derived soils), and AER-17 (warm per-humid with red and lateritic soils). In contrast, increasing trends were the most prominent in AER-5 (hot semi-arid with medium and deep black soils), AER-6 (hot semi-arid with shallow and medium black soils), and AER-19 (hot humid per-humid with red, lateritic, and alluvium-derived soils). Significant increasing trends were more prevalent during monsoon and post-monsoon months while decreasing trends were noted in pre-monsoon months. Correlation analysis showed strong positive correlations of SWC with rainfall (ρ = 0.70), actual evapotranspiration (ρ = 0.74), and NDVI (ρ = 0.65), but weak or negative correlations with temperature (ρ = 0.12). This study provides valuable insights for policymakers to delineate areas based on soil moisture availability patterns across seasons, aiding in agricultural and water resource planning under changing climatic conditions. [ABSTRACT FROM AUTHOR]

Climate change has increased the frequency and severity of weather extremes, including droughts, heat waves and compound drought and heatwave (CDHW) events. CDHW events profoundly impact water availability, agriculture, public health and energy production, particularly in the Horn of Africa (HOA). This study examined the historical spatiotemporal patterns of CDHW periods in the HOA during three periods (1951–1980, 1971–2000 and 1991–2020) using the ERA5 reanalysis dataset. This study utilized monthly Standardized Precipitation Evapotranspiration Index (SPEI) data to detect droughts and daily maximum temperature data to identify heatwaves for characterizing the duration, severity and magnitude of CDHW events. The results show a substantial increase in the duration of CDHW events in recent years, with durations reaching up to 25 days. The average duration of heat waves also increased from 7 days before 1993 to 18 days by 2011, culminating in a record‐breaking 43‐day heat wave in 2019. Most areas experienced a significant increase in heatwave duration by more than 12 days from the early period of 1951–1980 to the late period of 1991–2020. Although around 76% and 69% of the HOA exhibited insignificant heatwave trends in the first two periods, Ethiopia and Kenya experienced substantial increases of more than 18 days during the most recent period, with some durations exceeding 25 days in recent decades. The magnitude of CDHW events generally decreased as drought duration intensified, but specific areas, particularly southwest Kenya and Eritrea, exhibited higher CDHW values in the last period. These findings underscore the urgent need to understand and address CDHW events in the HOA. Targeted interventions for disaster risk reduction and resilience‐building are needed to mitigate the adverse effects of these events in this vulnerable region. This study provides a basis for future research and policy formulation in the HOA. [ABSTRACT FROM AUTHOR]

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

Changes in vegetation status generally also represents changes in the ecological health of islands and reefs (IRs). However, studies are limited of drivers and trends of vegetation change of Nansha Islands, China and how they relate to climate change and human activities. To resolve this limitation, we studied changes to the Normalized Difference Vegetation Index (NDVI) vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions. Trends of vegetation greenness were analyzed using Sen' s slope and Mann-Kendall test at two spatial scales (pixel and island), and driving factor analyses were performed by time-lagged partial correlation analyses. These were related to impacts from human activities and climatic factors under normal (temperature, precipitation, radiation, and Normalized Difference Built-up Index (NDBI)) and extreme conditions (wind speed and latitude of IRs) from 2016 to 2022. Results showed: 1) among the 22 IRs, NDVI increased/decreased significantly in 15/4 IRs, respectively. Huayang Reef had the highest NDVI change-rate (0.48%/mon), and Zhongye Island had the lowest (−0.29%/mon). Local spatial patterns were in one of two forms: dotted-form, and degradation in banded-form. 2) Under normal conditions, human activities (characterized by NDBI) had higher impacts on vegetation-greenness than other factors. 3) Under extreme conditions, wind speed (R2 = 0.2337, P < 0.05) and latitude (R2 = 0.2769, P < 0.05) provided limited explanation for changes from typhoon events. Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations 'Ocean Decade' initiative. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the trend in land surface temperature (LST) over time using the entire archive of the available cloud-free Landsat images from 1986 to 2022 for Jordan and its nine local climate zones (LCZs). Two primary datasets were used (i) Landsat-5; -8 imagery, and (ii) map of LCZs of Jordan. All LST images were clipped, preprocessed, and checked for cloud contamination and bad pixels using the quality control bands. Then, time-series of monthly LST images were generated through compositing and mosaicking processes using cloud computing functions and Java scripts in Google Earth Engine (GEE). The Mann–Kendall (MK) test and Sen's slope estimator (SSE) were used to detect and quantify the magnitude of LST trends. Results showed a warming trend in the maximum LST values for all LCZs while there was annual fluctuation in the trend line of the minimum LST values in the nine zones. The monthly average LST values showed a consistent upward trajectory, indicating a warming condition, but with variations in the magnitude. The annual rate of change in LST for the LCZs showed that the three Saharan zones are experiencing the highest rate of increase at 0.0184 K/year for Saharan Mediterranean Warm (SMW), 0.0185 K/year for Saharan Mediterranean Cool (SMC), and 0.0169 K/year for Saharan Mediterranean very Warm (SMvW), indicating rapid warming in these regions. The three arid zones came in the middle, with values of 0.0156 K/year for Arid Mediterranean Warm (AMW), 0.0151 for Arid Mediterranean very Warm (AMvW), and 0.0139 for Arid Mediterranean Cool (AMC), suggesting a slower warming trend. The two semi-arid zones and the sub-humid zone showed lower values at 0.0138, 0.0127, and 0.0117 K/year for the Semi-arid Mediterranean Cool (SaMC), Semi-arid Mediterranean Warm (SaMW) zones, and Semi-humid Mediterranean (ShM) zones, respectively, suggesting the lowest rate of change compared to other zones. These findings would provide an overall understanding of LST change and its impact in Jordan's LCZs for sustainable development and water resources demand and management. [ABSTRACT FROM AUTHOR]

Analyzing trends can provide insights into price behavior to predict future change. The primary objective was to examine prospective changes in monthly price over the entire period, between 2008 and 2021 using parametric and non-parametric techniques. Four domestic markets were chosen based on the maximum arrival of onions (Allium cepa L.) in Maharashtra and the Indian export market. Some markets fit the linear regression model; the errors do not conform to parametric assumptions, requiring application of distribution-free techniques. Using the mean of prices, Innovative Polygon Trend Analyses (IPTA) was applied. The IPTA plots for all domestic markets indicated upward trends in almost all months with regular polygons, with the exception of the export market. Plots indicated peak arrival months in markets exhibiting a narrower polygon structure, while lean arrival months showed a broader polygon. When results of trend analysis based on other tests were compared to the IPTA technique, there was good agreement across all approaches. The export market exhibited the least variability in prices, and the average monthly price ranges from 127.90 to 334.56 USD∙Mt−1. Post-monsoon and harvest months exhibited the highest average prices. Based on comparisons of trend analysis techniques, the IPTA methodology places a strong emphasis on identifying trends and offers insight through a visual examination of trend patterns. [ABSTRACT FROM AUTHOR]

The harmful effects of factors such as human-induced effects, greenhouse gases, fossil fuel consumption, urbanization and destruction of agricultural lands on the environment and climate change are increasing day by day. All these changes can create undesirable and permanent effects on human health, living species and the environment. The analysis of climate parameters on a regional basis is very important in understanding the effects of climate change and taking the necessary predictable steps to reduce its harmful effects. This study analyzes changes in various climate parameters of Ardahan province, such as temperature, precipitation amount, wind speed and sunshine duration. For this purpose, the changes in the three-year averages of the climate parameters measured by Ardahan Meteorological Station between 2001-2021 are analyzed. In addition, non-parametric Mann Kendall and Sen slope methods are applied to climate parameters, and monthly, seasonal and annual values of each parameter are evaluated according to the statistical significance level of 5%. As a result, increasing trends in the temperature values of the region and decreasing trends in the average precipitation, relative humidity and average wind speed values are determined. Thus, this study aims to understand the impacts of climate change and manage risks, as well as to provide the necessary climate data for thermal energy projects planned to be carried out in the region. [ABSTRACT FROM AUTHOR]

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

Based on data from 1966 to 2018, the present study analyses precipitation trends in the Zohreh–Jirahi basin in Iran. The homogeneity of data was estimated based on the Kolmogorov–Smirnov method. Missing data were reconstructed using inverse distance weighted (IDW) and ordinary-linear-kriging methods. The results were evaluated by the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). A multidimensional raster was generated containing precipitation values related to the statistical period years, and time-series data were produced in array format per unit area. Based on the period range, 34,267 points underwent the time-series analysis, and the trend change was assessed based on the Mann–Kendall method. The Sen’s slope was evaluated using yearly and monthly scales in these points, followed by producing raster maps. The IDW was selected with an R2 value of 0.95 as the optimal method of missing data reconstruction in this time period based on the model evaluation. The results showed no significant trends on a yearly scale, but on the monthly scale, December–April–November–August–September showed the highest ascending trends, respectively, February–December–March–May exhibited the highest descending trend, respectively, and June–July–September showed no trends. The maximum and minimum mean Sen’s Slope were estimated for December (0.213) and February (–0.68), respectively. Water resources management is inevitable, particularly in the agricultural sector as the main consumer with macro socioeconomic dimensions. Given the notable impact of water supply time to optimise and increase productivity, the current study can contribute to revising the cultivation patterns and time in the region. The recharge of aquifers, the storage process, and the consumption process should be compatible with forthcoming changes. [ABSTRACT FROM AUTHOR]

The wind has considerable effects on the ecosystem and evaporation as an essential parameter of the hydrological cycle. Therefore, determining historical changes in the wind will help to specify these effect levels. Although there are studies on the determination of wind speed trends by several researchers in Turkey, it is necessary to investigate the changes in the trend structure with recent data. For this purpose, the trends of monthly surface wind speed data from 1970 to 2021 belonging to 199 meteorology observation stations in Turkey are determined in the present study. The nonparametric Mann–Kendall test and Sen's slope method are used in the trend analysis accounting for serial correlation effects. The trend analysis results of wind speed data are evaluated temporally and spatially for seven geographical regions within Turkey. As a result of this study, a prominent part of stations in Turkey shows a decrease or significant decrease trend. In addition, as a result of comparisons made with previous studies, it is determined that the trend structure of the wind speed in the country has changed. In the annual and monthly wind speeds, it is observed that the number of stations has a "significant trend" decreased considerably. [ABSTRACT FROM AUTHOR]

The radiometric calibration network (RadCalNet) comprises four pseudo-invariant calibration sites (PICS): Gobabeb, Baotou, Railroad Valley Playa, and La Crau. Due to its site stability characteristics, it is widely used for sensor performance monitoring and radiometric calibration, which require high spatiotemporal stability. However, some studies have found that PICS are not invariable. Previous studies used top-of-atmosphere (TOA) data without verifying site data, which could affect the accuracy of their results. In this study, we analyzed the short- and long-term radiometric trends of RadCalNet sites using bottom-of-atmosphere (BOA) data, and verified the trends revealed by the TOA data from Landsat 7, 8, and Sentinel-2. Besides the commonly used methods (e.g., nonparametric Mann–Kendall and sequential Mann–Kendall tests), a more robust Sen's slope method was used to estimate the magnitude of the change. We found that (1) the trends based on TOA reflectance contrasted with those based on BOA reflectance in certain cases, e.g., the reflectance trends in the red band of BOA data for La Crau in summer and autumn and Baotou were not significant, while the TOA data showed a significant downward trend; (2) the temporal trends showed statistically significant and abrupt changes in all PICS, e.g., the SWIR2 band of La Crau in winter and spring changed by 1.803% per year, and the SWIR1 band of Railroad Valley Playa changed by >0.282% per year, indicating that the real changes in sensor performance are hard to detect using these sites; (3) spatial homogeneity was verified using the coefficient of variation (CV) and Getis statistic (Gi*) for each PICS (CV < 3% and Gi* > 0). Overall, the RadCalNet remains a highly reliable tool for vicarious calibration; however, the temporal stability should be noted for radiometric performance monitoring of sensors. [ABSTRACT FROM AUTHOR]

Rainfall characteristics are changing due to several reasons and change/trend detection is required. Literature survey reveals many relevant studies whose outcomes are divergent, possibly because different data series and different methodologies have been applied. This paper presents a critical appraisal of past studies and methodologies for trend analysis. Results of trend analysis of Indian rainfall data are presented. Data for all of India and for five homogenous regions (North-West, Central North-East, North-East, West Central, and Peninsular India) for 1871-2016 were used. The Pettitt change point test, regression, Mann-Kendall (MK), and Wavelet Decomposition were used to study different aspects of changes. Results of the change point test showed that most rainfall series had change points around 1957-65, possibly due to large-scale land use, cultivation, irrigation, and industrial changes in this period. Generally, rainfall for most homogenous regions and sub-divisions show falling trends; some are statistically significant. Series was also decomposed by the wavelet method. Approximate and detailed components of some decomposed series showed a significant declining trend. This work has focused on the magnitude of rainfalls; trends in rainfall intensities are also important. It is necessary to establish denser observation networks to collect short-term data and analyze. [ABSTRACT FROM AUTHOR]

The southern region of Bangladesh is one of the most severely affected regions by climate change, notably in terms of crop production. This study aims to analyze the trends in climatic parameters (air temperature, rainfall, and humidity) and their impacts on the yield of four significant crops in the southern coastal district of Bangladesh. The relationship between climatic parameters was estimated using the Mann–Kendall test, the Theil-Sen slope estimator, and multiple linear regression (MLR) modeling on the regional-level datasets from 1990 to 2016. The maximum temperature of the Aus, Aman, Boro, and Wheat crop growing seasons showed a significant increasing trend (p < 0.01), and the magnitude of changes varied from 0.4 to 0.5 °C/decade during the study period. The minimum temperature of the Aus growing season also showed an increasing trend (p < 0.01) at a rate of 0.06 °C/decade. However, the relative humidity of Aus growing season (− 0.7%/decade) and the rainfall of the wheat-growing season (− 87.5 mm/decade) showed significant decreasing trends (p < 0.05). The MLR model revealed that maximum temperature, minimum temperature, and rainfall all had a positive influence on Aus paddy production. The humidity had a significant negative impact on Aus and Aman paddy production, while Boro paddy production was adversely influenced by the maximum temperature and rainfall. All explanatory variables positively influenced wheat yield production. Climatic parameters showed significant influences on important crop production in the southern Bagerhat District of Bangladesh. In order to make agriculture sustainable in the face of climate change, this study shows that all the relevant authorities need to look at the climate-resilient crop cultivation system. [ABSTRACT FROM AUTHOR]

Introduction Groundwater is an essential natural resource that is widely used to meet domestic, industrial, and agricultural needs. In recent years, the amount of withdrawal from groundwater has been more than the amount of its recharging leading to going out of balance. Since groundwater is in the ground and it is not possible to observe directly, identifying its properties is time-consuming and expensive. On the other hand, problems such as inconsistent and incomplete input information, heterogeneous aquifers, etc., have made groundwater study difficult. In many watersheds, groundwater resources are the strategic and primary source of water supply for different users. However, groundwater extraction has exceeded the amount rate of recharge in many regions around the world, resulting in harmful ecological and environmental problems, such as water level decline, water quality degradation, drying up of wells, increased pumping costs, and land subsidence. Assessing groundwater resources for their available water volume and obtaining an accurate prediction of groundwater levels (GWL) is central to sustainable management (i.e., balancing between demand and supply) of groundwater and surface water resources in a watershed. Therefore, tools such as groundwater modeling are used to solve this problem. Simulation of groundwater flow with mathematical models is an indirect approach to solving problems with lower costs than direct methods. In fact, the use of mathematical modeling is to simulate the natural conditions of the water surface with mathematical relationships. Groundwater modeling is done using differential equations, and one of the most widely used methods in solving groundwater problems is the use of finite differences and finite elements. Accordingly, the groundwater modeling system (GMS) model and the MODFLOW code were used in this research to study the Mahabad aquifer. Next, the trend of changes in the groundwater level of the range was analyzed by non-parametric tests. Accordingly, the groundwater modeling system (GMS) model and the MODFLOW code were used in this research to study the Mahabad aquifer. Materials and Methods The study area of Mahabad is located in West Azarbaijan province. GMS software and MODFLOW code were used for groundwater simulation. Using the information of 22 observation wells, exploitation wells information, river information, recharge, and withdrawal from groundwater, the desired model was built. . The model was run in September 2015 for the steady-state and October 2010- September 2011 for the transient state with a monthly time step. The values for hydraulic conductivity and storage coefficient were calibrated for the steady and transient states, respectively. Aquifer thickness varied from 60 to 200 m, and the cell size was considered 200 × 200 m. Rainfall infiltration, return flow, and input flows feed the aquifer. Seventeen percent of the monthly rainfall was considered rainfall infiltration that fed the aquifer. Moreover, based on the wells' primary use, return water from the wells was considered about70, 75, and 20% for drinking water, industrial and agricultural wells, respectively. The GWL is higher in the South part of the aquifer compared to other parts and, as we move from the South part of the aquifer towards its central and southern regions, the GWL declines. In conclusion, the groundwater flows from the upper South part of the aquifer towards its lower part. More exploitation wells are in the aquifer's central section, and most of their extracted water is used for urban and agricultural purposes. It was then implemented in two stable and unstable modes and its performance was evaluated with root mean square (RMSE), mean absolute error (MAE), and coefficient of determination (R²) criteria. Various statistical methods have been provided to analyze the trend of time series. Among them, non-parametric methods are more useful in the time series of hydrological variables. These methods are suitable for time series that have elongation or skewness and are independent of the statistical distribution of the time series. In the following, the Mann- Kendall method and Sen’s slope were used to determine the trend of the groundwater level at significant levels of 90, 95, 99, and 99.9%. Results and Discussion The simulation results showed that there is a very good agreement between the simulation and observational data. The model evaluation criteria including RMSE, MAE, and R² for two stable and unstable modes were calculated as 0.84, 0.63, and 0.99, as well as 0.88, 0.72, and 0.98 m, respectively. These values showed the appropriate efficiency of the model. Based on the results, the highest level of groundwater was in the south of the Mahabad aquifer and the lowest level was in the north of the aquifer. The optimized values of hydraulic conductivity, special yield, aquifer thicknesses, values of exploitation wells, and aquifer transmissivity were determined from the groundwater simulation results. The results of the Mann-Kendall test showed that Haji Khosh, Gapis, and Gorg Tapeh stations had the highest downward trend. So, in these stations, the downward trend was more significant at the level of 0.99%. The Mann-Kendall Z-parameter values were positive for the Qom Qala station, which indicated the rising trend of the underground water level in this area. The results of Sen’s slope test also confirmed the results of the Mann-Kendall test. It was so that the Sen’s slope test showed that the downward slope of the three stations Haji Khosh, Gapis, and Gorg Tapeh occurs more strongly. Conclusion The results of this research showed that GMS and MODFLOW codes are suitable tools for simulating groundwater and the condition of the aquifer with proper accuracy. Also, the results of Mann-Kendall and Sen’s slope tests showed that out of 19 wells, almost 18 had a downward trend, which shows that the Mahabad aquifer is not in a favorable condition and with the increase in harvesting and decrease in rainfall, especially in recent years, its situation will worsen. The Mann-Kendall test showed that the Mahabad aquifer is in poor condition so out of the 19 investigated wells, approximately 18 wells had a downward trend in the groundwater level. The age slope estimator method also confirmed the Mann-Kendall results. Examining the obtained results exhibits that the use of new approaches for simulation provides the opportunity to manage and balance the allocation of groundwater resources effectively. Further, the use of new tools can be considered for implementing balancing scenarios related to groundwater resources. [ABSTRACT FROM AUTHOR]

A substantial drop in atmospheric visibility or visual range (VR) is documented in several parts of the world. We examined the long-term spatiotemporal variability in ground-based VR data for ten airports in Pakistan from 1980 to 2020. Average VR time series analysis was performed using nonparametric tests of Mann–Kendall (MK), Modified Mann–Kendall (MMK), Sen's Slope (SS), and Sequential Mann–Kendall (SMK), followed by spatiotemporal mapping. Bad VR (<5 km) conditions prevailed over more than 60% of the study period. Noticeably, VR was better during 1991–2000 due to the high average annual rainfall (905 mm) during the 1990s. Plain areas such as Faisalabad experienced the greatest number of bad VR days with hourly (92.85%), daily (95.35%), monthly (90.97%), and seasonal (90.97%) measurements, followed by Sialkot and Multan. The VR of lowlands in central, southern, and eastern Punjab and northern, central, and eastern Sindh showed decreasing trends. In contrast, the VR in coastal areas of south and southwestern Sindh, in the western highlands, and parts of Khyber Pakhtunkhwa (KPK) province, have indicated positive trends. The results of this study will support policymakers in catering to the issue of declining VR in the region by supporting and developing strategies to limit the factor associated with VR. [ABSTRACT FROM AUTHOR]

In this study, trend analyses of six climatic variables (mean, minimum, and maximum temperature, relative humidity, wind speed, and precipitation) for 1966-2020 are conducted for the Southeastern Anatolia Region, which is the main focus of the integrated development project in Turkey (Turkish acronym GAP). The trends for seasonal and annual periods are determined using the Mann-Kendall (MK) test, and Sen's slope method and regression analyses are used to find the trends' slopes. Moreover, Innovative Trend Analysis (ITA) is also used to find the time series changes for low, medium, and high values. As a result of the analyses, the mean, minimum, and maximum temperatures in the GAP region show increasing trends according to both methods. Significant trends are obtained at a limited number of stations for the precipitation, relative humidity, and wind speed with the MK test, while consistent decreasing trends are found at most stations with the ITA method. [ABSTRACT FROM AUTHOR]

Analysis of rainfall distribution and its changing pattern plays a vital role in managing water resources in a region. This work examined the spatio-temporal variability and trend of rainfall on yearly and season-wise scales during 1971–2013 in the Wainganga river basin situated in middle India. The Mann–Kendall (MK) test was implemented for identifying the temporal variation in rainfall trends. The magnitude of this changing trend was estimated by applying Sen's slope (SS) method. A paired sample t-test was also employed to appraise the statistical significance of changes in rainfall data. The results of MK and SS tests show both upward and downward trends. The results show positive and negative trends in the south-eastern and northwestern parts of the study area for annual rainfall. The monsoon rainfall also shows very close proximity with annual rainfall data trends. The t-test states that the observed changes in precipitation are statistically significant. After trend and pattern analysis, state-space models (SSMs) were used to predict rainfall for future scenarios. Four SSMs (single, double, and triple exponential, autoregressive integrated moving average (ARIMA)) were employed for rainfall prediction. The analysis shows that the ARIMA is best for rainfall prediction with architecture of (0,0,0) (2,1,0) and can be used in Wainganga River basin. [ABSTRACT FROM AUTHOR]

The flood in Kashmir valley has a long history and is considered as recurrent phenomena, though the flood occurred in 2014 was extremely severe due to its extent, intensity and impact on mankind. To understand the variation of this precarious climatic condition, the long-term variability of precipitation over Kashmir valley was analysed over a period of 1901–2018 on an annual, seasonal, monthly and weekly basis to investigate the pattern of precipitation and its linkage to flooding. The mean annual precipitation analysis exhibits only few (06) severe incidences (>1226mm). Sen's slope estimation exhibited a statistically positive trend during winter season (0.458 mm year−1) as compared to rainy season (-0.661 mm year−1) at the 5% level of significance. The major deficit (> −99%) in precipitation anomaly was recorded forming the September month as anomalous. September 2014 exceptionally confronted one incidence of sudden but continuous weekly high precipitation (>130 mm) with intensity of 22.82 mm day−1 during 15 years. [ABSTRACT FROM AUTHOR]

The study explores the seasonal rainfall and rainy days trend in the Himalayan Kingdom of Bhutan. Mann-Kendall and Sen's slope test was applied to detect the trend and magnitude of the trend for both the rainfall and rainy days. The trends are also analyzed with respect to the elevation of the climatic stations. Further, an attempt has been made to recognize the El-Ni ño- Southern Oscillation (ENSO)-rainfall interaction using station-based rainfall with the ENSO cycle considering the period of 33 years. Cross-correlation of ENSO and rainfall with respect to elevation has also been presented. The trend analysis showed that in the localized regions, both the rainfall and rainy days trend was significantly declining, however, the trend in most of the stations is hardly conspicuous which may be attributed to the influence of the orographic phenomena. From the ENSO-rainfall assessment, it was observed that rainfall in the southern foothills correlates negatively with the ENSO phenomena indicating intense rainfall after 1–2 months of the cooling phase of the Pacific Ocean. However, such an ENSO effect is not observed in the majority of the meteorological stations which may be attributed to the location of the station in the mountainous region where the topography affects the rainfall variation. [ABSTRACT FROM AUTHOR]

Groundwater overexploitation along with decreasing precipitation exacerbates groundwater level decline and causes groundwater drought. Efficient assessment of the drought is critical to water management, especially in drought-prone agriculture regions. It remains challenging to characterize groundwater drought quantitatively due to the difficulty in obtaining groundwater observation data and the complexity of groundwater flow systems. To this end, agglomerative hierarchical cluster analysis was performed on long-term groundwater levels to classify wells in the San Joaquin River Basin, California. A Modified Mann-Kendall (MMK) test was undertaken to detect seasonal groundwater level trends from 1980 to 2019, and the magnitude was calculated using Sen's slope estimator. A nonparametric Standardized Groundwater level Index (SGI) was used to quantify the characteristics of groundwater drought. Results show that long-term (40-year) temporal patterns in groundwater levels varied significantly over the San Joaquin River Basin. Significantly decreasing trends were observed among more than 34.6% of wells, with an average decline of 0.69 m/year. Wells suffered frequent and severe groundwater droughts in the last decade, which were mainly driven by heavy groundwater exploitation. Findings provide useful information about the long-term behavior of regional groundwater levels, which in turn help stakeholders monitor droughts and adapt groundwater management strategies. [ABSTRACT FROM AUTHOR]

In this study, temperature characteristics and heat load in the city of Dubrovnik are investigated by using temperature data observed at the local meteorological station in Dubrovnik for the period 1961--2019, satellite data collected by LANDSAT5 satellite for the period 2001-2010, and climate indices data obtained from simulations of an urban climate model (MUKLIMO_3) for the period 2001-2010. Trends in daily mean, maximum, minimum, and seasonal temperatures were analysed by using Sen's slope and the Mann-Kendall test. Results reveal rising trends for all of the studied temperature-related elements. However, it is demonstrated that temperature increase is greatest for the summer season with the highest rise for daily maximum temperatures. The same approach was applied to examine trends of climate indices (summer days and tropical nights), which indicates an increase in the number of both summer days and tropical nights. Results of satellite data of average summer land surface temperatures for the period 2001-2010 indicate that urbanised surfaces and bare rock areas heat up more than natural surfaces with vegetation. Climate indices (summer and hot days, warm evenings, and tropical nights) simulated by the urban climate model MUKLIMO&lowbar;3 also reveal that, on average, in the city of Dubrovnik urbanised surfaces heat up more than natural surfaces with vegetation and that nocturnal heat load is reduced in lower-density builtup areas. [ABSTRACT FROM AUTHOR]

Karnataka, a state in south India with nearly 80% of the cultivated land under rainfed farming, is very much dependent on rainfall for agricultural productivity. The spatio-temporal variability in observed rainfall over Karnataka is investigated using various data analytical techniques such as parametric and non-parametric methods, rotated empirical orthogonal function (REOF), clustering and spectral analysis. The observed data used for studying rainfall variability is the daily taluk-wise telemetric rain gauge data for a period of 1960–2016. A similar pattern in trend is observed in annual and south-west monsoon (SWM) rainfall over Karnataka such that taluks in the western and northern parts showed a decreasing trend, whereas the south interior part showed an increasing trend. A significant increasing trend in rainfall was found during pre-monsoon seasons whereas the northeast monsoon (NEM) rainfall showed a decreasing trend. The REOF analysis also indicated an upward (downward) trend in SWM and annual over the northern (southern) Karnataka and a weakening trend in the NEM rainfall. Using the hierarchical clustering method, six homogeneous rainfall clusters were identified over Karnataka based on distribution and variability of rainfall. The spectral analysis over different clusters showed significant oscillations in the annual and SWM rainfall in the 1970s and recent decades except the Western Ghat region where oscillations were much weaker during recent decades. The pre-monsoon and NEM rainfall also showed strong variability with a periodicity of 2–4 years in recent decades. The findings of this study can have implications while designing water resource management strategies across various sectors in Karnataka. [ABSTRACT FROM AUTHOR]

In this study, which analyzed the precipitation trend, course and frequency of Çanakkale province, which is located in Marmara Region as a geographical region and reflects the characteristics of Mediterranean climate in general, the total annual precipitation data recorded between 1929-2020 of 21 precipitation observation stations were used. First, the missing data of the stations were interpolated, and the lost years were completed and tested with 4 different homogeneity tests: SNHT, Pettitt, Buishand, Von-Neuman test. As a result of the test of precipitation observation stations with Mann-Kendall Test, Mann-Kendall Rank Correlation Test, Sen's Trend Test and Sen's Innovative Trend, the trend was determined precisely in 6 districts with the same trend result of 4 tests. The increasing trend in Ayvacık, Çan, Eceabat, Ezine and Lapseki districts; In Biga district, the decreasing trend was clearly demonstrated. In the remaining 6 districts, the test results were not evaluated significantly and determined according to the majority status. Accordingly, the upward trend was detected in Bozcaada and Yenice districts and decreased trend in Bayramiç and Gelibolu districts. In Center and Gökçeada district, no increasing or decreasing trends were found. [ABSTRACT FROM AUTHOR]

The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley's prestigious ecosystems and socio-economic components. The Himalayas's local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region's hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen's slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region's food security and ecological sustainability. [ABSTRACT FROM AUTHOR]

Renewable energies play a significant role in mitigating the climate change impacts. Wind and solar energy are projected to supply larger amount to the total renewable energy capacity of many nations. Long-term wind and solar data availability and analysis is vital for sustainable renewable energy farming. In this research, we analyze wind speed u- and v-components at 10 m height of the ERA5 daily reanalysis aggregates at a mesh of 31 Km during a long period (2010–2020) over the Red Sea and the Gulf of Suez coasts of Egypt. Google Earth Engine (GEE) code is developed and used for the analysis. The prime objective is to derive estimates on the spatio-temporal variability of speed, direction, and the wind energy estimates in the area. Further, the solar energy potential has been evaluated using reference data of the PVOUT – Photovoltaic power potential (kWh/m2/day) data, at nearly 1 km resolution, which is normalized at the evaluated sites, and then used to rank sites with their solar energy potential. Evaluation of estimates is carried out at selected thirteen sites distributed along the coasts to better understand the hybrid wind-solar energy potential. Frequency analysis is carried out to the wind speed spatial estimates to demarcate highest frequency wind events potential for wind farming. Reference in-situ wind speed observations available at daily and monthly time scales for Hurghada weather station is used for investigating the reanalysis data performance. The Hurghada site had the highest average wind speed (6.7 m s−1), frequency of events (75 %), and mean daily (60.4 kWh) and annual (22.02 MWh) wind energy. The windiest time intervals were the September month, 2017 year, and the summer season. The north had wind energy directions of 130°, while the south had 110°. Trend analysis showed declining trends for northern locations and rising yearly wind speed estimates for Berenice (0.005) and Halayeb (0.002). El-Tor location had the highest solar energy output, with a daily mean of 5.52 kWh/m2 and an annual mean of almost 2015 kWh/m2. The Hurghada, Jemsa, G. Zeit, and El-Tor sites achieved the highest rankings in terms of hybrid wind-solar energy potential. The results can be very valuable for optimal location of hybrid solar-wind energy facilities and provide viable and promising solutions for sustainably meeting Egypt's growing clean energy demands. [Display omitted] [ABSTRACT FROM AUTHOR]

The impact of climate change on annual and monthly air precipitation and temperature has received a great deal of attention by scholars worldwide. This study focuses on detecting trends in annual precipitation and temperature for Addis Ababa methodological station located in Addis Ababa. SPSS in combination with the excel spreadsheet used for analyzing the statistics. We were also used the Mann-Kendall trend test and Sen's slope method to detect trends and the magnitude of change. According to our analysis, the mean minimum temperature ranges between 8.45°C and 12.5°C, while, the mean maximum temperature varies between 21.1°C and 25.5°C From the analysis the monthly coefficient of variation (CV%) for both maximum and minimum temperature ranging from (5.4% in April) to (14.08% in December). According to the Mann Kendal test and Sen's slope estimate, the annual maximum temperature shows a statistically significant increasing trend but no significant positive or negative trend was detected in annual perception as well minimum temperature. [ABSTRACT FROM AUTHOR]

Changes in the rainfall amounts in a small island in the North Atlantic Ocean—Madeira Island—were analysed based on complete daily rainfall series aggregated into 1-, 3-, 6- and 12-month rainfall and annual maximum rainfalls of 41 rain gauges (1937/1938–2016/2017). The gaps of the daily rainfall data were filled in by the multivariate imputation by chained equations whose performance was evaluated. The Mann-Kendall test coupled with Sen's slope estimator was applied to detect and quantify trends. The sequential Mann-Kendall test was used to identify abrupt changes in trends. Results show a widespread downward trend in seasonal and annual rainfall, with the highest values in Madeira's central region. A strong association between the downward rainfall trends and the upward trends of the North Atlantic Oscillation Index was found. New insights into the understanding of the rainfall patterns in small island environments in the North Atlantic were produced. [ABSTRACT FROM AUTHOR]

Extreme cold events ("cold waves") have disastrous impacts on ecosystem and human health. Evidence shows that these events will still occur under current increasing mean temperatures. Little research has been done on extreme cold events, especially in developing countries such as South Africa. These events pose a significant threat due to the low adaptive capacity, urgent development needs and relatively inadequate infrastructure in South Africa. This study presents annual and seasonal, spatial and temporal trend analyses of extreme cold temperature events for the period 1960–2016. We apply the World Meteorological Organisation Commission for Climatology and Indices Expert Team on Sector‐Specific Climate Indices (ET‐SCI) to South Africa for the first time, with comparison to the World Meteorological Organisation Expert Team on Climate Change Detection (ETCCDI) indices previously used in South Africa. The extreme cold indices are calculated using the RClimDex and ClimPACT, respectively. Trends were calculated using the non‐parametric Mann‐Kendall test, Spearman Rank Correlation Coefficient and Sen's slope estimates. A decreasing trend is found for annual cold spell duration and cold wave frequency, at rates of 0.10 days.day−1 and 0.02 events.day−1, respectively. Seasonally, coldest day temperatures increased in autumn, with increases of 0.02°C.day−1 for the period 1960–2016. Regionally, increasing trends in annual cold spell duration days were evident in stations located in the Western Cape, Eastern Cape, North‐West Province, at a rate of 0.03 days.day−1. Increasing trends in cold waves were observed for stations in Northern Cape, Gauteng, KwaZulu‐Natal and the Eastern Cape Province, at a rate of 0.01 events.day−1. These results contribute to the awareness and recognition of the incidence and duration of cold extreme events in South Africa, seeing that studies suggest that anomalously cold events may persist in a warming world. [ABSTRACT FROM AUTHOR]

Spatial–temporal variations in precipitation significantly influence infiltration, runoff, and other hydrological processes; and thus, in turn, they influence the risk of natural disasters such as flooding, drought, and erosion. Knowledge of these processes is still limited in the Taihang Mountain region, which is a highly heterogeneous environment in northern China. In this study, annual precipitation data for 1968–2017 from 88 weather stations in the Taihang Mountain region were analyzed. The Mann–Kendall (M–K) test and precipitation-related indices (precipitation amount, Sen's slope, Precipitation Concentration Index (PCI), and Coefficient of Variation (CV)) were used to analyze the spatial and temporal trends in precipitation in this region. Nine predictors (elevation, longitude, latitude, slope gradient, slope aspect, maximum temperature (Tmax), minimum temperature (Tmin), difference between Tmax and Tmin (DT), and evapotranspiration (ET)) were used to predict the precipitation and the related indices. The results reveal that the annual precipitation generally decreased from 1968 to 2017, but the M–K test indicates a nonsignificant trend. The precipitation decreased from southeast to northwest with significantly different spatial variations over the five decades investigated. The decrease in the PCI was not significant, and it generally decreased from northeast to southwest, suggesting a higher risk of flooding and drought in the northeast. The CV was 0.18–0.32, indicating a moderate spatial variation. In addition, the CV slightly decreased during the 50 years investigated. Multiple linear regression revealed that the amount of precipitation could be predicted from the latitude and longitude. The slope trend could be predicted based on latitude. PCI could be predicted based on longitude and elevation. CV could be predicted based on elevation, longitude, and Tmax. This suggests that the precipitation was mainly influenced by the geographical factors in the Taihang Mountain. This is useful information for the prediction of precipitation and for water management in this mountain region. [ABSTRACT FROM AUTHOR]

Warm extreme temperature events or 'heatwaves' have disastrous impacts. Several high-impact heatwave events have recently occurred in the Global North, resulting in significant losses of human life and dire effects on economies. The expected increases in the frequency and intensity of extreme heat events under climate change pose a significant threat to South Africa. South Africa, a developing country, with an increasing population, faces many socioeconomic challenges. This study presents the first comprehensive annual and seasonal, spatial and temporal trend analyses of daily maximum and minimum extreme temperature events recorded from 20 meteorological stations across South Africa, spanning 1960–2016. Trend results based on the World Meteorological Organization Expert Team on Climate Change Detection (ETCCDI) and the World Meteorological Organization Commission for Climatology and Indices Expert Team on Sector-Specific Climate Indices (ET-SCI). Indices describing the characteristics of warm extremes are calculated using RClimDex and ClimPACT, respectively. The non-parametric Mann-Kendall test, Spearman rank correlation coefficient and Sen's slope estimates were used to determine the statistical significance and magnitude of the calculated trend. Results show a general annual trend increase in maximum temperature at a rate of 0.02 °C year−1. The majority of stations reveals statistically significant trends in warm days and nights; with the strongest, general annual trend increases experienced in warm days at a rate of 0.15% year−1. Seasonally, the strongest increases of 0.11% days year−1 in warm days are evident for autumn, while increases of 0.07% days year−1 are calculated for summer. A general increasing trend in heatwave events is recorded at 0.03 events year−1 countrywide. [ABSTRACT FROM AUTHOR]

This study investigates the trends of precipitation and temperature extremes for the historical observations (1961–1990) and future period (2061–2090) in the Jhelum River Basin. Future trends are estimated by using ensemble mean of three general circulation models under RCP4.5 and RCP8.5. Therefore, statistical downscaling model has been used to downscale the future precipitation and temperature. A total of 15 precipitation and temperature indices were calculated using the RClimdex package. Man-Kendall and Sen's slope tests were used to detect the trends in climate extreme indices. Overall, the results of study indicate that there were significant changes in precipitation and temperature patterns as well as in the climate extremes in the basin for both observed as well as projected climate. Generally, more warming and increase in precipitation were observed, which increases from RCP4.5 to RCP8.5. For all the stations, increasing trends were found for both precipitation and temperature for twenty-first century at a 95% significance level. The frequency of warm days (TX90p), warm nights (TN90p), and summer days (SU25) showed significant increasing trends, alternatively the number of cold nights (TN10p) and cold days (TX10p) exhibited opposite behaviors. In addition, an increasing trend of warmest day (TXx) and coldest day (TNn) was observed. Our analysis also reveals that the number of very wet days (R90p) and heavy precipitation days (R10 mm) will likely increase in the future. Meanwhile, the Max 1-day (RX1-day) and 5-day (RX5-day) precipitation indices showed increasing trends at most of the stations of basin. The results of the study is of potential benefit for decision-makers to develop basin wide appropriate mitigation and adaptation measures to combat climate change and its consequences. [ABSTRACT FROM AUTHOR]

Impact of climate change over the hydrological system in a region can be identified through statistical characterization of hydrometeorological parameters such as rainfall, temperature, humidity and evaporation. In order to understand the influence of climate change, statistical trend characteristics of rainy days, non-rainy days and evaporation rate in the Limbang River Basin (LRB) in Sarawak, Malaysia, Northern Borneo was assessed in the present research. Annual rainfall and monthly evaporation data, over a period of 46 years, (1970 - 2015) corresponding to three rain gauging stations, the Limbang DID, Ukong and Long Napir were used in the research. Linear regression model, Mann Kendall and Sen's slope estimator techniques were applied to detect the statistical trends in rainy days and evaporation. A statistically significant increasing trend in annual rainy days was found at all the stations. Non-rainy days showed a statistically significant decreasing trend at Limbang DID and Ukong. Monthly evaporation rates showed an overall increasing trend and the greatest increasing trend in evaporation was observed in September (2.55 mm/year) for the Limbang DID and in December (2.61 mm/year) for Ukong. Evaporation measured at the Ukong station also showed a non-significant decrease during June and September. A comparison of the evaporation controlling meteorological variables such as rainfall, temperature and relative humidity indicates inter-influence at various strengths. Along with local precipitation characteristics, wind and fluctuation of atmospheric temperature over the region plays a vital role in increased rate of evaporation from the region. Overall, the analysis identified a statistically significant increasing trend in rainy days and evaporation in the LRB. The results of the present research can be used as critical planning data for micro and macro hydroelectric projects in the river basin. [ABSTRACT FROM AUTHOR]

Android operating system, since its first start, is growing very fast and takes a large space in smart devices market. It is built and developed on Linux and designed basically for touch screen devices such as, mobiles, tablets, etc. Mobile devices are markedly complicated and feature-rich; therefore they are prone to reliability of software and performance problems. Because of the small resources, smart devices, such as CPU, RAM, suffer from problems. One of these problems is Software Aging (SA). SA is recognized in long running OSs as a shortage in resources, performance retreating, and finally failure. SA is looked at from two sides, namely the poor response time of application which represents the end user side and the shortage in metrics related to device resources, such as RAM and storage. In this paper, a set of eight experiments is conducted to distinguish SA in Android mobiles. These experiments are conducted to find the correlation between Launch Time (LT) with RAM and storage metrics covered in this paper. Statistical methods, such as Mann Kendall test, Sen’s slope, Spearman rank correlation, and Design of Experiment (DOE) are used to prove the correlation statistically. These experiments assist to detect SA, which will be helpful in the rejuvenation strategy of applications. [ABSTRACT FROM AUTHOR]

This study mainly aimed at gathering information on durian production trends and distribution in Peninsular Malaysia. Time series data from 2000 to 2017 involving planted areas and their respective production of durian were used for the analysis. The production trends and the magnitude of the slopes for all planted areas were then analyzed using Mann- Kendall and Sen's slope estimator. The results indicated that the hectarage of planted areas showed a downward trend in most parts except for Raub and Rembau districts. Despite the decrease in areas planted with durian, some areas exhibited an upward trend in annual production, particularly in the northern and central regions. This study also revealed that there was a shift in the distribution of durian production throughout the study period. These findings will be useful for policymakers and practitioners to improve durian orchard planning and management. However, future research should be conducted to determine the impact of climate variability on the shifting of durian production in Peninsular Malaysia. [ABSTRACT FROM AUTHOR]

As a typical inland river basin in China, the Shiyang River Basin is characterized by its special mountain-basin structure. The ecological health in the basin is related to the sustainable development of the economy and society. At present, there are few studies on net primary productivity (NPP) in the Shiyang River Basin, and the existing analysis of the relationship between NPP and climatic factors is lacking. The upper mountainous area and the middle and lower oasis areas in the Shiyang River Basin were selected as the study area. The NPP of the study area was estimated using the Thornthwaite Memorial Model. The spatial and temporal characteristics of NPP were analyzed by Sen’s slope method. Based on the sensitivity analysis, the correlation of the main climate factors to NPP was estimated. According to the aforementioned work, the variation trend of the future NPP was predicted. The results showed that NPP in the study area increased from 1981 to 2015 with the increase in temperature and precipitation. The spatial heterogeneity of the change trend of NPP was not significant, but the spatial heterogeneity of the rangeability was strong. The NPP was highly sensitive to precipitation, relative humidity and net solar radiation. By integrating the changes in climatic elements, the temperature, precipitation and relative humidity contributed the main parts of the change in NPP. The NPP is predicted to increase by 4.9–8.1% by 2050 according to the amplitude of climate change over the past 35 yrs. [ABSTRACT FROM AUTHOR]

This study presents an interface, ‘Climate Change Trend Analysis (CCTA)’, developed in MATLAB® environment to analyze the trends using non-parametric statistical methods, Mann-Kendall (MK) test and modified Mann-Kendall (MMK) test with Sen’s slope estimator. The interface was used to determine trend in annual and seasonal (kharif) rainfall depths in Pune district acquired from 13 observatories. The developed interface automates the trend analysis process, which can further use for detecting variability and trends in the meteorological as well as other hydrological and agricultural parameters. The observed rainfall trends during monsoon would play a significant role for rainfed agriculture in Pune district. [ABSTRACT FROM AUTHOR]

• The temperature is rising in lower troposphere and declining in lower stratosphere. • Water vapor has increasing trend in lower part of troposphere. • O 3 is rising in lower/lower-mid troposphere, while declining in lower stratosphere. • Total column integrated methane has a significant increasing trend. • Total carbon-monoxide has not shown any significant trend. The present work has been carried to analyze the changes in trend of temperature, water vapor and ozone profiles at different atmospheric layers, total column integrated methane (TCH4) and total column integrated carbon-monoxide (TCO) over the Indian region. The atmospheric column was divided into few atmospheric layers: surface-850 hPa, 850–500 hPa, 500–100 hPa, 100–50 hPa and 50–1 hPa. Monthly averages of these parameters were calculated from AIRS Level 2 Standard Products for a decade from 2003 to 2012. A non-parametric statistical test with seasonal modification was applied to check the trends of various parameters. Monthly means were used to examine the seasonal dependency in the trend, and allowing more information from the data to be used. The layer average temperature in surface-850 hPa layer has shown significant increase in overall annual trend over eastern part, southern part and averaged over whole India with an increase of 0.041 K/year, 0.034 K/year and 0.034 K/year, respectively. The overall trend was decreasing over all but southern parts in 100–50 hPa layer at the rate of 0.079 K/year over whole India. For water vapor trends, it has been found that layer integrated water vapor (LIWV) in surface-850 hPa layer has significant overall increasing trend over western part, southern part and averaged over whole India with the rate of increase of 0.555%/year, 0.598%/year and 0.486%/year respectively. For LIWV (850–500 hPa), only western part has significant increasing trend at a rate of 0.879%/year. However, LIWV in 500–100 hPa layer does not show any significant trend. Total water vapor (TWV) has shown significant annual increasing trend over all the parts except over the central part. The increasing trend has been estimated as 0.962%/year over whole India. The layer integrated ozone (LIOZ) in surface-850 hPa has significant increasing trend over western part (0.062%/year) and southern part (0.071%/year). In 500–100 hPa layer, the LIOZ has statistically significant decreasing trend over whole India at a rate of 0.112%/year. For LIOZ averaged over whole India in 100–50 hPa, there is significant decreasing trend with a rate of 0.273%/year. Overall, the ozone concentration is increasing near surface, whereas it is decreasing in lower stratosphere. The total column ozone (TOZ) has not shown any significant trend. The column integrated methane has shown an increasing trend (0.366%/year) over all parts of the country, whereas, TCO has not shown any significant trend. [ABSTRACT FROM AUTHOR]

In the present study, two districts of North-East region of Bangladesh; a flood prone area with high temperature and maximum precipitation, respectively, were selected along-with two widely cultivated Boro rice varieties in Bangladesh. Reference evapotranspiration (ETO) during the study period from 1994 to 2010 was estimated with the daily meteorological data utilizing the FAO Penman-Monteith method. A MAKESENS trend model was adopted for the assessment of both Mann-Kendall test and Sen's rate of change over the study period. During the study period, the potential crop water requirement of Bangladesh Rice Research Institute dhan 28 (B28) and BRRI dhan 29 (B29) in Moulvibazar has been declined by -3.953 mm year-1 and -5.182 mm year-1, respectively; whereas it has been raised by 2.483 mm year-1 and 2.387 mm year-1, respectively in Sylhet. The climatic parameters affecting the observed and projected trends in Potential water requirement differed both significantly and insignificantly over the months of the year. For both varieties, maximum water demand was observed in mid-season stage; whereas the development stage, the water demand was found to be minimum. [ABSTRACT FROM AUTHOR]

A comprehensive evaluation of trends in annual instantaneous maximum flows (AIMF) from 153 gauge stations located in 26 river basins in Turkey is presented. Two traditional non-parametric trend tests, the Mann-Kendall (MK) and Spearman's rho (SR), are used to quantify the significance of trends, while Sen's slope method is applied to determine the magnitude of trends. The traditional tests indicate that the AIMF records of 57 stations showed statistically decreasing trends, while those of six stations showed an increasing trend. Sen's trend method, which provides more detailed assessment of the trends in different clusters (low, medium and high), was applied to the AIMF series and the results were compared with traditional tests. Sen's trend method indicated that all flow clusters at nine stations have increasing or decreasing trends, although no significant trend was detected by the MK and SR tests. [ABSTRACT FROM AUTHOR]

Abstract Understanding the trend of temperature and rainfall is of prime importance for climate change related research. This research aims to identify the trends of temperature and rainfall for the last 50 years (1966–2015) for Bangladesh. To detect the trends, the non-parametric Mann–Kendall test in combination with a trend-free pre-whitening approach for correcting the time series to eliminate the influence of serial correlation has been used whereas the Sen's slope method is used for identification of the trend value. Maximum, minimum, and mean monthly temperatures have been analyzed to identify the monthly, seasonal and annual trend. Four seasons are distinct in Bangladesh, namely, pre-monsoon, monsoon, post-monsoon and winter. In case of rainfall, mean monthly rainfall, 1-day maximum rainfall and consecutive 3-day maximum rainfall are analyzed in a similar fashion. For maximum, minimum and mean monthly temperature, the majority of the stations show an increasing trend for all three indices. Monsoon season observes highest increasing trend of 0.015 °C/yr for mean monthly temperature whereas the winter season shows the negative trend of −0.002 °C/yr. On an annual basis, the trend is increasing with a value of 0.008 °C/yr or 0.4 °C in 50 years having significance level, p <.05. On the other hand, mean rainfall shows an increasing trend for the three seasons except for winter, however, significance level in this case is p >.10. The trend of mean rainfall for annual basis shows an increasing trend of 5.675 mm/yr. The trend in one day and consecutive three-day maximum rainfall depicts that the trend is increasing in few places whereas in other places the trend is decreasing with no significant change. The research concludes that the climate of Bangladesh is getting cooler and drier for winter, on the other hand, warmer and wetter for the rest of the year. Highlights • Data did not show significant serial correlation except for post monsoon temperature and winter rainfall series • In case of rainfall, the country as a whole observed no significant trend for all the three indices analyzed. • It has been predicted that, because of climate change, there will be gradual increase of temperature and change in rainfall pattern [ABSTRACT FROM AUTHOR]

Drought is referred as a natural calamity which negatively affects various sectors especially water resources, food security and the economy of the country. High altitude regions as compared to low-lying areas, are more vulnerable and sensitive to changing climate. In order to comprehend the entire drought phenomena, analyzing drought trends with respect to elevation for different time scales is of great significance. Therefore, the present study is an attempt to investigate the spatiotemporal variation of meteorological droughts and to explore the relationship between elevation and drought dynamics over the Indian extent of Indus river basin, which is an important drainage system of the Indian sub-continent as far as agricultural productivity and water supply is concerned. Heterogeneity of the elevation spread over the basin ranging from 93 to 8489 m, makes it suitable for exploring the elevation relationship with drought characteristics. For this purpose, gridded monthly precipitation, maximum and minimum temperature data of 0.120 × 0.120 spatial resolution (1956 grids) for a time period of 42 years (1979–2020) is utilized to study the drought characteristics. Drought events are identified based on Standardized Precipitation Evapotranspiration Index (SPEI). Computation of SPEI-annual and SPEI-seasonal (pre-monsoon, monsoon, post-monsoon and winter) is done on the basis of climatic water balance, connecting to the droughts. Modified Mann-Kendall test and Sen's slope method have been used to detect significant trends in the region. Results show that the trends in the drought indices have very high heterogeneity across different seasons. Overall, 13% (14%) grids show drying (wetting) trends for annual SPEI time series analysis. However, seasonally, it is found that monsoon and post- monsoon seasons have larger areas in the basin with wetting trends. Moreover, the pre-monsoon season has a larger area with drying trends. The study region has experienced 0%–10% and 0%–5% severe and extreme drought frequency respectively, over the time period 1979–2020. A relationship between drought and elevation is observed, depicting wetting trend is associated with elevations up-to around 2000 m with decreasing rate of wetting whereas, for the altitudes from 2000 to 6000 m drying trends prevails. However, a lesser rate of drying is observed for the higher elevations above around 4000 m as compared to altitudes between 2000 and 4000 m. The plausible causes of this certain behavior of SPEI trend with elevation is determined by further analysis of the trend of meteorological parameters (precipitation and PET) which were utilized for the computation of SPEI. Both precipitation and PET trends are found to be responsible for the SPEI trends along the elevation gradient. • Elevation-dependent drought characteristics over Indian extent of Indus river basin is explored for the period 1979–2020. • Wetting is associated with elevations up to around 2000 m, followed by drying trends along further altitude gradients. • Combination of PET and precipitation trends are responsible for the behavior of SPEI trends with respect to elevation. • The findings of the study point towards the drying (wetting) of the region at higher (lower) altitudes. [ABSTRACT FROM AUTHOR]

Rainfall is the dynamic weather parameter having a significant role in the agriculture livelihood. Growth in agriculture and other related sectors depends mainly on the adequate amount and timely availability of rainfall. Variability in precipitation exerts a huge impact on human beings and agriculture. This variation gives the necessity to study the regular pattern of rainfall. The present study aims at analysing the trends in rainfall intensity across various blocks of Tiruchirappalli district using daily rainfall data for the period 1990 to 2017. Non-parametric tests such as Mann- Kendall test and Sen's slope estimator were employed for this purpose. Results revealed that two blocks showed statistically significant increasing trends (95% confidence level) and one block showed significant decreasing trend (95% confidence level) and the remaining eleven blocks showed no significant trends. [ABSTRACT FROM AUTHOR]

Climate change analysis is essential, considering the numerous economic and ecological implications of this critical global environmental issue. This paper analyzes the spatial and temporal trends of mean air temperature in Romania's most important agricultural area, the south and south-eastern region, between 1961 and 2009. In this respect, multiannual (the entire period) and multidecadal (1961-1990, 1971-2000, 1981-2009) trends were analyzed using the Mann-Kendall test and Sen's slope method at 23 weather stations, annually, seasonally and for the growing season of the region's main agricultural crops (maize and wheat). Multiannually, the results showed statistically significant temperature increases, on all temporal scales (maximum rate of 0.06 °C/year recorded in summer, equivalent to a net temperature rise of 2.82 °C), except for the autumn season (cooling without statistical significance). Multidecadally, the 1961-1990 period is marked by a general cooling, especially in autumn (maximum values of −0.07 °C/year or over 2 °C net cooling). In the 1971-2000 and 1981-2009 periods, a general warming was observed (maximum in summer for both multidecades, when positive rates peaked at 0.09 °C/year, or 2.5-3 °C net warming), but the warming of the last three decades is the most prominent in terms of spatial average magnitude and trend significance. Upon analysis of the impact of climate warming on agricultural yields (maize) through linear regression, in the 1991-2000 decade, considered as case study, it was found that in 32 % of the total analyzed area there are evident relationships between the two variables ( p value <0.05). In this case, a dependency of 33-50 % (40 %, on average) of maize to climate was found, and a sensitivity (loss) ranging between 0.9 and 1.5 t/ha/year (1.2 t/ha/year, on average) for a 1 °C temperature rise. At the same time, significant losses (of up to 1.7 t/ha/year) of maize for a 1 °C temperature rise were identified in 51 % of the area, but with little p value significance (between 0.05 and 0.1). It is however necessary to analyse the agro-climatic results cautiously, considering that only one decade of climate-agriculture relationship was studied. The results can be useful first and foremost for mitigating the climate change impact on agricultural systems, by prioritizing future adaptation strategies enforced by policy makers. [ABSTRACT FROM AUTHOR]

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

The objective of this study was to assess trends in maximum and minimum temperatures and total monthly rainfall in the Punjab province of Pakistan. Non parametric Mann-Kendall and Sen's slope techniques were employed to find trend strength and magnitude. Serial correlation in data was removed by using TFPW (Trend Free Pre-Whitening) approach. Monthly data of maximum and minimum temperatures and total rainfall was obtained from Regional Meteorological Office (Lahore) for nine districts of Punjab for the period 1961- 2014. The maximum temperature showed a significant increasing trend at Rawalpindi and Faisalabad with a Sen Slope of 0.010°C/year, while significant increasing trends at eight stations were observed in minimum temperature on annual basis. All stations have experienced increasing trends in rainfall out of which only two stations have shown significant trend annually. Overall in Punjab, maximum temperature has shown a significant upward trend in spring (0.028°C/year) and downward trend in summer season (-0.013°C/year). While in minimum temperature, significant increasing trends were observed in all seasons excluding summer. A significant increasing trend in rainfall was observed in summer (1.79 mm/year), autumn and on annual basis (3.23mm/year). The results indicate that spring season is warming and the decreasing trend in summer temperature is caused by increasing trend of rainfall in the province. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess trends in maximum and minimum temperatures and total monthly rainfall in the Punjab province of Pakistan. Non parametric Mann-Kendall and Sen's slope techniques were employed to find trend strength and magnitude. Serial correlation in data was removed by using TFPW (Trend Free Pre-Whitening) approach. Monthly data of maximum and minimum temperatures and total rainfall was obtained from Regional Meteorological Office (Lahore) for nine districts of Punjab for the period 1961- 2014. The maximum temperature showed a significant increasing trend at Rawalpindi and Faisalabad with a Sen Slope of 0.010°C /year, while significant increasing trends at eight stations were observed in minimum temperature on annual basis. All stations have experienced increasing trends in rainfall out of which only two stations have shown significant trend annually. Overall in Punjab, maximum temperature has shown a significant upward trend in spring (0.028°C /year) and downward trend in summer season (-0.013°C /year). While in minimum temperature, significant increasing trends were observed in all seasons excluding summer. A significant increasing trend in rainfall was observed in summer (1.79 mm/year), autumn and on annual basis (3.23mm/year). The results indicate that spring season is warming and the decreasing trend in summer temperature is caused by increasing trend of rainfall in the province. [ABSTRACT FROM AUTHOR]

The main objective of this study is to evaluate discernible long term trends in streamflows of four major rivers of Pakistan, namely Kabul, Indus, Jhelum, and Chenab. For each river, the first hydrological station where flow rate is measured after its entry to Pakistan, has been selected. The stations, thus selected on Kabul, Indus, Jhelum and Chenab are Warsak, Tarbela, Mangla and Marala, respectively. The average monthly streamflow data for each of the four stations was collected from Irrigation department, Lahore for the period 1962-2011. The annual as well as seasonal analysis of average monthly streamflows was conducted using the Mann Kendall non-parametric test. For each case, the trend slopes were estimated using the Sen's slope method. A trend free pre-whitening (TFPW) approach was used to account for the auto correlation in the time series. Results indicate increasing trends for winter streamflows and decreasing trends for summer streamflows. For the spring season, Warsak exhibited decreasing trend, whereas the other stations showed increasing trends. Annual flow had a decreasing trend at all stations. The trends identified in this study may be partially attributed to the effects of climate change in Pakistan. [ABSTRACT FROM AUTHOR]

This study aims to investigate separate and combined impacts of land-use and climate variability on hydrological components in the Johor River Basin (JRB), Malaysia. The Mann-Kendall and Sen’s slope tests were applied to detect the trends in precipitation, temperature and streamflow of the JRB. The Soil and Water Assessment Tool (SWAT) was calibrated and validated using measured monthly streamflow data. The validation results showed that SWAT was reliable in the tropical JRB. The trend analysis showed that there was an insignificant increasing trend for streamflow, whereas significant increasing trends for precipitation and temperature were found. The combined (climate + land-use change) impact caused the annual streamflow and evaporation to increase by 4.4% and 1.2%, respectively. Climate (land-use) raised annual streamflow by 4.4% (0.06%) and evaporation by 2.2% (−0.2%). Climate change imposed a stronger impact than land-use change on the streamflow and evaporation. These findings are useful for decision makers to develop better water and land-use policies.Editor Z. W. Kundzewicz; Guest editor V. Krysanova [ABSTRACT FROM AUTHOR]

For sustainable water resource management, it is important to determine the relationship between streamflow and other variables that influence availability of water resources. However, many catchments do not have sufficient data to allow for a more detailed study of these relationships. We faced a similar challenge in the Chengcun Basin (limited historical data: from 1986-1999); and therefore we used a new approach to overcome this. We found that, using nonparametric trend methods in conjunction with the climate elasticity analyses and the 2D visualization of hydrologic data, it is possible to assess the relationships between streamflow and other hydro-climatic variables. In the past, streamflow trends in the basin were more correlated with precipitation than with potential evapotranspiration (PET). In addition, there is a gradual shift in the hydrological regime of the catchment, which may affect the occurrence of available water resources and activities that depend on them. In addition, based on our climate sensitivity analyses, the streamflow is dependent and more sensitive to variations in precipitation than to PET (δ Q=0.79δ P+0.42δ E; precipitation elasticity, ɛ =1.32; PET elasticity, ɛ =−2.10). Therefore pending more detailed studies, the use of our approach will provide a rapid means to assess the variation of water resources (streamflow) in a watershed. In the future, we hope to carry out related research in other watersheds and also perform a more detailed studies to improve upon the results of this study. [ABSTRACT FROM AUTHOR]