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This study presents a comprehensive analysis of rainfall trends in the middle Euphrates region of Iraq, extending from 1980 to 2018, including wide region between the stations of Samawa, Al-Najaf, Karbala, Hilla, and Diwaniya. The research aims to fill a critical gap in the understanding of regional hydrological patterns and provide essential insights for sustainable water resource management. Using advanced statistical methods, such as the Mann-Kendall test and Sen’s slope estimator, along with autocorrelation and cross-correlation analyses, we detected slight trends that were not previously reported. Principally, the Mann-Kendall test indicated no significant overall trends, while Sen’s slope estimator identified slight positive and negative trends at specific stations, highlighting local climatic variations. the findings reveal that all stations, except Samawa, indicated stationarity and homogeneity, with a particularly strong positive mutual correlation between Karbala and Hilla stations (0.7693 at lag 0). This research contributes new insights into rainfall variability in the Middle Euphrates, in Iraq, which presents significant data to improve water resource management strategies and inform future hydrological studies in the region.

This study presents a comprehensive analysis of rainfall trends in the middle Euphrates region of Iraq, extending from 1980 to 2018, including wide region between the stations of Samawa, Al-Najaf, Karbala, Hilla, and Diwaniya. The research aims to fill a critical gap in the understanding of regional hydrological patterns and provide essential insights for sustainable water resource management. Using advanced statistical methods, such as the MannKendall test and Sen’s slope estimator, along with autocorrelation and cross-correlation analyses, we detected slight trends that were not previously reported. Principally, the Mann-Kendall test indicated no significant overall trends, while Sen’s slope estimator identified slight positive and negative trends at specific stations, highlighting local climatic variations. the findings reveal that all stations, except Samawa, indicated stationarity and homogeneity, with a particularly strong positive mutual correlation between Karbala and Hilla stations (0.7693 at lag 0). This research contributes new insights into rainfall variability in the Middle Euphrates, in Iraq, which presents significant data to improve water resource management strategies and inform future hydrological studies in the region. [ABSTRACT FROM AUTHOR]

Interaction between rainfall and groundwater is a complex phenomenon as it varies spatially with respect to local hydrogeological characteristics and temporally with hydro meteorological variations. To understand the resilience of the groundwater system to the changing climate, rainfall-groundwater interaction needs to be analysed in detail. The Rainfall and Time Trends (HARTT) have been widely used in recent studies to model the impact of the rainfall and the groundwater level fluctuation. However, not many such studies have been reported in tropical hilly areas. Bhadra reservoir catchment is a tropical hilly catchment in India which is characterised by heavy rainfall, steep topography and shallow water table conditions and significant subsurface flow conditions. The area is largely dependent on groundwater for irrigation and drinking water supply. Nonparametric statistical methods such as Mann–Kendall (MK) test, Sen's slope estimator and Sequential Mann–Kendall Test (SQMK) are used to study the temporal trends in the rainfall and static groundwater levels. Further, contribution of rainfall to groundwater level fluctuation is analysed using HARTT model. Study shows a decreasing trend in rainfall and groundwater level in the upper catchment. Further, 1 mm increase or decrease in the rainfall anomaly is estimated to cause 0.0012 m decrease or increase in the depth to water table. Only 36% of the groundwater level fluctuation is explained by rainfall induced recharge; nevertheless, the relation is non-uniform throughout the catchment. Spatial variation in topography and hydrogeological conditions is suspected to have significant impact on the rainfall and groundwater interaction leading to poor coefficient of determination for the regression model between rainfall anomaly and the groundwater level fluctuations. [ABSTRACT FROM AUTHOR]

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen's slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors. [ABSTRACT FROM AUTHOR]

Rainfall is the most important fundamental physical parameter among the climate, as this parameter determines the environmental condition of the particular region, which affects the agricultural productivity. Global warming or climate change, is one of the most important worldwide issues discussed among scientists and researchers. One of the consequences of climate change is the alteration of rainfall patterns and an increase in temperature. The drastic changes in rainfall pattern showed a significant impact on society, and therefore its up-to-date information is needed to estimate the spatial distribution and variability at all points of the territory. In this paper, a study on trend analysis of rainfall data observed at Anasi, Haliyal, Kadra, and Supa rain gauge stations in Karnataka, India, was carried out. For this purpose, the annual 1-day maximum rainfall (AMR) and annual total rainfall (ATR) series were generated from the daily rainfall data and used in trend analysis. A non-parametric Mann-Kendall (MK) test was applied to evaluate the presence of significant trend in AMR and ATR, while the rate of significant trend was computed by Sen's slope estimator (SSE). The MK test results indicated that there is a decreasing trend in AMR series of Anasi, Haliyal, Kadra, and Supa. The study showed that the rate of decreasing trend in the AMR series of Anasi, Haliyal, Kadra, and Supa is computed as 1.4 mm/year, 0.1 mm/year, 0.6 mm/year, and 0.2 mm/year, respectively. For the ATR series, the rate of decreasing trend for Anasi was computed as 23.8 mm/year, whereas 11.2 mm/year for Supa, whereas the rate of increasing trend was 4.3 mm/year for Haliyal and 2.2 mm/year for Supa. This paper illustrated the application of the MK test and SSE for analyzing the trend in AMR and ATR of Anasi, Haliyal, Kadra, with Supa and the results obtained from the study. [ABSTRACT FROM AUTHOR]

Daily time series with continuous records of mean air and soil temperature from 127 meteorological stations—fairly distributed over the country—were used to compute monthly temperature trends, as well as changes in the timing of the first and the last frost days over Romania since 1961. Results show that the frequency of the number of days with daily temperature averages below 0 °C in case of air and soil surface temperature is stable for most months, except for January, when (for both soil and air temperature), the number of days with a temperature below 0 °C is decreasing in the majority of the stations. The occurrence of the first day with (mean air and soil surface) temperatures below 0 °C, presents a delay in the south, south-east, and west, and an earlier occurrence in eastern and central regions. The occurrence of the last day with a mean air and soil surface temperature below 0 °C shows a stable trend for most stations (except for some small areas in the north, south-east and south-west of Romania). The regime of the land temperature is more stable, due to the physical characteristics of the soil, compared to the more versatile atmosphere. Linkages between thermal parameters and large-scale atmospheric circulation are also discussed. [ABSTRACT FROM AUTHOR]

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

In order to grasp the evolutionary trend of drought and vegetation in various regions of North China, and to analyze the degree of response of vegetation to different drought types, it is of guiding significance for drought mitigation work. In the paper, data from 90 meteorological stations in North China were used to construct the standardized precipitation evapotranspiration index (SPEI), and the normalized vegetation index (NDVI) was selected to quantify the vegetation coverage. Then, the Sen's slope estimator, Mann-Kandall test, correlation analysis, and Copula-Bayesian conditional probability formula were used to analyze the drought sensitivity of vegetation in North China. The results show that: (1) the SPEI value in most parts of North China showed a extremely significant increase, the SPEI value in some parts of North China showed a extremely significant decrease, the NDVI value in the western and northern regions of North China showed an extremely significant increase, and the rest of the regions showed an extremely significant decline. (2) Drought and vegetation in North China were dominated by insignificant spatial clustering, with high and low values of drought and vegetation clustering in small areas. (3) In North China, the correlation between annual scale SPEI and NDVI was good, the response rate of vegetation to drought was slower and the sensitivity was low, the correlation between month-scale SPEI and NDVI was better in some parts of Henan, and the vegetation was more sensitive to drought, and the joint distribution function of NDVI and SPEI was the most consistent with the Clayton Copula function. (4) The likelihood of lowest vegetation coverage occurring in North China was decreasing with decreasing drought, the likelihood of lower vegetation coverage occurring was increasing from extreme to moderate drought and decreasing from moderate to light drought, and the likelihood of medium, higher and highest vegetation coverage all increase with decreasing drought. [ABSTRACT FROM AUTHOR]

This paper is an effort of geo-statistical analysis of rainfall variability and trend detection in the eastern Hindu Kush region located in the north-west of Pakistan. The eastern section of the HK region lies in the western part of Pakistan. Exploring rainfall variability and quantifying its trend and magnitude is one of the key indicators among all climatic parameters. In the study area, Pakistan Meteorology Department (PMD) has established seven meteorological stations: Drosh, Chitral, Dir, Timergara, Saidu Sharif, Malam Jabba, and Kalam. Daily, mean monthly, and mean annual rainfall time series data for all the met stations were geo-statistically analyzed in the GIS environment for detecting monthly and annual variability in rainfall, variability, and trend detection. Mann–Kendall (MK) and Theil-Sen's slope (TSS) statistical tests were applied to rainfall data. Initially, the MK test was applied for detection of trends and TSS test was used to quantify the change in magnitude. The results indicate that the rainfall variability in intensity and trend pattern detection. The analysis confirms that an extremely significant rainfall trend in the case of mean annual rainfall was predicted at Dir and Malam Jabba meteorological stations. Opposite to this, at Kalam and Chitral stations, a less significant rainfall trend was noted. In a similar context, no prominent rainfall trend has been found at Drosh, Timergara, and Saidu Sharif meteorological stations. Likewise, using TSS, an extremely negative variation in the magnitude of rainfall was verified at Kalam and Malam Jabba. However, a noteworthy positive change in rainfall magnitude has been noted at Dir and Saidu Sharif meteorological stations. The findings of this research have the potential to assist the decision and policy makers and academicians to think truly and conduct more scientific research studies to mitigate climate change. [ABSTRACT FROM AUTHOR]

In this paper, the trend analysis of groundwater level with reference to rainfall for a period from 1979 to 2022 has been carried out for the Thar district of Jaisalmer where the annual rainfall is the minimum in the state of Rajasthan. This area has not been researched for this kind of study earlier. Rainfall data have been collected from IMD (Indian Metrological Department) Pune whereas the groundwater data have been collected from CGWB (Central Ground Water Board, Govt. of India), GWD (Ground Water Department, Govt. of Rajasthan) and India-WRIS portal, Govt. of India. The collected data have been analysed in terms of fluctuations in groundwater level. Being located in the Thar Desert, Jaisalmer is the third largest and one of the hot districts in India where water availability plays a critical role. The statistical analysis has been performed by using Microsoft excel and XLSTAT statistical software in which Innovative trend analysis (ITA), Mann-Kendall Trend analysis Test (MK test) and Sen's slope estimator have been used. It has been observed that the yearly rainfall shows significantly upward trend (p < 0.05) during the study period whereas the groundwater level has significantly decreasing trend (p = 0.044) which indicates that groundwater level is rising. ITA support the results of MK test. The climatic and geological factors including unauthorized extraction of groundwater for irrigation purposes are also responsible for groundwater level fluctuation. In order to get the optimum out of the incident rainfall in the district, it is necessary to carry out a comprehensive study considering all relevant variables using advanced technology of assessment, measurement and extraction of groundwater, consumptive use of water, artificial recharge and regular monitoring at the level of local authorities in the field. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of temperature trends is vital for assessing the impacts of climate change on a regional scale. In this context, the present study focuses on Madhya Pradesh state in Central Indian region to explore the spatial-temporal distribution patterns of temperature changes from 1951 to 2021. Gridded temperature data obtained from the Indian Meteorological Department (IMD) in 1° × 1° across the state are utilised to analyse long-term trends and variations in temperature. The Mann-Kendall (MK) test and Sen’s slope (SS) estimator were used to detect the trends, and Pettitt’s test was utilised for change point detection. The analysis reveals significant warming trends in Madhya Pradesh during the study period during specific time frames. The temperature variables, such as the annual mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin), consistently increase, with the most pronounced warming observed during winter. The trend analysis reveals that the rate of warming has increased in the past few years, particularly since the 1990s. However, Pettitt’s test points out significant changes in the temperature, with Tmean rising from 25.46 °C in 1951–2004 to 25.78 °C in 2005–2021 (+0.33 °C), Tmax shifting from 45.77 °C in 1951–2010 to 46.24 °C in 2011–2021 (+0.47°C), and Tmin increasing from 2.65 °C in 1951–1999 to 3.19 °C in 2000–2021 (+0.46 °C). These results, along with spatial-temporal distribution maps, shed important light on the alterations and variations in monthly Tmean, Tmax, and Tmin across the area, underlining the dynamic character of climate change and highlighting the demand for methods for adaptation and mitigation. [ABSTRACT FROM AUTHOR]

In recent decades, a plethora of natural disasters, including floods, storms, heat waves, droughts, and various other weather-related events, have brought destruction worldwide. In particular, Algeria is facing several natural hydrometeorological and geological hazards. In this study, meteorological parameters (precipitation, temperature, relative humidity, wind speed, and sunshine) and runoff data were analyzed for the Wadi Ouahrane basin (northern Algeria), into which drains much of the surrounding agricultural land and is susceptible to floods. In particular, a trend analysis was performed using the Mann–Kendall (MK) test, the Sen’s slope estimator, and the Innovative Trend Analysis (ITA) method to detect possible trends in the time series over the period 1972/73–2017/2018. The results revealed significant trends in several hydro-meteorological variables. In particular, neither annual nor monthly precipitation showed a clear tendency, thus failing to indicate potential changes in the rainfall patterns. Temperature evidenced a warming trend, indicating a potential shift in the local climate, while streamflow revealed a decreasing trend, reflecting the complex interaction between precipitation and other hydrological factors.

Karnataka state has the second highest rainfed agricultural land in India, where agricultural output relies heavily on rainfall. The Shimsha basin, a sub-basin of Cauvery in the state, comes under a semi-arid region and predominantly consists of rainfed agricultural land. Rainfall patterns have changed dramatically with time resulting in frequent floods and droughts. Understanding the spatiotemporal distribution of rainfall and its change patterns in the area would benefit sustainable agriculture planning and water resources management practices. The current study aims to determine the variability and trend in rainfall. The daily rainfall data of the Shimsha basin from 1989 to 2018 is collected, and the annual, seasonal, and monthly rainfall totals and the number of rainy days are derived. All the time series are subjected to statistical methods to examine rainfall variability and trend. The mean, standard deviation, coefficient of variation (CV), and Standardized Anomaly Index are used for the preliminary and variability analysis, while the coefficient of skewness and kurtosis are used to understand the rainfall distribution characteristics. The homogenous and serially independent series are identified by homogeneity and serial correlation tests. The trend in the homogenous and serially independent series is identified by Mann–Kendall and Spearman's rank correlation tests, while the magnitude of the trend is quantified using the Sen's slope technique, and the trend change point is evaluated using the sequential Mann–Kendall test. Based on the study, the average rainfall in the study area is 801.86 mm, with CV ranging from 43.3 to 22.27%. The southwest monsoon (SWM) season brings the greatest rain to the basin, followed by the post-monsoon (PM), summer, and winter seasons. In the annual time frame, except one station, all other stations have shown significant or insignificant increasing trends. The seasonal rainfall has shown insignificant rising trends during the summer and winter seasons while insignificant increasing and decreasing trends during the PM season. The SWM season has indicated significant increasing trends, insignificant increasing and decreasing trends. Overall, the study area has noticed an increased annual and seasonal rainfall except for the post-monsoon season, during which the rainfall showed a considerable decline. The findings of the study are helpful in water resource management, agricultural planning, and socioeconomic development in the study area. [ABSTRACT FROM AUTHOR]

As a semi-arid Mediterranean country, Tunisia is affected by the impacts of climate change, particularly the coastal regions like the Cap-Bon. Irregular rainfall, rising temperatures and the recurrence of extreme events are all indicators that affect ecosystems and populations and make them more vulnerable to the influence of climatic variables. Therefore, an analysis of the trends of climate variables can contribute to facilitating the development of effective adaptation strategies. In this matter, this study was conducted to assess the homogeneity and trends of minimum and maximum air temperature (Tmin and Tmax) and precipitation (P) in the Cap-Bon region. Daily data were collected from the meteorological station of Nabeul for the period of 1982–2020. Pettitt and SNHT tests for homogeneity were applied to identify the breakpoints in multi-time scales of Tmax, Tmin and P data series. The Mann–Kendall (MK) test was used to detect the change in the time-series trend. A modified Mann–Kendall (mMK) test was used to remove the autocorrelation effect from the data series. Both the MK and mMK tests were used at the 5% significant level. The magnitude of the climatic trend was estimated using the non-parametric Sen's slope estimator. Contrary to Tmin and P, the results of the homogeneity tests revealed the existence of significant breakpoints in the annual, seasonal and monthly Tmax time series. For most cases, the breakpoint occurred around the year 2000. For Tmin, significant breakpoints were recorded in March and April, while a significant shift in the P time series was detected in December. The Mann–Kendall results show a significant warming trend in annual Tmax, with magnitudes equal to 0.065 and 0.045 °C/year before and after the breakpoint, respectively. Nevertheless, non-significant tendencies were observed in the annual Tmin and P time series. On the monthly time scale, Tmax exhibited a significant upward trend in June and August, before the observed breakpoints, with Sen's slope values equal to 0.065 and 0.045 °C/year, respectively. Regarding the Tmin data, a significant positive trend was observed in July at a rate of 0.033 °C/year. [ABSTRACT FROM AUTHOR]

The detection of rainfall trends is vital for water resource development in small island states such as Trinidad and Tobago. This study investigates whether climate change affects rainfall trends and conducts statistical analysis of annual, seasonal, and decadal cumulative rainfall data obtained from two meteorological stations in Trinidad and Tobago for the period 1990-2020. Using XLSTAT, the nonparametric Mann-Kendall's test was conducted at a 5% significance level to detect whether trends in the rainfall data existed, and the nonparametric Sen's slope estimator was used to detect the magnitude of the trends. The results showed no statistically significant trends in Trinidad and Tobago's annual, seasonal, or decadal rainfall over the 30 years considered. This result indicates that Trinidad and Tobago are safe from abrupt changes in rainfall trends due to climate change and highlights the significance of conducting localized climate studies rather than solely depending on the predictions of global climate models. [ABSTRACT FROM AUTHOR]

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Introduction and Objective: One of the main factor s of the reducing agricultural production is the irrigation water salinity. Mazandaran province is one of the most important citrus -producing area in Iran, where the groundwater used for supplying the irrigation water in citrus orchards of the province. The main objective of this paper was to determine map spatial and temporal variations of groundwater salinity (EC) in the coastal strip of Mazandaran province with an area of 8252 km 2 . The collected data of 300 wells of the study area were measured by Mazandaran Regional Water Authority for 9 consecuti v e years and defined for ArcGIS 10.7.1 software as the average ECs for each 6 months. Material and Methods: EC maps w ere obtained by ordinary kriging (OK) for each 6 - month periods from and the beginning of 2012 to the end of 2020, by using ArcGIS 10.7.1 software. According to the derived empirical function of the effect of EC on the citrus yield (Y=100 -13(EC -1.4)). According to this function, ECs of 1.40, 2.17, 2.94 and 3.71 dS/m, corresponding to relative yields of 100, 90, 80 and 70% were selected, respectively. Thereby, areas belonging to the classes of 100%, 90 -100%, 80 -90% and <70% were outlined. In addition, th e M ann–Kendall test an d Sen ’ sslop e wer e use d t o pr ojec t futur e changes . Results: The result of EC maps indicated that the salinity of groundwater increases from west to east of the province. The Mann -Kendall test result showed a significant temporal trend of the size of the area below the <70% yield (EC >3.71 dS/m) and 100% (EC <1.40 dS/m), presenting that the salinity of groundwater can be a concern for citrus orchards in the coastal strip of Mazandaran province. The equation given by Sen’s slope estimator denoted that if this trend is continuing, the area under 100% yield will reach to zero in 2021 and the yield of citrus in the coastal strip will reach below 70% at the latest by 2047. Conclusion: This study has shown that the salinity of groundwater was increasing in the eastern part over the time and it covered a wider area around the Miankaleh lagoon, which may be due to the leakage of the lagoon to the groundwater aquifer in that area. The reduction of groundwater quality over the time can be attributed to two factors: reduced rainfall in recent years and digging illegal wells and subsequently consumed extraction of wells in the region. Taken together, it is suggested that the wells in the area will be exploited completely controlled to prevent the reduction trend of its quality . [ABSTRACT FROM AUTHOR]

Managing climate change-induced impacts on livelihoods in the Himalayan belt is a challenging task. This is because livelihoods are highly vulnerable to climate change and depend on both biophysical and social processes. In this study, the vulnerability of livelihoods to climate variability was investigated in Jammu province. The variability of climate variables was studied by applying Mann–Kendall test and Sen's Slope estimator. Similarly, vulnerability index was applied to assess livelihood vulnerability. The result of the study showed that weather stations in Katra, Batote and Banihal showed negative trend in rainfall during 1987–2019, while Samba, Rajouri and Jammu showed positive trend. However, only Jammu district showed significant trend at 0.01 level of significance. Similarly, Katra, Bhaderwah and Jammu showed negative trend in average maximum temperature while Banihal and Batote showed positive trend. However, none of the weather stations showed a significant trend at the 0.01 level of significance. The livelihood vulnerability index results showed that Ramban and Kishtwar districts were the most vulnerable, while Jammu district was the least vulnerable to climate variability. The vulnerability results show that mountainous regions and remote districts are particularly vulnerable to climate variability and change. The results of this study could be useful for livelihood vulnerability mitigation and planning in Jammu province and other mountainous regions of India and the world. [ABSTRACT FROM AUTHOR]

Daily time series with continuous records of mean air and soil temperature from 127 meteorological stations—fairly distributed over the country—were used to compute monthly temperature trends, as well as changes in the timing of the first and the last frost days over Romania since 1961. Results show that the frequency of the number of days with daily temperature averages below 0 °C in case of air and soil surface temperature is stable for most months, except for January, when (for both soil and air temperature), the number of days with a temperature below 0 °C is decreasing in the majority of the stations. The occurrence of the first day with (mean air and soil surface) temperatures below 0 °C, presents a delay in the south, south-east, and west, and an earlier occurrence in eastern and central regions. The occurrence of the last day with a mean air and soil surface temperature below 0 °C shows a stable trend for most stations (except for some small areas in the north, south-east and south-west of Romania). The regime of the land temperature is more stable, due to the physical characteristics of the soil, compared to the more versatile atmosphere. Linkages between thermal parameters and large-scale atmospheric circulation are also discussed.

The drainage modulus is an important indicator in the drainage system design of farmlands. Changes in the drainage modulus determine the effectiveness of drainage projects, and thus agricultural production. Thus, in this research, the trends in the drainage modulus of the Huaibei Plain, China were examined. The drainage modulus was estimated using the average draining method at 16 meteorological stations located in different areas of the Huaibei Plain during the period of 1960–2017. The trends of the drainage modulus were investigated using the Mann–Kendall test and Sen's slope estimator. The periodicities of the drainage modulus were investigated using wavelet analysis. The major environmental factors affecting the drainage modulus were investigated using the contribution rate method. The results showed that the mean drainage modulus (q1, q3) had increasing trends and significant 2.4-year and 2.5-year periodicities, respectively. An increase in building lots was the main factor that influenced the variability in the drainage modulus. Rapid urbanization increased the risk of agricultural waterlogging. These results provide important references for scientific planning in agriculture and farmland drainage engineering. [ABSTRACT FROM AUTHOR]

Land desertification is a significant research area among current global ecological and environmental issues. Desertification not only affects the ecological environment, but is also closely related to human society. With the development of new technology, outstanding progress has been made in the development of desertification monitoring and evaluation indicators. The objective of this study was to assess the trends and distribution of land desertification in northern China using time-series GIMMS NDVI 3 g and MODIS-NDVI remote sensing data from 1991 to 2019. The Dimidiate Pixel Model was chosen to calculate the Vegetation Coverage Index (VCI). The Sen's slope estimator and the Mann–Kendall statistical test were used to analyze the spatial trends of the VCI. The residual trend method was applied to assess human and climate factor induced land degradation. Data from the study area showed that the total area of desertification in northern China decreased year by year from 1991 to 2019, but the area of very severe desertification demonstrated an increasing trend. At the same time, areas of severe, moderate, and mild desertification showed a decreasing trend. From the overall analysis, a trend of overall decrease and local aggravation of land desertification was revealed. The residual analysis showed that desertification control measures and favorable climatic conditions have played key roles in the process of desertification reversion; while climate fluctuations, reclamation and livestock have led to the development of further desertification. [ABSTRACT FROM AUTHOR]

The present study investigates long-term changes in the rainfall regime over the Sabarmati River Basin, Western India, during 1981–2020 using computational and spatial analysis tools. Daily gridded rainfall data from India Meteorological Department (IMD) at 0.25 × 0.25 spatial resolution was employed to determine changes in rainfall at annual, monthly, and seasonal scales and analyze changes in rainfall characteristics using different thresholds for dry/ wet days and prolonged spells over Western India. Mann–Kendall test, Sen slope estimation, and linear regression analysis indicate that annual and monsoon rainfall over the basin has increased while the rest of the seasons have shown a declining trend. However, none of the trends obtained was found to be statistically significant. Spatial analysis of rainfall trends for each decade between 1980 and 2020 revealed that certain parts of the basin had experienced a significant declining trend during 1991–2000. Monthly rainfall analysis indicates the presence of a unimodal distribution of rainfall and a shift in rainfall towards later monsoon months (August and September). It is also inferred that days with moderate rainfall have decreased while low and extreme rainfall events have increased over the basin. It is evident from the study that the rainfall regime is highly erratic, and the study is important in understanding the changes in the rainfall regime during the last 40 years. The study has significant implications for water resource management, agricultural planning, and mitigation of water-related disasters. [ABSTRACT FROM AUTHOR]

This study investigates the trend in monthly and annual rainfall, and minimum and maximum temperature (Tmin and Tmax) in the Savannah region of Togo. The historical data of Mango and Dapaong weather stations from 1981 to 2019 were used. A serial correlation test was applied to all time series to identify serially independent series. A Non-parametric Mann–Kendall (MK) test was applied to serially independent series. The magnitude of the trend was calculated using the Sen's slope (SS) method. For the data influenced by serial correlation, a modified version of the Mann–Kendall test was applied. An open-source library package was developed in the R language, namely, "mkmodified". For annual rainfall, results showed a significant increasing trend at Dapaong (p < 0.05) and a non-significant decreasing trend at Mango (p > 0.05) at 95%. There was an increasing trend in the Tmin both at Mango and Dapaong. No statistically significant trend was found at Mango (p > 0.05), while at Dapaong (p < 0.05), a significant trend was found at 95%. Simlarly, there was a statistically increasing trend in the Tmax both at Mango and Dapaong. Rainfall in Dapaong has increased (5.50 mm/year) whereas in Mango, it has decreased (−0.93 mm/year). Tmn increased by 0.04 and 0.008 °C per year in Mango and Dapaong, respectively. Tmax increased by 0.03 and 0.02 °C per year in Mango and Dapaong, respectively. A Rainfall Anomaly Index (RAI) was also used to present a temporal variation in rainfall; the historical series presented drier years. Many studies have analysed the trend of climate parameters in northern Togo, but none of them has specifically targeted the Savannah region that is considered the poorest region of the country. [ABSTRACT FROM AUTHOR]

The effect of climate prevails on a diverse time scale from days to seasons and decades. Between 1993 and 2013, global warming appeared to have paused even though there was an increase in atmospheric greenhouse gases. The variations in oceanographic variables, like current speed and sea surface temperature (SST), under the influence of the global warming hiatus (1993–2013), have drawn the attention of the global research community. However, the magnitude of ocean current and SST characteristics oscillates and varies with their geographic locations. Consequently, investigating the spatio-temporal changing aspects of oceanographic parameters in the backdrop of climate change is essential, specifically in coastal regions along Kuroshio current (KC), where fisheries are predominant. This study analyzes the trend of ocean current and SST induced mainly during the global warming hiatus, before and till the recent time based on the daily ocean current data from 1993 to 2020 and SST between 1982 and 2020. The Kuroshio extent is delineated from its surrounding water masses using an aggregation of raster classification, stretching, equalization, and spatial filters such as edge detection, convolution, and Laplacian. Finally, on the extracted Kuroshio extent, analyses such as time series decomposition (additive) and statistical trend computation methods (Yue and Wang trend test and Theil–Sen’s slope estimator) were applied to dissect and investigate the situations. An interesting downward trend is observed in the KC between the East coast of Taiwan and Tokara Strait (Tau = −0.05, S = −2430, Sen’s slope = −5.19 × 10−5, and Z = −2.61), whereas an upward trend from Tokara Strait to Nagoya (Tau = 0.89, S = 4344, Sen’s slope = 8.4 × 10−5, and Z = 2.56). In contrast, a consistent increasing SST in trend is visualized in the southern and mid-KC sections but with varying magnitude.

This paper has examined the variability and trends of rainfall in the Borana zone, southern Ethiopia. Monthly rainfall data from 1981 to 2018 were obtained from the National Meteorological Agency (NMA) of Ethiopia. Mean, standard deviation and coefficient of variation were employed to analyze temporal variability. Mann–Kendall (MK) test and Sen's slope estimator (SEE) were used to determine trend and its magnitude, respectively. The inverse weighting distance (IDW) interpolation technique was employed to generate surface data and produce spatial rainfall maps. April and Belg were the wettest month and season, respectively. On an annual basis, Arero (741 mm) followed by Teltele (629 mm) were the wettest stations, whereas the Dillo station (285 mm) was the driest. Rainfall is highly variable on a monthly and seasonal basis than annual timescale. Meher rainfall has shown a significant rainfall increase (P-value

Climate change is considered as a significant man-made global environmental challenge currently faced by the mankind today. The warming has a direct impact on the temperature sensitive snow and ice cover, geo-hazards and water supply.Objective of this study is to assess the long term climate changein the Kumaun Himalaya region. Monthly temperature and rainfall India Metreological Department (IMD) data of years from 1907 to 2015 has been processed in the study. Monthly trend and statistical significance of rainfall and temperature were estimated using Mann-Kendall (MK) Test and the Sen’s Slope Estimator.The results show that monthly, annual and seasonal air temperature has increasing trend at significant level during the past 109 years, as against the global average of 0.5°C. The overall monthly and annual precipitation has decreasing trend at significant level in all weather station under study except Mukteshwar.Annual mean minimum temperature of the Kumaun Himalaya region showed a very significant increasing trend and has increased by 1.026°C per 110 years during the period 1907-2015. This warming is mainly contributed by the winter and post-monsoon seasons, which have shown increasing trend at significant level as compared to other seasons in the last century. The rainfall over the region showing significant decreasing trend in monthly rainfall over the time In monsoon season, rainfall is showing decreasing trend at significant level all over the Kumaun region but winter, pre monsoon and post monsoon season showing high degree of variability in trend and magnitude of rainfall. [ABSTRACT FROM AUTHOR]

Analysis of historical data on rainfall and streamflow provides useful information for water resources management in a river basin. The objective of this study was to assess the variations and trend analysis of rainfall and streamflow data in the upper Maduru Oya sub watershed in Sri Lanka during a 30 year period (1989 October to 2019 September) using daily rainfall data from two gauging locations (Padiyathalawa and Bibile) and daily average streamflow data from one gauging location (Padiyathalawa). Descriptive statistics were used to assess the variations. The Mann Kendal Trend Test (MK test) and Innovative Trend Analysis method (ITA) were used to analyze the trend, and Sen's Slope Estimator was used to assess the magnitude of the trend. Based on the MK test, most of the rainfall trends obtained are in an increasing direction, and streamflow trends are in a decreasing direction. Rainfall trends found in Padiyathalawa are not statistically significant. Annual, First Inter Monsoon, March, and May time scales of rainfall showed significant upward trends at Bibile (p<0.1) while streamflow in January, April, and September showed significant negative trends (p<0.1) at Padiyathalawa. The results displayed by all three tests were in very good agreement for rainfall. ITA results showed similar trend types of 77%, 95% and 41% at Padiyathalawa and Bibile rainfall and streamflow, respectively. A significant positive (p<0.01) strong and lower correlation between the trend value of the ITA and the Z value of the MK test were found for rainfall and streamflow, respectively. Changes in rainfall are not sufficient to explain the observed trends in streamflow. Therefore, future research should be directed at the causal aspects of streamflow change in this watershed. [ABSTRACT FROM AUTHOR]

We analyzed the distribution and number of forest fire occurrences, burned areas, and seasonality, and their trends of human- and lightning-caused small (<200 ha) and large (≥200 ha) fires from 1959 to 2021 in the forested 14 subregions of Alberta, based on the Canadian National Fire Database. We applied a non-parametric statistical test, i.e., Mann–Kendall and Sen's slope estimator, for the patterns and magnitudes of the trends. Our results revealed that all subregions experienced significantly increasing trends of fire occurrences, either monthly or yearly, except the Alpine subregion. In the burned area case, nine ecoregions demonstrated significantly decreasing monthly trends for small fires caused by humans, except for an increasing trend in the Lower Boreal Highlands subregion in May. For seasonality, we found one to two days for both early start and delayed end of fire season, and eventually two to four days longer fire seasons in five ecoregions. This study provides an updated understanding of the fire regimes in Alberta. It would be helpful for fire management agencies to make strategic plans by focusing on high-priority regions to save lives and properties. [ABSTRACT FROM AUTHOR]

Farmers usually do not know the precise output that is affected by climatic factors such as temperature and rainfall and are characterized by inter-annual variability, part of which is caused by global climate change. No study covers the influences of climate factors on yield and yield risk in the context of chickpea farming in Andhra Pradesh, India. In this context, this study aimed to investigate the trends in climate change variables during Rabi season (October to January, 1996-2020) and evaluated their variability on chickpea yields across different agro-climatic zones in Andhra Pradesh by employing Just and Pope production function. Four non-parametric methods-Alexandersson's Standard Normal Homogeneity Test, Buishand's Range Test, Pettitt's Test and Von Neumann's Ratio Test are applied to detect homogeneity in the data. Mann--Kendall (MK) test and Sen's slope (SS) method were employed to analyze monthly rainfall trends and minimum and maximum temperature trends. Results of Just and Pope (panel data) quadratic and Cobb-Douglas methods revealed that monthly minimum temperature positively influenced the mean yield of chickpea (0.22% and 0.16%, respectively). However, rainfall (-0.41% and -0.31%) and maximum temperature (-0.08% and -0.04%) negatively influenced the mean yield of chickpea under quadratic and Cobb-Douglas models, respectively. Accordingly, rainfall (0.08% and 0.06%) and maximum temperature (0.83% and 0.72%) positively influenced the yield variability and minimum temperature (-0.77% and -0.67%) reduced yield variability of chickpea under quadratic and Cobb- Douglas models respectively. In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh. [ABSTRACT FROM AUTHOR]

The study was conducted to analyze spatial and temporal variations of lightning activity over Sri Lanka and the surrounding coastal belt region bounded by 5.75–10.00 N and 79.50–89.00 E. Flash data collected by the Lightning Imaging Sensor (LIS) on NASA's Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2014 and the Lightning Imaging Sensor placed on the International Space Station (ISS) from 2018 to 2021 were used for the study. The Mann-Kendall test and Sen's slope estimator were applied to annual and seasonal lightning data from 1998 to 2014 to identify the trends in the TRMM dataset. A positive slope of 0.23 was obtained for annual flash densities, while a slope of 0.956 was obtained for First Inter-Monsoon (FIM) seasonal data. Considering the ISS data, the annual variation of lightning activity in 2020 displays the lowest flash density, whereas the highest is represented in 2019 with a value of 10.48 flashes km−2 year−1. The highest mean flash density is observed in Colombo in 2019 at a value of 34.85 flashes km−2 year−1. Overall, April displayed the highest annual flash distribution from 2018 to 2021, whereas the second peak was mostly viewed around September and November. All districts have displayed a significant amount of lightning during April for the period 2018 to 2021. FIM displayed the highest lightning distribution over the country. When considering the seasonal variation, districts belonging to the wet zone and intermediate zone displayed most flashes during the FIM. [ABSTRACT FROM AUTHOR]

Rainfall variability and water scarcity are the major issues in the semi-arid Marathwada region of Maharashtra. Analysis of seasonal and annual rainfall distribution and trends over the Marathwada is the main objective of the research. Therefore, district-wise monthly rainfall data of 8 districts for 121 years (1901–2021) in the Marathwada was employed, while coefficient of variation (CV), Mann–Kendall (MK), Sen's slope estimator (SSE), innovative trend analysis (ITA), inverse distance weighted (IDW), and rainfall departure from the mean methods were used for analyses. The results showed that monsoon (22.7%) and annual (21.3%) rainfall variability is less than that of post-monsoon (59.9%), winter (110%), and pre-monsoon (67%) seasons. The MK and ITA result specified no significant trends (positive and negative) in monsoon, post-monsoon, and annual rainfall over the region. During the winter (Z = − 1.65) and pre-monsoon (Z = − 1.67) seasons, a significant decreasing trend in rainfall was observed for the Marathwada. However, negative changes (− 25.54% and − 30.81%) in the magnitude of winter and pre-monsoon rainfall were significant in the region. Annual rainfall 55% of the time was below the long-term annual average rainfall (776 mm) of Marathwada. The region experienced three extremely wet years (1916, 1983, and 2019) and two dry years (1920 and 1972). Although seasonal and annual rainfall variations, the monsoon and annual rainfall have not shown significant positive or negative trends over the Marathwada region during 1901–2021. Since Marathwada is vulnerable to water scarcity, this study could help policymakers associated with water resources and agriculture management. [ABSTRACT FROM AUTHOR]

The effect of climate prevails on a diverse time scale from days to seasons and decades. Between 1993 and 2013, global warming appeared to have paused even though there was an increase in atmospheric greenhouse gases. The variations in oceanographic variables, like current speed and sea surface temperature (SST), under the influence of the global warming hiatus (1993–2013), have drawn the attention of the global research community. However, the magnitude of ocean current and SST characteristics oscillates and varies with their geographic locations. Consequently, investigating the spatio-temporal changing aspects of oceanographic parameters in the backdrop of climate change is essential, specifically in coastal regions along Kuroshio current (KC), where fisheries are predominant. This study analyzes the trend of ocean current and SST induced mainly during the global warming hiatus, before and till the recent time based on the daily ocean current data from 1993 to 2020 and SST between 1982 and 2020. The Kuroshio extent is delineated from its surrounding water masses using an aggregation of raster classification, stretching, equalization, and spatial filters such as edge detection, convolution, and Laplacian. Finally, on the extracted Kuroshio extent, analyses such as time series decomposition (additive) and statistical trend computation methods (Yue and Wang trend test and Theil–Sen's slope estimator) were applied to dissect and investigate the situations. An interesting downward trend is observed in the KC between the East coast of Taiwan and Tokara Strait (Tau = −0.05, S = −2430, Sen's slope = −5.19 × 10−5, and Z = −2.61), whereas an upward trend from Tokara Strait to Nagoya (Tau = 0.89, S = 4344, Sen's slope = 8.4 × 10−5, and Z = 2.56). In contrast, a consistent increasing SST in trend is visualized in the southern and mid-KC sections but with varying magnitude. [ABSTRACT FROM AUTHOR]

Abstract Background Understanding the climate variability at local scale could help suggest local adaptation responses to manage climate associated risks. This paper analyzed the variability and trend of climate in semi-arid Borana zone of southern Ethiopia over the period 1981–2018 using Mann–Kendall (MK) test, Sen’s Slope Estimator (SEE) and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) climate data (daily precipitation, daily maximum temperature (Tmax) and minimum temperature (Tmin)) were collected from National Meteorology Agency (NMA) of Ethiopia. Results The results revealed the study area received a mean monthly precipitation of 39.19 mm and a monthly mean Tmax and Tmin of 29.66 °C and 16.31 °C were observed respectively. Rainfall shows a significant increasing trend during August, October and November and extremely variable during December, January and February where CV > 100%. Tmax shows a significant warming trend during August but January, February, August and October exhibited similar trend for Tmin. Rainfall and Tmin shows a significant trend during Meher and no trend for the rest of the seasons. Mean annual rainfall shows a significant increase where no trend observed for both Tmax and Tmin at this timescale. Decadal rainfall and Tmin exhibited no trend but Tmax show significant warming trend during 2001–2010 decade. Better rainfall and cooler temperature were observed in the north central, northeastern and northwestern whereas the southeastern and southwestern regions were drier and warmer. Conclusion Rainfall is highly variable than temperature both at temporal and spatial scales in Borana. The intensity of rainfall decreases from the northeastern and northwestern parts towards the southwest while temperature increased from the north central parts towards the southwest for Tmax and the southeast for Tmin. The effect of topography is substantial for the local scale variability observed in the study area. Internal variability is observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.

As a semi-arid Mediterranean country, Tunisia is affected by the impacts of climate change, particularly the coastal regions like the Cap-Bon. Irregular rainfall, rising temperatures and the recurrence of extreme events are all indicators that affect ecosystems and populations and make them more vulnerable to the influence of climatic variables. Therefore, an analysis of the trends of climate variables can contribute to facilitating the development of effective adaptation strategies. In this matter, this study was conducted to assess the homogeneity and trends of minimum and maximum air temperature (Tmin and Tmax) and precipitation (P) in the Cap-Bon region. Daily data were collected from the meteorological station of Nabeul for the period of 1982–2020. Pettitt and SNHT tests for homogeneity were applied to identify the breakpoints in multi-time scales of Tmax, Tmin and P data series. The Mann–Kendall (MK) test was used to detect the change in the time-series trend. A modified Mann–Kendall (mMK) test was used to remove the autocorrelation effect from the data series. Both the MK and mMK tests were used at the 5% significant level. The magnitude of the climatic trend was estimated using the non-parametric Sen’s slope estimator. Contrary to Tmin and P, the results of the homogeneity tests revealed the existence of significant breakpoints in the annual, seasonal and monthly Tmax time series. For most cases, the breakpoint occurred around the year 2000. For Tmin, significant breakpoints were recorded in March and April, while a significant shift in the P time series was detected in December. The Mann–Kendall results show a significant warming trend in annual Tmax, with magnitudes equal to 0.065 and 0.045 °C/year before and after the breakpoint, respectively. Nevertheless, non-significant tendencies were observed in the annual Tmin and P time series. On the monthly time scale, Tmax exhibited a significant upward trend in June and August, before the observed breakpoints, with Sen’s slope values equal to 0.065 and 0.045 °C/year, respectively. Regarding the Tmin data, a significant positive trend was observed in July at a rate of 0.033 °C/year.