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The spatiotemporal variability of rainfall, particularly in the context of climate change, has been imperative for examining the cropping patterns, farming sustainable crop production, and food security in rainfed areas. To that end, trend analysis was done to study the change in rainfall patterns in the mid-hills of Himachal Pradesh. The study investigated the historical rainfall data from 1971 to 2020 on a monthly, annual, seasonal, and decadal basis by using the variability analysis methods, viz., standard deviation (SD), coefficient of variance (CV), and transformed annual precipitation departure (Z). The trend analysis was also done by Mann-Kendall (MK) and Sen's slope estimator (SSE) test and linear regression model. The annual rainfall in the region was 1115.1 mm, which showed a decreasing trend (Z =  - 0.79 mm/year). Based on the linear regression model, the decrease in annual rainfall was about - 2.28 mm/year. The monthly and seasonal variability of rainfall exhibited a sensitivity to change. The months of January, April, July, and September showed an increasing trend, whereas the rest of the other months showed a decreasing trend. The seasonal rainfall (summer, monsoon, and post-monsoon) showed a decreasing trend, whereas the winter season depicted an increasing trend. During the entire study period, 1988 recorded as the wettest year, with highest annual rainfall of about 2205.0 mm and monsoon rainfall of about 1653.0 mm. The highest annual (2205.0 mm) and monsoon (1653.0 mm) rainfall was recorded in the year 1988. The decadal analysis of the rainfall on an annual basis revealed a decrease in rainfall during the periods 1971-1980, 2001-2010, and 2011-2020 as compared to 1981-1990 and 1991-2000. The rainfall over the study region confirms the strength of the change in trend. Thus, the erratic rainfall pattern makes the cropping calendar shorter and affects the agricultural productivity., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The high variability of the sub-desert climate, especially in the south-eastern region of Morocco, has severe socioeconomic impacts on the inhabitant's way of life, as is the case in the Daoura watershed, where this variability is associated with droughts or exceptional rainfall. The data collected from the Guir-Ziz-Rheriss hydraulic agency were processed, corrected and analyzed using the Climatol package (version 4.0.0) developed in R software to homogenize rainfall data. Through this work, the significance and amplitudes of annual and monthly rainfall trends were defined using the Mann-Kendall test and Sens's slope estimator, while comparing the results of raw and homogenized data. The Daoura watershed has a sub-desert climate, and the homogenization process revealed a few rainfall stations with significant positive trends at confidence levels ranging from 90% to 95%. According to the raw and homogenized data, the majority of these stations are located in the High Atlas (CR1) and Anti-Atlasic (CR2) zones, where there is considerable spatiotemporal variability in rainfall from one year to the next. The essential objective of this scientific paper was to analyze the spatiotemporal variability of monthly and annual precipitation and to study their trends through rainfall data homogenized by the climatol package (version 4.0.0) from 13 stations over a period (1957-2018). The contribution of this study to science is the rainfall data it offers, which is useful for managing natural resources in sub-desert areas. [ABSTRACT FROM AUTHOR]

The effects of global warming and climate change appear as increasing or decreasing trends in hydrometeorological records in different locations. Identifying trends in long-term (more than 30 year) data is possible through a variety of methodologies as well as classical Mann–Kendall (MK), Regression (R), Spearman's Rho (SR) methods in addition to the innovative trend analysis (ITA) approaches. The most used method in the literature is the MK trend determination test, but it has limited assumptions, and the trend slope is calculated according to Sen's median procedure. However, Sen's approach is an empirical methodology that considers a single median slope from all possible consecutive lag slopes. This paper provides the theoretical probability distribution function (PDF) that matches Sen's slopes, and an innovative probabilistic trend slope methodology is proposed with a set of slope risk levels, rather than statistical slope calculation. The application of the proposed methodology is presented for long-term Danube River annual discharge data in Romania and precipitation records at Antalya resort center in the south along the Mediterranean coast of Turkey. A set of trend lines, objectively different risk levels, are obtained. It has been determined that there are decreasing and increasing monotonic trends in each historical time series record. Therefore, for extreme events, it is possible to consider a particular risk level trend characteristic, i.e., floods and droughts, rather than the classical mean or median level trend definition. [ABSTRACT FROM AUTHOR]

Investigating the temporal dynamics of rainfall in a changing climate, especially in rainfed agriculture regions, is crucial for analyzing climate-induced changes and offering adaptation options. Since Mizoram experiences unfavorable impacts of rain nearly every year, the region rainfall has been altering over the years, and vital climatic activity is becoming uncontrollable. The current study is primarily concerned with the changing trend of rainfall over Mizoram, which includes both short-term persistence (STP) and long-term persistence (LTP) of rainfall in seasonal and annual time series of rainfall overseeing for the period of 25 years of daily average rainfall from 1996 to 2020 collected collectively from the seven stations over the study area of Mizoram. Four different Mann-Kendall method iterations were used to analyze rainfall trends: the original or conventional method (without autocorrelation) (MnKn1), removing lag-1 autocorrelation (trend-free pre-whitening), considering multiple lag autocorrelation (more than lag-1 autocorrelation) (MnKn3), and Hurst coefficient or LTP (MnKn4). In the analysis, the study found that during monsoon, station Lawngtlai (LT) observed the highest rainfall having a Z value of 1.986, increased by 0.466 cm/year, while station Serchhip (SC) observed the lowest rainfall having Z value of −2.282, decreased by −0.163 cm/year. After applying modified MnKn4, we observed LTP of rainfall in winter at station Lawngtlai (LT) with an increasing trend and other stations observing STP in almost all seasons either increasing or decreasing trend. Therefore, possible climate change adaptation measures should be made to optimize rainfall use for various applications for the states of Mizoram. [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]

Agricultural intensification is increasing global demand for water, with groundwater especially susceptible given its year-round reliability. Climate change impacts on groundwater recharge exacerbate uncertainties for future access and use, especially for large aquifers across alluvial plains such as the Indus Basin of Pakistan. To generate better understanding of climate change impacts on groundwater balances in such contexts, we used MODFLOW 2005 to quantify the groundwater budget of the Northern Rohri Canal Command Area under RCP 4.5 and 8.5 climatic scenarios, while also taking climatic regionalisation into account. Under a baseline scenario, total annual pumping in the northern Rohri command was estimated to be 3.619 billion cubic metres (BCM), and the total net loss in storage over the simulation period from October 2010 to April 2014 was estimated at 1.244 BCM per year. By 2047, net decline in storage is projected to more than double to 2.185 per year under RCP 4.5 scenario and 2.214 under RCP 8.5. Our estimates suggest that a sustainable yield across the command area should be managed at approximately 3 ± 0.3 BCM per year to ensure sufficient adaptive reserves of groundwater for access during times of drought and inadequate surface supply, while also reducing waterlogging impacts from high watertables. This first-time estimate of sustainable yield provides irrigation system managers with an overall guide from which divisional-scale measures to achieve the goal can be identified through stakeholder engagement. [ABSTRACT FROM AUTHOR]

Climate change has been designated the most serious environmental challenge of the twenty-first century, and it will remain so in the future. To adapt to the ill effects of climate change and variability, location-specific climate analysis is essential to provide actionable evidence for informed decision making. The goal of this research was to evaluate current and future rainfall and temperature trends in central Ethiopia. We took 33 (1986–2018) years of daily rainfall and temperature data from ten stations from the National Meteorological Services Agency. The Markov chain model was used to fill in the missing values. Trends of climate variables and their extremes were analyzed using the Mann–Kendall trend test. The results showed that rainfall exhibited significant increasing trends (p < 0.05) at 80% of the stations included in the study. The start of the Kiremit season varied from June (Jun 4 at Bako) to July (Jul 1 at Shashemane) among stations; it starts June 4, June 6, and June 24 at Bako, Ambo, and Melkassa. For Asgori, the cessation date was October 1, and for Ambo, it was October 17. The average growing season varies from 95 to 136 days, and we found the shortest and longest growing seasons at Melkassa (95 days) and Ambo (136 days). The Sen's slope results showed that rainfall increased in most of the study sites from 0.2* to 12.44*, whereas it decreased from − 0.12* to − 0.21*. This has implications for agricultural practices and crop and variety choices for major crops grown in the area. To solve this problem, policymakers must work on creating awareness for the local community, which can help them withstand future climate change. [ABSTRACT FROM AUTHOR]

Climate change is already a fact, where the intensity and frequency of changes in climate extremes and their impacts on various physical and biological systems contribute to global warming. The United Nations Global Sustainable Development Goal 13 calls for urgent action to address climate change and its impacts. The goals call for strengthening resilience and adaptive capacity at the national and local levels. Goal 13- Climate Action, is one of the nine goals for which India has shown a positive push. Tamil Nadu ranked second with a composite score of 74 and is listed as a Front Runner under the Performance towards SDG's goals in 2020-21. The National Action Plan on Climate Change Assessment declares that the climate parameter is important at the regional and local scale to estimate its impacts on various sectors. Hence in the present study, an attempt is made to analyze the trend and prediction of rainfall and temperature using statistical techniques like-Homogeneity test, Box and Whisker Plot test, Coefficient of Variability, Cluster Dendrogram, Mann-Kendall, Sen's slope, and ARIMA model in Dindigul district, Tamil Nadu, India. The rainfall and temperature data are collected from 15 rainfall stations spread across the district for 39 years, from 1981 to 2020. The results can help prioritize new strategies for managing available water resources to sustain the agriculture sector's dependence in the study area. The ongoing Action Plans of the Government of Tamil Nadu to achieve climate change mitigation measures are listed. These recommendations could be utilized by agriculturalists, agro-climatologists, and decision-makers to scientifically support development in the study area. [ABSTRACT FROM AUTHOR]

Rainfall is the primary resource for freshwater. Changes in the rainfall trend pattern influence the economic development of the country by tremendously affecting different economic sectors due to the absence or shifting of rainfall at particular periods of the year. This research aims to find the monthly, seasonal, and annual trend in the precipitation pattern and the relationship between the precipitation and time in Keragala, Bingiriya, and Mahawilachchiya in Sri Lanka in the Agroecological Region WL3, IL1a, DL1f, respectively. Daily Rainfall data were collected from 1961 to 2005 from the selected rainfall gauging stations. The Mann-Kendall test and the Augmented Dickey-Fuller test indicate the stationarity of rainfall. Keragala and Bingiriya show the annually insignificant increasing trend and Mahawilachchiya shows the annually insignificant decreasing rainfall trend. Different seasons show different trends in different agroecological regions. These changes show that climate change has influenced the rainfall trends and hence some impacts are faced by the agriculture and aquaculture sector in the country due to these trend changes, even though those are statistically insignificant. Climate change has taken up an inordinate primary place in the water management system. [ABSTRACT FROM AUTHOR]

In this study, trend analysis of the lake surface areas was performed on the Google Earth Engine (GEE) platform in the period of 1985–2022 with Landsat 5/7/8/9 (TM) (ETM +), and (OLI) satellite images. The study analyzed 10 lakes, including Acigol, Aksehir, Beysehir, Burdur, Egirdir, Ilgin, Isikli, Karatas, Salda, and Yarisli in the Türkiye Lakes Region. In this analysis, the normalized differentiated water index was calculated for each of the 3147 satellite images, and water surfaces were extracted from other details using Otsu's threshold method. In the study's accuracy, the overall accuracy and F1-score values were calculated to be over 90% for all lakes. Moreover, the relationship between the changes in the surface areas of the lakes was evaluated using correlation analysis, with the sea surface temperature obtained from the NOAA satellite and the evaporation, temperature, and precipitation parameters obtained from the Era-5 satellite being used. In addition, the change of the area on the lake surface was analysed using Mann–Kendall (MK), Sen's slope, and sequential MK test statistics. During the 37 years between 1985 and 2022, there was no significant change in the Acigol surface area, but a slight increasing trend was observed. Decreases of 76.07, 4.68, 41.77, 5.44, 37.56, 28.97, 78.65, 7.26, and 81.02% were determined in the lakes of Aksehir, Beysehir, Burdur, Egirdir, Ilgin, Isikli, Karatas, Salda, and Yarisli, respectively. The application of this method in the lakes region and monitoring these lakes, which are of great importance for Türkiye, provide valuable information in determining the lakes' organizational strategies. [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]

The paper analyzed the spatial-temporal variability of rainfall and detection of potential trend change point over Kosi River basin, Kumaon Lesser Himalaya, India, using long-term gridded data and historical metrological records in hilly river basin of Uttarakhand. The Mann-Kendall (MK) test was used to determine the spatio-temporal trend using IMD (0.25° × 0.25°) gridded rainfall data during 1901–2015. The Theil-Sen slope was used to determine the magnitude of change in rainfall during the study period. Additionally, the sequential Mann-Kendal (SQ-MK) test and Pettitt's test has been used to find the abrupt change point in historical time series (1980–2019). Results of the study show that northeastern and southwestern parts of the Kosi River basin exhibit a statistically significant decreasing trend in both June and July months at 5% significance level. Northeastern and southwestern parts of the basin exhibit a statistically significant decreasing trend for monthly and annual rainfall. The range of Sen's slope values varies from −0.6 to −6.6 mm/year. Based on the analysis of SQ-MK and Pettitt's test, the change points for Almora, Mukteshwar, and Hawalbagh were 1991, 2004, and 1998 respectively. Therefore, this paper attempts to provide actionable knowledge for irrigation water planning, water management, and soil and water conservation for Uttarakhand. [ABSTRACT FROM AUTHOR]

The climatic variability changes in the world impact the growth of cash crops and India is no exception. In this research work, Mann-Kendall and Sen's slope estimator have been used to study the possible existence of trend in the production of tea and its price for Guwahati, Kolkata, North-India, South India and India as a whole. The analysis reveals blunt increasing trend in annual data set (2011-2022), but mixed for month wise analysis. [ABSTRACT FROM AUTHOR]

Temperature variability may have direct and indirect impacts on the environments of the Accra and Kumasi Metropolises in Ghana. This study analysed temperature and trends in temperature in both cities using in-situ measurements from one meteorological station in both cities from 1986 to 2015. The temperature indices were computed using the RClimdex package from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). The temperature time series was pre-whitened before the Mann–Kendall trend and Sen's slope estimator analysis were applied. Initial analysis revealed minimal variation in temperature in both cities. The results from the analysed temperature indices revealed an increase in warm days and a general rise in the minimum temperature compared to maximum temperatures. Mann Kendall and Sen's slope revealed significant trends in the annual and seasonal (dry and wet seasons) in minimum temperature in both cities. These might lead to an increased rate of heat-stressed diseases and an overall rise in urban warming in both cities. The analysis of temperature, indices and trends provided comprehensive insights into the temperature of Accra and Kumasi. The results highlight the essence of evaluating temperature indices and trends in light of Climate Change concerns. It is recommended that urban green and blue spaces should be incorporated into land use plans as these policy directions can aid regulate the temperature in both cities. [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 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]

The amount of rainfall and its pattern is very important factors that mostly affect agriculture system. Because of the scientific community's concern of global climate change over last century and today, statistical analysis of rainfall has been a major concern. The primary objective of this study is to provide detailed knowledge of the rainfall pattern in a smaller area such as district level is an essential prerequisite for agricultural planning and management. For this purpose, the monthly rainfall and rainy days for the last 25 years, i.e., 1987-2011, in Chhatarpur district have been collected for trend analysis by the Dept. of Agro. Meteorology, JNKVV, Jabalpur, Madhya Pradesh. This study performed to detect the trend of rainfall and rainy days of Chhatapur district of M.P. for the period 1987-2011. The change point analysis has been examined to see if there has been a shift in the data. The Mann-Kendall test, Sen's slope test, Spearman's rho test, regression and change point analysis were used to examine the trends in rainfall parameters. An important finding of this research is that the yearly rainfall from the monsoon season is declining significantly. During the month of May, Chhatarpur has seen an increase in rainfall. The number of wet days is not changing much in May, even though the rainfall has increased dramatically by 5%. The change point study found no significant change in rainfall or wet days between 1987 and 2011. [ABSTRACT FROM AUTHOR]

Abstract Background This paper presents the trend analysis of temperature and the effect of climate variation in the city of Addis Ababa, Ethiopia. The paper seeks to provide up-to-date information for the better management of climate change in the city. The analysis is based on the temperature difference in the city over two stations—Bole and Entoto. The overall purpose of this study is to investigate the possible trend of temperature variation as well as the effect of climate change in the study area. Method The Mann-Kendall (MK) trend test and Sen's slope estimate were employed to find the nature of the temperature trend and significance level in the city. Results It was found that the MK2/MK3 statistic (Z) value for minimum, maximum and average temperatures for Bole station are 6.21/5.99, 2.49/2.6, and 6.09/6.14 respectively. The positive Kendall's Z value shows an upward trend and implies an increasing trend over time. This indicates a significant increase in the trend at a 5% level of significance since the significance level (alpha) is greater than the computed p-value (0.05 > p-values (0.0001)). Whereas for Entoto station, the MK1 statistic (Z) results are 1.64 for minimum, while the MK2/MK3 static (Z) are 0.71/0.65 for the maximum, and 0.17/1.04 for average temperature, and this positive value shows an indicator of an increasing trend. However, the increase is not significant at the 5% significant level since the computed p-value is larger than the significant level (alpha = 0.05). Conclusions There is a tendency of temperature increments in Bole station. This could be due to the influence of climate change which can lead to weather extremes in the capital city. Therefore, the study recommends that the variability of temperature needs further monitoring technique, and there is a need to consider the increasing temperature trend to minimize its effects on human health.

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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]

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.

This study examines the trends of temperature and rainfall as an evidence of climate change and variability in Jimma city, southwestern Ethiopia. Historical rainfall and temperature data of forty years (1978–2017) obtained from Ethiopian Meteorological Agency and household questionnaire survey (n=150) were used to assess the climate trend of Jimma city. Descriptive statistics have been used to assess people's perceptions towards climate change. Rainfall and temperature variability were analyzed using standard deviations, coefficient of variation (CV), rainfall anomaly index and standard precipitation index. The magnitude of the linear trends is estimated using the Sen's slope estimator, and Mann–Kendall test to check the statistical significance of the trends. Findings revealed that average maximum and minimum temperature showed statistically significant trend. The magnitude of increasing trends of monthly maximum temperature varies between 0.033 and 0.045 °C/year in January and April, respectively. For minimum temperature the magnitude of trends vary between 0.081 °C/year in November and 0.025 °C/year in April. Annual rainfall variability is relatively stable with 11% CV, while monthly rainfall variability was found to be very high in December, January, and February with CV 115, 80, and 75, respectively. The result from household survey shows that 85% perceived the increasing trends of temperature. The community perceived that climate change is having an impact on vector-borne diseases. Our results indicate that climate-borne disease and pests, food insecurity, frequent drought and flooding appear to have a significant relationship with climate change with p value 0.000, 0.029, 0.010, and 0.047, respectively. Thus, it is crucial to plan for climate change adaptation and mitigation strategies to minimize the potential impacts of climate change in the study area. [ABSTRACT FROM AUTHOR]

Characterization of nonlinear trends in time series of hydroclimatic variables exhibiting nonstationarity is necessary for more realistic projections of climate change and for optimal design of hydraulic structures. The present study was conducted to demonstrate the applicability of a novel Monte-Carlo-based singular spectrum analysis (SSA) to characterize nonlinear trends in historical time series of rainfall characteristics. Long-term (1960–2015) rainfall records for 17 gauges located in the Malaprabha River Basin, India, were used to analyze spatiotemporal variabilities of trends in rainfall totals and number of rainy days for annual and seasonal time periods. While the traditional Sen's Slope and Mann–Kendall (MK) trend tests indicated statistically nonsignificant decreasing monotonic trends at most gauge stations, SSA revealed the existence of steep nonlinear trends and distinct change points in the direction of the trend over the period of record for both rainfall and rainy days. Results of this study demonstrate the potential for SSA to extract crucial information on the trajectories of nonlinear trends and change points in time series of hydroclimatic variables that exhibit nonstationarity. [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]

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]

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]

Trend analysis of streamflow and its linkages to rainfall can facilitate the development of water resource management plans for watersheds. The present study focuses on trends in observed streamflow of the lower Tamiraparani river sub-basin in Tamilnadu, India using Mann - Kendall test and Sen's slope estimator for a period of 30 years. From this analysis, both the annual streamflow, annual rainfall increased very marginally at the rate of 0.1799 m3/s/year and 4.3741 mm/year, respectively. Similarly, in the northeast monsoon period, both the rainfall and streamflow were increased very minimally during the analysis period. However, the observations made during the southwest monsoon showed declining trends for most of the rainfall stations and no significant trend was observed for streamflow. The calculated Spearman's Rho correlation factor (p) between rainfall and streamflow showed weak correlation during summer (0.26) and very strong correlation during northeast monsoon (0.83), strong correlation during southwest monsoon (0.53) and moderate correlation during winter (0.40). From this analysis, using Mann - Kendal test and Spearman's correlation it implies that other than precipitation and temperature, urbanization, watershed and ecological development of the catchment area could have also influenced the trends of streamflow. [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]

Global climate change is significant, and the spatiotemporal variations of precipitation associated with it are pronounced. Based on the daily precipitation data from 10 weather stations located from southeast to northwest across China from 1961–2017, the Mann–Kendall trend test was generally applied to analyze the spatiotemporal variations of precipitation. The factors influencing the precipitation changes were investigated. The results revealed that (1) the annual, summer, and winter rainfall amount (RA) exhibited increasing rates of 16.36, 12.31, and 2.49 mm/10 year, respectively. The change rates of annual rainfall days (RD) were 2.68 day/10 year in the northwest region and −1.88 day/10 year in the southeast. The annual and seasonal daily precipitation on rainy days (RP) exhibited an increasing trend. (2) All of the RA, RD, and RP values initially increased, then decreased, and then slightly increased from Southeast to Northwest China. These results proved that the RA increased with the increase of light rain in Northwest China and heavy rain in Southeast China. In addition, changes in the monsoon have altered the rate at which RA, RD, and RP vary with distance from the sea. These findings may help to provide suggestions for the rational spatial utilization of water resources in China.

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]

Abstract: Understanding spatial–temporal patterns of terrestrial vegetation response to climate change (long‐term greening/browning) is important for developing strategies to mitigate degradation. Semiarid rangelands are especially susceptible to degradation, which challenges wildlife conservation and human livelihoods that depend on livestock production. In the cold‐arid Trans‐Himalayan ecosystem (northern India), temperature is increasing, and it is also becoming progressively wetter. Yet, counter‐intuitively, there are widespread concerns over degradation. We evaluated whether greening/browning patterns in long‐term satellite‐derived vegetation indices (normalized difference vegetation index [NDVI]) are consistent across different spatial and temporal scales using 6 datasets: MODIS (250 m, 500 m, 1 km, and 5.5 km), SPOT 1 km, and GIMMS 8 km. Results indicate browning in the spring and greening in late summer. Location of hotspots of degradation (browning) was broadly consistent across spatial scales (10−2–102 km2) and were found in regions with warmer temperature and at higher elevations. Broadly, the spatial/temporal pattern of browning does not coincide strongly with location and timing of human land use via livestock grazing. This geographical and seasonal context indicates that vegetation response may be more strongly related to climate than to human land use (overgrazing). Importantly, the dynamic nature of greening/browning, across space and time, is not captured by composite annual metrics (sum‐NDVI, max‐NDVI, and mean‐NDVI). This reiterates the importance of both intraannual and interannual assessments. Location of hotspots indicates that degradation occurs in a spatially contiguous manner, but these are not stationary and instead shift with seasons. Overall, the results show that evaluating the consistency of greening/browning trends across different spatial/temporal scales is critical for understanding and managing vegetation degradation. [ABSTRACT FROM AUTHOR]

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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]