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

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

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

The current study investigated spatiotemporal trends in hydro-meteorological data on seasonal and annual scale in the Kabul River Basin (KRB). Thirty years (1981–2010) precipitation and temperature gridded data of 88 stations were retrieved from National Centers for Environmental Prediction, Climate Forecast System Reanalysis (NCEP-CFSR). Streamflow data of the four hydrometric stations (Chitral, Chakdara, Warsak, and Nowshera) was provided by the Water and Power Development Authority (WAPDA), Pakistan. The Mann–Kendall and Sen's slope tests were applied at a significance level of 5% to identify trends. To avoid the serial correlation's effect on the test results, Trend Free Pre-Whitening (TFPW) was applied. Spatial maps of precipitation and mean temperature were prepared using the geographic information system-based Inverse Distance Weighting method. Non-significant trends were identified for precipitation during winter, summer, autumn, and annually at 92%, 93%, 86%, and 80% grid stations, respectively. Significant decreasing trends were observed during the spring at 63% of the grid stations. Similarly, non-significant trends were found for mean temperature during winter, spring, summer, and annually in 74%, 60%, 79%, and 60% grid stations, respectively, while 48% of the grid stations showed significant increasing trends during the autumn. Streamflow at Chitral indicated significant increasing trends during winter (ZMK = 2.37) and spring (ZMK = 2.40), whereas significant increasing trends were found at Chakdara on annual and seasonal basis. Significantly increasing trends were detected at Warsak during autumn (ZMK = 2.09). The findings can be beneficial for water resource managers, planners, researchers, and hydrologists for their professional applications. [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]

Riparian systems across the Southwest United States are extremely valuable for the human and ecological communities that engage with them. However, they have experienced substantial changes and stresses over the past century, including non-native vegetation expansion, vegetation die-offs, and increased fire activity. Vegetation management approaches, such as ecological restoration, may address some of these stressors as well as reduce the risk of future impacts. We apply remote sensing to inform restoration priorities along the upper Gila River within the San Carlos Apache Reservation and Upper Gila River watershed. First, we develop a spatially and temporally explicit trend analysis across three observed climate periods (1985–1993, 1993–2014, 2014–2021) using the Landsat-derived indices to quantify changes in riparian vegetation conditions. These maps can be used to identify areas potentially more at risk for degradation. Second, we analyze changes in riparian vegetation within a climate framework to better understand trends and the potential effect of climate change. Vegetation greenness has largely increased throughout the watershed despite intensifying drought conditions across our study period, though areas within the lower watershed have shown increased stress and higher rates of wildfire and other disturbances over the past 5-years. Nevertheless, small-scale restoration activities appear to show improving vegetation conditions, suggesting efficacy of these restoration activities. Results from this study may be integrated with restoration objectives to develop a restoration plan that will help riparian vegetation communities adapt to change.

Abstract 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.

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.

Climate change debate has been ongoing for at least two decades world over. However, an understanding of how much change has occurred in developing countries remains limited. Using a combination of daily Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and gauge rainfall data, this study analysed whether rainfall characteristics over 30 years (1989 to 2018) in Zimbabwe exhibited any significant trends. Firstly, Kappa statistic and a confusion matrix were used to test the appropriateness of CHIRPS satellite derived rainfall estimates for carrying out trend analysis. Thereafter, the Mann Kendall test, Sen's slope and kriging were used, to detect trends, ascertain magnitude of change and map the spatial variation in rainfall characteristics, respectively. The rainfall characteristics included: Total Number of Wet Days (TNWD), Maximum Number of Consecutive Wet Days (MNCWD), Maximum Number of Consecutive Dry Days (MNCDD) and Maximum Rainfall per Day (MRD). Validation results showed that overall accuracy ranged from 0.862 to 0.897 while kappa statistic ranged from 0.739 to 0.81, suggesting a substantial agreement between satellite derived- and gauge rainfall. No statistically significant trends were detected for the four rainfall characteristics analysed at 95% confidence interval. Although no significant trends were detected at 95% confidence interval to signal climate change it was observed that MNCDD, MRD and TNWD were increasing while MNCWD was generally decreasing. This key finding opens new opportunities for geographically targeted and integrated intervention strategies for agricultural and water management in Zimbabwe. This is particularly important considering that Zimbabwe mainly depends on rain fed agriculture and understanding of the key rainfall characteristics can enable proper planning and decision making in terms of adaptation that which can ensure water availability and food security. Food security is fundamental in achieving national security. In addition, this study opens opportunities for further studies on the factors that influence the trends through using sub-daily and daily satellite data for a relatively longer period i.e., >30 years. It is therefore our contention that fine spatial and temporal scales adopted in this study yield better characterisation of changes in rainfall regimes, hence brings out better insights on understanding intra-seasonal fluctuations for climate change detection studies.

Daily and monthly rainfall data provided by surface rain gauges in the Amazon Basin are sparse and defective, making it difficult to monitor rainfall patterns for certain portions of its territory, in this sense, estimations of precipitation from remote sensing calibrated with rain gauge data are key to overcome this problem. This paper presents a spatiotemporal analysis of the precipitation distribution for Rondônia State, in southwestern Amazonia. Data from Climate Hazards Group InfraRed Precipitation and Station (CHIRPS) were analyzed, using a pooled time analysis of a forty-year period (1981–2020). Data obtained from remote sensing were validated by rain gauges distributed over the study region. Pixel-by-pixel trend analyzes were developed by applying the Mann-Kendall test and Sen's slope test to study the magnitude of the trend. The analysis revealed that CHIRPS presents a tendency to underestimate precipitation values in most cases. Among the metrics, mean values between very good (<±15%) and good (±15–±35%) were observed using PBIAS; mean RMSE values range from 57.8 mm to 107.9 mm; an average agreement level of 0.9 and an average SES of 0.5; and good fit for the linear regression model (average R2 > 0.70) for about 64.7% of the stations. Sen' slope spatialization results show a reduction of approximately −15 mm year−1, with decrease mainly in the Northern Region of Rondônia, which has extensive areas where the native forest has been replaced by pasture. [ABSTRACT FROM AUTHOR]

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

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

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]

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

IntroductionPrecipitation as the most important climatic element is always studied from two perspectives of time and place. Emphasis on the time perspective determines temporal changes and emphasis on the location perspective determines the spatial variation of precipitation. Since Iran is located in an arid and semi-arid region, it lacks large internal and adjacent water resources to supply moisture to its precipitation, and as a result, most of its precipitation moisture sources must be supplied from the surrounding water levels. One of the methods that can be used to study the course of rainfall in the past and present is to analyze the trend of time series at different scales. So far, statistical methods have been presented for the analysis of time series routines, which can be divided into two general categories: parametric and non-parametric methods. Southeastern Iran, which includes Sistan-Baluchestan province, Kerman, southern Khorasan and the eastern parts of Hormozgan province, They are one of the arid regions of Iran. Restriction on water resources and annual precipitation in this part of the country have severely limited agricultural and industrial activities. The lives and deaths of the majority of people are also related to the low precipitation that falls throughout the year. Therefore, considering that a comprehensive study on precipitation trends in the region has not been done, the purpose of this study is to investigate the annual and seasonal precipitation trends by stations in southeastern Iran. The results of this study can play an important role in understanding the precipitation trend in the southeast region for planning related to water resources management, management of unexpected events such as floods and also the optimal utilization of those precipitations.MethodologyIn order to conduct this study, in order to recruit rainy periods, daily precipitation data were obtained from synoptic stations in the southeast of the country, including selected stations in the three provinces of Hormozgan, Sistan and Baluchestan and Kerman during a 30-year period (1987-2016). Two Mann-Kendall tests and the Sen’s Slope Estimate are among the most common non-parametric methods of trend analysis when considering hydrometeorology. Various studies conducted using these two methods indicate the importance of their widespread use in the rapid evolution of time. Identify the data change using the Man-Kendall method, specify its type and time. The non-parametric Kendall test was proposed by Mann and then developed by Kendall (1975) based on ranking data in a time series. This method is widely and widely used in the analysis of the process of hydrological and meteorological series.Discussion and resultsThe trend of average annual, seasonal precipitation and maximum 24-hour precipitation in southeastern IranConsidering that in the annual, seasonal and maximum 24-hour precipitation trend diagrams, the intersection of the U and U' sequences above and below the significant lines did not occur, which means that acceptance is random (acceptance of H0 hypothesis) and there is no significant trend (H1) variable. Precipitation is in the southeast of Iran and in fact the condition is -1.96 (ti)< U or 1.96 (ti) >U and has a static series.In the Sen's Slope Estimate test, the total reduction of winter precipitation slope was equal to -0.350 mm, which in the case of 95% confidence of the upper and lower slopes of this slope is equal to -0.123 and -0.835, respectively, and in the case of 99% of the slopes. High and low are 1.604 and -2.318, respectively, per year. The Sen’s Slope Estimate test for annual rainfall, summer, autumn, winter and maximum 24-hour precipitation has estimated the negative precipitation slope. Mann Kendall test estimate shows a decrease in precipitation in winter of -1.71 per year.Annual, seasonal and maximum 24-hour precipitation trend by stations in southeastern IranIn the study of changes in annual precipitation using Mann-Kendall test, it is observed that the annual precipitation trend in most stations in the southeast (except Bam and Chabahar) has a decreasing trend. The Sen’s Slope Estimate showed is the highest precipitation at any given time at Bandar-Lengeh station at -4.16 mm per year. The time series of Man-Kendall test in the seasons of the year indicates that in spring, summer and autumn, the precipitation trend in most stations is decreasing, but this trend is not significant in any of the stations in southeastern Iran and only in winter precipitation In Bandar-Lengeh, Jask and Kish stations, it has a decreasing trend at 95% significance level. Sen’s Slope Estimate data showed that the amount of precipitation decreases in the mentioned stations.ConclusionThe results of by using Methods the Mann-Kendall test showed that the mean annual precipitation trend as well as spring, summer and autumn seasons of southeast Iran was not significant and only winter precipitation had a significant and decreasing trend. Estimates of the slope of sen indicate that the slope of precipitation in southeastern Iran in winter is -0.350 mm in year. The annual precipitation trend of BandarAbbas, BandarLengeh, Abumousa and Kish stations at 95% and Jask and Iranshahr stations at 90% were significant. Test statistics showed that the highest annual precipitation reduction was at the Bandar-e-Lange station at -4.16 mm in year. In spring, summer, and fall, precipitation was not significant in any of the stations in the southeast of Iran and winter precipitation in Bandar-e-Lengh, Jask, and Kish stations had a 95% significant decrease. Assessment of 24-hour rainfall variations showed that the above mentioned precipitation had a decreasing trend at 99.9% at BandarAbbas stations and 95% at Bandarlange, Jask, Abumousa and Kish stations. According to the tests and analyzes performed in this study, what is certain is that in all stations in southeastern Iran, a significant positive trend in annual, seasonal and maximum 24-hour rainfall was not observed at the level of 99% and 95%, and most precipitation trends from It is a kind of decrease and has revealed the fact of decrease in rainfall in the southeastern climate of Iran during the years 1987 to 2016, which decrease in annual rainfall is mostly related to the winter of -1.71 per year.

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. [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]

In the present day, the acceleration of urban surface heat impacts resulting from urbanization and industrialization is critical for citizens and municipal governments in developing-country cities. The previous key findings have indicated the association between urban surface heat and the following areas: forests, mixed agricultural land, built-up area, and water bodies. This study was motivated by a lack of knowledge regarding the variation of temperature, evaporation, and humidity in Central Vietnam's major region. The non-parametric Mann–Kendall test, Sen's slope estimator, and Landsat image analysis were employed to determine the trend and statistical significance of the variables across the 42-year study period for Da Nang city and Quang Nam province. Our results show that Da Nang city has a consistent trend with a high correlation between temperature, evaporation, and relative humidity, whereas Quang Nam province showed an inverse relationship between temperature and relative humidity since the beginning of the regional urbanization. The maximum, minimum, and mean temperatures have increased by at least 0.29 °C in Quang Nam province and 0.71 °C in Da Nang city since 2000. Between 1979 and 2021, the frequency of days with temperatures exceeding 35 °C has increased by two and seven days during the past decade at the meteorological stations in Da Nang and Tam Ky, respectively. The temperature in Da Nang city varied from 31.80 °C to 32.82 °C with high temperatures concentrated in urbanized regions with less coverage of small trees, plants, and water bodies. Thus, the results of this study will serve as a scientific basis for decision-makers and regional officials for land-use management and to increase community awareness of sustainable planning, particularly in Da Nang city and Quang Nam province in Central Vietnam. [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]

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

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The present study aims to investigate the homogeneity of runoff time series and also to review the existence of trends in Tale Zang hydrometric station (the hydrometric station at the inflow into the Dez reservoir) runoff, using 61 years (1956–2016) daily recorded data. The Pettit test, which is a common method in investigating the homogeneity of time series, was used to identify change points. Both Mann-Kendall and auto-correlated Mann-Kendall tests were applied to analyze the existence or non-existence of trends in each annual, seasonal, and monthly time series observed in a runoff. In time series, significant trends at the 95% level of confidence were recognized, upper and lower limit values were presented for Sen's slope and it was tested for the increasing or decreasing trends in nature. Based on the results of this study, the significant change point at the 95% level of confidence was recognized in the annual, spring, summer, autumn, March, May, June, July, August, September, and October data sets in 1997,1997, 1999, 1997, 1999, 1999, 1999, 1997, 2000, 2007 and 2008, respectively. Analyzing the existence of a trend at the 95% level of confidence indicated that in spring, and in March, September, and October, for both Mann-Kendall and auto-correlated Mann-Kendall tests, the trend is significant and additive until the change point. HIGHLIGHTS Investigating the changes in long term runoff time series at the Tale Zang hydrometric station for the first time.; Investigating the magnitude of the change point or trend at the 95% level of confidence.; Studying the existence or nonexistence of trends before and after the change point of confidence.; Determining the upper and lower limits of Sen's slope.; Assisting water resource planners to make appropriate decisions.;

Drought forecasting is being considered an important tool to help understand the rainfall pattern and climate change trend. Drought is a prolonged period of months or years in which an area, whether surface water or groundwater, becomes insufficient in its water supplies. Drought is considered as the most difficult but least known environmental phenomenon, impacting more persons than any other. There are several indices used to classify droughts. For this study, precipitation-based drought indices are considered (i.e., SPI, RAI and Percentage Departure of Rainfall). The objective of the research is to examine and determine the possible rainfall trends over the Jalore district of South-West Rajasthan in Luni river basin. In this research, trend analysis using the rainfall data from the years 1901 to 2021 was carried out on a monthly, seasonal and annual basis. To define the current trend path, the Mann-Kendall test and Sen's slope estimator test were used. In order to detect the trend and its change in magnitude over a particular period of time, Sen's slope estimator was used. During the southwest monsoon, declining rainfall leads to short-term meteorological droughts, which have severe effect on the agriculture sector and Jalore district's water supplies, while rising rainfall during other seasons tends to mitigate the severity of drought. The result of research reveals that there is rise of pre-monsoon and post-monsoon rainfall, but it also depicts a fall in the annual rainfall which reflects in reduced Winter and S-W monsoon rainfall. HIGHLIGHTS To assess possible drought severity and duration in the Jalore district of S-W Rajasthan region.; The study also deals with identification of drought patterns, and changes with the 121 years of the time span.; Trend analysis is carried out using Mann-Kendall test to quantify the rainfall pattern & characteristics.; To estimate the magnitude of trend using Sen's slope.;

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

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

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

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

In this study, we analyze sea surface height referenced against the WGS84 ellipsoid at the Hon Dau tidal gauge station (Hai Phong, Vietnam), in front of the Red River Delta, between 1961 and 2020. The annual sea level varied from 165.23 cm to 206.06 cm in this period (+20.28 cm over 60 years). The average water level was 190.87 cm for 60 years, with higher annual values in recent years, especially from 2016 to the present (above 201.5 cm). The Mann–Kendall (MK) test with Sen's slope estimator and Şen's innovative trend analysis (ITA) were applied and compared to estimate the sea level rise. These methods showed complete agreement among tests with significant rising trends of about 3.38 mm/year with the MK test and 3.08 mm/year with the ITA method for 1961–2020. During the last 20 years (2001–2020), the mean sea level increased about 7.16 mm/year (MK test and Sen's slope), 7.38 mm/year (ITA method), and around twice higher than the rate of the region and globally. The MK test and ITA method provided similar results for periods: 1961–2020, 1961–1980, and 2001–2020, with relatively stable monotonic related trend conditions. For the period 1981–2000, with a more nonmonotonic trend, the MK test and ITA method provided different trends and allowed to illustrate the specificity of each method. [ABSTRACT FROM AUTHOR]

Temperature and precipitation variations have huge environmental, socio-economic impacts. This study aims to detect the trend of temperature, precipitation, and discharge from 2000-2020 in the district Ghotki. Mann Kendal test and Sen’s slope were applied by using XLSTAT in MS Excel to investigate the significance of all trends. The results showed that the annual rainfall trend was increased with the highest intensity noted in 2003; 275mm and 2010; 271 mm. The trend in the monsoon season was increased with the highest slope 0.863 by comparing with non-monsoon which showed the slope was 0.642. The annual temperature was increased an average temperature recorded in 2016; 28.5 & 2018; 28 °C. Further, the summer-autumn season’s trend has sharply increased. While the trend of Ghotki feeder discharge was slightly increased in January due to the continuous flow of water and less demand for water during the Rabi season. But in July, the highest discharge was recorded in 2010 due to heavy rainfall and flood situations over the study area. The trend in Kharif was continuously declined due to farmers started sowing sugarcane crops instead of rice and cotton which need less irrigation water. It is concluded that the performance of MK and SS tests was consistent at the verified significance level.

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

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

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

As a major threat to ecosystem functions and national food security, soil erosion also exerts an influence on the water quality in basins and the operation and maintenance of hydropower plants. Existing discussions about trends of soil erosion focus mainly on its variation and mutation over time. Few studies have addressed the spatial mutation of soil erosion and its influence mechanism. In this research, Sen's slope estimation was coupled with a Mann–Kendall model to explore the spatiotemporal distribution, spatial mutation characteristics and influence mechanisms of soil erosion, and conduct a case study on the Middle and Lower reaches of the Lancang River Basin (ML-LRB) in China. There are three main conclusions from this study: (1) During 2000–2019, the annual soil erosion in the ML-LRB variation ranged from 0 to 7.00 × 103 t/(km2·a) with a multi-year mean of 1.53 × 103 t/(km2·a), decreasing year by year from north to south, while an increasing trend began to appear in the central above region after 2015. (2) The areas with decreased soil erosion were much larger than those with increased soil erosion during 2000–2019, and there was a concentrated increase in soil erosion in Dali and in Xishuangbanna. (3) The mutation of the soil erosion intensity was spatially consistent with that of the Normalized Difference Vegetation Index (NDVI). Overall, this paper provides a new perspective for the study of factors affecting the trends and spatial mutation of soil erosion. [ABSTRACT FROM AUTHOR]

Daily and monthly rainfall data provided by surface rain gauges in the Amazon Basin are sparse and defective, making it difficult to monitor rainfall patterns for certain portions of its territory, in this sense, estimations of precipitation from remote sensing calibrated with rain gauge data are key to overcome this problem. This paper presents a spatiotemporal analysis of the precipitation distribution for Rondônia State, in southwestern Amazonia. Data from Climate Hazards Group InfraRed Precipitation and Station (CHIRPS) were analyzed, using a pooled time analysis of a forty-year period (1981–2020). Data obtained from remote sensing were validated by rain gauges distributed over the study region. Pixel-by-pixel trend analyzes were developed by applying the Mann-Kendall test and Sen’s slope test to study the magnitude of the trend. The analysis revealed that CHIRPS presents a tendency to underestimate precipitation values in most cases. Among the metrics, mean values between very good (2 > 0.70) for about 64.7% of the stations. Sen’ slope spatialization results show a reduction of approximately −15 mm year−1, with decrease mainly in the Northern Region of Rondônia, which has extensive areas where the native forest has been replaced by pasture.

Climate change, which is one of the main determinants of agricultural production, has started affecting the pattern of crop growth, productivity, and quality of produce from the last few couple of decades in various agro-climatic zones globally. Any change in climatic factors such as temperature, evapotranspiration (ET), and rainfall is bound to have a significant impact on agricultural production. Thus, climate monitoring, trend analysis, and model-based prediction are highly significant to mitigate the climate change impacts on crop growth patterns, production, and quality traits. A study was thus undertaken at Punjab Agricultural University, Ludhiana, India, to (1) estimate reference evapotranspiration (ETo) using FAO-ETo calculator; (2) study and detect trend in long-term (1970–2019) recorded temperature (Tmin and Tmax), rainfall and ETo using Mann–Kendall's test, Sen's slope test, standard normal homogeneity test (SNHT), and Pettitt's test in XLSTAT software; (3) study correlation of ETo with Tmin, Tmax, and rainfall; and (4) develop regression models for estimating ETo on seasonal and annual basis. All the tests indicated a significant trend in Tmin (increasing) and ETo (decreasing) during all seasons (spring, summer, autumn, and winter), as well as on annual basis at 5% level of significance, whereas no trend was recorded in Tmax and rainfall data. The SNHT and Pettitt's test confirmed the existence of a change-point in both ETo and Tmin data for all seasons as well as on annual basis. Both Mann–Kendall's and homogeneity tests indicated no trend or change point in Tmax (except a change-point during spring) and rainfall data. The positive correlation of ETo with Tmax, wind speed (vw), and sunshine hours (SSH) formed an increasing trend in ETo with increase in these variables and vice-versa. The negative correlation of ETo with relative humidity (RHmin and RHmax), rainfall, and Tmin indicated a decreasing trend in ETo. The study offers a basis to predict the futuristic climate scenarios in the region for planning crops and manage irrigation to mitigate the climate change impacts on agricultural production. The statistical comparison indicated that the developed models were sufficiently accurate and would be useful in simplified estimation of ETo on seasonal and annual basis for the study region. [ABSTRACT FROM AUTHOR]

The aggravating deforestation, industrialization, and urbanization are becoming the principal causes for environmental challenges worldwide. As a result, satellite-based remote sensing helps to explore the environmental challenges spatially and temporally. This investigation analyzed the spatiotemporal variability in land surface temperature (LST) and its link with elevation in the Amhara region, Ethiopia. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST data (2001–2020) were used. The pixel-based linear regression model was used to explore the spatiotemporal variability of LST changes. Furthermore, Sen's slope and Mann-Kendall trend test were used to determine the magnitude of temporal shifts of the areal average LST and evaluate trends in areal average LST, respectively. Coefficient of variation (CV) was also used to analyze spatial and temporal variability in seasonal and annual LST. The seasonal LST CV varied from 1.096–10.72%, 0.7–11.06%, 1.29–14.76%, and 2.19–10.35% for average autumn (September to November), summer (June to August), spring (March to May), and winter (December to February) seasons, respectively. The highest inter-annual variability was observed in the eastern, northern, and south-western districts than that in the other parts. The seasonal spatial LST trend varied from −0.7–0.16, −0.4–0.224, 0.6–0.19, and −0.6–0.32 for average autumn, summer, spring, and winter seasons, respectively. Besides, the annual spatial LST slope varied from −0.58 to 0.17. Negative slopes were found in the central, mid-western, and mid-northern districts in annual LST, unlike the other parts. The annual variations of mean areal LST decreased insignificantly at the rate of 0.046°C year−1 (P<0.05). However, the inter-annual variability trend of annual LST increased significantly. Generally, the LST is tremendously variable in space and time and negatively correlated with elevation. [ABSTRACT FROM AUTHOR]

Copyright of Water & Soil is the property of Ferdowsi University of Mashhad Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Three timescale i.e. monthly, seasonal and annual rainfall data of Bundelkhand region, Central India, was analyzed for 40 years (1981-2020). The annual mean average rainfall for the region ranges between 657.7 mm and 1146.4 mm for the studied period with the month August receiving the highest amount of rainfall. The region receives about 90 % of its annual rainfall during South West Monsoon period i.e. from June to September. Temporal trend of rainfall for different timescale was analysed using nonparametric Mann-Kendall test and Sen's slope estimator. Increasing and decreasing trend were found for the three timescale in which the study was carried out. Annual rainfall trend of Bundelkhand region is found to follow decreasing trend except for Sagar district. A decreasing South West Monsoon rainfall trend was also observed in 11 districts of Bundelkhand region. [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]

Three timescale i.e. monthly, seasonal and annual rainfall data of Bundelkhand region, Central India, was analyzed for 40 years (1981-2020). The annual mean average rainfall for the region ranges between 657.7 mm and 1146.4 mm for the studied period with the month August receiving the highest amount of rainfall. The region receives about 90 % of its annual rainfall during South West Monsoon period i.e. from June to September. Temporal trend of rainfall for different timescale was analysed using nonparametric Mann-Kendall test and Sen’s slope estimator. Increasing and decreasing trend were found for the three timescale in which the study was carried out. Annual rainfall trend of Bundelkhand region is found to follow decreasing trend except for Sagar district. A decreasing South West Monsoon rainfall trend was also observed in 11 districts of Bundelkhand region.