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It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics of the Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the data were subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03 days/year and decrease in consecutive wet days (CWD) at 0.02 days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5 °C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) data for a period of 40 years (1980-2019) was used to detect the trend characteristics of daily average temperature in the state of Kerala, India. Data extracted from a total of fifty locations in the state were statistically processed using Mann-Kendall (MK) and Spearman's Rho (SR) tests to detect the trend, Pettitt test to identify the single change point, and Theil-Sen's method for the calculation of the rate of change. The MERRA-2 product is validated for the study region according to statistical indicators. The daily average temperature in the state during the period of study varies between 16.56 and 32.64 °C. The spatial pattern of daily average maximum temperature shows higher temperature domains in the central and southern parts of the state. Trend characteristics of daily average temperature assessed through MK and SR tests show a significant increasing trend in all stations, with maximum values in stations located in the northern part of the state. Change point detected through the Pettitt test divided the sampling stations into three groups based on the change in daily average temperature characteristics in the years 2002 (north zone), 2009 (south zone), and 2012 (central zone), indicating nonunique spatial variability in temperature characteristics in the state. The rate of change in the daily average temperature assessed indicates an increase at the rate of an average of 0.013 °C.year -1 . During the whole study period, the daily average temperature showed an overall increase of 0.54 °C, and for the 100-year futuristic prediction, the daily average temperature in the state shows an average increase of 1.35 °C. Among the stations, a higher rate of increase in daily average temperature is shown by stations located in the eastern part of the Pathanamthitta, Idukki, and Kollam districts. Though the rise in daily average temperature is not much higher, its spatial characteristics require more attention because, in recent times, the study area has faced repeated, severe, and long drought conditions along with sunburn incidents. As an agrarian state, a change in the temperature domain will adversely affect the overall agricultural production and will evoke not only a food crisis but also economic as well as water resources issues. The result obtained can be used as holistic basic information for understanding the impending effect of climate change in the state to frame better mitigation as well as management strategies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study assesses trends in rainfall in Madhya Pradesh, Central India, over the long (1871–2016) as well as short (1987–2016) temporal scales. The region is home to disadvantageous groups of the population including vulnerable tribals who depend on rainfall-based agriculture and forest products. Therefore, any disruption in rainfall trends due to climate change needs to be documented for better planning. This study focuses on two meteorological subdivisions, East and West Madhya Pradesh, which receive a major portion of rainfall through the Bay of Bengal branch and the Arabian Sea branch of the Indian Summer Monsoon. The study is based on the rainfall series provided by the Indian Institute of Tropical Meteorology, Pune, India. This study used the Mann–Kendall test to detect a trend and Sen's Slope to estimate the magnitude of change in rainfall. Statistically significant negative trends were detected in total annual (− 1.125 mm y − 1) and monsoon (− 1.242 mm y − 1) rainfall over long-term observation in East Madhya Pradesh only. However, during the last 30 years, no trends have been recorded in East Madhya Pradesh. In West Madhya Pradesh, rainfall has not recorded any trend for long- as well as short-term observation periods. The non-availability of a trend in rainfall during May and October at both meteorological subdivisions shows that there is no shift in the duration of the monsoon season over long as well as short temporal observations. The decreasing rainfall trends in Eastern Madhya Pradesh over the long-term observation seem to be caused by changing patterns of tropical cyclone frequency in the Bay of Bengal. [ABSTRACT FROM AUTHOR]

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R 2  = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Rainfall variability is a key element in water resource management. There has been significant variability in rainfall in Arunachal Pradesh, with the state being in the highest rainfall zone in India. The present study attempts to investigate the annual rainfall trend along with the change points in the rainfall time series, considering more than a hundred years of data (1901–2002) in eleven districts of Arunachal Pradesh. First, a serial correlation test was conducted on the entire time-series data for the three districts to detect the serially independent time series, followed by the non-parametric Mann–Kendall test and Spearman's rank correlation test to ascertain the presence of a statistically significant trend in hydrological climate variables. Sen's slope method was applied to estimate the magnitude of the trend. Pre-whitening, trend free pre-whitening Mann–Kendall, and bias corrected pre-whitening, along with two variance correction approaches, are applied to the serially correlated data. All the districts under consideration show a decreasing trend in rainfall in the investigation over the years. A comparative study of the trend test method was also carried out. Further, to identify the trend change points in the time series, a sequential Mann–Kendall test is conducted. Assessing 100 years of time series data for the region makes the study unique of its kind and is likely to play a vital role in environmental policymaking. Furthermore, it will be helpful for water resource management, land use, land cover management, sustainable agricultural planning, and the overall socio-economic development of the region. [ABSTRACT FROM AUTHOR]

Compound extremes can be expressed as the joint distribution or dynamic interaction of multiple variables and the interdependence of several extremes that have major effects on the agricultural sector. Analysis of these compound extremes in space-time varying domains is a challenging task for climate experts. It is even difficult to forecast such compound extremes in future climate when several widely accepted global climate models (GCMs) and regional climate models (RCMs) are available. Thus, an attempt is made to develop a compound extreme index considering precipitation, temperature, and runoff, with a specific focus on promoting sustainable water resource management, particularly for the benefit of the agricultural sector. This work presents a new outlook on the modeling framework for compound drought and hot extremes (CDHE) by developing the Standardized Compound Extreme Event Index (SCEEI), and highlights their time-varying evaluation (trend and prediction) along with severity assessments. The SCEEI is derived using three individual indices: Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Standardized Temperature Index (STI), which are obtained from three physical variables (precipitation, runoff, and temperature) followed by multivariate Gaussian distribution. The applicability of the SCEEI is explained with a case study on the Brahmani and Baitarani rivers of eastern India, aiming at the modeling of dry and hot extremes at a regional scale. Further, the time-varying evaluation of CDHE events—the projection of the extremes—is studied in machine learning (ML)-based ensemble future. Random forest (RF) and support vector regression (SVR) MLs are employed to derive ensemble future from seven RCM models of the Coordinated Regional Downscaling Experiment (CORDEX). The linear scaling approach (LSA)-based bias-corrected data were used as input for the ensembling process. The RF-predicted ensembles performed statistically better for the study area. The extreme events and their severities are further assessed in RF-predicted future ensembles. The two-tail-based Mann–Kendall test, followed by Sen's slope estimator, is used to investigate the trend-based time-varying evaluation of CDHE events. The notable conclusion drawn from this study is that the severity and frequency of CDHE events are increasing in the ensemble future climate, particularly in representative concentration pathway (RCP) 8.5. The developed multivariate framework might allow new prospects for suitable statistical analysis techniques for dependent compound extremes in climate-related studies and hydrology, which is further necessary for applying an adaptation strategy to boost resilience and adapt society for future climatic extremes. [ABSTRACT FROM AUTHOR]

Significant variations are detected in extreme rainfall characteristics over Ambica river basin, Gujarat. The frequent flooding in Ambica basin has become a persistent phenomenon over last decade. Based on new knowledge and understanding in Extreme Value Theory (EVT), the discrepancies in extreme rainfall characteristics over entire basin are analyzed considering the daily rainfall series of 25 rain gauge stations for period of 1961–2017. At each station, the threshold value was selected as 90th percentile rainfall for computing the excesses of Peak over Threshold (POT) series. To examine the variations in rainfall pattern, basic rainfall indices viz. total annual rainfall (PRCPTOT), rainy days (RD) and simple daily intensity index (SDII) are calculated. To assess the non-uniformity of extreme rainfall, coefficient of variation (Cv) has been found. Non-parametric tests like Modified Mann-Kendall (MMK) test and Sen's slope test were used for evaluating the trend. The western parts of the basin show a declining trend in PRCPTOT and SDII, wherein stationarity has been observed for RD. The stations in the central region show a significantly declining trend in total annual rainfall. The SDII and RD are found to be higher and lower respectively for the stations situated in eastern parts of the basin. It has been found that 20 %, 4 % and 17 % of stations exhibit significant decreasing trends in PRCPTOT, RD and SDII respectively. The western basin has lesser values of coefficient of variation (Cv) as compared to stations in eastern part. At the majority of stations, extreme rainfall duration and frequency were found to be stationary, whereas intensity of extreme rainfall is found to be non-stationary. Also, it has been found that 16 % of stations exhibit significant decreasing trends in extreme rainfall intensity and duration, which demonstrates the consequences to water availability in near future. [ABSTRACT FROM AUTHOR]

Since historical times, the climate of the earth has been changing. In terms of diversity and population, India is a vast country. Any significant change in its climatic conditions can have an impact on the country's entire economic and cultural structure. Temperature is the most important variable when focussing on climate change study. This study aims to recognise the changing trend of temperature in India. For this purpose, temperature data from 1901 to 2020 has been analysed. To find out the variability in temperature, various statistical tools were applied. The Mann-Kendall method has been used along with Sen's slope estimator for determining the trend and slope magnitude. ARIMA modelling is applied to the data series to forecast the temperature trend. The study has shown that variability in temperature is increasing in recent years and the temperature trend is increasing in all the months, especially in the cold months of November, December and January. The average annual temperature of India in the year has increased significantly in the past 120 years. The trend analysis of temperature is tested significantly statistically at a 95% confidence level. [ABSTRACT FROM AUTHOR]

The climate trend is one of the most dominant factors likely to affect the structure and function of the wetlands of Keoladeo and Bhitarkanika. This study compares the climate conditions and trends of two Ramsar sites in India, the Bhitarkanika and Keoladeo wetlands. Forty-year climate data (1980-2020) were used to identify and measure the strength of possible climate change in these habitats. Mann-Kendall's test, Sen's slope estimates and Sequential Mann-Kendall's (SQMK) test were used to study the long-term and short-term trends of rainfall and climate of Bhitarkanika and Keoladeo. The results of this study matched those of earlier studies conducted at a larger geographical scale. The study indicated significant changes in the parameters of rainfall and temperature trends. A significant increase in annual rainfall (Sen's slope = 5.24E+00, New p value = 2.75E-02) was observed at Bhitarkanika, while the trend at Keoladeo was positive but insignificant. Both ecosystems are getting warmer. Seasonal changes were also identified in the rainfall and temperature. The summer temperature rise was comparatively stronger at Keoladeo (Tmax: Sen's slope=2.33E-02, New p value=2.45E-02; Tmin: Sen's slope=2.68E-02, New p value=1.39E-02). An increase in monsoon temperature was also recorded in both ecosystems. Both wetland ecosystems are vulnerable to climate change, but the Keoladeo wetland is at higher risk because stronger temperature changes have occurred in the past four decades. The SQMK test also suggests a more erratic climate in the Keoladeo wetlands. The study highlights the comparative changes occurring in both ecosystems. This is the first study identifying both long-term and short-term changes in these wetlands at a smaller geographical scale. [ABSTRACT FROM AUTHOR]

Global warming is a biggest issue around the world. In this research paper, the temporal and spatial trend analysis of seasonal and annual rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat state of India has been analysed using the data of 11 rain gauge stations installed in Bhogavo watershed. Linear regression, Mann–Kendall Test, Sen's slope test and innovative trend analysis methods are used to carry out monthly and annual rainfall trend analysis. In addition to the rainfall analysis, a number of rainy days change in magnitude as a percentage of mean rainfall have also been analysed using linear regression and Sen's slope method, respectively. The IDW method is used to develop a spatial distribution of annual and seasonal rainfall trend over the study area. From the results, it is concluded that annual rainfall shown increasing (positive) trend at nine stations out of 11 stations. The highest value of change in magnitude of trend as a percentage of mean monthly rainfall has been obtained in the month of July, attributing increasing trend at Sayla station and lowest value magnitude of trend as a percentage of mean rainfall in the monthly rainfall has been obtained in the month of August, attributing decreasing trend at Bavla station. [ABSTRACT FROM AUTHOR]

The present study aims to identify and measure the impact of climate change on rainfall patterns in the Uttar Dinajpur district of West Bengal. The hydro-meteorological time series rainfall data was collected from the IMD and CHRS data portals and subsequently analysed using various statistical methods. Agriculture in this district is the main economic activity, but the rainfall propensity is very unpredictable and sporadic that has a significant impact on agriculture. The rainfall results (1901-2019) were examined and assessed using statistical techniques for Mann-Kendall's Z-statistic and Sen's slope estimators. From the estimation, it is understood that the pre-monsoon, monsoon, and winter seasons have positive trends in rainfall, whereas the post-monsoon rainfall shows a negative trend and both Mann-Kendall and Sen's slope projections depict the same. Likewise, January, February, April, May, June, July, August, and December reflect upward positive change, while a downward trend (decline trend) was recorded in March, September, and October. The winter Kharif crops are more impacted by this negative or decreasing pattern of seasonal rainfall than other crops. The maximum average monthly rainfall in July (892.1 mm) and January showed the lowest average monthly rainfall of 63.3 mm. The results revealed that during the monsoon season the maximum rainfall (75.2%) occurred and the coefficient of variance value is 20.4%. In the winter season, the minimal rainfall (2.87%) with a coefficient of variance (CV) is 72.9%. The rainfall forecast using SMOreg and linear regression methods has been calculated. This research contributes greatly to adopting different strategies by the planners, researchers, numerous government institutions, and NGOs for the overall development of the study area. This study may also be effective in the management of water resources in the study region. [ABSTRACT FROM AUTHOR]

India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar, malaria control in this region is critical for malaria elimination efforts in all the three countries. For identifying hotspots for targeted intervention, malaria data from 385 public health sub-centers across Mizoram were analyzed in the Geographic Information System. Almost all the sub-centers reporting high Annual Parasite Index (> 10) are located in Mizoram's districts that border Bangladesh. Getis-Ord G i * statistic shows most of the sub-centers located along the Bangladesh border in the Lawngtlai and Lunglei districts to be the malaria hotspots. The hotspots also extended into the Mamit and Siaha districts, especially along the borders of Lawngtlai and Lunglei. Analysis of terrain, climatic, and land use/land cover datasets obtained from the Global Modelling and Assimilation Office and satellite images show Mizoram's western part (Lawngtlai, Lunglei, and Mamit districts) to experience similar topographic and climatic conditions as the bordering Rangamati district in the Chittagong division of Bangladesh. Climatic trends in this region from 1981 to 2021, estimated by the Mann-Kendall test and Sen's slope estimates, show an increasing trend in minimum temperature, relative humidity, rainfall, and the associated shift of climatic pattern (temperate to tropical monsoon) could facilitate malaria transmission. The quasi-Poisson regression model estimates a strong association (p < 0.001) between total malaria cases, temperature range, and elevation. The Kruskal-Wallis H test shows a statistically significant association between malaria cases and forest classes (p < 0.001). A regional coordination and strategic plan are required to eliminate malaria from this hyper-endemic malaria region of North-East India., (© 2023. The Author(s).)

Climate change (precipitation and temperature) has significantly affected the hydrological regimes and future climate projection. Integration of climate model with physical based model is crucial for quantitative measurement of changes in surface water regime. For accurate estimation, modelling framework need finer scale resolution of climate model output. In this study, we examined the bias corrected, statistically downscale models drawn from the NASA, Earth Exchange Global Daily Downscaled Projections–Coupled Model Intercomparison Project Phase 5 (NEX-GDDP-CMIP5) over the study region. The rainfall and temperature projection output from the INMCM-4, MRI-CGCM3 and their ensemble mean performed well over the Mahi River basin (MRB), India. In this study, the climate data integrated with the SWAT model to analyse the potential impact of climate change on the discharge of MRB. The finding indicates that in the near future (2011–2040) projection of annual average streamflow increases by 76.74% based on the INMCM-4 outputs, 25% based on the MRI-CGCM3 outputs, and 24.53% based on the ensemble mean in comparison to the baseline period (1981–2010). Further, the modelling results of mean monthly streamflow in rainy season indicated that the lowest and highest streamflow changes will be ranging from about 631.07–2718.42 m3/s as observed by INMCM-4, 491.71–2938 m3/s observed by MRI-CGCM3, 513.02–2270.18 m3/s observed by ensemble mean, in the near future. Similarly, in the summer season, the lowest level of stream flow is found to be 158.27 m3/s observed by MRI-CGCM3, 193.38 m3/s (ensemble mean) and 258.53 m3/s (INMCM-4), respectively. Additionally, the streamflow trend was assessed by Mann–Kendall and Sen's slope method at the monthly, seasonal and annual scales. The future streamflow projection represented the ascending trend observed in south west and winter monsoon, while the descending trend was observed in pre-monsoon and post-monsoon under the INMCM-4, MRI-CGCM3, and ensemble mean. Results on projected precipitation, temperature and streamflow accretion would help to develop effective adaptation measures for reducing the impacts of climate change and to work out long-term water resource management plans in the river basin. [ABSTRACT FROM AUTHOR]

In this study, the long-term trends in climatological parameters, viz., maximum temperature (TMAX) and minimum temperature (TMIN), are determined over 68 years (i.e., June 1951 to May 2019) using the gridded observation datasets (1° × 1° spatial resolution) of India Meteorological Department over the Narmada river basin, India. Multiple non-parametric techniques, viz., modified Mann-Kendall (MMK), Sen's slope (SS), and Spearman's rho (SR) tests, are used to determine monthly, seasonal, and annual trends over individual grids. The trends are also analyzed for the climatic variables spatially averaged over the entire basin to draw general conclusions on historical climate change. The results reveal a significant spatiotemporal variation in trends of TMAX and TMIN over the basin. In general, both the parameters are found to be increasing. Furthermore, the hottest months (April and May) have become hotter, and the coldest month (January) has become colder, implying a higher probability of increasing temperature extremes. Furthermore, the entire duration of 68 years is divided into two epochs of 34 years, i.e., 1951–1984 and 1985–2018, and the trend analysis of TMAX and TMIN is also carried out epoch-wise to better understand/assess the signals of climate change in recent years. In general, a relatively higher warming trend was observed in the latter epoch. As a majority of the basin area is dominated by agricultural lands, the implications of the temperature trends and their impacts on agriculture are succinctly discussed. The information reported in this study will be helpful for proper planning and management of water resources over the basin under the changing climatic conditions. [ABSTRACT FROM AUTHOR]

This article presents the distribution of seasonal snow cover in the Trans-Himalayan region of Ladakh over the observation period of 2000–2019. Seasonal snow cover area and duration have been monitored and mapped based on the MODIS Normalised Difference Snow Index (NDSI). Using different MODIS cloud removal algorithms, monthly mean cloud-covered areas have been reduced to 3%. Pixel-wise approaches using Mann–Kendall (MK) and Sen's slope trend tests allow to assess seasonal and annual trends of snow cover days (SCD) and snow cover area (SCA) across seven delineated subregions of Ladakh. Analyses include the impact of topographical parameters (elevation, slope, aspect). Overall, the mean annual SCA amounts to 42%, varying from 15% in August to 71% in February. However, large differences of SCA have been detected between and within subregions. The trend analysis of SCA shows a non-significant, slight increase for summer as well as for the entire year and a decrease for spring and winter seasons. The SCD trend analysis indicates more pixels with a significant increase than a decrease. In total, 12% of all pixels show an increasing trend in summer, 6% over the entire year, 3% in autumn, and 2% in spring and winter, whereas less than 2% of all pixels show a decreasing trend in all seasons. The results are important for regional irrigated agricultural production and freshwater supply in the context of climate change. [ABSTRACT FROM AUTHOR]

Climatic changes have a significant impact on the hydrologic behavior of a river especially its discharge. Sustainable management of water resources necessitates an examination of spatiotemporal variation in climatic parameters such as precipitation and temperature to quantify their relationships with the river discharge. The present study develops both parametric and non-parametric models by modifying the tools of 'R' statistical software (version 3.2.2) to investigate variations in 11 climatic parameters for a 117-year dataset (1900–2017) in Ganges River basin of India. The novelty of the modified hydroclimatic spatiotemporal trend model is its ability to explore seasonal trends and Sen's slopes of climatic parameters while avoiding trend-autocorrelation complications using an advanced Mann–Kendall test and Sen's slope estimator. Furthermore, relationships among the Sen's slopes of each climatic parameter are assessed to investigate the trend interdependencies. Parametric modeling has been performed to develop relationships among precipitation and remaining climatic parameters. Model validation results suggest non-parametric model to quantify relationships between precipitation and river discharge for a long-term data series. The results demonstrate that the forecasted precipitation exhibits a gradually decreasing trend leading to a significantly decreasing trend in river discharge (15–21%) for the next three decades (2030, 2040 and 2050). The model outcomes guide the water managers towards framing sustainable policies for managing water supplies, floods and droughts, hydropower development, barrage operation control, and environmental flows. [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]

Climate change is a pressing issue that is affecting the lives and livelihoods of millions of people across the world. This study investigates the trend analysis and spatial-temporal variations of temperature and precipitation on a monthly, seasonal, and annual basis in Rajasthan state, India, over the past 40 years (1981-2020). The trend analysis of temperature and precipitation were analysed using the Mann-Kendall test at the confidence level of 95%. The magnitude (slope) was determined by using Theil-Sen's slope test. The results of the analysis revealed significant positive and negative trends of temperature and precipitation observed on a monthly, seasonal, and annual basis in all the 33 districts of Rajasthan state. The summer season experienced the maximum average temperature, while the winter season had the minimum. The study also found that the northern and western parts of Rajasthan experience "Mawat" rain during the winter due to cyclones happening in the Mediterranean Sea during that season. The annual average temperature and precipitation were observed to be maximum in the southern part and minimum in the northern and western parts of the state. The findings of this study provide valuable information for the future management of water resources and the likely impact of activities on the hydrologic cycle and natural resources in Rajasthan state. [ABSTRACT FROM AUTHOR]

Apple cultivation is one of the most important sources of livelihood in Indian side of the Himalayas. The present study focuses on the apple orchards of Himachal Pradesh, a state within the Himalayan Mountains, a major apple producers of India. In the study, it is found that the optimum apple growing conditions in the region have been consistently shifting and farmers are shifting their orchards to the higher altitudes. For example, orchards have shifted to 1500-2500 meters in the 2000s compared to the cultivated elevation of 1200-1500 meters during 1980s. As of 2014, apples are being cultivated at an elevation of more than 3500 meters, for example, the newly developed orchards of Leo village in upper Kinnaur and Keylong area of Lahul and Spiti districts. Chilling hours for different districts are calculated. The trend of temperature during the growth period, winter session and annual rainfall have been analysed using Mann-Kendall and Sen's slope test. Data catalogued from different time periods indicates that the northward shift (towards higher altitude) is due to changes in chilling hours, total annual rainfall and mean surface temperature during the apple growing season. The mean surface temperature in all the districts has increased by almost 0.5°C during last 2000-2014. These changes are directly related to global warming. While the changing climate is reducing the apple production in low altitudinal regions of the state, it is creating new opportunities for apple cultivation in higher altitudes as conditions are getting more favourable for apple growth in those higher regions. The associated socio-economic changes are posing new societal issues for the local farmers., Competing Interests: The authors declare no competing interests.

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]

Quantification of water-budget components is an essential step in the planning and management of water resources in any river basin. Recently several studies emphasized that climate change would inevitably affect terrestrial hydrology. This study applies distributed hydrological modeling using the Variable Infiltration Capacity (VIC) model to simulate the water balance components in the Sina basin, a drought-prone region in India. We analyzed the long-term spatiotemporal dynamics of precipitation, evapotranspiration, surface runoff, and baseflow components, and their alterations due to impending climate change. The study employed the Mann-Kendall test and Sen's slope estimators to analyze the spatiotemporal trends of the water balance components during the baseline (1980–2010) and for the near future (2019–2040) periods. For the baseline period, precipitation exhibited an increasing trend, particularly during the monsoon season. On the evaluation of the annual water balance components, it showed that the basin has a low annual rainfall (~ 718 mm) and relatively a very high annual evapotranspiration (~ 572 mm) during 1980–2010, which might be the main reason for frequent droughts in the study basin. Further, for analyzing the climate change impacts on the water budget in the Sina basin, the VIC model was forced with outputs from a set of global climate models for near future (2019–2040) for two emission scenarios RCP4.5 and RCP8.5. Analysis of the results revealed that the water balance components in the near future would be negatively affected by climate change despite their increasing pattern in the baseline period. In comparison to the baseline (1980–2010), the surface runoff would decrease by as much as 32% for the near future, which stresses for planning and adaptation of appropriate mitigation measures in the basin. [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]

Devising effective strategies to retard the negative impacts of extreme climatic events on water security in general and environmental water balance in specific is imperative, especially in semi-arid rural-Western-India, where climate change has markedly increased water scarcity in domestic and agricultural sectors. This exploratory research thus aimed at investigating the water budget against mismanagement of available water resources for remote-marginalized villages in rural-Nashik (West-India). Investigation entailed visual interpretation of LULC analysis (2008–2017) using fine-scale Google Earth imageries, rainfall-runoff analysis using SCS-CN method, determining the supply-demand potential of water storage structures using field-experimentations and PRA tools, and estimation of season-wise water-budget using hydrological (water-balance) equations. Results identified agriculture as the major land-use (~ 78%) followed by hilly regions (~ 16%) and water bodies (~ 3%). Surface runoff was found as the dominating hydrological phenomenon (33–89% of monsoonal rainfall) followed by surface storage (6–36% of annual rainfall) and groundwater flow (4–82% of annual rainfall). Deforestation over hills for firewood, which reduced forest cover by 52%, was observed as the primary concern for soil erosion, thereby siltation of water bodies and higher runoff against percolation. Erratic rainfall patterns (departure range − 42 to 83% during 1998–2017) coupled with sub-graded irrigational systems confined the agricultural practices to one season [South–West monsoon (June–September)]. High unmet drinking water demand (73% to 98%) forced women communities to fetch water by walking 4.5 ± 1.5 km. Considering the urgent response to collectively combat water-budget imbalance, integrated water security plans were proposed using decentralized participatory watershed development approaches. [ABSTRACT FROM AUTHOR]

Analysis of spatial and temporal changes of long-term precipitation and extreme precipitation distribution at a local scale is very important for the prevention and mitigation of water-related disasters. In the present study, we have analyzed the long-term trend of 116 years (1901–2016) of precipitation and distribution of extreme precipitation index over the Kosi River Basin (KRB), which is one of the frequent flooding rivers of India, using the 0.25° × 0.25° resolution gridded precipitation datasets obtained from the Indian Meteorological Department (IMD), India. The non-parametric Mann–Kendall trend test together with Sen's slope estimator was employed to determine the trend and the magnitude of the trend of the precipitation time series. The annual and monsoon seasons revealed decreasing trends with Sen's slope values of −1.88 and −0.408, respectively. For the extreme indices viz. R10 and R20 days, a decreasing trend from the northeastern to the southwest part of the basin can be observed, whereas, in the case of highest one-day precipitation (RX1 day), no clear trend was found. The information provided through this study can be useful for policymakers and may play an important role in flood management, runoff, and understanding related to the hydrological process of the basin. This will contribute to a better understanding of the potential risk of changing rainfall patterns, especially the extreme rainfall events due to climatic variations. [ABSTRACT FROM AUTHOR]

The impacts of anthropogenic activities on the earth atmosphere and its systems have been engaging attention planners, governments and politicians worldwide. The countries across the world are engaged in working out the impacts and associated variability's to the projected climate change. In the twentieth century many recent studies show changes in rainfall patterns of India as well as changes in weather conditions climate changes, decrease in rainfall duration and rainfall amount and increase in rainfall intensity paper describe Climate Change Impact Studies on Rain Madhya Pradesh, India. The rainfall data collected for a period of 1901 to 2019from the District Land Record Department of Chhatarpur and Indian Meteorological Department, New Delhi (IMD). The results historical rainfall records of Chhatarpur district have been analysis using statistical and Mann Results are also discussed for the future climate change scenario in rainfall variability of thearea. [ABSTRACT FROM AUTHOR]

Maximum and minimum temperatures (Tmax and Tmin) are indicators of changes in climate. In this study, observed and gridded Tmax and Tmin data of Dehradun are analyzed for the period 1901–2014. Observed data obtained from India Meteorological Department and National Institute of Hydrology, whereas gridded data from Climatic Research Unit (CRU) were used. Efficacy of elevation-corrected CRU data was checked by cross validation using data of various stations at different elevations. In both the observed and gridded data, major change points were detected using Cumulative Sum chart. For Tmax, change points occur in the years 1974 and 1997, while, for Tmin, in 1959 and 1986. Statistical significance of trends was tested in three sub-periods based on change points using Mann–Kendall (MK) test, Sen's slope estimator, and linear regression (LR) method. It has been found that both the Tmax and Tmin have a sequence of rising, falling, and rising trends in sub-periods. Out of three different methods used for trend tests, MK and SS have indicated similar results, while LR method has also shown similar results for most of the cases. Root-mean-square error for actual and anomaly time series of CRU data was found to be within one standard deviation of observed data which indicates that the CRU data are very close to the observed data. The trends exhibited by CRU data were also found to be similar to the observed data. Thus, CRU temperature data may be quite useful for various studies in the regions of scarcity of observational data. [ABSTRACT FROM AUTHOR]

Highlights • Open source CRU temperature time series dataset has been proposed to study temperature variation for Gangotri glacier. • CRU data is in close agreement with field data. • Significant increasing trends for T mean and T min with no significant trend for T max on an annual scale. • Total of 8 change points were identified from 3 annual time series. Abstract The absence of continuous long term meteorological dataset has led to limited knowledge of glaciers' response to climate change over Himalayas. This study presents an open source long term temperature dataset Climatic Research Unit (CRU) available since 1901 to study trend analysis of temperature (T max , T min and T mean) for Gangotri basin in Himalayas. The study first establishes close agreement between CRU time series data and observed temperature dataset available from National Institute of Hydrology (NIH), Roorkee for a period of 11 years from 2005 to 2015 using standard anomaly, Wilcoxon Signed-Rank (WSR) and correlation tests. The close agreement of CRU with NIH data validate the use of CRU time series to study variation in meteorological parameter for hilly terrain of Himalayas. The second part includes application of different statistical tests such as Mann-Kendall (MK), Sen's slope and CUSUM technique on CRU data to detect existence of any possible trends and identification of change points in T max , T min and T mean on long term scale. On annual scale, significant increasing trends for T mean and T min were observed with no significant trend for T max. On seasonal and monthly scale, T max showed significant decreasing trend for monsoon season and increasing trend for winters while T min show significant increasing trend for all months (except May) and seasons. CUSUM technique identified 8 change points from 3 annual time series with 2 for T mean (1974 and 1999), 3 each for T max (1941, 1975 and 1999) and T min (1941, 1965 and 1999) respectively. Overall, significant increase in T min with no significant trend for T max has been identified over the study area. [ABSTRACT FROM AUTHOR]

Coastal West Bengal, the low-lying landward extension of the continental shelf of the Bay of Bengal is one of the most vulnerable regions to climate change. Extreme climate -driven multifarious threats, including tidal gushes, deluge with sea water, permanent submergence of land, occurrence of salinity and water scarcity have taken a toll on food and environmental security of the region. The present article discusses sea-level-rise trends in the estuaries of West Bengal coast and compares it with other coastal region of India, based on estimates derived from tide-gauge data. The PSMSL (Permanent Service for Mean Sea Level) tide data have been analysed to detect the changes of sea level trend using Mann-Kendall non-parametric test and the magnitudes of such trends have been estimated using Sen's slope. The results affirmed that the rate of sea level changes for four stations, namely, Garden Reach, Diamond Harbour, Haldia and Gangra in West Bengal coast are found to be +7.48, +4.27, +3.24 and +2.06 mm yr-1 whereas for the stations Mumbai and Cochin in west coast the rate of changes were +0.78 and +2.07 mm yr-1 and for Chennai and Vishakhapatnam in east coast the rate of changes were +1.06 and +1.00 mm yr-1. The rise in sea level in West Bengal coast was more during the last ten years (2005-2014) and it increased by 1.65% of long term average in the region. The information on rate of sea level would help in implementing defences against coastal flooding and salinity due to rising sea level. [ABSTRACT FROM AUTHOR]

In the past few decades, continuous intervention with the environmental landscape in the form of land use practices (water diversions, deforestation, local agriculture practices, industrialization etc.) in the Haridwar district of Uttarakhand, India, has impacted the region on various accounts. This is likely to be further aggravated in view of the increasing variability in the weather condition. Thus, there is urgent need felt to quantitatively asses the future climatic scenario for initiating and effectively undertaking the adaptation strategies for safe and sustained agricultural growth. For undertaking this study, PRECIS RCM data was downloaded for Roorkee grid station for the period (1961-2090). This PRECIS RCM data was biased corrected by merging two different bias correction methods which involves correcting mean and standard deviation simultaneously. Observed and bias corrected daily data was tested for their significance at 95% probability of occurrence employing various statistical methods such as correlation coefficient, mean bias error, normalized mean squared error, and Z and F statistical tests. These tests revealed that the difference between the observed and bias corrected PRECIS RCM data was insignificant. Trend analysis was done using Mann-Kendall’s test and Theil Sen’s Slope. Analysis of the bias corrected data revealed that the Roorkee station will, in general, record increasing trends in rainfall (at 5.83 mm/year), maximum temperature (at 0.05 °C/year), and minimum temperature (at 0.04 °C/year). This indicates that by 2090 AD present normal rainfall of 1006 mm/year will rise to 1447 mm/year; maximum temperature of 30.1 °C will rise to 33.9 °C and minimum temperature of 17.5 °C will rise to 20.5 °C by 2090. This weather scenario cautions at the future agronomic practices for sustained productivity. Grain yield of rice cv. Sharbati for the period 2014-2090 was simulated by running DSSAT CERES rice model with PRECIS RCM weather data of Haridwar district and RCP CO2 emission scenarios. The simulation result showed that if the crop is grown with the existing soil and crop management conditions, rice productivity of Haridwar in general will decrease 31.7 kgs/ha/year. This could be attributed to the climate change and decreased rice yields from increased maximum temperature. In the case of RCP 2.6 and RCP 4.5, the effect of CO2 on grain yields is more pronounced compared to RCP 6.0 and RCP 8.5. With the higher CO2 concentrations (above 450 ppm), the rice crop cv. Sharbati did not show much CO2 fertilization effect. DSSAT CERES rice simulations under climate change and higher CO2 concentrations showed that the yields will decline with the advancing climate change but CO2 intervention will compensate the loss in yield. [ABSTRACT FROM AUTHOR]

Effective management of water resources is crucial for sustainable development in any region. When considering computer-aided analysis for resource management, geospatial technology, i.e., the use of remote sensing (RS) combined with Geographic Information Systems (GIS) proves to be highly valuable. Geospatial technology is more cost-effective and requires less labor compared to ground-based surveys, making it highly suitable for a wide range of agricultural applications. Effectively utilizing the timely, accurate, and objective data provided by RS technologies presents a crucial challenge in the field of water resource management. Satellite-based RS measurements offer consistent information on agricultural and hydrological conditions across extensive land areas. In this study, we carried out a detailed analysis focused on addressing agricultural water management issues in India through the application of RS and GIS technologies. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we systematically reviewed published research articles, providing a comprehensive and detailed analysis. This study aims to explore the use of RS and GIS technologies in crucial agricultural water management practices with the goal of enhancing their effectiveness and efficiency. This study primarily examines the current use of geospatial technology in Indian agricultural water management and sustainability. We revealed that considerable research has primarily used multispectral Landsat series data. Cutting-edge technologies like Sentinel, Unmanned Aerial Vehicles (UAVs), and hyperspectral technology have not been fully investigated for the assessment and monitoring of water resources. Integrating RS and GIS allows for consistent agricultural monitoring, offering valuable recommendations for effective management. [ABSTRACT FROM AUTHOR]

India is one of the rapidly urbanizing major economies in the developing world. As it embarks on its urban transition, many small tier-2 cities are already experiencing a large-scale transformation. This study examines the effects of surface urban heat island intensity (SUHI) effect from 2001 to 2020 on a tropical coastal urban complex, Bhubaneswar and Cuttack, a rapidly expanding tier-2 twin city in the Eastern Indian region. Our study reveals a clear discernible annual nighttime SUHI for both Bhubaneswar and Cuttack (0.75 ± 0.08 and 1.22 ± 0.07 °C) with a growth rate of 0.18 ± 0.07 and 0.13 ± 0.07 °C/decade, respectively. Surprisingly, the annual daytime SUHI is weakening for Bhubaneswar. Both night and daytime SUHI showed substantial seasonality with a clear asymmetry during the day and night. Daytime urban cool island effect was observed for Cuttack with Bhubaneswar reporting weak SUHI for daytime during dry seasons. Around the periphery of the cities, the diurnal temperature range (DTR) was found to be the highest. Furthermore, A decrease of 2 °C in the DTR has been reported over the past two decades. The urbanization effect on the local thermal climate of both cities is seen beyond the physical urban limits. Such changes, even in tier-2 cities, have significant potential to modulate local climate and underscore the need for detailed studies in the rapidly urbanizing cities of India and the world to enable disaster resilience, climate-proofing, and sustainability. [ABSTRACT FROM AUTHOR]

Understanding the spatio-temporal pattern of natural vegetation helps decoding the responses to climate change and interpretation on forest resilience. Satellite remote sensing based data products, by virtue of their synoptic and repetitive coverage, offer to study the correlation and lag effects of rainfall on forest growth in a relatively longer time scale. We selected central India as the study site. It accommodates tropical natural vegetation of varied forest types such as moist and dry deciduous and evergreen and semi-evergreen forests that largely depend on the southwest monsoon. We used the MODIS derived NDVI and CHIRPS based rainfall datasets from 2001 to 2018 in order to analyze NDVI and rainfall trend by using Sen's slope and standard anomalies. The study observed a decreasing rainfall trend over 41% of the forests, while the rest of the forest area (59%) demonstrated an increase in rainfall. Furthermore, the study estimated drought conditions during 2002, 2004, 2009, 2014 and 2015 for 98.2%, 92.8%, 89.6%, 90.1% and 95.8% of the forest area, respectively; and surplus rainfall during 2003, 2005, 2007, 2011, 2013 and 2016 for 69.5%, 63.9%, 71.97%, 70.35%, 94.79% and 69.86% of the forest area, respectively. Hence, in the extreme dry year (2002), 93% of the forest area showed a negative anomaly, while in the extreme wet year (2013), 89% of forest cover demonstrated a positive anomaly in central India. The long-term vegetation trend analysis revealed that most of the forested area (>80%) has a greening trend in central India. When we considered annual mean NDVI, the greening and browning trends were observed over at 88.65% and 11.35% of the forested area at 250 m resolution and over 93.01% and 6.99% of the area at 5 km resolution. When we considered the peak-growth period mean NDVI, the greening and browning trends were as follows: 81.97% and 18.03% at 250 m and 88.90% and 11.10% at 5 km, respectively. The relative variability in rainfall and vegetation growth at five yearly epochs revealed that the first epoch (2001–2005) was the driest, while the third epoch (2011–2015) was the wettest, corresponding to the lowest vegetation vigour in the first epoch and the highest in the third epoch during the past two decades. The study reaffirms that rainfall is the key climate variable in the tropics regulating the growth of natural vegetation, and the central Indian forests are dominantly resilient to rainfall variation. [ABSTRACT FROM AUTHOR]

Due to the changing climate and other factors, such as land-use changes, urbanization, industrialization, deforestation, and developmental activities, the bearing influence is observed in the hydrologic cycle and in the frequency and magnitude of hydrological extremes. For sustainable development, it is essential to investigate the trend of extreme event occurrences. In this study, the trend of the annual and seasonal daily rainfall in various categories for time series 1965 to 2016 has been examined in the Sabarmati River Basin in India through the nonparametric Mann-Kendall test with Sen's slope estimator. The spatiotemporal trend distributions of annual and seasonal daily rainfall in various categories have been represented in ArcGis. The annual daily rainfall has shown a positive trend in the heavy to very heavy category. In the months of July and September, the positive trend in daily rainfall in the heavy to very heavy category indicates the tendency of extreme rainfall event occurrences [ABSTRACT FROM AUTHOR]

Understanding the rainfall pattern is tough for the solution of several regional environmental issues of water resources management, with implications for agriculture, climate change and natural calamity such as floods and droughts. Statistical computing, modelling and forecasting meteorological data are the key instruments for studying these patterns. This study aims to establish the rainfall trends of the two stations of Assam viz. Guwahati and Dhubri. The collected data is secondary in nature and obtained from the website of Global Precipitation Climatology Project (GPCP) of NASA, Goddard Space Flight Centre, United States consisting of 36 years monthly rainfall records for the period 1979-2014. We have performed Sen's slope method and Mann-Kendall test to assess the magnitude along with the statistical significance of trend. So far as monthly analysis is concerned, a gradual decrease in rainfall has been observed for maximum months in both the stations. Moreover, seasonal analysis has witnessed a noticeable similarity between the stations that is the presence of significant downward trend for winter and monsoon months over the entire period of 1979-2014. [ABSTRACT FROM AUTHOR]

The study of rainfall trends and spatio-temporal evolution (patterns) helps in understanding and planning the utilization of water resources for diverse sectors of the economy, such as agriculture and industries, and also provides indications of climate change. The present study investigates trends and patterns of seasonal, half yearly, and annual rainfall over Visakhapatnam-Chennai Industrial Corridor (VCIC) using non-parametric Mann Kendall and Getis-Ord-Gi* statistics at a district level from 1901 to 2015. The annual rainfall trend for the entire VCIC region shows a significant positive trend at 90%, which is driven by a significant positive trend in monsoons. The intensity of spatial pattern differs across the seasons. However, the annual pattern shows an intensifying hot spot (23% of VCIC), oscillating hot spot (23%), and no pattern (18%). The positive trend in rainfall during monsoon seasons in north-eastern districts and post-monsoon seasons in the southern districts of VCIC has influenced the intensifying hot spot patterns. These trends and patterns are required for carrying out a climate risk assessment for various sectors like urban and industrial areas to plan and propose suitable adaptation measures to cope with extreme rainfall events. [ABSTRACT FROM AUTHOR]

This work reports climate change signals and long-term trend analysis of climate variables, meteorological drought, and extreme climate indexes over the tropical state of Kerala in India. The trend analysis reveals statistically significant decrease of annual and southwest monsoon rainfall (as much as 63 mm and 55 mm per decade, respectively). A decrease in number of annual rainy days (up to 2.8 days=decade) is also reported. Temperature trend analysis indicates an increasing trend with as high as 1.3°C=decade. The spatiotemporal variation of extreme climate indexes across Kerala shows a decreasing trend of extreme precipitation indexes and an increasing trend of extreme temperature indexes. R95 and R95p decreased in northern and southern Kerala whereas R5 index increased in central and southern regions. Warm days have significantly increased whereas cold days exhibit a decreasing trend across the state. The increase in warmer nights is statistically significant whereas colder nights are decreasing in central and southern regions. Meteorological drought using Standardized Precipitation Index (SPI) reveals increasing occurrence of droughts in Kerala with higher frequencies over southern and central Kerala. [ABSTRACT FROM AUTHOR]

The current study analyzes the changes in the climate pattern of Bharathapuzha river basin in Kerala, India, which experiences a significant imbalance in water availability since 1990. The analysis of the climatic variables shows that there are three climatic zones existing in the basin. The trend in the historic climatic variables is estimated using the non-parametric Mann-Kendall test and the Sen slope analysis. A discrete wavelet analysis is also performed to separate only the long period component of the signal, and its trend is also studied. A significant decreasing trend is observed in the rainfall. However, a monotonous long-term increasing trend is detected for monthly average temperatures and monthly minimum temperatures. The sequential Mann-Kendall test result shows a significant change in the climatic pattern after 1980. The rainfall effectiveness of the basin is analyzed using indices. A drought analysis is also conducted using Standardized Precipitation Index (SPI) in different time scales since climatic zones 2 and 3 in the catchment are drought-prone areas in recent years. A detailed analysis on the existence of climate change in this region is conducted for the first time. These results can be further used for planning and development of climate change adaptation policies for the basin. [ABSTRACT FROM AUTHOR]

Impacts of the changing climatic regime on the trends of Indian summer monsoon rainfall (ISMR) are explored in this study for the Indian Himalayan region (IHR). The analysis is carried out for the period of 1951-2007 using a daily high resolution gridded data from APHRODITE project. At first, the percent departures of decadal rainfall are estimated from the long-term June to September rainfall values for the western, central, and eastern Himalayan (WH, CH, and EH) regions. Next, changes in the frequency of strong and weak phases of monsoon intra-seasonal oscillation are investigated. A non-parametric statistical method (Sen's slope estimator) is applied to the seasonal (i) mean rainfall, (ii) maximum rainfall, and (iii) frequency of extreme rainfall events of WH, CH, and EH regions to identify changes in their decadal, multiple year normals (NY1; 1951-1980 and NY2; 1981-2007) and long-term (NY3; 1951-2007) trends. The inter annual to inter decadal variabilities of the frequency of extreme rainfall events are explored by analyzing statistically significant intrinsic mode functions of the empirical mode decomposition (EMD) method. Results of our analyses have revealed existence of an alternative decadal oscillation of scanty and excessive summer monsoon rainfall trends for the WH, whereas excessive rainfall is observed in the last three decades (1980-2007) over the CH region. It is also observed that the frequencies of both monsoon strong and weak phases are decreasing for the entire Himalayan region. No significant trend is observed for the WH and CH regions for the normal periods NY1, NY2, and NY3 when seasonal average rainfall is considered. However, a significant ( p value < 0.05) negative trend of −0.04 mm/day rain is observed for the EH region during NY1 period. Similarly, the seasonal maximum rainfall trends for all the normal periods are found to be negative of which trends of −0.12 and −0.43 mm/day during NY3 and NY1 are observed for WH and EH regions, respectively ( p value < 0.05). No significant enhancement in the extreme rainfall event frequencies is observed for the entire IHR during 1951-2007. However, a statistically insignificant positive trend in the extreme event frequencies is observed for the EH region. A dominant cycle of ∼ 2.7 years of high frequency of extreme rainfall events is observed for all the regions whereas, a 12.2-, 15.3-, and 5.8-year cycles are observed for the WH, CH, and EH regions, respectively. [ABSTRACT FROM AUTHOR]

Monthly rainfall data from 1901 to 2011 for 45 stations of Madhya Pradesh were used to analyze the changed rainfall trend of the region. Spatial distribution and temporal variation of rainfall were observed in the seasonal and annual series. Mann-Kendall test and Sen's slope were used in the study for the trend analysis. Standard normal homogeneity test and Mann-Whitney-Pettitt test were applied for detection of break point in the series. Change percentage was calculated for seasonal and annual series for 111 years. Trend analysis was then done by dividing the entire series into two divisions before and after the break point. The impact of extreme events of rainfall on the trend was evaluated on the whole and partial series (before and after the break point). Variation in the spatial distribution of annual and monsoon rainfall was observed, which showed decreasing trend. The probable break point in the series was 1978 and extreme negative event of rainfall became frequent in the years after the break point from 1979 to 2011. The annual decrease of −6.75 % of rainfall is observed from 1901 to 2011. [ABSTRACT FROM AUTHOR]

One of the probable impacts of global warming is changes in flood frequency and magnitude, and this poses a potential threat to downstream reservoir flood control systems at dam sites. It is important to study the climate change impact on rainfall and, consequently, on inflows into the reservoir at dam sites for reservoir operation, for making decisions about irrigation extensions or flood control operations, for the safety of the dam, and for sustainable development. In this study, the trend of the hydrological parameters of rainfall and inflows within the catchment area of the Dharoi Dam reservoir basin were analyzed considering the changing climate. The results of this study show that annual rainfall and the daily rainfall in the "heavy category" had a positive trend in June, July, and August. The peak daily inflows of the year showed a positive trend, and the trend of the peak daily inflows was positive in July, August, and September. [ABSTRACT FROM AUTHOR]

Evaluating status, variability and identifying the factors influencing groundwater quality is essential to manage and conserve groundwater resources. The present study aims to examine groundwater quality for 15 water quality parameters from 84 stations in arid and semi-arid districts of Rajasthan, India, using annual data from 2000 to 2018. Statistical methods such as descriptive test statistics, Mann-Kendall (MK) test, Sen's slope estimation, and Principal component analysis (PCA) were used to analyze the hydrochemical parameters. While World Health Organisation (WHO) and Bureau of Indian Standards (BIS) guidelines were used to assess the suitability of groundwater for domestic purposes, sodium adsorption ratio (SAR), electrical conductivity (EC), and United States Salinity (USSL) diagrams were used for irrigation suitability. Further Generalized Additive Model (GAM) was used to explore the effect of climatic (precipitation, temperature) and anthropogenic (net irrigated area (NIA), fertilizer usage, industrialization, and population) variables on groundwater quality. The empirical results reveal that in groundwater of the study area sodium (Na+) and potassium (K+) were the dominating cations, while chloride (Cl−) and bicarbonate (HCO 3 −) were the dominating anions. The groundwater was predominantly Na–Cl type. Further, most stations witnessed an increasing trend in calcium, magnesium, sodium, chloride, bicarbonate and sulphate and a decreasing trend in potassium, fluoride and nitrate. The SAR, EC, and USSL indicate that the groundwater in the region is suitable for irrigation if salinity control measures are implemented. Chloride, fluoride and sodium concentrations exceeded the prescribed guideline limits in most stations, jeopardizing the suitability of water for drinking and posing significant health hazards. The GAM analysis revealed that anthropogenic variables significantly impact the groundwater quality parameters compared to the climatic variables. Accordingly, it is suggested that anthropogenic parameters must be addressed while formulating groundwater resource management policies. Thus, policies should focus on the stringent enactment of regulations and guidelines controlling the excessive use of fertilizers, implementing proper disposal of municipal solid and liquid waste, and managing industrial pollutants. [Display omitted] • The results reveal that groundwater in the examined districts is generally neutral to slightly alkaline. • On average, Na+ + K+ were the dominating cations, while Cl− and HCO 3 − were the dominating anions. • Majority of observation stations witnessed an increasing trend in Ca2+, Mg2+, Na+, Cl−, HCO 3 −, and SO 4 2−. • The SAR, EC, and USSL indicate that the groundwater in the region is suitable for irrigation purposes. • GAM analysis revealed a significant anthropogenic influence on groundwater quality. [ABSTRACT FROM AUTHOR]

Growing population and climate change have altered the hydro-climatic trend from past decades. This manuscript analyses the abrupt shift in these time series and their changing pattern using historical data sets. The Pettitt test and the Standard Normal Homogeneity Test were used to evaluate the time series' homogeneity. The Concentration Index, Precipitation Concentration Index and Seasonality Index were employed to analyse the spatial variability of daily, monthly and seasonal rainfall patterns over the Aghanashini River watershed. Furthermore, the temporal trend in the rainfall, streamflow, and temperature time series was investigated using Mann–Kendall (MK) and the graphical Innovative-Şen (IŞ) test. Clear evidence of climate change impact on the rainfall and streamflow pattern was recognized, as there is an upward shift in the maximum temperature time series and a downward shift in the rainfall and streamflow time series after 2001. The rainfall indices showed that the watershed has fewer percentage of rainy days and stronger rainfall seasonality, indicating a possible risk of flash floods in the downstream of the watershed. Additionally, the results of the MK and IŞ trend tests paralleled each other and provided support for the findings emphasized by rainfall indices. [ABSTRACT FROM AUTHOR]

Climate change significantly impacts the global hydrological cycle, leading to pronounced shifts in hydroclimatic extremes such as increased duration, occurrence, and intensity. Despite these significant changes, our understanding of hydroclimatic risks and hydrological resilience remains limited, particularly at the catchment scale in peninsular India. This study aims to address this gap by examining hydroclimatic extremes and resilience in 54 peninsular catchments from 1988 to 2011. We initially assess extreme precipitation and discharge indices and estimate design return levels using non-stationary Generalized Extreme Value (GEV) models that use global climate modes (ENSO, IOD, and AMO) as covariates. Further, hydrological resilience is evaluated using a convex model that inputs simulated discharge from the best hydrological model among SVM, RVM, random forest, and a conceptual model (abcd). Our analysis shows that the spatial patterns of mean extreme precipitation indices (R1 and R5) mostly resemble with extreme discharge indices (Q1 and Q5). Additionally, all extreme indices, including R1, Q1, R5, and Q5, demonstrate non-stationary behavior, indicating the substantial influence of global climate modes on extreme precipitation and flooding across the catchments. Our results indicate that the random forest model outperforms the others. Furthermore, we find that 68.52% of the catchments exhibit low to moderate hydrological resilience. Our findings emphasize the importance of understanding hydroclimatic risks and catchment resilience for accurate climate change impact predictions and effective adaptation strategies. [ABSTRACT FROM AUTHOR]

We use Soil and Water Assessment Tool (SWAT) to simulate the combined effects of land use/land cover (LU/LC) and climate change on the hydrological response of the Upper Betwa River Catchment (UBRC), a semi-arid region in Central India. We execute this model for two different time periods, 1982–2000 and 2001–2018, using the LU/LC data of 1990 and 2018, respectively. We classified the Landsat satellite images of 1990 and 2018 to obtain the dominant LU/LC classes (water body, built-up, forest, agriculture, and open land) in the catchment. The water body, built-up areas, and cropland have increased by 63%, 65%, and 3%, respectively, whereas forest cover and open land decreased by 16% and 23% in the UBRC from 1990 to 2018. The observed climate data in UBRC shows an increase in the average temperature and decrease in the total rainfall during the period between 1980 to 2018. Once the model is set up, we perform the calibration and validation by using the SWAT Calibration Uncertainty Program (SWAT-CUP). We considered two time periods (1991–1994 and 2001–2007) for the calibration and (1995–1998 and 2008–2014) for the validation. For both these time periods, the calibration and validation result of our model is satisfactory. The output of our calibrated model shows a relative decrease in rainfall (12%), surface runoff (21%), and percolation (9%) in the catchment during the period between 2001–2018 as compared to 1982–2000. Finally, we simulate the surface runoff and percolation in the UBRC using the future climate change scenario. We used the bias-corrected multi-model ensemble of CMIP6 GCMs for four different climate scenarios (2023–2100) by assuming no change in the existing LU/LC. We do this for two different time slices: one from 2023–2060 and the other from 2061–2100. For all the climate scenarios, rainfall and surface runoff in the catchment are expected to decrease by 15–40% and 50–79% as compared to the baseline period of 1982–2018. Percolation in the catchment will have a mixed response. It is expected to decrease by 18% in the middle part of the catchment and increase about 25% in the remaining parts of the catchment. [ABSTRACT FROM AUTHOR]

This study aims to assess the climate change impact on the rainfall and temperature data of the Vadodara-Chhotaudepur district of India and to focus on the environmental challenges related to the rainfall and temperature in the present state of development, land use, industrialization, and urbanization. The study utilized nine trend analysis methods, namely linear regression (LR), Sen's robust slope estimator (SS), Mann–Kendall test (MK), Spearman's rank correlation (SRC), the trend-free pre-whitening (TFPW), variance correction approach by Hamed and Rao (1998) with MK test (MK-CF1), variance correction approach by Yue and Wang (2004) with MK test (MK-CF2), block bootstrap with MK test (BBS-MK), and graphical method as innovative trend analysis (ITA), applied on monthly, annual, and seasonal scales. Additionally, the study also employed four homogeneity analysis methods, including Pettitt's test, standard normal homogeneity test (SNHT), Buishand's test, and Von Neumann Ratio test (VNRTs). The IMD (Indian meteorological department) gridded long-term rainfall data from 1901 to 2019 and temperature data from 1951 to 2019 are used in the present study to assess the homogeneity and trends of the data series. Results showed a warming trend of maximum temperature (MaxT) and minimum temperature (MinT) at the monthly, annual, and seasonal time scale and significant (at 5%) warming trend in annual MinT in the entire study area. Annual rainfall showed negative trend in the study area with significant (at 5%) negative trend in eastern deforested area western industrial and area adjacent to thermal power station. The change point is detected in annual rainfall time series in eastern forest area in 1959 and western area in 1983, i.e., after development of the industries and commissioning of thermal power station in the western study area. The trend rate of MaxT and MinT has been recognized as 0.004 °C/year and 0.019 °C/year, respectively, for the data period of 1951 to 2019. The annual rainfall trend rate has been observed as −0.743 mm/year for the data range 1901 to 2019. All trend analysis methods revealed consistent results except MK-CF2 method, which portraits greater number of significant trends in trend analysis methods. [ABSTRACT FROM AUTHOR]

The Himalayas have become synonymous with the hydropower developments for larger electricity demands of India's energy sector. In the Himachal Himalayas though, there are only three large storage dams with more than 1000 megawatts (hereafter MW) capacity that have very serious environmental issues. However, hundreds of small runoff-river hydropower plants across the Himachal Himalayas are a serious threat to the river regimes and Himalayan biota. There are 965 identified hydropower projects (hereafter HPPs) having a potential capacity of 27,436 MW in the Himachal Pradesh as of December 2019 as per the Directorate of Energy of the state. Out of the 965 identified, 216 are commissioned, including less than 5 MW plants, with an installed capacity of 10,596 MW, and were operational by December 2019. Only 58 projects are under construction among the identified with an installed capacity of 2351 MW, 640 projects are in various stages of clearance and investigation with an installed capacity 9260 MW, 30 projects are to be allotted with 1304 MW installed capacity, and merely four projects are disputed/cancelled with installed capacity of 50.50 MW. The large number of HPPs are sanctioned without proper consideration of negative environmental and geohazard impacts on the Himalayan terrestrial biota. In this work, our focus was on the hydropower and climate change impact on the Himalayan river regimes of the Chenab, the Ravi, the Beas, the Satluj, and the Yamuna river basins. We analyzed basin-wise rainfall, temperature, and soil moisture data from 1955 to 2019 to see the trend by applying the Mann–Kendall test, the linear regression model, and Sen's slope test. A basin-wise hazard zonation map has been drawn to assess the disaster vulnerability, and 12 hydropower sites have been covered through the primary survey for first-hand information of local perceptions and responses owing to hydropower plants. [ABSTRACT FROM AUTHOR]

The climate data (maximum temperature, minimum temperature and rainfall) of forty year (1974- 2013) was analysed for kharif (May to October) and rabi (November to April) seasons in Punjab, India. The non-parametric Mann-Kendall and Sen's methods were used to determine trend (positive or negative) in climate data over a period of 40 years. A decrease in rainfall and increase in temperature from northeast to south-west Punjab during both the kharif and rabi seasons was observed. No significant temporal variation was observed in maximum temperature and rainfall during both the seasons, but a significant increase in minimum temperature over the years was observed in different zones of Punjab. On an average, minimum temperature is increasing at 0.05oC per year during both the seasons. [ABSTRACT FROM AUTHOR]

The oriental fruit fly, Bactrocera dorsalis (Hendel) is a major pest of mango crop in India and the present studies conducted to estimate the number of generations in relation to changing temperature on mango fruits across eight different geographically isolated major mango growing locations of India. The prediction of insect pest generations and generation time was done for baseline (1961 to 1990), present (1969 to 2005), near future (2021 to 2050) and distant future (2071 to 2098) periods using A1B emission scenario data from the regional circulation model (RCM), Providing Regional Climates for Impacts Studies (PRECIS) model. The degree days models using minimum and maximum temperature were used to obtain cumulative degree days (DD) for each generation of B. dorsalis using a temperature threshold of 13°C. It was estimated that faster accumulation of degree days would make possible for occurrence of one or two additional generations with shortened mean life cycle (5 to 7 days less) in near and distant future climate change periods compared to baseline and present periods at majority of locations. Increased number of generations and reduction of generation time at majority of mango growing locations of India suggest that the incidence of B. dorsalis may likely to increase due to projected increase in temperatures during future climate change scenarios. [ABSTRACT FROM AUTHOR]

ABSTRACT This study aimed at identification of abrupt change points ( CPs) and detection of gradual trends in 34-year (1980-2013) annual rainfall at nine stations of an Indian arid region. The CPs were determined by five tests and their significance was examined by two tests. Furthermore, trends were tested by three tests and their magnitudes were quantified by two tests. Novelty of the study lies in investigating significance of trends sequentially over years by applying Mann-Kendall (M-K) test. The identified CPs were similar for standard normal homogeneity test and cumulative deviations test at most stations. In contrast, Pettitt and Bayesian tests detected CP in years 2002 and 2005 at six and three stations, respectively, and their significance was verified. Results of sequential M-K test did not match with other tests' results. The mean annual rainfall after CP (350-627 mm) increased by 14-80% of the amount before CP (306-444 mm) with 7-42% reduction in coefficient of variation. The box-whisker plots supported these findings. Results of trend tests indicated statistically significant trends at Anjar, Bhachau, Mandvi and Rapar. Trend magnitudes by linear regression prior to CP (−6.2 to 7.1 mm year−1) showed an overall increase after CP (4.7-40.8 mm year−1) with negative trend at one station. Sen's slope test, showing good harmony with linear regression, revealed that trend magnitudes after CP were 2-10 times higher than that for 34-year period at six stations. Results of M-K test applied for sequential periods emphasized that rainfall trends are becoming stronger over time. This finding suggests that significance level of increasing rainfall trends may further increase in future. Finally, findings of this study are useful for planners and decision makers for developing policies to meet the challenges of the heightened rainfall in study area. Also, the approach used here may be adopted in other parts of the globe. [ABSTRACT FROM AUTHOR]