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The main objective of this study is to obtain a better understanding of the spatial and temporal variability and trends of rainfall and river flow in the Cobres River basin, southern Portugal, using statistical tools. The present study is focused on the analysis of the trends in annual precipitations and river flow at a regional scale over 40 years (1960-2000). Datasets of daily precipitation recorded in eight rainfall stations and three river flow stations were analyzed. The nonparametric Mann-Kendall and Sen's methods were used to determine whether there was a positive or negative trend in rainfall data with their statistical significance. A detailed statistical analysis applied to the river flow and rainfall time series of all gauges indicates that rainfall is highly temporally variable and there is a decrease in the annual rainfall amount for the period studied (1960-2000). Thus, there are signs of significant rainfall reduction in the basin, and in fact, some rain gauges show a small rainfall increase during the recent decades. The annual river flow variation has a cyclic behavior with a period length of approximately 10 years. The results seem integrated to the global and European continental scale findings: Decreasing trends are dominant for almost all indices; most of the calculated slopes are statistically insignificant; the distribution of positive and negative slopes in the area is extremely irregular; and the changes in basin are more significant compared to other studies. [ABSTRACT FROM AUTHOR]

This study presents an analysis of long-term rainfall variability and trends in the summer monsoon region of Southeast Asia, encompassing Lao People's Democratic Republic (Lao PDR), Thailand, Vietnam, Cambodia, and Myanmar, as well as their respective river basins. Utilizing Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) having a spatial resolution of 5 km spanning from 1981 to 2021, rainfall variability and trends were examined. Data preprocessing and geospatial analysis were conducted using R-Studio and ArcGIS software. The Mann–Kendall (MK) test and Sen's slope estimator were employed for annual and seasonal rainfall trend analysis. Myanmar exhibited the highest average annual rainfall of 2137 mm during the study period, while Thailand had the lowest (1641 mm). Over the past four decades, the Peninsula Malaysian Basin experienced the highest average annual rainfall (2691 mm), whereas the Chao Praya Basin recorded the lowest (1311 mm). Increasing trends in rainfall were observed across all five countries and nine major river basins. Vietnam displayed the highest annual rainfall trend of 5.63 mm/year, while Lao PDR exhibited the lowest trend (3.16 mm/year). Among the river basins, the Chao Phraya Basin demonstrated the maximum annual rainfall trend (11.21 mm/year), while the Peninsula Malaysia Basin had the minimum trend (1.21 mm/year). These findings could significantly contribute to climate change monitoring in the region and can aid policymakers in sectors such as agriculture, urban planning, and disaster management. [ABSTRACT FROM AUTHOR]

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

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]

Streamflow alteration is one of the most noticeable effects of changes in rainfall patterns (both intensity and amount) in the Himalayan region. Additionally, the impact of climate change on the localized rainfall patterns is particularly significant, which is more crucial in the Himalayas. This study carries out a comprehensive analysis on temporal variability of the rainfall and its relation to streamflow in a typical mountain river basin, located in the southern aspect of central Himalayas. The primary objective of this study is to analyze seasonal and annual rainfall trends across rain gauge stations within the selected Kali Gandaki (KG) River Basin. Monthly rainfall data were used to examine the rainfall and streamflow trends. Mann-Kendall (MK) trend test, Sen's slope, and sequential MK (SQMK) analysis were employed to evaluate monotonic trends on homogenized time series data. Our findings revealed the formation of an anticlockwise hysteresis loop between streamflow and rainfall within the catchment. Understanding the relationship between streamflow and rainfall would provide a foundation for effective water resources management. [ABSTRACT FROM AUTHOR]

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

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]

Rainfall is one of the dominating climatic parameters that affect water availability. Trend analysis is of paramount significance to understand the behavior of hydrological and climatic variables over a long timescale. The main aim of the present study was to identify trends and analyze existing linkages between rainfall and streamflow in the Nilwala River Basin (NRB) of Southern Sri Lanka. An investigation of the trends, detection of change points and streamflow alteration, and linkage between rainfall and streamflow were carried out using the Mann–Kendall test, Sen's slope test, Pettitt's test, indicators of hydrological alteration (IHA), and Pearson's correlation test. Selected rainfall-related extreme climatic indices, namely, CDD, CWD, PRCPTOT, R25, and Rx5, were calculated using the RClimdex software. Trend analysis of rainfall data and extreme rainfall indices demonstrated few statistically significant trends at the monthly, seasonal, and annual scales, while streamflow data showed non-significant trends, except for December. Pettitt's test showed that Dampahala had a higher number of statistically significant change points among the six rainfall stations. The Pearson coefficient correlation showed a strong-to–very-strong positive relationship between rainfall and streamflow. Generally, both rainfall and streamflow showed non-significant trend patterns in the NRB, suggesting that rainfall had a higher impact on streamflow patterns in the basin. The historical trends of extreme climatic indices suggested that the NRB did not experience extreme climates. The results of the present study will provide valuable information for water resource planning, flood and disaster mitigation, agricultural operations planning, and hydropower generation in the NRB. [ABSTRACT FROM AUTHOR]

The Dongting Lake basin, located in the middle Yangtze River region, has long been under the threat of climate change. However, there has been a lack of comprehensive analysis and research on the long-term trends and interactions among hydrometeorological factors within the region. To address this gap, this study collected data from 31 meteorological stations in the region and employed statistical analysis methods, including the non-parametric Mann–Kendall test, Sen's slope test, and cross-wavelet analysis. The results revealed significant increases in temperatures, especially in the spring season, while summer, winter, and annual rainfall also exhibited a significant increase. However, spring and autumn rainfall showed a non-significant decrease, and there was a clear decreasing trend in annual streamflow. Interestingly, evaporation demonstrated a significant increasing trend. The annual average temperature and annual runoff exhibited approximately negative correlations in the 6–10-year resonance period and positive correlations in the 4–6-year resonance period. There are significant positive resonance periods in the relationship between annual precipitation and annual runoff within the range of 0–12 years, indicating that precipitation has a substantial impact and serves as the primary source of runoff. Furthermore, there was a transition between "abundance" and "dry" periods in the annual runoff around 4 a, occurring before and after 1973 and 2005. The change points in annual precipitation and runoff were identified as 1993 and 1983. [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]

Satellite-based precipitation products, (SbPPs) have piqued the interest of a number of researchers as a reliable replacement for observed rainfall data which often have limited time spans and missing days. The SbPPs possess certain uncertainties, thus, they cannot be directly used without comparing against observed rainfall data prior to use. The Kelani river basin is Sri Lanka's fourth longest river and the main source of water for almost 5 million people. Therefore, this research study aims to identify the potential of using SbPPs as a different method to measure rain besides using a rain gauge. Furthermore, the aim of the work is to examine the trends in precipitation products in the Kelani river basin. Three SbPPs, precipitation estimation using remotely sensed information using artificial neural networks (PERSIANN), PERSIANN-cloud classification system (CCS), and PERSIANN-climate data record (CDR) and ground observed rain gauge daily rainfall data at nine locations were used for the analysis. Four continuous evaluation indices, namely, root mean square error (RMSE), (percent bias) PBias, correlation coefficient (CC), and Nash‒Sutcliffe efficiency (NSE) were used to determine the accuracy by comparing against observed rainfall data. Four categorical indices including probability of detection (POD), false alarm ratio (FAR), critical success index (CSI), and proportional constant (PC) were used to evaluate the rainfall detection capability of SbPPs. Mann‒Kendall test and Sen's slope estimator were used to identifying whether a trend was present while the magnitudes of these were calculated by Sen's slope. PERSIANN-CDR performed well by showing better performance in both POD and CSI. When compared to observed rainfall data, the PERSIANN product had the lowest RMSE value, while all products indicated underestimations. The CC and NSE of all three products with observed rainfall data were also low. Mixed results were obtained for the trend analysis as well. The overall results showed that all three products are not a better choice for the chosen study area. [ABSTRACT FROM AUTHOR]

The aim of the study is to analyze the spatio-temporal variability and projection of rainfall and temperature (2021-2040) in Suha watershed, North West highlands of Ethiopia. The study used 4 km × 4 km reconstructed (blended) monthly rainfall and temperature data from National Meteorological Agency of Ethiopia (NMAE) and Royal Netherlands Meteorological Institute (KNMI) of Cen Trends v1 (0.25° × 0.25°), respectively. Mann–Kendall test, Sen's slope estimator, coefficient of variation, autoregressive integrated model , and the inverse distance weighted tool were used to analysis the rainfall and temperature variability for different timescale and agroecology. The coefficient of variation showed the existence of high seasonal variability than the year-to-year in the watershed. Kiremt (main rainy season) rainfall showed substantial inter-annual variability throughout the time of observation (1990–2020). Besides, the Mann–Kendall test and the Sen's slope estimator detected that except, Belg (little rainy season) rainfall, all the others including the annual exhibited a nonsignificant increasing trend at p < 0.05. Spatially, the upper part of the watershed is wetter than the lower portion and a large portion of it (40%) received 930–1024 mm of rainfall per year. The minimum temperature showed a decreasing trend (0.01 °C per year), while the maximum temperature exhibited the opposite result (0.02 °C per year). The seasonal variability in both cases showed mixed outcomes. Forty-two percent of the watershed experiences a minimum temperature of 10.6–12.0 °C, whereas 45% experiences a maximum temperature between 24.1 and 26.0 °C. Meanwhile, the projected result showed that there is a decreasing trend for mean annual rainfall and an increasing trend for mean annual temperature from 2021 to 2040. Hence, policymakers have to give priority to the designing and application of area-specific adaptive strategies to curb the impact of climate variability. Rainwater harvesting and small-scale irrigation practice could be possible options. [ABSTRACT FROM AUTHOR]

Climate change can have an influence on rainfall that significantly affects the magnitude frequency of floods and droughts. Therefore, the analysis of the spatiotemporal distribution, variability, and trends of rainfall over the Mahi Basin in India is an important objective of the present work. Accordingly, a serial autocorrelation, coefficient of variation, Mann–Kendall (MK) and Sen's slope test, innovative trend analysis (ITA), and Pettitt's test were used in the rainfall analysis. The outcomes were derived from the monthly precipitation data (1901–2012) of 14 meteorology stations in the Mahi Basin. The serial autocorrelation results showed that there is no autocorrelation in the data series. The rainfall statistics denoted that the Mahi Basin receives 94.8% of its rainfall (821 mm) in the monsoon period (June–September). The normalized accumulated departure from the mean reveals that the annual and monsoon rainfall of the Mahi Basin were below average from 1901 to 1930 and above average from 1930 to 1990, followed by a period of fluctuating conditions. Annual and monsoon rainfall variations increase in the lower catchment of the basin. The annual and monsoon rainfall trend analysis specified a significant declining tendency for four stations and an increasing tendency for 3 stations, respectively. A significant declining trend in winter rainfall was observed for 9 stations under review. Likewise, out of 14 stations, 9 stations denote a significant decrease in pre-monsoon rainfall. Nevertheless, there is no significant increasing or decreasing tendency in annual, monsoon, and post-monsoon rainfall in the Mahi Basin. The Mann–Kendall test and innovative trend analysis indicate identical tendencies of annual and seasonal rainfall on the basin scale. The annual and monsoon rainfall of the basin showed a positive shift in rainfall after 1926. The rainfall analysis confirms that despite spatiotemporal variations in rainfall, there are no significant positive or negative trends of annual and monsoon rainfall on the basin scale. It suggests that the Mahi Basin received average rainfall (867 mm) annually and in the monsoon season (821 mm) from 1901 to 2012, except for a few years of high and low rainfall. Therefore, this study is important for flood and drought management, agriculture, and water management in the Mahi Basin. [ABSTRACT FROM AUTHOR]

Background: Projecting future streamflow variation or the hydrological impact of climate change plays a pivotal role in the sustainable implication of planning water resources management. Therefore, this study predicts the potential of climate change's impact on hydrological components in the Upper Awash Basin (UAB). The study applied a statistical downscaling model (SDSM) to generate future high-resolution climate data from the climate model output of the Canadian Second Generation Earth System Model (CanESM2) and the National Centers for Environmental Prediction (NCEP) under the representative concentration pathways (RCP4.5 and RCP8.5) scenarios. To analyze the trend of future rainfall and temperature, non-parametric Mann-Kendall, Modified Mann-Kendall tests, Sen's slope estimator, and changing point (Pettit) tests were used. The output of downscaled climate data is used as input to a calibrated and validated Soil and Water Assessment Tool (QSWAT) model to assess the impact of future climate change on UAB hydrology. Results: The results show that annual rainfall and temperature are significantly increased (p < 0.05) in the UAB under RCP4.5 and 8.5 for the model ensemble mean for both short- and long-term scenarios. The change in the rainfall, the maximum and minimum temperature is mostly visible in the second period (the 2060s). Climate change is likely to cause persistent decreases in surface runoff (SUR_Q) and increases in actual evapotranspiration (ET) under all climate scenarios in the three periods. Reduction in SUR_Q despite an increase in rainfall could be due to an increment in both temperature and ET. The study also identified inconsistent seasonal changes in projected future precipitation that considerably impact overall climatic conditions. Conclusions: This research is essential to develop an interdisciplinary approach that integrates environmental policies for the coherent use and management of water resources for future climate change and ecological protection in the basin, including other similar basins. [ABSTRACT FROM AUTHOR]

The hydroclimatic extremes such as floods and droughts have been causing damage and losses with rising frequency than ever before. The human-induced and internal climate variability create extreme events and local hydrometeorological changes influencing climate-sensitive sectors. This research is aimed at analyzing the recent changes in the hydrometeorological extremes using indices over the Bilate basin in Ethiopia. Mann-Kendall and Sen's slope estimator were used to examine changes in hydrometeorological extreme indices. The rainy days' rate of change falls between +10.64 mm in the downstream to −10.67 mm in the upstream north. The wet day rainfall and heavy rainfall day indices were stronger in the basin's southwest, implying more likely flood events. The consecutive dry days show a rising tendency with more variability, while the consecutive wet days show no trend with less variability. The change point analysis revealed inconsistencies for the majority of the extreme indices. The stations' average warmest nights and days significantly increased at a rate of 0.0358°C and 0.0320°C per annum, respectively. The coldest nights in most of the stations show a significant and negligible rise in the basin while on the coldest days more than half of the stations declining. The peak flow in the annual and seasonal time series shows a rising trend and a dominant rise in most low flow indices, which possibly flashes downstream flooding. The global and local climate anomalies revealed a weak correlation, but with overlap of wet and drought years. Basin water resource plans may benefit from identified overlap cross of threshold years for improved flood control and drought monitoring. [ABSTRACT FROM AUTHOR]

This study examines the spatial and temporal changes in temperature and precipitation extremes from 1951 to 2020 in the West African transboundary Benue River Basin, which frequently experiences impacts from extreme events. The existing studies in the region have relied on sparse observation data, hindering a comprehensive understanding of the spatial variability of climate extremes. High-resolution gridded climate data can be used to explore how climate extremes vary spatially and temporally across transboundary river basins. This study is the first attempt to employ 0.25° × 0.25° daily ERA5 temperature and precipitation data to comprehensively assess spatiotemporal changes of climatic extremes in a West African transboundary river basin. The study applied the non-parametric Mann-Kendall test and Sen's slope method to analyze temperature and precipitation extremes in the Benue River Basin. Results show a significant increase in mean maximum temperature (Tmax) of approximately ≥ 2 °C, indicating rising mean Tmax. Analysis of temperature indices reveals significant positive trends, with the number of warm days (TX90p) increasing by 8%. In contrast, evaluations of maximum 1-day (RX1day) and 5-day (RX5day) precipitation exhibit widespread reductions of 22.5% and 45%, respectively, indicating decreasing rainfall over most areas. Examinations of consecutive dry days (CDD) display higher mean changes in the northern basin extending to western Chad (70 to ≥ 110 days), revealing a link between lower annual precipitation and increased temperatures. However, we also found a basin-wide decrease in CDD ranging from ≤-2 to ≥-10 days. Overall, this study shows that the maximum temperature increases faster than the minimum temperature in the study area and that extreme temperature changes are more pronounced than extreme precipitation. These findings hold crucial implications for understanding the evolving climate dynamics in this vulnerable basin, emphasizing the urgency for adaptive measures in the face of escalating climate challenges. [ABSTRACT FROM AUTHOR]

The variability of the Indian Summer Monsoon Rainfall (ISMR), lasting from June to September, has a major impact on the Indian economy and ecosystem. An attempt to assess the temporal fluctuation of ISMR with the long‐distance interaction indicators has been presented here. This also corroborates the argued statement of a weakening relationship between ISMR and Indian Summer Monsoon Index (ISMI) due to significant temporal fluctuation. Monsoon indices: the ISMI, East Asian Summer Monsoon Index (EASMI), South Asian Summer Monsoon Index (SASMI), and Western‐North Pacific Monsoon Index (WNPMI) have been studied to create a correlation, coherency, and teleconnection with the ISMR over the Mahanadi River basin (MRB) during 1948–2017. High‐resolution gridded precipitation data were employed to assess the statistical properties of the monsoon and to address the correlation, coherency, and teleconnection with the ISMR. Spearman's rank‐based correlation test, a non‐parametric Mann‐Kendall trend test, and Sen's slope have been used to assess the statistical properties of observed precipitation and the monsoon indices. Furthermore, wavelet transform coherence is used to detect transient correlations between ISMR and monsoon indices that have previously been uncorrelated. SASMI (ρ = 0.440) dominates ISMI (ρ = 0.422) as the most significant and influential long‐distance indicator with ISMR. The findings were reconfirmed on a sub‐basin scale, with the middle Mahanadi River Basin (MMRB) being the most significant and influential, whereas the upper Mahanadi River Basin and lower Mahanadi River Basin were the second and third most influential, respectively. Plain Language Summary: A study on precipitation, where its variability, seasonal shift, and long‐distance interaction with climate have been investigated. In the face of climate change, a substantiated assessment of the Indian Summer Monsoon Rainfall (ISMR)'s relationship with the Indian Summer Monsoon Index (ISMI) and a reclassification of the dominant monsoon index are presented. The study investigates rainfall over the Mahanadi River Basin (MRB) and the large‐scale monsoon indicators to identify the most influential long‐distance interactions for spatial and temporal variability and trends in seasonal precipitation throughout the MRB from 1948 to 2017. The study revealed that MRB experiences a monsoonal precipitation drop of 0.905 mm/year, which is driven by a significant drying trend in middle Mahanadi River Basin (MMRB) (−1.717 mm/year, −0.184%/year) and a wetting trend in lower Mahanadi River Basin (LMRB) (0.439 mm/year). The pattern interpretation of monsoon precipitation over LMRB creates positive centers and a relatively negative center at upper Mahanadi River Basin (UMRB) and north of MMRB, suggesting relatively high precipitation over the coastal plains of LMRB and feeble precipitation over the MMRB and UMRB. The long‐distance interaction of ISMR with monsoon indices suggests the most influential SASMI interaction, and ISMI was undervalued by ρ = 0.018. The result agrees with the time‐frequency analysis, where a period from 1971 to 2006 experienced weak coherence, suggesting a feeble condition and a weakening relationship between ISMR and ISMI. Key Points: The drying trends of middle Mahanadi River Basin (−2.185 mm/year) and upper Mahanadi River Basin (−1.717 mm/year) appear statistically significant at 98% and 90% CI, respectivelySouth Asian Summer Monsoon Index dominates on the basin scale (Mahanadi River Basin) for long‐distance interaction with ρ = 0.440, while Indian Summer Monsoon Index (ISMI) (ρ = 0.422) has been undervaluedISMI has experienced 36 years (1971–2006) of weak coherence and is in a condition where its relationship with ISMR has become feeble [ABSTRACT FROM AUTHOR]

Floods are one of the most destructive natural hazards in Pakistan, causing significant damage. During monsoons, when westerly winds and concentrated rainfall occur in rivers' catchments, floods become unmanageable. Given the limited resources of Pakistan, there has been minimal effort to quantify the amount of rainfall and runoff generated by ungauged catchments. In this study, ten hill torrents in Koh e Suleiman (District Rajanpur and DG Khan), an area affected by flash flooding in 2022 due to extreme precipitation events, were investigated. The Hydrologic Engineering Centre's Hydrologic Modeling System (HEC-HMS), a semi-distributed event-based hydrological model, was used to delineate streams and quantify runoff. Statistical analysis of the rainfall trends was performed using the non-parametric Gumbel extreme value analysis type I distribution, the Mann–Kendall test, and Sen's slope. The results of the study show that the total inflow to the river Indus is 0.5, 0.6, 0.7, and 0.8 MAF for 25, 50, 100, and 200 years of return period rainfall, respectively. This study presents appropriate storage options with a retention potential of 0.14, 1.14, and 1.13 MAF based on an analysis of the hydrology of these hill torrents to enhance the spate irrigation potential as flood control in the future. [ABSTRACT FROM AUTHOR]

The rapidly changing climate affects vulnerable water resources, which makes it important to evaluate multi-year trends in hydroclimatic characteristics. In this study, the changes in cold-season temperature (November–April) were analyzed in the period of 1951–2021 to reveal their impacts on precipitation and streamflow components in the Liwiec River basin (Poland). The temperature threshold approach was applied to reconstruct the snowfall/rainfall patterns. The Wittenberg filter method was applied to the hydrograph separation. The Mann–Kendall test and Sen's slope were applied to estimate the significance and magnitude of the trends. An assessment of the similarity between trends in temperature and hydroclimatic variables was conducted using the Spearman rank-order correlation. The shift-type changes in river regime were assessed via the Kruskal–Wallis test. The results revealed that temporal changes in both snowfall, rainfall, and baseflow metrics were significantly associated with increasing temperature. Over 71 years, the temperature rose by ~2.70 °C, the snowfall-to-precipitation ratio decreased by ~16%, the baseflow increased with a depth of ~17 mm, and the baseflow index rose by ~18%. The river regime shifted from the snow-dominated to the snow-affected type. Overall, this study provides evidence of a gradual temperature increase over the last seven decades that is affecting the precipitation phase and streamflow component partitioning in the middle-latitude region. [ABSTRACT FROM AUTHOR]

This research entailed the acquisition of long-term (1980–2020) meteorological data (rainfall, temperature, and runoff) which was used to compute the values for the mean annual, monthly, and seasonal hydro-climate variables to establish their trend and behavior. To substantiate if the patterns of runoff are in any way due to the changing climate, the meteorological data were subjected to non-parametric tests—Mann–Kendall (MK), Sen's slope estimator, Kendall tau, and partial correlation. MK trend test for runoff, rainfall, and temperature (on an annual and seasonal basis) revealed significant trends on an annual scale. Nevertheless, rainfall data did not exhibit any, observable trend on a seasonal scale. On both annual and seasonal scales, temperature values showed increasing trends. In the entire period considered (1980–2020), runoff also exhibited a remarkable increase in trend. Sen's estimator values ranged from − 0.04 to 3.23. The results of the Kendall tau correlation showed that runoff is positively correlated to rainfall (tau = 0.222), with a high confidence level (95%). Again, the partial correlation analysis of runoff and climatic variables for annual and seasonal timescale, results show that the runoff is significantly (rxy.z = 0.315) affected by both rainfall and temperature. It is therefore recommended that future research should utilize robust input–output models to determine the amount of water stress in the basin. As a sustainable management approach, artificial surface water reservoirs should be constructed to complement the available water from the Sokoto-Rima river and alleviate the water stress experienced by the population. [ABSTRACT FROM AUTHOR]

This paper addresses the nexus of climate change and variability, soil moisture and surface runoff over the Lake Baikal catchment. Water level and distribution of dissolved and suspended matter over Lake Baikal are strongly affected by river inflow during rain-driven floods. In this study, we evaluate river flow changes at 44 streamflow gauges as well as related precipitation, evaporation, potential evaporation and soil moisture obtained from the ERA5-Land dataset. Based on Sen's slope trend estimator, Mann–Kendall non-parametric test, and using dominance analysis, we estimated the influence of meteorological parameters on river flow during 1979–2019. We found a significant correlation between the precipitation elasticity of river flow and catchment characteristics. Half of the gauges in the eastern part of the Selenga River basin showed a significant decreasing trend of average and maximum river flow (up to −2.9%/year). No changes in the central volume date of flood flow have been found. The reduction in rainfall amount explains more than 60% of runoff decrease. A decrease in evaporation is observed in areas where precipitation decrease is higher than 0.8%/year. Catchments, where the precipitation trends are not as substantial, are associated with increasing evaporation as a result of the increasing potential evaporation. Negative precipitation trends are accompanied by negative trends of soil moisture. Finally, the study reveals the sensitivity of catchments with steep slopes located in humid areas to precipitation change. [ABSTRACT FROM AUTHOR]

Drought depends upon many factors such as lack of precipitation, sunshine duration, and altitude. In this study, future rainfall trend pattern was studied, and an attempt was made to quantify the amount of rainfall deficit to cause drought occurrence and corresponding required water for the recovery of future drought. The non-standardized anomaly index (AI) was used to quantify the water deficit for future drought event, which is based on CMIP 6 climatic model generated rainfall data under the four different shared socioeconomic pathways' (SSPs) scenarios (SSP 1–2.6, SSP 2–4.5, SSP 3–7.0, and SSP 5–8.5) for the chosen study area (the upper Tapti River basin in central India). Our study found out that the future rainfall pattern would be an increasing trend for all the SSPs scenarios up to the end of the twenty-first century. Particularly, SSP 5–8.5 scenario projected increasing rainfall pattern and more number of drought events than other SSPs. In specific season, the future monsoon season showed more number of drought events. The water required for drought recovery was found increased from SSP 1–2.6 to SSP 5–8.5 scenario. The results presented in this study are helpful to adopt drought management activity in response to changing rainfall pattern under climate change aspect. [ABSTRACT FROM AUTHOR]

Long-term rainfall trends analysis under climate change, particularly in developing countries where rainfed agriculture is substantial, is vigorous to evaluate rainfall variability brought changes and propose possible adaptation measures. Hence, the study was designed to evaluate annual and seasonal long-term trends in rainfall in Wabe Shebele River Basin in Ethiopia using gridded monthly precipitation data derived from Climate Research Unit (CRU TS 4.1) with 0.5° × 0.5° resolution from 1920 to 2019 years. The time series trend of annual and seasonal rainfall was detected by employing innovative trend analysis (ITA). The results were compared with the most widely used Mann–Kendall (MK) test and Sen's slope estimator method. The basin was sub-divided into ten sub-basins for easy analysis. The MK test result revealed a non-significant decrease in annual and seasonal rainfall trends that occurred in most sub-basins and the entire basin. The results of the ITA method showed that the scattered plot was accumulated on the 1:1 (45°) straight line, indicating no trend for most of the sub-basins. The trends vary within sub-basins and rainfall magnitude while the decreasing and increasing trends were within ± 10%. The finding indicates that statistics for Φ are non-uniform spatial and temporal and show no significant trends at a 5% significant level in the most sub-basins. The comparison of the three selected methods indicates that ITA performs better in trend investigation. Hence, the ITA method provides results in graphical form, which makes a straightforward interpretation of trends based on rainfall intensity. Rainfall trends investigation is vital for agricultural development where combining the possible adaptation measures to climate change is vigorous during water resources planning and development for agriculture. Accordingly, the strategic plan is recommended for the practical activity of agriculture by considering the decline and variability of rainfall patterns in the sub-basins particularly and in the basin generally. [ABSTRACT FROM AUTHOR]

In the eastern Mediterranean region of the Middle East and North Africa, pluvial flooding has become a common and severe climate change consequence event that requires immediate attention. The Wadi-Gaza basin is a critical source of surface water in Palestine; nevertheless, climate change and anthropogenic processes are altering the basin's hydrological features, resulting in a series of extreme and disastrous flooding events in the coastal plain at the basin downstream. The Mann–Kendall test, Sen's slope estimator, and the IPTA method that was used to analyze historical rainfall in the basin from 1979 to 2013 refer to a declining trend pattern, which reduces the surge of runoff discharge. Moreover, the future projection for the total monthly rainfall under the ensemble model of CIMP5 for the RCP scenarios of 2.60, 4.50, and 8.50 demonstrate a general decreasing trend in the rainfall with a variation ranging between about − 36 and − 53%. The frequency analysis for the maximum daily rainfall using different computing approaches shows that the theoretical maximum rainfall values for the assessment of flooding events were assigned to 22, 31, 35, 45 52, 59, 66, and 77 mm for the whole basin for the return periods (T) of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. The land cover–land use of the basin shows that 51% is barren land while the other portion is divided between urban (~ 16%), agricultural (~ 13%), and natural (~ 20%) lands. However, the type of soil that covers the basin is classified mainly as clay, loam, and sandy clay. According to the hydraulic analysis of downstream flooding, the volume of surge water that might reach the coastal plain in the event of water storms of 22 and 77 mm is around 6 and 118 million cubic meters, respectively. The area at risk of inundation due to floods in the Wadi-Gaza is between 3 and 17 km2, covering around 5–29 percent of the Gaza Strip's middle governorate area, respectively. [ABSTRACT FROM AUTHOR]

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety. • Identifies trends & non-stationarity in climatic variables using advanced trend tests. • Reveals shift in seasonal rainfall patterns with higher intensity. • Utilizes Innovative trend analysis to find nature of potential hidden trend. • Reveals greater daily temperature variations and potential for extreme events. [ABSTRACT FROM AUTHOR]

The assessment of hydro-climatic trends is useful in water resource planning, especially in river basin scale. This study investigated the trends of streamflow in the Kelani river and its association with rainfall over a 31-year period. Streamflow and rainfall were assessed using Innovative Trend Analysis (ITA) method and Mann Kendall test (MK) with Sen's slope estimator. The association between streamflow and average catchment rainfall was studied using Spearman's rho correlation coefficient (ρ). Both ITA and MK tests confirmed the decreasing annual and seasonal streamflow trend from midstream to downstream of the Kelani river basin. A decreasing trend of rainfall was recorded at 75 % and 63 % stations during the southwest monsoon (SWM) and second inter-monsoon (SIM), respectively. However, annual, northeast monsoon (NEM) and first inter-monsoon (FIM) rainfall showed an increasing trend at 63 %, 88 % and 100 % stations, respectively. There was a significant association between streamflow and catchment rainfall (p < 0.05) for 70 % of stations suggesting that the variation of streamflow is mainly attributed to the variation of catchment rainfall. The decreasing trend of streamflow and rainfall during SWM and SIM towards the downstream area with the increasing temperature trend indicate a drying tendency of the Kelani river basin over the study period. [ABSTRACT FROM AUTHOR]

Trend analysis of hydrometeorological data is vital for proper water resources planning and management. This paper examines the trends of the hydrometeorological data in Gilgel Gibe catchment and whether the trends are significant. Daily rainfall, temperature, and streamflow data of the stations in/around (nearby) the catchment (7 stations for rainfall, 4 stations for temperatures, and 6 stations for streamflow) for a period longer than 25 years were collected and then analyzed to detect the variability and the changes in trend. Prior to conducting trend tests, the missed data were filled, and their inconsistencies were also adjusted. The nonparametric Mann-Kendall test along with Sen's slope technique was employed to detect monotonic trends in the data series. The results showed that, on average, the rainfall exhibits an insignificant increasing tendency. It was also observed that there is, in general, an increasing trend in temperature (both maximum and minimum) in the study area. The analysis of the stream flows indicated that only one station (Bulbul Nr. Serbo) showed a positive slope at a 5% significance level. Two stations (Aweitu Nr. Babu and Gibe Nr. Seka) showed a slightly increasing trend, whereas the remaining 3 stations (Gibe Nr. Assendabo, Aweitu at Jimma, and Kitto Nr. Jimma) indicated an insignificant decreasing trend. The streamflow of the catchment generally shows a tiny decreasing tendency (0.007% per year) at its outlet. However, the results in general specified statistically insignificant trend changes of the hydrometrological data of the study catchment. [ABSTRACT FROM AUTHOR]

Precipitation trend detection is vital for water resources development and decision support systems. This study predicts the climate change impacts on long-term precipitation trends. It deals with the analysis of observed historical (1960–2010) and arithmetic mean method in assembling precipitation from CMIP5 Global Climate Models (GCMs) datasets for a future period (2020–2099) under four emission scenarios. Daily precipitation data of 32 weather stations in the Xijiang River Basin were provided by National Meteorological Information Centre (NMIC) of the China Meteorological Administration (CMA) and Global Climate Models (GCMs) with all four emission scenarios statistically downscaled using Bias Correction Special Disaggregation (BCSD) and applied for bias correction via Climate Change Toolkit (CCT). Nonparametric Mann–Kendall test was applied for statistical significance trend analysis while the magnitude of the trends was determined by nonparametric Sen's estimator method on a monthly scale to detect monotonic trends in annual and seasonal precipitation time series. The results showed a declined trend was observed for the past 50 years over the basin with negative values of MK test (Z) and Sen's slope Q. Historical GCMs precipitation detected decreasing trends except for NoerESM1-M which observed slightly increasing trends. The results are further validated by historical precipitation recorded by the Climate Research Unit (CRU-TS-3.1). The future scenarios will likely be positive trends for annual rainfall. Significant positive trends were observed in monsoon and winter seasons while premonsoon and postmonsoon seasons will likely be slightly downward trends. The 2040s will likely observe the lowest increase of 6.6% while the 2050s will observe the highest increase of 11.5% over the 21st century under future scenarios. However, due to the uncertainties in CMIP5, the future precipitation projections should be interpreted with caution. Thus, it could be concluded that the trend of change in precipitation around the Xijiang River Basin is on the increase under future scenarios. The results can be valuable to water resources and agriculture management policies, as well as the approach for managing floods and droughts under the perspective of global climate change. [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]

The article provides a long-term trend analysis of the Kesinga catchment daily gridded rainfall at a (0.25° × 0.25°) high spatial resolution from 1901 to 2020 (120 years). The trend in seasonal and annual rainfall was detected using rank-based nonparametric statistical tests, namely Spearman's rho and Mann-Kendall test, which are used for detecting monotonic trends in time series data at the 5% significant level, smoothing curve, Sen's slope test, and a plot of innovative trend analysis. The results showed that statistically significant trends had a pattern with both positive (increasing) and negative (decreasing) trends, with positive and negative trends evident in the winter and negative trends shown in the monsoon, PREMON, and annual seasons. The middle of the study area revealed the highest negative trend, and the lower Kesinga catchment showed the lowest negative annual rainfall trend. In the entire Kesinga catchment, the seasonal data and annual rainfall both showed statistically significant and non-significant patterns. Consistently, the MK and SR tests were both conducted at the validated significance level. In various contexts, the statistically significant massive trend that has occurred was negative (70%). If the current pattern continues in the future, there will be a scarcity of water and more strain on the control of water resources at the given grids in corresponding temporal scales. [ABSTRACT FROM AUTHOR]

The effect of climate variability on the rainfall pattern is canvassed on the Uma Oya river basin, Sri Lanka, consisting of 5 rainfall gauging stations. The Uma Oya basin (720 km2) is given utmost precedence due to environmental concerns seen in the ongoing Uma Oya multipurpose development project (529 million USD worth) which is expected to divert water to the southeast dry zone of the country while adding 231 GWh/year electricity to the national grid. The rainfall data for a period of 26 years (1992–2017) were analysed using Mann–Kendall's test and Sen's slope estimator test to identify the rainfall trends. Both of these trend analysis test results depict only one negative trend for Hilpankandura Estate for the month of June; however, the seasonal trend analysis and annual trend analysis do not support this observation. Nevertheless, Mann–Kendall's test showed potential positive trends for the 3 rainfall gauging stations Kirklees Estate, Ledgerwatte Estate, and Welimada Group only in the 1st intermediate period (March-April), and this is well supported by the monthly trend analysis. Other than these trends, the results do not show any significant negative trends in the Uma Oya catchment. Therefore, the results vividly explain that there is no threat of water scarcity to the catchment area being resistant to changing global climate for the past 26 years. [ABSTRACT FROM AUTHOR]

Drought and intensive land use can interact as stressors on riparian vegetation, especially along rivers flowing through seasonally dry landscapes. Knowledge of past riparian vegetation response to drought and land use change can provide land managers with a better understanding of changes induced by upstream management actions, climate change, and chronic stressors. To investigate the response of riparian vegetation productivity to drought and land use, we developed a 21‐year time series (2000–2020) of growing season vegetation dynamics using near‐infrared reflectance of vegetation (NIRV) derived from satellite data across 30 watershed subbasins that drain into the San Francisco Bay Delta in central California, USA. We observed a strong response of riparian vegetation to drought, but rapid recovery and very few long‐term declines in productivity. At a local level, vegetation communities' response to drought and post‐drought productivity dynamics were highly variable across biophysical settings and land use gradients. Most of the riparian areas with long‐term declines in NIRV were located in the lower elevation Coast Range on the western side of the study area where there is little to no water engineering or agricultural irrigation runoff to subsidize riparian vegetation. Riparian areas with the greatest long‐term increase were along rivers draining the higher elevation Sierra Nevada range to the east. Our results suggest that river systems with a high proportion of water originating as snowmelt may be more buffered against long‐term drought‐driven declines in productivity than those dependent exclusively on winter rainfall. The long‐term increase in NIRV in the vast majority of riparian areas within our study area may also have been driven in part by increasing atmospheric CO2 concentrations, which have been shown to increase plant water use efficiency. [ABSTRACT FROM AUTHOR]

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

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen's slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (RNDVI-RF = 0.189, P ≤ 0.001) and annual (RNDVI-RF = 0.637, P ≤ 0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes. [ABSTRACT FROM AUTHOR]

Climate change information at the scale of basin is vital for planning, development and use of water. The Tapi basin is climatically responsive. Hydrological response of a basin is based mainly on rainfall and temperature. Variations in climate at regional scales impacts fundamental features of our life. Thus, in the present work, trend analyses of regional time series (1971-2004) of minimum, mean, maximum temperatures and rainfallis performed for monthly, annual and seasonal scales for the Tapi basin. Correlogram is utilized for evaluation of dependence of data. Mann-Kendall test and Mann-Kendall test with block bootstrapping are applied for the evaluation of trend significance. Sen's slope test is applied for the evaluation of trend magnitude. Sequential Mann-Kendall test is applied for assessment of beginning and end of the trend. Statistically significant positive trends are detected in regional annual and winter Tmean time series with their beginning in years 1974 and 1972, respectively. [ABSTRACT FROM AUTHOR]

Highlights • Comparison of IMD and TRMM-TMPA, CMORPH, PERSIANN, and MSWEP precipitation data. • Mann–Kendall (MK), modified Mann–Kendall (MMK), and Sen's Slope for trend analysis. • PERSIANN precipitation data has shown better trend result with the IMD data. Abstract This study compares the precipitation trend from the gridded rain gauge data collected by India Meteorological Department (IMD) and Multisatellite High Resolution Precipitation Products (HRPPs) including Tropical Rainfall Measurement Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) version 7, Climate Prediction Center Morphing (CMORPH) version 1.0, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1 for the river basins of India. The IMD and HRPPs are of the same spatial resolution (0.25° × 0.25°) and extend from 1998 to 2015. The gridded precipitation datasets are compared for 25 river basins of India. TRMM, CMORPH, PERSIANN, and MSWEP datasets accuracy for the river basins are assessed by comparison with IMD using root mean square error (RMSE) and correlation coefficient (CC) methods. The Mann–Kendall (MK) and modified Mann–Kendall (MMK) tests are applied for analyzing the data trend, and the change is detected by Sen's Slope using all datasets for annual and seasonal time periods. Variation in precipitation is high (>20%) in the northern part of India in all datasets. All these basins located at the elevations above 2000 m. The annual and monsoon trend pattern for TMPA, CMORPH, PERSIANN, and MSWEP matched with IMD data in the north, northwest, and central part in 1–2, 22–25, and parts of 3, 12, and 21 river basins (1998–2015). The calculated results implied that the TMPA precipitation product (in terms of accuracy) and PERSIANN (in terms of annual and monsoon trend) show a better agreement with IMD and they can be used in climate studies and hydrological simulation in locations/river basins where the number of rain gauges is not adequate to quantify the spatial variability of precipitation. [ABSTRACT FROM AUTHOR]

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event. In this study, 40 years (1982–2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series. From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment. • Through rainfall analysis design storm,evaluated and further used as an input data for HEC-HMS hydrological modelling. • Annual and monthly Trend analysis of 40 years rainfall from 8 rain gauge stations is studied using statistical tests, and graphical technique. • Using IDF method with Gumbel's frequency distribution, Isohyetal maps, IDF curves and tables were prepared. • No statistically significant trend was found and results from graphical and Statistical Trend Analysis methods are consistent. • The results obtained are site specific, so more reliable, hence can be used with greater confidence for deriving design storm. [ABSTRACT FROM AUTHOR]

Semiarid regions play a pivotal role in global ecosystem and environmental governance. Changing environment (climate and land use variation) has led to the disruption of hydrology in semi-arid regions and ecological degradation in some area. Understanding their hydrological response to changing environments is crucial for ecological rehabilitation and optimal water resource allocation. This research, conducted in a Chinese semiarid watershed, integrates multi-field models about hydrology, meteorology and geography to investigate hydrological processes in typical hydrological years. The results indicate that the climate in this region is drying, and the likelihood of extreme weather events is increasing with global warming. Projecting changes from 2010 to 2060, 9.21% of grassland converting to 5.63% of forest and 3.58% of gully built-up land. As a result, the flood peak increases by 22.99% in typical drought years, while it decreases by 36.77% in normal years. Based on our analysis of the rainfallrunoff process in typical drought and normal years, we identify two distinct effects: the "local rainfall-runoff effect" and the "global rainfall-runoff effect", respectively. However, in typical wet years, the streamflow state is primarily controlled by intense and concentrated precipitation. This research provides insights into the effect of ecological restoration and typical climate variations on hydrological cycle in semiarid regions, thus contributing to more informed decision-making in environmental management and water resource planning. [ABSTRACT FROM AUTHOR]

Studying rainfall patterns is very important because agricultural production and flood conditions depend on proper water management. Therefore, accurately identifying trends in climate scenarios is essential to achieve this goal. This study, therefore, analyses rainfall trends using the Mann–Kendall test (MKT), modified Mann–Kendall test (MMKT), Spearman rank correlation (SRC), Şen slope estimator (SSE), and innovative trend analysis method (ITAM). This investigation analyses annual, monsoon, autumn, summer, and winter rainfall trends using the most extensive hydrometeorological time series from 1901 to 2020. Five such methods of trend analysis use 120 years of gridded meteorological data from the India Meteorological Department for the neighbouring four river basins Kangsabati, Keliaghai, Silabati, and Dwarkeswer in east India. For the winter period, no significant trend is detected using the MKT, MMKT, SRC, and SSE. While the ITAM detects a significant trend at 88% of grid points of the study area. During other seasons, the MKT, MMKT, SRC and SSE notice trends for 76% of grid points with less significance than the ITAM method. Overall results obtained using the ITAM and MMKT methods are proved to be more effective in detecting sensitive trends. This study can serve as scientific support for the identification and strategic mitigation of climatic change impacts on water management to reduce the risk of climate change. [ABSTRACT FROM AUTHOR]

The aim of the present study is to examine the trends in magnitude and intensity of precipitation and peak floods of different magnitudes for seven major river basins in India. Data pertaining to daily flows for about 30-odd years and precipitation for 61 years (from 1951 to 2012) were analysed. Linear trends were calculated for the number of rainy days, rainfall intensity and occurrence of flood peaks for all basins. Using the Sen’s slope estimator, it was found that annual peak rainfall increases for most of the basins in India. From the Mann–Kendall test and Sen’s slope, it was found that the Cauvery and Brahamani and Baitarani basins show a rising trend in the number of rainy days, but the trend was falling for five other basins. When the basins were classified as mountains and plains, it was found that the number of daily rainfall events of different magnitudes was more in the mountains compared to the plains. The rivers which flow from west to east direction have more rainy days compared to those which flow towards the west. It was observed that in general the number of rainy days was falling while the number of intense events was increasing. The number of flood peaks of smaller magnitude in different decades showed slight falling trend. It was also found that there was falling or no trend for severe floods. Anthropogenic activities (construction of storage reservoirs, diversions, urbanization, land-use change, and soil and water conservation measures, etc.) have probably affected the generation of peak floods in the rivers of India. River regulation through storage reservoirs in the past 50 years has resulted in the reduction of peak flows. Hence with the same rainfall, the flood peaks would have increased under virgin conditions. [ABSTRACT FROM AUTHOR]

The Yellow River Basin has been considered to have the most serious soil erosion in the world, and identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. This study used the Universal Soil Loss Equation (USLE) to estimate the spatial and temporal changes in soil erosion from 1985 to 2020 and analyzed the controlling factors. The results indicated that from 1985 to 2020, the average erosion modulus in the Yellow River Basin was 1160.97 t∙km−2∙yr−1, and the erosion modulus in the middle reach was significantly greater than in the lower and upper reaches. Changes in vegetation coverage, rainfall and land use controlled 38.95%, 40.87% and 9.21% of soil erosion changes, respectively. Among them, the area in which soil erosion was decreased due to increased vegetation coverage accounted for 70.77% of the area controlled by vegetation coverage, while the area in which soil erosion was increased due to increased rainfall accounted for 86.62% of the area controlled by rainfall. These results prove the effectiveness of vegetation restoration projects in controlling soil erosion in the Yellow River Basin, but more attention needs to be paid to the impact of rainfall on soil erosion in the future. [ABSTRACT FROM AUTHOR]

The study addresses the long-term trend in rainfall, minimum and maximum temperature, and the climate indices for the river catchments located in the diverse climate of the Western Ghats of India. The dry sub-humid Chaliyar catchment and humid Kajvi catchment have shown a dramatic change in the decadal rainfall, with the decade 1950–1960 being the point of change. The monsoon rainfall has decreased in the Chaliyar and Netravati catchments and increased insignificantly in the Kajvi catchment. With the increase in mean temperature, the number of rainy days is decreasing, and intense rainfall is increasing in the pre-monsoon. The increase in minimum temperature is more severe in all three catchments, irrespective of the region's climate. The decline in rainy days is more figurative in the humid and per-humid catchments and has seen a 16–20% decrease in R × 1 day, R × 3 day, and R × 5 day in the past six decades with an insignificant increase in the dry sub-humid catchment. The frightful increase in warm days/nights with a decrease in cool days/nights has been alarming for the extremity of temperature in future years. The significant changes in the forest area in Chaliyar and Kajvi catchment and the increase in a built-up area in Netravati may have a decisive role in the nonseasonal variability in rainfall and temperature along with increasing greenhouse gases. In the case of meteorological drought studied using the Standardized Precipitation Index (SPI), moderate droughts have occurred over the Chaliyar and Kajvi, and extreme droughts over the Netravati catchments with no reduction in the frequency or severity of short-duration extreme rainfall events. The geographical location of the catchment has a greater impact on the characteristics of the rainfall and meteorological drought, and these changes in the hydrological regimes of the catchment have a significant bearing on the water availability in the catchments in the future years. [ABSTRACT FROM AUTHOR]

This study aims to investigate trends and spatiotemporal variability of precipitation during the period of 1980-2015 in the Main Central Ethiopian Rift Valley Lakes Basin. Mann-Kendall (MK) and Sen's Slope (SS) estimation were used to detect the trends and magnitudes respectively. The Inverse Distance Weighting method was employed for spatial interpolations. The results revealed that the rainfalls had experienced less concentrated and highly variable in the central rift floor. The trend analysis showed that out of 21 stations, 4 stations (Koshe, Bulbula, Kofole and Shashamane) in annual; six stations (Koshe, Bulbula, Tora, Wulberg, Wondogenet, and Shashamane) in spring; and only one station (Shashamane) in summer showed significantly decreasing trends with - 4.5 to -15.59 mm/year range. All stations in spring rainfall revealed no positive trends. Conversely, in both annual and summer rainfall statistically significant increasing trends exhibited for Ejersalelle and Adamitulu with 6.4 to 7.94mm/year range. In monthly time scales, the significant decreasing and increasing trends were also investigated for a few stations. Increasing trends could lead to an increase in potential for water resources whereas variability and decreasing trends could boost over-exploitation of water resources. This study would be provided useful information for management of water resources in the study area. [ABSTRACT FROM AUTHOR]

This study evaluates the spatiotemporal rainfall variability over the semimountainous Soan River Basin (SRB) of sub-Himalayan Pothwar region, Pakistan. The temporal rainfall trend analysis of sixteen rain gauges was performed on annual basis with long-term (1981–2016) data. The results depicted that there is substantial year-to-year and season-to-season variability in rainfall patterns, and rainfall patterns are generally erratic in nature. The results highlight that most of the highland rainfall stations showed decreasing trends on annual basis. The central and lowland stations of the study area recorded an increasing trend of rainfall except for Talagang station. The average annual rainfall of the study area ranges between 492 mm and 1710 mm in lowland and high-altitude areas, respectively. Of the whole year's rainfall, about 70 to 75% fall during the monsoon season. The rainfall spatial distribution maps obtained using the inverse distance weighting (IDW) method, through the GIS software, revealed the major rainfall range within the study area. There is a lack of water during postmonsoon months (November–February) and great differences in rainfall amounts between the mountainous areas and the lowlands. There is a need for the rational management of mountainous areas using mini and check dams to increase water production and stream regulation for lowland areas water availability. The spatiotemporal rainfall variability is crucial for better water resource management schemes in the study area of Pothwar region, Pakistan. [ABSTRACT FROM AUTHOR]

Meghalaya is known to receive the most torrential rainfall in the world, but the region suffers from water shortage as soon as the rain recedes, and the dry season starts. Changes in rainfall patterns and distribution can have a profound impact on water availability in a watershed, and therefore, examining spatial and temporal variations in rainfall is essential. However, the long-term rainfall variations in Meghalaya are not well explored. In this study, we take up two important watersheds in Meghalaya, i.e. Umiam and Umtru watersheds, to study the spatial and temporal rainfall variations. Using the gridded rainfall data from the Indian Meteorological Department from 1901 to 2018, we show that annual, winter, pre-monsoon, and monsoon rainfall is decreasing, whereas the post-monsoon rainfall is increasing. We use the innovative trend analysis (ITA) method to identify the trends in low-, medium-, and high-intensity rainfall. We find that low- and medium-intensity rainfall is in decreasing trend while high-intensity rainfall is increasing across annual and seasonal time scales. Lastly, we cross-check the trends detected using the innovative trend analysis method with a widely accepted Mann-Kendall (MK) test. We find that the results obtained by using the two methods generally concur; however, the ITA can detect non-monotonic trends in different rainfall intensities and is more sensitive to hidden patterns than the MK test. [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]

Irregular and occasional rainfall poses problems for the government authorities to meet the demand of water for drinking and agricultural tenacities of the people dwelling in four important districts of Tamil Nadu viz. Madurai, Theni, Sivagangai and Ramanathapuram. Proper design and management of water resources is essential to address this issue. Therefore, a study on spatio-temporal variations on rainfall trend was done over the Vaigai river catchment, based on the long-term rainfall records for the period from 1959 to 2016. Trend analyses were examined at seven stations by the Kendall‘s Tau (non-parametric test) to determine the trends. Sen‘s slope estimator was used to estimate the slope of trend, Cumulative deviations & CUMSUM test were used to identify shift detection for yearly and seasonal rainfall seasons. The analysis displayed a reduction in rainfall in catchment area for most of the rainfall stations except Periyakulam and Veerapandi stations for the past 58-year period spatio-temporally. Also, the findings of change point detection, predicted for yearly and seasonal rainfall series by Cumulative deviations & CUMSUM tests are in agreement with the existence of shift deduction during 1988 over these two stations. The findings will help the authorities for effective planning of irrigation systems, storage and distribution of available water. [ABSTRACT FROM AUTHOR]

The study is carried out with changing long-term trend and variation in one of the significant climatic element. The daily gridded rainfall data of spatial resolution 0.25°x 0.25°, for the last 46 years i.e. 1970-2015, has been processed for the Asan watershed located in Doon Valley, Uttarakhand. The non-parametric Mann-Kendall (MK) test together with Sen's Slope Estimator has been used for the determination of trend and slope magnitude in the watershed respectively. The gridded statistics of annual and seasonal precipitation trends have been studied here to achieve the objective. It has been observed that the magnitude of precipitation in annual and monsoonal time series are increased for all grids except for grid 6 and 8 which show a decreasing trend. The Post Monsoon time series shows a decreasing trend in all grids except for grid 6 which show positive whereas both the summer and winter rainfall show increasing trend except for grid 6. The Coefficient of variability shows variation for annual and seasonal rainfall suggesting overall insignificant changes in the area. [ABSTRACT FROM AUTHOR]