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This paper focuses on sea surface temperature (SST) trends due to the importance of temperature difference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fish population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann–Kendall, (MK) (Mann in Econom: J Econom Soc 13:245–259, 1945; Kendall in Rank Correlation Methods, Charless Griffin, London, 1975) and innovative trend analysis (ITA) (Şen in J Hydrol Eng 17(9):1042–1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into five clusters considering fish life as "hot," "warm-hot," "warm," "cold," and "very cold." According to ITA, SST in all coastal areas tends to increase except for winter season during "very cold" (0–10 °C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fish population, tourism habit, precipitation regime, and drought feature. [ABSTRACT FROM AUTHOR]

Long-term groundwater level analysis, which is usually based on traditionally defined hydrological years is essential in an era of global warming and other climatic and environmental changes, especially in urban areas. A complex interplay of multiple factors influencing the groundwater level makes the investigation of their interdependencies a challenge. Based on multiple data sets and a long time series available as well as specific geological and hydrological conditions, a semi-urban district of Wrocław/Poland was selected as a case study for investigating these dependencies. This paper presents an interdisciplinary approach to the analysis of groundwater level fluctuations by combining mathematics, signal processing, hydrogeology, and meteorology. Applying well-known methods from disciplines other than hydrogeology, the authors investigated seasonal behavior and similarity of groundwater level fluctuations during 15 hydrological years. Based on segmentation and agglomerative clustering (AHP), five classes of groundwater levels fluctuations for predefined hydrologic years and the corresponding seasons were identified and compared to the classification scheme by Pleczyński. Additionally, the relationship between precipitation and groundwater level was investigated using Pearson, Kendall and Spearman correlations. This led to the identification of "typical" and "untypical" seasons for the correlation between the cumulative precipitation sum and groundwater levels. The results presented here will be used for further investigations of groundwater level fluctuations using additional factors and statistical methods. These aim to identify periods that describe similarities better than the commonly used hydrological year. [ABSTRACT FROM AUTHOR]

This study was undertaken to address how near-surface soil water content (SWC) patterns have varied across diverse agroecological regions (AERs) of mainland India from 1979 to 2022 (44 years) and how these variations relate to environmental factors. Grid-wise trend analysis using the Mann–Kendall (MK) trend test and Sen's slope was conducted to determine the trends and their magnitudes. Additionally, we used Spearman's rank correlation (ρ) to explore the relationships of ESA CCI's near-surface SWC data with key environmental variables, including rainfall, temperature, actual evapotranspiration, and the normalized difference vegetation index (NDVI). The results revealed significant variations in SWC patterns and trends across different AERs and months. The MK trend test indicated that 17.96% of the area exhibited a significantly increasing trend (p < 0.1), while7.6% showed a significantly decreasing trend, with an average annual Sen's slope of 0.9 × 10−4 m3 m−3 year−1 for mainland India. Areas with the highest decreasing trends were AER-16 (warm per-humid with brown and red hill soils), AER-15 (hot subhumid to humid with alluvium-derived soils), and AER-17 (warm per-humid with red and lateritic soils). In contrast, increasing trends were the most prominent in AER-5 (hot semi-arid with medium and deep black soils), AER-6 (hot semi-arid with shallow and medium black soils), and AER-19 (hot humid per-humid with red, lateritic, and alluvium-derived soils). Significant increasing trends were more prevalent during monsoon and post-monsoon months while decreasing trends were noted in pre-monsoon months. Correlation analysis showed strong positive correlations of SWC with rainfall (ρ = 0.70), actual evapotranspiration (ρ = 0.74), and NDVI (ρ = 0.65), but weak or negative correlations with temperature (ρ = 0.12). This study provides valuable insights for policymakers to delineate areas based on soil moisture availability patterns across seasons, aiding in agricultural and water resource planning under changing climatic conditions. [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]

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The objective of this paper is to investigate the projected regional responses of univariate and bivariate behaviors of extreme precipitation to climate change over the upper-middle Huaihe River Basin. Based on twelve GCM outputs under historical, RCP4.5 and the observations at 32 rainfall stations, the equidistant cumulative distribution function matching method (EDCDFm) was utilized to bias correct daily precipitation during the historical (1961–2005) and future (2021–2080) periods. Four precipitation indices combinations were introduced based on eight precipitation indices to characterize the regional-scale changes of precipitation events, which designate the duration, intensity and amount of heavy and weak precipitation in a year. Their dependence structures were captured by Copulas. Kendall return period (KRP) were applied to discuss hazard scenarios and we quantified the spatial variability of KRPs under different marginal values. The results indicated that projected precipitation characteristics including the average intensity, the amount of annual precipitation, the intensity and amount of extreme precipitation together with annual extremes displayed increasing trends, while the changes of consecutive wet and dry days did not present pronounced trends. Decreased KRPs in the vast majority of the territory manifested that the frequency of simultaneous floods and droughts in a year as well as that of extreme heavy precipitation events would augment. Obvious spatial heterogeneity of the changes of KRP was partly attributed to the topography difference, especially the coastal areas along the main stream of the Huaihe River. Consequently, there will be a higher risk of water resources-related issues in this region for upcoming decades. • Significant decreases will occur in the intensity and amount of heavy precipitation for upcoming decades. • Change rates of precipitation indices combinations illustrate obvious spatial heterogeneity. • The frequency of simultaneous floods and droughts in a year and that of extreme heavy precipitation events will augment. [ABSTRACT FROM AUTHOR]