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Despite trees' critical role in regulating global warming, their direct transpiration‐induced cooling (TIC) effects in response to background climate at the global scale are currently not well understood by ground observations. We used the global observation‐based SAPFLUXNET data set to quantify the trees' TIC and investigate how hydroclimatic variables affect TIC across biomes. Results show that TIC (i.e., air temperature reduction (ΔT)) was highest in tropical rainforests (3.24°C m−2 d−1) and lowest in temperate grassland deserts (0.06°C m−2 d−1). ΔT was mainly driven by air temperature and vapor pressure deficit in warm‐wet biomes, while precipitation and soil water content (SWC) in hot‐dry biomes. Globally, we found an average critical SWC threshold (SWCcrit) for ΔT (0.37 m3 m−3), with higher values in warm‐wet and lower values in hot‐dry biomes. These findings provide novel insights into the role of trees in mitigating global warming and improving the hydroclimatic constraints in models. Plain Language Summary The fact that trees play an important role in mitigating global warming, yet we still don't completely understand their transpiration cooling (TC) under changing climate using ground data. This study used the first global sap flow database to find out the trees' TC and their hydroclimatic controlling mechanisms across different biomes. We found the highest TC in tropical rainforests and the lowest in temperate grassland deserts. Among the selected site variables, air temperature, and vapor pressure deficit were important drivers of TC in warm‐wet biomes, while precipitation and soil water content in hot‐dry biomes. The amount of soil water restricted TC in different ways across biomes, with higher threshold values in warm‐wet and lower values in hot‐dry biomes. These findings are likely to develop more integrated and effective climate mitigation and adaptation strategies and improve the model's representation of hydroclimatic constraints. Key Points Transpiration‐induced cooling is highest in tropical rainforests, moderate in temperate forests, and lowest in temperate grassland deserts The transpiration‐induced cooling is mainly driven by available energy in warm‐wet biomes, while water availability in hot‐dry biomes Globally, we found an average critical soil water content threshold (SWCcrit), with higher values in warm‐wet biomes and lower values in hot‐dry biomes

Analyzing trends of annual rainfall and assessing the impacts of these trends on the hydrological regime are crucial in the context of climate change and increasing water use. This research investigates the recent trend of hydroclimatic variables in the Senegal River basin based on 36 rain gauge stations and three hydrometric stations not influenced by hydraulic structures. The Man Kendall and Pettitt’s tests were applied for the annual rainfall time series from 1940 to 2013 to detect the shift and the general trend of the annual rainfall. In addition, trends of average annual flow rate (AAFR), maximum daily flow (MADF), and low flow rate (LFR) were evaluated before and after annual rainfall shift. The results show that the first shift is situated on average at 1969 whereas the second one is at 1994. While the first shift is very consistent between stations (between 1966 and 1972), there is a significant dispersion of the second change-point between 1984 and 2002. After the second shift (1994), an increase of annual rainfall is noticed compared to the previous period (1969–1994) which indicates a not significant, partial rainfall recovery at the basin level. The relative changes of hydrologic variables differ based on the variables and the sub-basin. Relative changes before and after first change-point are significantly negative for all variables. The highest relative changes are observed for the AAFR. Considering the periods before and second shifts, the relative changes are mainly significantly positive except for the LFR.

Against the backdrop of global warming, assessing the effects of climate change on hydrological processes is crucial for local water resource management. Variations in temperature, precipitation, and runoff at four different timescales in the Fuhe River Basin were evaluated based on observational data collected from 1960 to 2020 using the Mann–Kendall test. The findings indicated significant increases in average temperatures for the annual, flood season, and non-flood season periods, rising by 0.0197, 0.0145, and 0.0278 °C every annum, respectively (p < 0.01). Precipitation exhibited non-significant upward trends at all timescales (p > 0.1). The trend in flood season runoff was also non-significantly upward, whereas annual runoff and non-flood season runoff displayed non-significant downward trends (p > 0.1). Flood season temperature decreased with increasing altitude, exhibiting a significant Pearson correlation coefficient of −0.744 at the 0.01 level. Conversely, annual, flood, and non-flood season precipitation significantly increased with increasing altitude, with Pearson correlation coefficients of 0.678 at the 0.01 level, 0.695 at the 0.01 level, and 0.558 at the 0.05 significance level, respectively. Precipitation and runoff exhibited similar trends throughout the year, increasing initially and then decreasing over time, reaching maximum values in June. Climate change is likely responsible for the hydrological alterations in the study basin. The findings of the study could provide references for water resource management decisions in the Fuhe River Basin.

As global warming produces dramatic climate changes, water management is facing increasingly serious challenges. Given to the process of climate change and its complex effects on watershed hydrology, this paper investigates the spatial and temporal variation characteristics of major climatic factors (i.e., precipitation and temperature) over the upper Yangtze River basin (UYRB), China. The statistical analyses are based on annual and seasonal scales during 1951–2020 with a recorded period of seven decades. The Mann–Kendall nonparametric test and R/S analysis are used to record the temporal trends (past and future) of climate variables; the Pettitt test, standard normal homogeneity test and Buishand test are used to detect the homogeneity in climate series. The sensitivities of the streamflow to climatic parameters are assessed at the watershed scale, especially considering the Three Gorges Dam’s (TGD) effect on changing runoff. The results of the study indicate that the annual precipitation of 29 out of 34 series indicate homogeneity, while 31 out of 34 annual mean temperature series show heterogeneity, with jump points around 1997 in the mean temperature of 20 sites. Detectable changes in precipitation were not observed during 1951–2020; however, the temperature increased significantly in the whole basin on annual and seasonal scales, except for several stations in the eastern part. The magnitude of increase in air temperature in high altitudes (Tibet Plateau) is higher than that in low altitudes (Sichuan Plain) over the last seven decades, and future temperatures continue to sharply increase in high altitudes. The TGD plays an important role in explaining the seasonal variations in streamflow at Yichang station, with streamflow experiencing a sharp increase in winter and spring (dry season) and a decrease in summer and autumn (rainy season) compared to the pre-TGD period. The streamflow variation at an annual scale is mainly regulated by climate fluctuation (variation in precipitation). During the last seven decades, increasing air temperature and decreases in rainfall and runoff signify reduced water resources availability, and the climate tends to be warmer and drier over the basin. The sensitivity of the streamflow to watershed precipitation is higher than that to temperature, with variation in annual rainfall explaining 71% of annual runoff variability.

Vegetation plays a dual role in the Earth’s climate system: it removes atmospheric CO2 through photosynthesis while emitting biogenic volatile organic compounds (BVOCs), which can weaken the net carbon sink and contribute to air pollution. To assess the long-term interplay between carbon uptake and BVOC emissions, and to clarify how vegetation characteristics and climate regulate this relationship, we developed a Biogenic Carbon Efficiency Index (BCEI). The BCEI integrates BVOC emissions with gross primary productivity (GPP) to quantify their spatial ratio, thereby capturing the concurrent “source” and “sink” attributes of vegetation. We characterize the spatiotemporal heterogeneity of the BCEI across China and identify its dominant environmental drivers. The BCEI decreases from southeast to northwest, and during 2001–2020 exhibited a declining trend over 78% of the country, with increases mainly in Southwest China and on the Shandong and Liaodong Peninsulas. Driver analyses indicate that variables linked to hydrothermal conditions, including temperature, precipitation, evapotranspiration, and soil moisture, primarily control BCEI variability. Across most regions, the BCEI is negatively correlated with soil moisture and precipitation, positively correlated with evapotranspiration, and shows regionally varying associations with temperature. These findings deepen understanding of vegetation’s dual role as a source and sink and its driving mechanisms, providing a theoretical basis for optimizing regional vegetation management strategies.

Spatial trend analysis is a crucial tool for identifying changes and variability in weather conditions over time, providing essential information to formulate environmental management and monitoring policies. This study investigates hydroclimatic and variable trends in Brazil, using the Mann–Kendall contextual method (CMK) as an analytical basis. The data, collected at the Climate Research Unit (CRU) between 1960 and 2020, were analyzed to understand climate dynamics in different regions of the country. The results reveal average increases of 0.48 °C and 0.32 °C at maximum and minimal temperatures, while the average precipitation recorded a reduction of 0.30 mm. In addition, Evapotranspiration (ETo) showed negative trends, with magnitudes of the order of − 2.28 mm. A negative correlation between precipitation and temperature stands out, indicating a tendency for precipitation to reduce as temperatures increase. These findings are extremely relevant, given the country's vulnerability to extreme climate events and their significant dependence on water resources for a variety of economic and social activities. The increases observed at maximum and minimal temperatures, along with the reduction in precipitation and medium evapotranspiration, reflect ongoing climate change and challenges associated with hydroclimatic variability. In light of these conclusions, coordinated actions at local, regional and national levels are imperative to ensure water safety and promote the country's sustainable development in the face of ongoing climate change. This study promises a solid basis for guiding policies and practices aimed at mitigating the impacts of hydroclimatic variability and strengthening the resilience of Brazilian communities in the face of evolving climate challenges.

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.

Modelling the river flow process during uncertain climatic conditions is a challenging task. This paper attempts to apply the hydrological model based on the least action principle (HyMoLAP) at Chitral and Gilgit stations with few modifications. The topographic wetness index, the concept of degree-day factor and snowmelt (SM) using the snow cover area (SCA) have been incorporated into the improved HyMoLAP-SM structure. It is found that the HyMoLAP-SM model significantly enhanced the accuracy of the river flow estimation and forecast. Furthermore, the model seems highly sensitive to the choice of nonlinearity parameter and moderately sensitive to SM coefficients. Moreover, the response of river flow to climate change scenarios has been projected by utilizing modelled outcomes under temperature and precipitation variations. Overall, the results suggest that average river flow may get increased (reduced) by about 60% (40%) by the increase (decrease) in temperature. On the other hand, an increase (decrease) in precipitation at Chitral (Gilgit) may increase (decrease) the average flow by about 27% (200%) [19% (8%)] at the respective station. These results may be utilized for future flood/agricultural planning in Pakistan. Additionally, results obtained in this study may not be applicable to other geographical regions or interchangeable with other modelling purpose.

Reservoir construction has led to the development of numerous wetlands, and these wetlands play an important role in global environmental change. In this paper, we investigate the relationship between reservoir wetlands and hydroclimatic variables. We used the MODIS land cover product to extract the wetland area of the Sanmenxia Reservoir, China. Then, various indices of reservoir wetland landscape patterns were calculated. Principal component analysis was performed to build the Sanmenxia Reservoir wetland comprehensive landscape pattern index (CLPI) to depict the changes in Sanmenxia Reservoir wetlands from 2001 to 2013. Pearson correlation analysis was used to assess their relationship. The following results were obtained. Firstly, the Sanmenxia Reservoir wetland area considerably declined and the landscape heterogeneity decreased from 2001 to 2013, especially in 2004. Secondly, the CLPI is significantly negatively correlated with annual runoff and significantly positively correlated with annual sediment discharge, annual average water level and annual shallow groundwater table in Sanmenxia Reservoir regions. Additionally, due to the decline in the reservoir wetland area, the values of Shannon’s diversity index and Simpson’s diversity index decreased in the study area. Therefore, the study suggests that maintaining a stable and healthy reservoir wetland area should be the focus of ecological reservoir management.

Biological invasions and climate pose two of the most important challenges facing global biodiversity. Certainly, climate change may intensify the impacts of invasion by allowing invasive plants to increase in abundance and further expand their ranges. For example, most aquatic alien plants in temperate climate are of tropical and subtropical origins and the northern limits of their ranges are generally determined by minimum winter temperatures, and they will probably expand their distributions northwards if climate warms. The distribution of five invasive aquatic plants in freshwater systems across continents were investigated. Their global distributions in the current climate were modeled using a recently developed ensemble species distribution model approach, specifically designed to account for dispersal constraints on the distributions of range-expanding species. It was found that the species appear capable of substantial range expansion, and that low winter temperature is the strongest factor limiting their invasion. These findings can be used to identify areas at risk of recently introduction of neophytes, and develop future monitoring programs for aquatic ecosystems, prioritizing control efforts, which enables the effective use of ecological niche models to forecast aquatic invasion in other geographic regions.