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Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Tribe Zyginelline leafhoppers can transmit plant viruses and are important pests that affect agriculture, forestry, and animal husbandry, causing serious economic losses. The potential distribution patterns of Zyginellini will change under climate change. Therefore, the best-performing random forest and maximum entropy models among 12 commonly used ecological niche models, alongside an ensemble model, were selected to predict the changes in habitat suitability distribution of Zyginellini under current and future climate scenarios [represented by two shared socio-economic pathways (SSPs), namely SSP126 and SSP585, for three periods (2050s, 2070s, and 2090s)] in China and the Indo-China Peninsula for the first time., Results: The results revealed that the distribution of Zyginellini was mainly dominated by minimum temperature of coldest month. Under current and future climate scenarios, Zyginellini was mostly distributed southeast of the 400 mm equivalent precipitation line in China, and Vietnam. Under the future SSP126 scenario, the alert areas will mainly be concentrated in Hunan, Jiangxi, Zhejiang, Anhui, and Hebei in China, alongside Myanmar and Thailand in the Indo-China Peninsula. Meanwhile, in the SSP585 scenario, the alert areas in China will increase, whereas there will be little change in the Indo-China Peninsula. Interestingly, from the current to the future, the cores of Zyginelline distribution occurred around rivers and mountains, and shifted from Guizhou along the Yuanjiang River system to higher latitudes in Hunan., Conclusion: Zyginellini prefers higher latitude river-mountain systems under climate change. Our results will contribute to effective pest control strategies and biogeographical research for Zyginellini alongside other Cicadellidae insects. © 2023 Society of Chemical Industry., (© 2023 Society of Chemical Industry.)

Tropical regions are characterized by hydrological extreme events, which are likely to be exacerbated by climate change. Therefore, quantifying the extent to which climate change may damage a hydrological system becomes crucial. This paper aims to evaluate the findings from previous research on projected impacts of climate change on hydrological systems located in regions bounded by the Tropic of Cancer and the Tropic of Capricorn. It intends to provide an in-depth understanding of the climatic conditions, applied approaches, climate change impacts on future streamflow, and measures to reduce prediction uncertainty in the tropics. The review revealed that there is a significant variation in the magnitude of climate change impacts on streamflow in the tropics. The reason for the inconsistent trend prediction is that projections are heavily dependent on the trajectory of greenhouse gas emissions, climate model structural differences, and uncertainty of downscaling methods and hydrological models. Therefore, to minimize the uncertainty and maximize confidence in streamflow projections, it is essential to apply multi-member model ensembles and to clarify the adaptation strategy (coping, adjusting, or transforming).

The Upper Indus Basin (UIB) heavily depends on its frozen water resources, and an accelerated melt due to the projected climate change may significantly alter future water availability. The future hydro-climatic regime and water availability of the Hunza basin (a sub-basin of UIB) were analysed using the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections. A data and parameter parsimonious precipitation-runoff model, the Distance Distribution Dynamics (DDD) model, was used with energy balance-based subroutines for snowmelt, glacier melt and evapotranspiration. The DDD model was set up for baseline (1991-2010), mid-century (2041-2060) and end-century (2081-2100) climates projections from two global circulation models (GCM), namely EC-Earth3 and MPI-ESM. The projections indicate a substantial increase in temperature (1.1-8.6 °C) and precipitation (12-32%) throughout the twenty-first century. The simulations show the future flow increase between 23-126% and the future glacier melt increase between 30-265%, depending on the scenarios and GCMs used. Moreover, the simulations suggest an increasing glacier melt contribution from all elevations with a significant increase from the higher elevations. The findings provide a basis for planning and modifying reservoir operation strategies with respect to hydropower generation, irrigation withdrawals, flood control, and drought management., (© 2022. The Author(s).)

Climate change alters the river flow regimes causing significant changes in the structure and function of an aquatic ecosystem, ultimately affecting river health. This study applied a customized framework consisting of 1-index, 4-components, 6-indicators, and 43-metrics, to assess river health for two seasons and future periods, in the Marshyangdi Watershed, Nepal. Hydrological, water quality, biological and physical conditions were assessed using simulated results from a hydrological model, physiochemical analysis of water samples, macroinvertebrates assemblages analysis, and physical habitat condition assessment, respectively. Climate change impact on river health was assessed based on projected climate (precipitation and temperature) based on regional climate models under representative concentration pathways (RCP) 4.5 and 8.5 scenarios until the mid-century. Results showed moderate river health condition in both the seasons and it's deterioration for future scenarios and periods. It reveals the need to formulate appropriate measures for the conservation of the river health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The detailed analyses of the water balance components (WBCs) of the catchment help assess the available water resources, especially in the arid climate regions for their sustainable management and development. This paper mainly used the Soil and Water Assessment Tool (SWAT) model to analyze the variation in the WBCs considering the change in the Land Use and Land Cover (LULC) and meteorological variables. For this purpose, the model used the inputs of LULC and meteorological variables between 2001 and 2020 at 5 years and daily time intervals, respectively, from the Chittar river catchment. The developed models were calibrated using SWAT-CUP split-up procedure (pre-calibration and post-calibration). The model was found to be good in calibration and validation, yielding the coefficient of determination (R 2 ) of 0.94 and 0.81, respectively. Furthermore, WBCs of the catchment were estimated for the near future (2021-2030) at the monthly and annual scales. For this endeavor, LULC was forecasted for the years 2021 and 2026 using Cellular Automata (CA)-Artificial Neural Network (ANN), and for the same period, meteorological variables were also forecasted using the smoothing moving average method from the historical data., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Streamflow patterns support complex ecosystem functions and services. However, the direct impacts of flow regulation and climate change on patterns of streamflow are less studied. This study aims to analyse the sensitivity of streamflow patterns to the effects of flow regulation and climate change in the Goulburn-Broken catchment in Victoria, Australia. Daily streamflow was classified into low, medium, high, and overbank flow metrics using a statistical quantile-based approach. Trends and percent changes in streamflow metrics during the 1977-2018 period were analysed, and effects of change in rainfall, regulation, and flow diversion on streamflow patterns were predicted using a generalized additive model and path analysis. Low flows and medium flows increased by 26%, and high flows and overbank flows decreased by 31% during the period between 1977 and 2018. While current river regulation and flow diversion practices would dominate future change in magnitude, duration, and frequency of the streamflow, the timing of flow metrics would be dominated by variation in rainfall. These could bring a new ecological and environmental risk to the riverine ecosystem. It is recommended to increase the duration of high flows (90-120 days) and overbank flows (10-30 days) and the frequency of overbank flows to at least once every 1-2 years during wet periods to mitigate ecological and environmental risks of climate change and flow regulation in the Goulburn-Broken catchment., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Recent drought events in the Mekong River Basin (MRB) have resulted in devastating environmental and economic losses, and climate change and human-induced alterations have exacerbated drought conditions. Using hydrologic models and multiple climate change scenarios, this study quantified the future climate change impacts on conventional and flash drought conditions in the MRB. The Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC) models were applied to estimate long-term drought indices for conventional and flash drought conditions over historical and future periods (1966-2099), using two emission scenarios (RCP 4.5 and RCP8.5), and four climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For the conventional drought assessment, monthly scale drought indices were estimated, and pentad-scale (5 days) drought indices were computed for the flash drought evaluations. There were overall increases in droughts from the SWAT model for the conventional drought conditions and overall decreases from the VIC model. For the flash drought conditions, the SWAT-driven drought indices showed overall increases in drought occurrences (up to 165%). On the contrary, the VIC-driven drought indices presented decreases in drought occurrences (up to -44%). The conventional and flash drought evaluations differ between these models as they partition the water budget, specifically soil moisture differently. We conclude that the proposed framework, which includes hydrologic models, various emission scenarios, and projections, allows us to assess the various perspectives on drought conditions. Basin countries have differential impacts, so targeted future adaptation strategy is required., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

An understanding of water sufficiency provides a basis for informed-planning, development and management of water resources. This study assessed spatio-temporal distribution in water sufficiency in the Extended East Rapti watershed in Nepal. The "Palika" (local government unit) is considered as a spatial-scale and seasons and future periods as temporal-scale. The water sufficiency was evaluated based on water sufficiency ratio (WSR) and water stress index (WSI). A hydrological model was developed to simulate water availability. An ensemble of multiple Regional Climate Models was used for assessing climate change impacts. Results showed water sufficiency by mid-century is projected to decrease; WSR by 40% and WSI by 61%. Despite projected decrease in water sufficiency, annually available water resources are projected as sufficient for the demands until the mid-century, however, seasonal variability and scarcity in future is projected in most Palikas. Such results are useful for water security planning in the Palikas., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Evapotranspiration (ET) is a critical variable in the world's water cycle, and plays a significant role in estimating the impact of environmental change on the regional hydrothermal cycle. Moreover, as an essential of eco-hydrological processes, changes in ET may exceptionally impact the local climate and provide indicative information on the eco-system's functioning. The Hailar River Basin (HRB), located in northern China, is one of the most sensitive areas to climate warming. Under the influence of climate change in recent years, the vegetation dynamics of the basin have been significant and have had profound effects on the regional water cycle conditions and hydrological processes. The HRB is located in a semiarid region and ET is the main mode of water consumption. The ET response to climate change and vegetation dynamics is the focus of research on ecohydrological processes in this basin. In this study, a distributed hydrological model, the BTOPMC model, is used to evaluate the actual ET in the HRB from 1981 to 2020, based on in situ meteorological data as well as LAI data obtained by satellite remote sensing. The seasonal, interannual and spatial dynamics of ET were characterized. The contribution of meteorological factors to ET was calculated by sensitivity analysis and multiple linear regression analysis, and the predominant elements influencing the difference in ET in the HRB were also discussed. The results show that: (1) estimated ET values can clarify over 85% of the seasonal variation in the observed values (R 2 = 0.79, P < 0.001; R 2 = 0.84, P < 0.001), which demonstrates that the model has a high precision. (2) Over the past 40 years, the annual ET has shown a clear increasing trend and a large spatial heterogeneity in its spatial distribution, which is consistent with the trend of vegetation. It mainly shows that the eastern forest area is larger than the central forest-grass transition area and the western meadow steppe area. (3) Sensitivity and influential factor contribution analyses show that the main factor driving interannual variability in ET is climate warming, followed by precipitation. At the same time, vegetation dynamics also play a crucial role in ET, especially in areas with different vegetation types and high coverage, while climatic factors also have a strong influence on ET indirectly through vegetation. Due to its special geographic location, the HRB is more sensitive to global climate change and is a typical ecologically fragile area. Therefore, this study has important scientific value and social significance for maintaining ecological security and the sustainable use of water resources., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Climate change plays a key role in changing vegetation productivity dynamics, which ultimately affect the hydrological cycle of a watershed through evapotranspiration (ET). Trends and correlation analysis were conducted to investigate vegetation responses across the whole Upper Jhelum River Basin (UJRB) in the northeast of Pakistan using the normalized difference vegetation index (NDVI), climate variables, and river flow data at inter-annual/monthly scales between 1982 and 2015. The spatial variability in trends calculated with the Mann-Kendall (MK) trend test on NDVI and climate data was assessed considering five dominant land use/cover types. The inter-annual NDVI in four out of five vegetation types showed a consistent increase over the 34-year study period; the exception was for herbaceous vegetation (HV), which increased until the end of the 1990s and then decreased slightly in subsequent years. In spring, significant (p<0.05) increasing trends were found in the NDVI of all vegetation types. Minimum temperature (Tmin) showed a significant increase during spring, while maximum temperature (Tmax) decreased significantly during summer. Average annual increase in Tmin (1.54°C) was much higher than Tmax (0.37°C) over 34 years in the UJRB. Hence, Tmin appears to have an enhancing effect on vegetation productivity over the UJRB. A significant increase in NDVI, Tmin and Tmax during spring may have contributed to reductions in spring river flow by enhancing evapotranspiration observed in the watershed of UJRB. These findings provide valuable information to improve our knowledge and understanding about the interlinkages between vegetation, climate and river flow at a watershed scale., Competing Interests: The authors have declared that no competing interests exist.

Climate warming accelerates the hydrological cycle, especially in high-latitude and high-altitude areas. The increase in temperature will increase the amount of snow and glacier melting and change the runoff, which will affect the operations of cascade reservoirs significantly. Therefore, taking the upper reaches of the Yellow River with an alpine climate as an example, we propose an improved SIMHYD-SNOW, which considers the snowmelt runoff process. The impacts of climate changes on the runoff process were revealed based on the SIMHYD-SNOW model using the precipitation and temperature data predicted by the SDSM model. A model for the maximum power generation of the cascade reservoirs in the upper reaches of the Yellow River was constructed to explore the impacts of climate changes on the inter-annual and intra-annual hydropower generation of the cascade reservoirs at different periods in the future. The results show that climate change has changed the spatial and temporal allocation of water resources in this area. The future runoff will decrease during the flood period (July to September) but increase significantly during the non-flood period. The inter-annual and intra-annual hydropower generation under the RCP8.5 climate change scenario is significantly lower than the RCP2.6 and RCP4.5 climate change scenarios, and as the CO2 emission concentration increases, this gap increases significantly. This study can provide technical references for the precise formulation of water resources management under climate change., Competing Interests: The authors have declared that no competing interests exist.

The incision of the Sanmen Gorge marks the birth of the modern Yellow River, but its timing varies from the late Miocene-early Pliocene to the late Pleistocene (∼0.15 Ma), and the suggested forcing mechanisms vary from the uplift of the Tibetan Plateau to global climate change. Here, we report sedimentologic, geochronologic, and provenance data from a drill core near the Sanmen Gorge, the last gorge along the main course of the Yellow River. Our results indicate that typical river channel deposits, with detritus from the Ordos Block in the upstream regions, started to accumulate in the Sanmen Gorge at ∼1.25 Ma. When integrated with river terrace evidence from the upstream and downstream regions, the results provide robust evidence that the final integration of the modern Yellow River occurred at ∼1.25 Ma, consistent with the beginning of the Mid-Pleistocene transition (MPT). We propose that the accelerated lowering of eustatic sea level during the MPT may play as important a role as tectonism in driving the birth and evolution of the modern Yellow River., (Copyright © 2022 Science China Press. Published by Elsevier B.V. All rights reserved.)

Among the projected effects of climate change, water resources are at the center of the matrix. Certainly, the southern African climate is changing, consequently, localized studies are needed to determine the magnitude of anticipated changes for effective adaptation. Utilizing historical observation data over the Olifants River Catchment, we examined trends in temperature and rainfall for the period 1976-2019. In addition, future climate change projections under the RCP 4.5 and RCP 8.5 scenarios for two time periods of 2036-2065 (near future) and 2066-2095 (far future) were analysed using an ensemble of eight regional climate model (RCA4) simulations of the CORDEX Africa initiative. A modified Mann-Kendall test was used to determine trends and the statistical significance of annual and seasonal rainfall and temperature. The characteristics of extreme dry conditions were assessed by computing the Standardized Precipitation Index (SPI). The results suggest that the catchment has witnessed an increase in temperatures and an overall decline in rainfall, although no significant changes have been detected in the distribution of rainfall over time. Furthermore, the surface temperature is expected to rise significantly, continuing a trend already evident in historical developments. The results further indicate that the minimum temperatures over the Catchment are getting warmer than the maximum temperatures. Seasonally, the minimum temperature warms more frequently in the summer season from December to February (DJF) and the spring season from September to November (SON) than in the winter season from June to August (JJA) and in the autumn season from March to May (MAM). The results of the SPI affirm the persistent drought conditions over the Catchment. In the context of the current global warming, this study provides an insight into the changing characteristics of temperatures and rainfall in a local context. The information in this study can provide policymakers with useful information to help them make informed decisions regarding the Olifants River Catchment and its resources., Competing Interests: The authors have declared that no competing interests exist.

Alterations of abiotic factors (e.g., river water temperature and discharge) will definitely affect the fundamental processes of aquatic ecosystems. The purpose of this study was to examine the impact of climate change on the structure of fish assemblages in fast-flowing rivers belonging to the catchment of the major Eastern European river, the Nemunas. Five catchments of semi-natural rivers were selected for the study. Projections of abiotic factors were developed for the near (2016-2035) and far future (2081-2100) periods, according to four RCP scenarios and three climate models using the HBV hydrological modelling tool. Fish metric projections were developed based on a multiple regression using spatial data. No significant changes in projections of abiotic and biotic variables are generally expected in the near future. In the far future period, the abiotic factors are projected to change significantly, i.e., river water temperature is going to increase by 4.0-5.1 °C, and river discharge is projected to decrease by 16.7-40.6%, according to RCP8.5. By the end of century, the relative abundance of stenothermal fish is projected to decline from 24 to 51% in the reference period to 0-20% under RCP8.5. Eurythermal fish should benefit from climate change, and their abundance is likely to increase from 16 to 38% in the reference period to 38-65% under RCP8.5. Future alterations of river water temperature will have significantly more influence on the abundance of the analysed fish assemblages than river discharge., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Assessing the vulnerability of different sectors to climate change has great importance in determining the appropriate adaptation measures to deal with climate change impacts on a river basin scale. In this research, using a framework for modeling the agronomic system vulnerability to climate change, vulnerability assessment under different scenarios was conducted for the Gorganrud River Basin located in the agro-ecological zone of the Caspian coastal plain of Iran. Considering exposure, susceptibility, and lack of resilience components, 12 indicators were chosen and quantified for both agronomic-environmental and socio-economic aspects. The SSM-iCrop2 model was used to simulate crop yield under current and climate change scenarios across the basin. The analysis indicates that in the current condition, the vulnerability level is different across the watersheds of the Gorganrud River Basin. By applying the climate change scenarios, agronomic system vulnerability would increase in the basin to some extent, particularly in Madarsu and Tilabad watersheds attributed with high vulnerability (0.63 and 0.61, respectively). This justifies the need to implement adaptation plans for encountering water shortage in the future. The analysis also suggests that the vulnerability of the agronomic system for adaptation scenarios characterized by less water consumption under climate change conditions is going to be slightly different from the vulnerability under the climate change scenarios. Due to an increase in agronomic system vulnerability under climate change scenarios, coupled with the fact that most watersheds (except Chehelchai, Nardin, and Narmab) are moderately vulnerable even under current conditions, policymakers and planners should promote crop and livelihood diversification programs aiming to prevent an increase in agronomic vulnerability., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Climate change is predicted to significantly alter hydrological cycles across the world, affecting runoff, streamflow, and pollutant loads from diffuse sources. The objectives of this study were to examine the impacts of climate change on streamflow, total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) loads in the subtropical Logan-Albert catchment, Queensland, Australia. We calibrated the Soil Water Assessment Tool (SWAT) against event monitoring data in the Logan and Albert rivers, respectively. Hydrological and water quality effects of an ensemble of 11 dynamically downscaled high-resolution climate models were assessed with SWAT under high (Representative Concentration Pathway 8.5 - RCP8.5) and intermediate (RCP4.5) emission scenarios. Streamflow decreased most in winter and spring and decreased least in summer. This followed the predicted seasonal changes for precipitation, although decreases tended to be amplified due to increasing evaporative loss. TSS, TN, and TP loads showed a similar pattern to streamflow, with the largest decreases predicted for the dry season under RCP8.5 by the 2080s. Annual TSS load decreased by 34.3 and 54.2%, TN load decreased by 29.8 and 30.5%, and TP load by 24.9 and 4.4% for the Logan and Albert sites, respectively. The results of this study indicate that for subtropical river-estuary systems, climate warming may lead to lower streamflow and contaminant loads, reduced flushing, and greater relative importance of point source loads in urbanising catchments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This study investigates changes in river flow patterns, in the Hunza Basin, Pakistan, attributed to climate change. Given the anticipated rise in extreme weather events, accurate streamflow predictions are increasingly vital. We assess three machine learning (ML) models - artificial neural network (ANN), recurrent neural network (RNN), and adaptive fuzzy neural inference system (ANFIS) - for streamflow prediction under the Coupled Model Intercomparison Project 6 (CMIP6) Shared Socioeconomic Pathways (SSPs), specifically SSP245 and SSP585. Four key performance indicators, mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2 ), guide the evaluation. These models employ monthly precipitation, maximum and minimum temperatures as inputs, and discharge as the output, spanning 1985-2014. The ANN model with a 3-10-1 architecture outperforms RNN and ANFIS, displaying lower MSE, RMSE, MAE, and higher R 2 values for both training (MSE = 20417, RMSE = 142, MAE = 71, R 2 = 0.94) and testing (MSE = 9348, RMSE = 96, MAE = 108, R 2 = 0.92) datasets. Subsequently, the superior ANN model predicts streamflow up to 2100 using SSP245 and SSP585 scenarios. These results underscore the potential of ANN models for robust futuristic streamflow estimation, offering valuable insights for water resource management and planning.

Identifying the individual and combined hydrological response of land use landscape pattern and climate changes is key to effectively managing the ecohydrological balance of regions. However, their nonlinearity, effect size, and multiple causalities limit causal investigations. Therefore, this study aimed to establish a comprehensive methodological framework to quantify changes in the landscape pattern and climate, evaluate trends in streamflow response, and analyze the attribution of streamflow events in five basins in Beijing from the past to the future. Future climate projections were based on three general circulation models (GCMs) under two shared socioeconomic pathways (SSPs). Additionally, the landscape pattern in 2035 under a natural development scenario was simulated by the patch-generating land use simulation (PLUS). The Soil and Water Assessment Tool (SWAT) was applied to evaluate the streamflow spatial and temporal dynamics over the period 2005-2035 with multiple scenarios. A bootstrapping nonlinear regression analysis and boosted regression tree (BRT) model were used to analyze the individual and combined attribution of landscape pattern and climate changes on streamflow, respectively. The results indicated that in the future, the overall streamflow in the Beijing basin would decrease, with a slightly reduced peak streamflow in most basins in the summer and a significant increase in the autumn and winter. The nonlinear quadratic regression more effectively explained the impact of landscape pattern and climate changes on streamflow. The trends in the streamflow change depended on where the relationship curve was in relation to the threshold. In addition, the impacts of landscape pattern and climate changes on streamflow were not isolated but were joint. They presented a nonlinear, non-uniform, and coupled relationship. Except for the YongDing River Basin, the annual streamflow change was influenced more by the landscape pattern. The dominant factors and the critical pair interactions varied from basin to basin. Our findings have implications for city planners and managers for optimizing ecohydrological functions and promoting sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.The financial support was provided by the National Key Research and Development Program of China (No. 2019YFD11004021)., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Climate extremes, such as heat waves, droughts, extreme rainfall can lead to harvest failures, flooding and consequently threaten the food security worldwide. Improving our understanding about climate extremes can mitigate the worst impacts of climate change and extremes. The objective here is to investigate the changes in climate and climate extremes by considering two time slices (i.e., 1962-1990 and 1991-2019) in all climate zones of Pakistan by utilizing observed data from 54 meteorological stations. Different statistical methods and techniques were applied on observed station data to assess changes in temperature, precipitation and spatio-temporal trends of climatic extremes over Pakistan from 1962 to 2019. The Mann-Kendal test demonstrated increasing precipitation (DJF) and decreasing maximum and minimum temperatures (JJA) at the meteorological stations located in the Karakoram region during 1962-1990. The decadal analysis, on the other hand, showed a decrease in precipitation during 1991-2019 and an increase in temperature (maximum and minimum) during 2010-2019, which is consistent with the recently observed slight mass loss of glaciers related to the Karakoram Anomaly. These changes are highly significant at 5% level of significance at most of the stations. In case of temperature extremes, summer days (SU25) increased except in zone 4, TX10p (cold days) decreased across the country during 1962-1990, except for zones 1 and 2. TX90p (warm days) increased between 1991-2019, with the exception of zone 5, and decreased during 1962-1990, with the exception of zones 2 and 5. The spatio-temporal trend of consecutive dry days (CDD) indicated a rising tendency from 1991 to 2019, with the exception of zone 4, which showed a decreasing trend. PRCPTOT (annual total wet-day precipitation), R10 (number of heavy precipitation days), R20 (number of very heavy precipitation days), and R25mm (very heavy precipitation days) increased (decreased) considerably in the North Pakistan during 1962-1990 (1991-2019). The findings of this study can help to address some of the sustainable development goals related climate action, hunger and environment. In addition, the findings can help in developing sustainable adaptation and mitigation strategies against climate change and extremes. As the climate and extremes conditions are not the uniform in all climate zone, therefore, it is suggested to the formers and agriculture department to harvest crops resilient to the climatic condition of each zone. Temperature has increasing trend in the northern Pakistan, therefore, the concerned stakeholders need to make rational plans for higher river flow/flood situation due to snow and glacier melt., Competing Interests: The authors have declared that no competing interests exist.

In many parts of the world, climate change has already caused a decline in groundwater recharge, whereas groundwater demand for drinking water production and irrigation continues to increase. In such regions, groundwater tables are steadily declining with major consequences for groundwater-surface water interactions. Predominantly gaining streams that rely on discharge of groundwater from the adjacent aquifer turn into predominantly losing streams whose water seeps into the underground. This reversal of groundwater-surface water interactions is associated with an increase of low river flows, drying of stream beds, and a switch of lotic ecosystems from perennial to intermittent, with consequences for fluvial and groundwater dependent ecosystems. Moreover, water infiltrating from rivers and streams can carry a complex mix of contaminants. Accordingly, the diversity and concentrations of compounds detected in groundwater has been increasing over the past decades. During low flow, stream and river discharge may consist mainly of treated wastewater. In losing stream systems, this contaminated water seeps into the adjoining aquifers. This threatens both ecosystems as well as drinking and irrigation water quality. Climate change is therefore severely altering landscape water balances, with groundwater-surface water-interactions having reached a tipping point in many cases. Current model projections harbor huge uncertainties and scientific evidence for these tipping points remains very limited. In particular, quantitative data on groundwater-surface water-interactions are scarce both on the local and the catchment scale. The result is poor public or political awareness, and appropriate management measures await implementation., (Copyright © 2022. Published by Elsevier Ltd.)

The Ganges-Brahmaputra-Meghna (GBM) delta is one of the world's largest deltas. It is currently experiencing high rates of relative sea-level rise of about 5 mm/year, reflecting anthropogenic climate change and land subsidence. This is expected to accelerate further through the 21st Century, so there are concerns that the GBM delta will be progressively submerged. In this context, a core question is: can sedimentation on the delta surface maintain its elevation relative to sea level? This research seeks to answer this question by applying a two-dimensional flow and morphological model which is capable of handling dynamic interactions between the river and floodplain systems and simulating floodplain sedimentation under different flow-sediment regimes and anthropogenic interventions. We find that across a range of flood frequencies and adaptation scenarios (including the natural polder-free state), the retained volume of sediment varies between 22% and 50% of the corresponding sediment input. This translates to average rates of sedimentation on the delta surface of 5.5 mm/yr to 7.5 mm/yr. Hence, under present conditions, sedimentation associated with quasi-natural conditions can exceed current rates of relative sea-level rise and potentially create new land mass. These findings highlight that encouraging quasi-natural conditions through the widespread application of active sediment management measures has the potential to promote more sustainable outcomes for the GBM delta. Practical measures to promote include tidal river management, and appropriate combinations of cross-dams, bandal-like structures, and dredging., Competing Interests: Declaration of competing interest There is no conflict of interest among the authors., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Monitoring and assessing ecological quality (EQ) can help to understand the status and dynamics of the local ecosystem. Moreover, land use and climate change increase uncertainty in the ecosystem. The Luanhe River Basin (LHRB) is critical to the ecological security of the Beijing-Tianjin-Hebei region. To support ecosystem protection in the LHRB, we evaluated the EQ from 2001 to 2020 based on the Remote Sensing Ecological Index (RSEI) with the Google Earth Engine (GEE). Then, we introduced the coefficient of variation, Theil-Sen analysis, and Mann-Kendall test to quantify the variation and trend of the EQ. The results showed that the EQ in LHRB was relatively good, with 61.08% of the basin rated as 'good' or 'excellent'. The spatial distribution of EQ was low in the north and high in the middle, with strong improvement in the north and serious degradation in the south. The average EQ ranged from 0.58 to 0.64, showing a significant increasing trend. Furthermore, we found that the expansion of construction land has caused degradation of the EQ, whereas climate change likely improved the EQ in the upper and middle reaches of the LHRB. The results could help in understanding the state and trend of the eco-environment in the LHRB and support decision-making in land-use management and climate change.

The impact of climate change on the oxygen saturation content of the world's surface waters is a significant topic for future water quality in a warming environment. While increasing river water temperatures (RWTs) with climate change signals have been the subject of several recent research, how climate change affects Dissolved Oxygen (DO) saturation levels have not been intensively studied. This study examined the direct effect of rising RWTs on saturated DO concentrations. For this, a hybrid deep learning model using Long Short-Term Memory integrated with k-nearest neighbor bootstrap resampling algorithm is developed for RWT prediction addressing sparse spatiotemporal RWT data for seven major polluted river catchments of India at a monthly scale. The summer RWT increase for Tunga-Bhadra, Sabarmati, Musi, Ganga, and Narmada basins are predicted as 3.1, 3.8, 5.8, 7.3, 7.8 °C, respectively, for 2071-2100 with ensemble of NASA Earth Exchange Global Daily Downscaled Projections of air temperature with Representative Concentration Pathway 8.5 scenario. The RWT increases up to7 °C for summer, reaching close to 35 °C, and decreases DO saturation capacity by 2-12% for 2071-2100. Overall, for every 1 °C RWT increase, there will be about 2.3% decrease in DO saturation level concentrations over Indian catchments under climate signals., (© 2022. The Author(s).)

Quantitatively, analyzing the driving mechanism of vegetation coverage change is of important significance for regional ecological environment evaluation and protection. Based on time series NDVI data and meteorological data of the Yellow River Basin (Inner Mongolia Section), the trend and significance of climate factors and vegetation coverage in the YRB (IMS) and four sub-regions (the Hetao Irrigation district, the Ten Tributaries region, the Hunhe river basin, and the Dahei river basin) from 2000 to 2018 were ascertained. We used geographic detectors to quantitatively analyze the effects of detection factors on vegetation coverage change. The results indicated that the spatial pattern of vegetation variation and climate change had obvious spatial heterogeneity. During 2000-2018, the regions with vegetation improvement (72.87%) were much greater than that with degradation (26.55%) in the YRB (IMS). Annual precipitation change (4.55%) was a key driving factor to the vegetation coverage change in the YRB (IMS). Among the four sub-regions, the land use conversion type demonstrated the largest explanatory power, but the q values of the four sub-regions were different from each other. The results of the interaction showed that land use change and annual precipitation change were the major driving factors that influenced regional vegetation coverage change. This study has an important reference value for improving the basin's ecological environment., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study assesses present-day extreme climate changes over China by using a set of phase 6 of the Coupled Model Intercomparison Project (CMIP6) statistical downscaled data and raw models outputs. The downscaled data is produced by the adapted spatial disaggregation and equal distance cumulative distribution function (EDCDF) method at the resolution of 0.25° × 0.25° for the present day (1961-2014) and the future period (2015-2100) under the Shared Socioeconomic Path-way (SSP) 2-4.5 than SSP5-8.5 emission scenario. The results show that the downscaling method improves the spatial distributions of extreme climate events in China with higher spatial pattern correlations, Taylor Skill Scores and closer magnitudes no matter single model or multi model ensemble (MME). In the future projections, large inter-model variability between the downscaled models still exists, particular for maximum consecutive 5-day precipitation (RX5). The downscaled MME projects that total precipitation (PTOT) and RX5, will increase with time, especially for the northwest China. The projected heavy precipitation days (R20) also increase in the future. The region of significant increase in R20 locates in the south of river Yangtze. Maxi-mum annual temperature (TXX) and percentage of warm days (TX90p) are projected to increase across the whole country with larger magnitude over the west China. Projected changes of minimum annual temperature (TNN) over the northeastern China is the most significant area. The higher of the emission scenario, the more significant of extreme climates. This reveals that the spatial distribution of extreme climate events will become more uneven in the future.

The normalized difference vegetation index (NDVI) is a useful indicator to characterize vegetation development and land use which can effectively monitor changes in ecological environments. As an important area for ecological balance and safety in China, understanding the dynamic changes in land cover and vegetation of the Yangtze River Basin would be crucial in developing effective policies and strategies to protect its natural environment while promoting sustainable growth. Based on MODIS-NDVI data and meteorological data from 2000 to 2019, the temporal and spatial distribution of vegetation coverage in the Yangtze River Basin during the past 20 years were characterized, and the impacts of human activities and climate change were quantitatively evaluated. We drew the following research conclusions: (1) From 2000 to 2019, the vegetation cover of the Yangtze River Basin presented a fluctuating inter-annual growth trend. Except for the Taihu Lake sub-basin, the vegetation cover in other sub-basins showed an upward trend. (2) The vegetation cover exhibited a spatial distribution pattern of "high in the middle and low in the east and west", with the multi-year average value of NDVI being 0.5153. (3) Areas with improved vegetation cover were significantly larger than the areas with degraded foliage. The central region has stronger overall trend of change than the east, and the east is stronger than the west. These vegetation cover changes are largely related to anthropogenic activities. (4) Vegetation cover changes due to precipitation and temperature exhibited significant spatial heterogeneity. While both temperature and precipitation influenced vegetation cover, the temperature was the leading climate factor in the area. (5) Anthropogenic and climate factors jointly promoted the change of vegetation cover in the Yangtze River Basin. Human activities contributed 79.29%, while climate change contributed 20.71%. This study could be used in subsequent studies analyzing the influencing factors affecting long-term vegetation cover in large-scale watersheds.

The critical significance of keeping the current information about the extent and dynamics of the cryosphere in the Himalayas cannot be understated. The climate of the Himalayas is vulnerable and interlinked with global-scale climate changes, and the hydrology of the region mainly depends on the cryosphere. This is the first study that has created glacier and glacier lake inventory that links the impact of cryosphere on streamflow to land system dynamic changes under the changing climate of the Upper Jhelum River Basin (UJRB) of the Kashmir Himalayan region. This study uses a series of satellite data (1980-2016) to assess the depletion of snow cover area (SCA), deglaciation, and dynamics of glacial lakes. Moreover, observational long-term hydrometeorological data were used to understand the variability in temperature, precipitation, and track changes of land system dynamics under depletion of streamflow. The results suggested an overall rise in temperature (T Max  = 0.05 ºC a -1 ; T Min  = 0.02 ºC a -1 ; T avg  = 0.06 ºC a -1 ) and a decrease in precipitation (2.9 mm a -1 ) between 1980 and 2016 with a significant increase in annual average temperature and decrease in annual precipitation at stations located at higher altitudes. The SCA showed a significantly decreasing (p < 0.01) trend in the glacierized sub-basins with an annual rate of decrease of -0.78% a -1 , -0.15% a -1 , -0.03% a -1 -0.90% a -1 for Lidder, Sindh, Vishow, and Rambiara sub-basins, respectively. The findings of this study reveal the high occurrence of glacier disintegration and deglaciation. During the period 2010-2016, a rapid rate of deglaciation was observed (18.34 ± 0.14 km 2 ), followed by 1992-2000 (15.61 ± 0.13 km 2 ). The average rate of retreat was observed to be 6.81 ± 1.5 m a -1 with a total retreat of 267 ± 80 m during 1980-2016, which is higher than reported from surrounding mountain ranges in the Himalayas. The mapped 244 glacial and high-altitude lake inventory covers a total surface area of around 15 km 2 , with 5.87 km 2 (40%) covered by 25 bedrock-dammed lakes. The glacial expansion and creation of new lakes are observed to be because of increasing glacier and snow melting between 1980 and 2016, which increases the risk of GLOF events in the future. The annual average discharge in UJRB significantly increased from 1991 to 1998 and was observed to be higher than the annual average of the respected gauge stations but shows significant depletion from 1998 onwards. The streamflow depletion under climate change is one of the reasons for land system dynamics in UJRB. The area under agriculture has decreased up to 63% with a massive expansion of built-up (399%), aquatic vegetation (523%), and plantation (765%) between 1992 and 2015., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

We employ the approach of Roderick and Farquhar (2011) to assess the sensitivity of runoff (R) given changes in precipitation (P), potential evapotranspiration (E p ), and other properties that change the partitioning of P (n) by estimating coefficients that predict the weight of each variable in the relative change of R. We use this framework using different data sources and products for P, actual evapotranspiration (E), and E p within the Amazon River basin to quantify the uncertainty of the hydrologic response at the subcatchment scale. We show that when estimating results from the different combinations of datasets for the entire river basin (at Óbidos), a 10% increase in P would increase R on average 16%, while a 10% increase in E p would decrease R about 6%. In addition, a 10% change in the parameter n would affect the hydrological response of the entire basin around 5%. However, results change from catchment to catchment and are dependent on the combination of datasets. Finally, results suggest that enhanced estimates of E and E p are needed to improve our understanding of the future scenarios of hydrological sensitivity with implications for the quantification of climate change impacts at the regional (subcatchment and subbasin) scale in Amazonia., (© 2020 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences.)

Due to the combined effects of global warming and human activities, the ecological environment of the Yellow River source area has undergone profound changes and desertification has become increasingly prominent. In this study, an optimal desertification monitoring index based on feature space was proposed for the Yellow River source area, and constructed using Landsat images. Then, the spatial and temporal variation of desertification in the Yellow River source area and its driving mechanism were studied using Geodetector. The main conclusions are as follows: (1) The newly proposed feature space-based desertification monitoring index has good applicability in the study area. The best inversion accuracy of the point-to-point Albedo-NDVI feature space model was 88.4%. (2) Desertification in the eastern and southern regions of the Yellow River source area has a tendency to increase, while the desertification situation in the central region is relatively stable. (3) From 1995 to 2015, there was a significant improvement in desertification in the study area, as evidenced by a decrease in desertification intensity. (4) As the intensity of human disturbance increases, the influence of natural factors on desertification gradually diminishes. The interaction of natural and anthropogenic factors has greater explanatory power for desertification than that of individual natural or anthropogenic factors. The research results can be used as a reference for decision-making on desertification control in the Three-River Source Region., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Bing Guo reports writing assistance was provided by Chinese Academy of Sciences. Bing Guo reports a relationship with Chinese Academy of Sciences that includes: non-financial support. Bing Guo has patent pending to licensee., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Climatic and hydrological changes of the scarcely gauged mountainous basins remain a challenge to study due to unavailability of observed data. The recent study aims to assess these changes using spatial decision tool statistical downscaling method (SDSM) and snowmelt runoff model (SRM) for the twenty-first century under representative concentration pathways (RCPs). SDSM considered absolute partial correlation coefficient (abs. Pr.) to evaluate efficiency predictors or the predictands of the Jhelum river basin. The performance evaluation of SDSM assessed using coefficient of determination (R 2 ) values for RCP 4.5 and RCP 8.5 under CMIP5 (CCSM4). The biases of the daily time series downscaled data removed by using mean-based biased correction method (MB-BC). Stream projection carried out using SRM by incorporating MODIS snow product. Statistical parameters R 2 and volume difference (Dv %) calculated for accuracy assessment of SRM for the simulated and observed discharge (2001-2018). Streamflow projections for the twenty-first century carried out by SRM using de-biased downscaled data. The R 2 indicator of SDSM ranged between 78-81% for temperature and 82-86% for precipitation under RCP 4.5 and RCP 8.5, respectively. The temperature results indicated an increasing trend of 1.5 o C and 3.8 o C for the twenty-first century under RCP 4.5 and RCP 8.5, respectively. The mean annual precipitation showed a rise of 2-7% while surface runoff projected a rising trend of 3.3-7.4% for RCP-4.5 and RCP-8.5 respectively till the end of the twenty-first century. The study results revealed that Jhelum basin will be wetter and warmer for the twenty-first century as compare to the baseline period. The hydrographs of the river predicted the occurrence of more extreme events in the region for the twenty-first century. These hydrographs may help for better water conservation and management strategies in the Jhelum basin for the twenty-first century., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper presents a new framework for evaluating the sustainability of basin-wide ecosystem services (ESs) including provisioning, regulating, supporting, and cultural services. In this framework, the Soil and Water Assessment Tool (SWAT) and MODSIM 1 models and experts' opinions are used to evaluate the ESs. To show the applicability of the proposed framework, it is applied to the Zarrinehrud river basin under three different climate change (CC) scenarios (i.e., RCP 4.5, 6.0, and 8.5) for two different time horizons (i.e., 2020-2049 and 2020-2098). This basin is the main water supplier of the largest hypersaline lake in the Middle East, Lake Urmia. In the next step, 128 water resources management (WRM) scenarios are taken into account considering the projects defined by Urmia Lake Restoration National Committee (ULRNC). All ecosystem services are evaluated considering all WRM and CC scenarios. Finally, a group COPRAS-based decision-making approach is used to determine the best WRM scenario under climate change. The results show that WRM scenario 128 is the best scenario for improving ecosystem services in the study area. This scenario includes some projects such as allocating water to the lake from new resources, rehabilitating irrigation and draining networks, and improving cropping patterns., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Erosion is a main form of soil degradation, with severe consequences on slope stability and productivity, and erosion studies are required to predict possible variations of such phenomena, also under climate change scenarios. Here we estimated distributed soil erosion within Valchiavenna valley in the Rhaetian Alps, drained by Mera river, and covering Italy, and Switzerland. We used a Dynamic-RUSLE (D-RUSLE) model, which provides spatially distributed estimates of soil erosion explicitly considering snow dynamic (accumulation/melting) and snow cover, and vegetation seasonality. The model was tuned here during 2010-2019, and validation was pursued using river turbidity data, used to assess riverine sediment transport. The model parameter R-factor for rainfall erosivity was estimated using a hydrological model Poli-Hydro, properly set up in the study area. C-factor for land cover was assessed against land cover maps, with seasonally variable Normalized Difference Vegetation Index from satellite images, to account for variable vegetation stage, and large leaf cover in summer. The K-factor related to erosion susceptibility was evaluated through soil texture and organic content. LS-factor depending on slope was assessed using a DTM. Poli-Hydro and D-RUSLE models were then used to project forward potential soil erosion under climate change scenarios until 2100. Climate series (temperature, precipitation) were generated using 4 shared socio-economic pathways (SSPs) of the Sixth Assessment Report of the IPCC, with 3 global circulation models, properly downscaled locally. We analysed expected soil erosion during 2051-2060, and 2091-2100. We found increase of potential soil erosion, with exception of the EC-Earth model for the SSP2.6. Erosion would especially increase in winter, in response to smaller snow accumulation, and larger liquid rainfall share thereby, and decrease in summer, as due to decreased precipitation. Our results suggest the need for adaptation strategies to counteract increasing soil loss in the future, and may highlight most critical areas of intervention., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

To understand the spatiotemporal changes of flood risk, we need to determine the way in which humans adapt and respond to flood events. One adaptation option consists of resettling away from flood-prone areas to prevent or reduce future losses. We use satellite nighttime light data to discern the relationship between long-term changes in human proximity to rivers and the occurrence of catastrophic flood events. Moreover, we explore how these relationships are influenced by different levels of structural flood protection. We found that societies with low protection levels tend to resettle further away from the river after damaging flood events. Conversely, societies with high protection levels show no significant changes in human proximity to rivers. Instead, such societies continue to rely heavily on structural measures, reinforcing flood protection and quickly resettling in flood-prone areas after a flooding event. Our work reveals interesting aspects of human adaptation to flood risk and offers key insights for comparing different risk reduction strategies. In addition, this study provides a framework that can be used to further investigate human response to floods, which is relevant as urbanization of floodplains continues and puts more people and economic assets at risk.

The effects of climate change on oligotrophic rivers and their communities are almost unknown, albeit these ecosystems are the primary habitat of the critically endangered freshwater pearl mussel and its host fishes, salmonids. The distribution and abundance of pearl mussels have drastically decreased throughout Europe over the last century, particularly within the southern part of the range, but causes of this wide-scale extinction process are unclear. Here we estimate the effects of climate change on pearl mussels based on historical and recent samples from 50 rivers and 6 countries across Europe. We found that the shell convexity may be considered an indicator of the thermal effects on pearl mussel populations under warming climate because it reflects shifts in summer temperatures and is significantly different in viable and declining populations. Spatial and temporal modeling of the relationship between shell convexity and population status show that global climate change could have accelerated the population decline of pearl mussels over the last 100 years through rapidly decreasing suitable distribution areas. Simulation predicts future warming-induced range reduction, particularly in southern regions. These results highlight the importance of large-scale studies of keystone species, which can underscore the hidden effects of climate warming on freshwater ecosystems.

We provide an assessment of thermal characteristics and climate change vulnerability for brook trout (Salvelinus fontinalis) habitats in the upper Shavers Fork sub-watershed, West Virginia. Spatial and temporal (2001-2015) variability in observed summer (6/1-8/31) stream temperatures was quantified in 23 (9 tributary, 14 main-stem) reaches. We developed a mixed effects model to predict site-specific mean daily stream temperature from air temperature and discharge and coupled this model with a hydrologic model to predict future (2016-2100) changes in stream temperature under low (RCP 4.5) and high (RCP 8.5) emissions scenarios. Observed mean daily stream temperature exceeded the 21°C brook trout physiological threshold in all but one main-stem site, and 3 sites exceeded proposed thermal limits for either 63- and 7-day mean stream temperature. We modeled mean daily stream temperature with a high degree of certainty (R 2 =0.93; RMSE=0.76°C). Predicted increases in mean daily stream temperature in main-stem and tributary reaches ranged from 0.2°C (RCP 4.5) to 1.2°C (RCP 8.5). Between 2091 and 2100, the average number of days with mean daily stream temperature>21°C increased within main-stem sites under the RCP 4.5 (0-1.2days) and 8.5 (0-13) scenarios; however, no site is expected to exceed 63- or 7-day thermal limits. During the warmest 10years, ≥5 main-stem sites exceeded the 63- or 7-day thermal tolerance limits under both climate emissions scenarios. Years with the greatest increases in stream temperature were characterized by low mean daily discharge. Main-stem reaches below major tributaries never exceed thermal limits, despite neighboring reaches having among the highest observed and predicted stream temperatures. Persistence of thermal refugia within upper Shavers Fork would enable persistence of metapopulation structure and life history processes. However, this will only be possible if projected increases in discharge are realized and offset expected increases in air temperature., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

In order to explore the characteristics of climate change in the future in the West Liao River Basin under the background of future climate change, this study analyzed the changes of the annual average temperature, annual precipitation, and annual evapotranspiration from 2021 to 2060 in the West Liao River Basin under the scenarios of RCP4.5 (low emission) and RCP8.5 (high emission) originated from Intergovernmental Panel on Climate Change's Fifth Assessment Report. The results show that (1) under the two different scenarios (RCP4.5 and RCP8.5), the annual average temperature in the West Liao River Basin is 7.67 °C and 8.12 °C, respectively, and the temperature shows an upward trend; the mutation years of RCP4.5 are more than those of RCP8.5; the annual average temperature of RCP4.5 is controlled by periods of 22 years and 29 years, while RCP8.5 has only one main period of 29 years; the contribution rates of the first eigenvector variance of EOF are 97.12% and 96.64%, respectively, and the change types are the same. The sensitive areas of variation are in the southwest and western regions respectively. (2) The annual precipitation in the West Liao River Basin under the two scenarios are 815.78mm and 798.64mm, with tendency rates of -20.51/mm/10a and 17.26/mm/10a; the mutation years in the West Liao River Basin under scenario RCP4.5 are mostly occurred in the 2030s and 2040s, while those under scenario RCP8.5 are mostly occurred in 2040s and 2050s; under scenario RCP4.5, the change is mainly controlled by shorter periods, while under scenario RCP8.5, the change is controlled by two main longer periods of 19 years and 28 years. Under the two scenarios of RCP4.5 and RCP8.5, the cumulative contribution rates of the variance of the first three eigenvectors of the EOF in the West Liao River Basin are 42% and 90.23% respectively. The first eigenvector is consistent, and the second and third eigenvectors are the reverse type of South (East)-North (West). (3) The results show that the annual evapotranspiration in the West Liao River Basin under the scenarios of RCP4.5 and RCP8.5 is 597.79mm and 618.45mm, respectively, and the trend rates are 18.20/mm/10a and 4.48/mm/10a; under scenario RCP4.5, the change is controlled by periods of 23 years and 29 years, while under scenarios RCP8.5, the change is controlled by periods of 18 years and 28 years; the contribution rates of the first eigenvector variance of EOF are 91.05% and 89.51% respectively, and they are consistent distribution, and their sensitive areas are in the southeast and central regions respectively., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The occurrence and severity of extreme precipitation events have been increasing globally. Although numerous projections have been proposed and developed for evaluating the climate change impacts, most models suffer from significant bias error due to the coarse resolution of the climate datasets, which affects the accuracy of the climate change assessment. Therefore, in this study, post-processing techniques (interpolation and bias correction methods) were adopted on the database for Policy Decision Making for Future Climate Change (d4PDF) model for extreme climatic flood events simulation in the Chao Phraya River Basin, Thailand, under + 4-K future climate simulation. Due to the limited number of the rain gages, the gradient plus inverse distance squared interpolation method (combination of multiple linear regression and distance weighting methods) was applied in this study. In the bias correction methods, the additional setting of monthly and seasonal periods was adjusted. The proposed bias correction approach deployed gamma distribution combined with generalized Pareto distribution setting with the seasonal period for the rainy season datasets, whereas only the gamma setting was applied with the monthly period during the dry season. The outcomes revealed that the proposed method could react to extreme rainfall events, expand dry days during dry season, and intensify rainfall amount during rainy season. The post-processing d4PDF trends of six sea surface temperature (SST) patterns (consists of 90 ensemble members) of two periods (near future: 2051-2070 and far future: 2091-2110) recorded the highest and lowest amounts of annual rainfalls of 4,450 mm/year in mid-stream of Nan River and 710 mm/year in the lower CPRB, respectively. Notably, the significant variances noted in the rainfall patterns among ensembles, demanding further investigation in future climate change, impact studies. The findings of the study provided novel insights on the importance of proper post-processing techniques for improving the robustness of d4PDF in climate change impacts assessment., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

While an array of ecological mechanisms has been shown to stabilize natural community dynamics, how the effectiveness of these mechanisms-including both their direction (stabilizing vs. destabilizing) and strength-shifts under a changing climate remains unknown. Using a 35-y dataset (1985 to 2019) from a desert stream in central Arizona (USA), we found that as annual mean air temperature rose 1°C and annual mean precipitation reduced by 40% over the last two decades, macroinvertebrate communities experienced dramatic changes, from relatively stable states during the first 15 y of this study to wildly fluctuating states highly sensitive to climate variability in the last 10 y. Asynchronous species responses to climatic variability, the primary mechanism historically undergirding community stability, greatly weakened. The emerging climate regime-specifically, concurrent warming and prolonged multiyear drought-resulted in community-wide synchronous responses and reduced taxa richness. Diversity loss and new establishment of competitors reorganized species interactions. Unlike manipulative experiments that often suggest stabilizing roles of species interactions, we found that reorganized species interactions switched from stabilizing to destabilizing influences, further amplifying community fluctuations. Our study provides evidence of climate change-induced modifications of mechanisms underpinning long-term community stability, resulting in an overall destabilizing effect.

Forecasting long-term consequences of global warming requires knowledge on thermal mortality and how heat stress interacts with other environmental stressors on different timescales. Here, we describe a flexible analytical framework to forecast mortality risks by combining laboratory measurements on tolerance and field temperature records. Our framework incorporates physiological acclimation effects, temporal scale differences and the ecological reality of fluctuations in temperature, and other factors such as oxygen. As a proof of concept, we investigated the heat tolerance of amphipods Dikerogammarus villosus and Echinogammarus trichiatus in the river Waal, the Netherlands. These organisms were acclimated to different temperatures and oxygen levels. By integrating experimental data with high-resolution field data, we derived the daily heat mortality probabilities for each species under different oxygen levels, considering current temperatures as well as 1 and 2°C warming scenarios. By expressing heat stress as a mortality probability rather than a upper critical temperature, these can be used to calculate cumulative annual mortality, allowing the scaling up from individuals to populations. Our findings indicate a substantial increase in annual mortality over the coming decades, driven by projected increases in summer temperatures. Thermal acclimation and adequate oxygenation improved heat tolerance and their effects were magnified on longer timescales. Consequently, acclimation effects appear to be more effective than previously recognized and crucial for persistence under current temperatures. However, even in the best-case scenario, mortality of D. villosus is expected to approach 100% by 2100, while E. trichiatus appears to be less vulnerable with mortality increasing to 60%. Similarly, mortality risks vary spatially: In southern, warmer rivers, riverine animals will need to shift from the main channel toward the cooler head waters to avoid thermal mortality. Overall, this framework generates high-resolution forecasts on how rising temperatures, in combination with other environmental stressors such as hypoxia, impact ecological communities., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Climate change is a global phenomenon that directly affects agriculture by altering crop yield, nutritional quality, pests, and plant diseases. The North Aegean Basin located in Turkey has considerable agricultural importance due to its fertile soils. Agricultural activities have increased significantly and uncontrollably in the last decade, resulting in dramatic changes in nitrate and phosphorus levels in surface water within the watershed. Changes in climatic conditions have the potential to impact the quantity and quality of water resources. Best management practices (BMPs) are presently utilized as a planning tool to enhance the quality of water resources. To develop policies in this regard, it is necessary to evaluate the effectiveness of BMPs. To this end, this study aims to investigate the potential effect of climate change on the surface water quality of the North Aegean Basin. For the period between 2010 and 2030, global climate data retrieved from Concentration Pathway (RCP) scenarios 4.5 and 8.5 and regionally downscaled were used to feed the Soil and Water Assessment Tool (SWAT) model. The various potential BMP scenarios were developed and simulated in the hydrological model by considering the effects of climate change. The RCP4.5 scenario reduced the precipitation by 15.11%, while the RCP8.5 scenario reduced the precipitation by 10.97%. Decreased precipitation also affected the runoff and the nutrient loads and concentrations. As a result of the RCP4.5 simulation, TP and TN concentrations increased by 24.42% and 58.45%, respectively, in the IST&#95;KEN014 station. Improvements were observed in TN and TP concentrations with the effect of applied BMP simulations. Also, the results revealed that the applied BMP scenarios may contribute to considerable reductions in nutrient loads. Considering the RCP4.5 scenario, BMPs reduced TN loads in the basin by 2.42-10.97%, while reducing TP loads by around 3.60-16.81%. Considering the RCP8.5 scenario, the BMPs reduced the TN loads in the basin between 2.21 and 10.04%, while they reduced the TP loads between 3.57 and 16.67%., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aimed to explore the long-term vegetation cover change and its driving factors in the typical watershed of the Yellow River Basin. This research was based on the Google Earth Engine (GEE), a remote sensing cloud platform, and used the Landsat surface reflectance datasets and the Pearson correlation method to analyze the vegetation conditions in the areas above Xianyang on the Wei River and above Zhangjiashan on the Jing River. Random forest and decision tree models were used to analyze the effects of various climatic factors (precipitation, temperature, soil moisture, evapotranspiration, and drought index) on NDVI (normalized difference vegetation index). Then, based on the residual analysis method, the effects of human activities on NDVI were explored. The results showed that: (1) From 1987 to 2018, the NDVI of the two watersheds showed an increasing trend; in particular, after 2008, the average increase rate of NDVI in the growing season (April to September) increased from 0.0032/a and 0.003/a in the base period (1987-2008) to 0.0172/a and 0.01/a in the measurement period (2008-2018), for the Wei and Jing basins, respectively. In addition, the NDVI significantly increased from 21.78% and 31.32% in the baseline period (1987-2008) to 83.76% and 92.40% in the measurement period (2008-2018), respectively. (2) The random forest and classification and regression tree model (CART) can assess the contribution and sensitivity of various climate factors to NDVI. Precipitation, soil moisture, and temperature were found to be the three main factors that affect the NDVI of the study area, and their contributions were 37.05%, 26.42%, and 15.72%, respectively. The changes in precipitation and soil moisture in the entire Jing River Basin and the upper and middle reaches of the Wei River above Xianyang caused significant changes in NDVI. Furthermore, changes in precipitation and temperature led to significant changes in NDVI in the lower reaches of the Wei River. (3) The impact of human activities in the Wei and Jing basins on NDVI has gradually changed from negative to positive, which is mainly due to the implementation of soil and water conservation measures. The proportions of areas with positive effects of human activities were 80.88% and 81.95%, of which the proportions of areas with significant positive effects were 11.63% and 7.76%, respectively. These are mainly distributed in the upper reaches of the Wei River and the western and eastern regions of the Jing River. These areas are the key areas where soil and water conservation measures have been implemented in recent years, and the corresponding land use has transformed from cultivated land to forest and grassland. The negative effects accounted for 1.66% and 0.10% of the area, respectively, and were mainly caused by urban expansion and coal mining.

Differentiating and clarifying the driving factors behind streamflow changes are critical for highlighting hydrological responses to changing environments. However, due to the limited number of hydrological stations, the dominant factor controlling global observed streamflow change remains unclear and intensely debated. Here, we revisit this scientific issue by using the most comprehensive dataset to attribute the observed global streamflow changes during 1960-2014. The results suggest that other factors than precipitation (P) and potential evaporation (E 0 ) are the most important contributors to global observed streamflow changes, which dominate streamflow change for 48.9-50.9% of the stations. In contrast, the dominant factor translated into P in 72.3-72.9% of stations when using reconstructed streamflow datasets, in agreement with most previous global assessments. These differences indicate that streamflow attributions using reconstructed streamflow might overestimate the effects of P while underestimating the roles of other factors, such as the vegetation and human impact. At the global scale, the other factors affected by many catchment characteristics and their impacts on streamflow change have remarkable regional differences. This study highlights the necessity to apply the observed data in streamflow attribution to avoid biased conclusions regarding the dominant factor of streamflow changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In the present study, hydro-meteorological variables of Chitral Basin in Hindukush region of Pakistan were studied to predict the changes in climatic components such as temperature, precipitation, humidity and river flow based on observed data from 1990 to 2019. Uncertainties in climate change projection were studied using various statistical methods, such as trend variability analysis via stationarity test and validation of regression assumptions prior to fitting of regression estimates. Also, multiple regression models were estimated for each hydro-meteorological variables for the given 30 years of observed data. Results demonstrated that temperature and, precipitation were inversely related with one another. It was observed from the regression model that temperature is decreases by 0.309 °C on the average increases in precipitation by one unit. Temperature also decreases for the increase in humidity by average 0.086 °C. Since, precipitation is negatively related with temperature, thus for increases in temperature the annual precipitation decreases by 0.278 mm annually. Humidity on the other hand, increases by 0.207% by increasing in precipitation and the temperature that causes humidity to decrease by 0.99%. Thus, it demonstrated that the flow in Chitral river increases due to precipitation by 0.306 m 3 /s for the change in precipitation by one unit. Findings from the present study negated the general perceptions that flow in the Chitral river has increased due to recession of glaciers with increase in the intensity of temperature., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The projections of mean temperature, precipitation (P), and potential evapotranspiration (PET) reflect the probabilities of long-term changes of hydrologic processes and induced extreme events. In this paper, we investigated the future changes in some pivotal climatic variables (mean temperature, precipitation, and potential evapotranspiration) under 1.5 °C, 2.0 °C, and 3.0 °C specific warming levels (SWLs) across the Indus River Basin of South Asia. The seven global climate models output under seven different emission scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from the latest Sixth phase of Coupled Model Intercomparison Project (CMIP6) are used for this purpose. The Penman-Monteith approach is applied to estimate PET, and the water balance equation is for reflecting water surplus/deficit. Results indicate that except for precipitation, the greater increases in temperature and PET are inclined to happen with continued global warming. The highest increase in temperature is accounted for 14.6% (2.4 °C), and the enhanced PET is estimated at 5.2% higher than the reference period (1995-2014) under 3.0 °C SWL. While the precipitation is projected to increase by the highest 4.8% for 2.0 °C warming level. The differences in regional climate for an additional 0.5 °C (2.0-1.5 °C) and 1.0 °C (3.0-2.0 °C) of warming, the temperature is projected to increase by 0.4 °C and 0.9 °C in the entire IRB respectively. The highest increase in mean temperature (5.1%) and PET (2.4%) in the IRB are predicted to intensify for an additional 1.0 °C than that of 0.5 °C of warming, but precipitation is intended to decrease by 0.4%. Spatially, the increase in temperature, precipitation, and PET are dominated towards high elevation in the upper basin (north) under all the SWLs. The increased variability in climatological parameters across IRB depicts an evident occurrence of both wet events (upper basin) as well as dry events (lower basin) with the increase in global average temperature rise. However, these findings provide an insightful basis for water resource management as well as initiating mitigation and adaptation measures in the IRB related to water surplus (floods) and water deficit (droughts)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Climate change is modifying the hydrological and thermal regimes of rivers worldwide, threatening the triggering of organisms' key life-cycle processes. European eel (Anguilla anguilla) is a critically endangered fish species that migrates over several thousand kilometres between its rearing habitats in continental waters of Europe and North Africa and its spawning area in the Sargasso Sea. Downstream migration of adult eels occurs during periods of decreasing river water temperature associated with high discharge but changes in these environmental cues may affected eel migratory conditions. An innovative multivariate method was developed to analyse long-term datasets of daily water temperature, discharge and eel passage in two European rivers. Over the past 50 years, water temperature and discharge increased in both rivers during the downstream migration period from August to November. Silver eels preferentially migrated at temperatures between 10 and 20 °C combined with high discharge. Environmental changes have resulted in the migration of silver eels under warmer water temperatures. This example illustrates how the changes in environmental cues have led to a growing mismatch between the migratory conditions preferentially selected and those actually used, which may threaten the completion of the eel's life cycle and ultimately the persistence of this already critically endangered species., (© 2021. The Author(s).)