Large increase in global storm runoff extremes driven by climate and anthropogenic changes

Stress in the City: Disentangling multi-stressor effects on an urbanized coral in a changing ocean

Reducing the negative impacts of global change on organismal physiology is a critical area of scientific investigation in the Anthropocene. Marine coastal ecosystems that exist downstream from urban centers are often subjected to excess nutrients, pathogens, and chemicals via runoff, which can harm organismal function, and may interact with climate change stress. To simultaneously investigate the individual and combined effects of locally-mediated (nutrient, bacterial) and globally-mediated (temperature) stressors on coral physiology, we conducted a multi-factor experiment utilizing the temperate, urban coral Astrangia poculata. Corals were incubated for 12 days with two levels of field-relevant nitrate concentrations at ambient (20 °C) and elevated (29 °C) temperatures, under fed or starved conditions. After 12 days, corals were challenged with an acute 4-h exposure to Escherichia coli, a known urban pathogen for A. poculata. Results show that the physiological impacts of E. coli exposure, nitrate, elevated temperatures, and starvation were interactive and nuanced. Elevated temperatures had the largest single factor impact, resulting in metabolic lethargy regardless of pathogen exposure, nitrate enrichment, or food level. However, corals under the combination of E. coli exposure, elevated nitrate, starvation, and high temperatures demonstrated metabolic hyperactivity, indicating energetic investment by hyper stressed corals in response to the pathogen. With this work, we move beyond pairwise interactions to demonstrate that the interactive effects of combined stressors may offer the key (and more realistic) answer to the fundamental question "How resilient will marine organisms be to locally-mediated stressors in an era of global change?"

Prediction of natural runoff in China based on multi-scenario climate models with self-attention neural networks

Climate change is increasingly affecting the global water cycle. Developing high-quality climate-runoff relationship models can help assess its impact on surface natural runoff, thereby enhancing resilience to water resource risks. This study extends the applicability paradigm of self-attention mechanisms to non-sequential hydrological modeling by developing a Self-Attention Artificial Neural Network (SAANN), which quantifies climate change impacts on China's natural runoff. The model was trained with climate, underlying surface, and natural runoff data from China (2000-2018), utilizing Bayesian optimization for hyperparameter tuning. Compared to the ANN, SAANN's mean square error (MSE) in the test set is reduced by 26.9 %, demonstrating its superior prediction performance. SAANN visualizes the attention relationships between input variables in the model's attention layer, highlighting key correlations similar to physical model principles. This improves both model interpretability and output reliability. Based on the methodology developed above, the study predicts natural runoff in China for the near-term (2041-2050), mid-term (2061-2070), and long-term (2091-2100) under two emission scenarios (SSP245 and SSP585), and examines the driving factors. The results show that natural runoff in China is expected to increase under various future scenarios. Notably, the increase rate under the SSP585 scenario is significantly higher than that under SSP245. The autumn increase is particularly pronounced compared to other seasons, and the northern basin generally experiences a higher increase rate than the southern basin. These changes may pose new adaptive challenges for agricultural production and water conservancy in China.

Warming leads to both earlier and later snowmelt floods over the past 70 years

Climate warming reduces snow cover in cold regions, altering snowmelt flood regimes with significant hydrological and ecological consequences. Existing evidence indicates that as climate warms, snowmelt tends to begin earlier in the season, leading to earlier snowmelt floods. Here we show that the timing of snowmelt floods can be either advanced or delayed under warming. Using streamflow observations from 1950-2020 and an event-based analysis that distinguishes flood-generating mechanisms across 2339 Northern Hemisphere, snow-affected catchments, we show that the earlier snowmelt effect can be substantially offset or even reversed by a decelerated snowmelt rate under warming. This results in delayed snowmelt floods in approximately 30% of the catchments, contributing to an overall minor shift on a hemispheric scale (-0.87 ± 2.4 days per decade). Our findings challenge the prevailing "warming leads to earlier snowmelt floods" paradigm, revealing a more complex pattern of changes in snowmelt flood in a warming world.

Hydrological connectivity shape the nitrogen pollution sources and microbial community structure in a river-lake connected system

Intensified agricultural and urban activities have exacerbated nitrogen pollution, posing a severe threat to freshwater ecosystems, particularly under intensified agricultural and urbanization activities. This study systematically examined Baiyangdian Lake (BYD) and its principal inflowing rivers, namely Fu River (FH), Baigouyin River (BGY), and Xiaoyi River (XY) to characterize the spatio-temporal distribution, primary nitrogen sources, and the impact on sediment microbial community structure. Results indicated pronounced seasonal variations in both nitrogen pollution loads and sources, with riverine nitrogen levels rising markedly from dry season (May) to wet season (August). Atmospheric deposition accounted for 43.9% of the nitrogen input dry season, whereas in wet season, agricultural fertilizers and sewage contributed 23.3 and 26.4%, respectively. Additionally, microbial communities exhibited distinct temporal and spatial patterns, with significantly higher diversity and species richness being during the wet season. The, microbial composition shifted, as evidenced by a decline in Proteobacteria and increases in Firmicutes and Actinobacteriota. River-lake connectivity emerged as a critical factor, with FH displaying a notably higher connectivity index in wet season compared to BGY and XY rivers. Structural equation modeling (SEM) analysis further revealed that river-lake connectivity was significantly and positively correlated with nitrogen pollution, was significantly and negatively correlated with microbial α-diversity. These findings demonstrated that river-lake connectivity directly influenced nitrogen concentrations, which in turn indirectly modulated microbial diversity.

Climate change will amplify the impacts of harmful microorganisms in aquatic ecosystems

More than 70% of the human population lives within five kilometres of a natural water feature. These aquatic ecosystems are heavily used for resource provision and recreation, and represent the interface between human populations and aquatic microbiomes, which can sometimes negatively impact human health. Diverse species of endemic aquatic microorganisms, including toxic microalgae and pathogenic bacteria, can be harmful to humans. Aquatic ecosystems are also subject to intrusions of allochthonous pathogenic microorganisms through pollution and runoff. Notably, environmental processes that amplify the abundance and impact of harmful aquatic microorganisms are occurring with increasing frequency owing to climate change. For instance, increases in water temperature stimulate outbreaks of pathogenic and toxic species, whereas more intense precipitation events escalate microbial contamination from stormwater discharge. In this Perspective we discuss the influence of aquatic microbiomes on the health and economies of human populations and examine how climate change is increasing these impacts.

Yield and Sensorial and Nutritional Quality of Strawberry (Fragaria × ananassa Duch.) Fruits from Plants Grown Under Different Amounts of Irrigation in Soilless Cultivation

Water scarcity is an ecological issue affecting over 10% of Europe. It is intensified by rising temperatures, leading to greater evaporation and reduced precipitation. Agriculture has been confirmed as the sector accounting for the highest water consumption globally, and it faces significant challenges relating to drought, impacting crop yields and food security. Sustainable practices, precision irrigation, and the development of drought-resistant crops are essential for the mitigation of this threat. Effective, innovative solutions are crucial for optimizing water use for intensive crops such as cultivated strawberries (Fragaria × ananassa). This study emphasizes the importance of identifying the genotypes most resilient to low water availability. Experimental trials involving reduced irrigation levels were set up to identify genotypes with a greater capacity to increase fruit quality and maintain fruit yield. Reduced water conditions positively influenced strawberry fruit quality, exhibiting improved citric acid, soluble solids, and color brightness linked to decreased water use, while firmness remained stable. Notably, the total phenolic content was most affected by stress, indicating strong antioxidant responses. With these interesting variations in fruit quality came a different response in plant yield. Plants belonging to the Lauretta and AN15,07,53 cultivars maintained a 98% fruit yield when grown under WS1 conditions. While the yield for the Francesca cultivar increased by 10% under the stressed WS1 conditions in comparison to the control conditions, water stress in the WS2 treatment caused a strong reduction in yield in all three genotypes. Overall, the findings emphasize the importance of identifying for each new cultivar the most appropriate water regime in order to amplify the quality of the fruit, thus maintaining high production standards and saving water.

Interpretable flash flood susceptibility mapping in Yarlung Tsangpo River Basin using H2O Auto-ML

Flash flood susceptibility mapping is essential for identifying areas prone to flooding events and aiding decision-makers in formulating effective prevention measures. This study aims to evaluate the flash flood susceptibility in the Yarlung Tsangpo River Basin (YTRB) using multiple machine learning (ML) models facilitated by the H2O automated ML platform. The best-performing model was used to generate a flash flood susceptibility map, and its interpretability was analyzed using the Shapley Additive Explanations (SHAP) tree interpretation method. The results revealed that the top four models, including both single and ensemble models, demonstrated high accuracy in the tests. The flash flood susceptibility map generated by the best-performing eXtreme Randomized Trees (XRT) model showed that 8.92%, 12.95%, 15.42%, 31.34%, and 31.37% of the study area exhibited very high, high, moderate, low, and very low flash flood susceptibility, respectively, with approximately 74.9% of the historical flash floods occurring in areas classified as moderate to very high susceptibility. The SHAP plot identified topographic factors as the primary drivers of flash floods, with the importance analysis ranking the most influential factors in such descending order as DEM, topographic wetness index, topographic position index, normalized difference vegetation index, and average multi-year precipitation. This study demonstrates the benefits of interpretable machine learning, which can provide guidance for flash flood mitigation.

Future runoff trends in the mang river basin of China: Implications of carbon emission paths

In recent years, the rapid development of the global economy has led to an increasing impact of the ongoing climate warming phenomenon on the hydrological cycle. In this context, the runoff changes affected by human activities are more severe. This study classifies climate scenarios based on carbon emission levels into "low-carbon" (SSP1-2.6, SSP2-4.5) and "high-carbon" (SSP3-7.0, SSP5-8.5) dual carbon development paths, and analyzes the evolution characteristics of runoff in the Mang River Basin in the near future (2021-2060) and far future (2061-2100) through driving the SWAT model. The main conclusions are as follows: (1) The suitability of the SWAT model in the Mang River Basin was confirmed with a high accuracy (R2 > 0.65, NSE > 0.8), and the parameters ESCO and SOL_AWC were found to have a high sensitivity to runoff. (2) Increased precipitation fluctuation and continuous temperature rise will be the climate change trend in the basin under the dual carbon pathway. It is estimated that by the end of the 21st century, the overall highest temperature will increase by 1.37-5.02 °C, with temperature increases of 0.53-0.63 °C/10a and 0.17-0.38 °C/10a under the "high carbon" and "low carbon" pathways, respectively. Furthermore, the far future precipitation levels are expected to be higher than near future levels across various climate scenarios, with this trend being especially significant under the "low-carbon" pathway. (3) With the influence of climate change, there is a larger increase in runoff volume under the "high-carbon" pathway, with the growth rate of SSP5-8.5 being the fastest at 0.099 m3/s·a, resulting in an overall runoff change of 30.65%. On the other hand, the runoff volume under the "low-carbon" pathway shows a slow growth trend, with an increasing rate that accelerates after the mid-21st century. The runoff change rates range from 0.046 to 0.079 m3/s·a. (4) Climate change will significantly alter the overall runoff conditions of the basin. With the passage of time and the increase of carbon concentration emission, the impact of temperature on basin runoff will become increasingly stronger. However, precipitation was still the dominant factor leading to changes in runoff. The overall climate environment within the basin will shift towards a warmer and wetter direction. This research will help in the future to adopt appropriate measures for soil and water conservation and ecological protection strategies in ecologically vulnerable areas affected by human activities and located in different geographical basins under the background of climate change.

Setting priorities for floods mitigation through forest restoration: The threshold elevation hypothesis

Nature based solutions (NbS) for flood regulation (e.g., forest restoration) need to be informed by the analysis of climate change and land-use/cover change (LUCC) effects on floods, but these effects are still poorly understood. In this study, it is hypothesized that effects of climate change and LUCC on floods exhibit an abrupt change at a threshold elevation with implications for forest restoration. The study was carried out in the Tena watershed located in Ecuadorian Amazon. Hydrological simulations were run using TETIS model for different climate and LUCC scenarios. Projected precipitation from the Global Climate Models (GCMs) under the SSP5-8.5 scenario of CMIP6 was assessed. Isolated and combined effects of climate change and LUCC on floods across an altitudinal gradient were analyzed at 42 flow sites. Obtained results confirm the hypothesis showing the existence of a threshold elevation at 590 m a.s.l., where abrupt changes on floods occurred. The effects of LUCC prevailed over the effects of climate change in the upper basin, while in the lower basin, effects of climate change prevailed, especially for small and medium flood events. The results suggest that native forest is priority in the area above the threshold elevation, informing restoration as a NbS for flood regulation in humid tropical basins in a context of climate change.

Thermodynamically inconsistent extreme precipitation sensitivities across continents driven by cloud-radiative effects

Extreme precipitation events are projected to intensify with global warming, threatening ecosystems and amplifying flood risks. However, observation-based estimates of extreme precipitation-temperature (EP-T) sensitivities show systematic spatio-temporal variability, with predominantly negative sensitivities across warmer regions. Here, we attribute this variability to confounding cloud radiative effects, which cool surfaces during rainfall, introducing covariation between rainfall and temperature beyond temperature's effect on atmospheric moisture-holding capacity. We remove this effect using a thermodynamically constrained surface-energy balance, and find positive EP-T sensitivities across continents, consistent with theoretical arguments. Median EP-T sensitivities across observations shift from -4.9%/°C to 6.1%/°C in the tropics and -0.5%/°C to 2.8%/°C in mid-latitudes. Regional variability in estimated sensitivities is reduced by more than 40% in tropics and about 30% in mid and high latitudes. Our findings imply that projected intensification of extreme rainfall with temperature is consistent with observations across continents, after confounding radiative effect of clouds is accounted for.

Bacterial accumulation dynamics in runoff from extreme precipitation

Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 104.5-6.3, 104.5-6.1, 104.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 104.0-6.0, 103.9-5.8, 103.2-4.9 CFU/mL, and viable bacteria = 106.4-8.0, 107.0-8.9, 106.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 109.38-11.31 CFU/m2 and 1011.84-13.25 cells/m2, respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change.

Reactive Nitrogen Species Generated from Far-UVC Photolysis of Nitrate Contribute to Pesticide Degradation and Nitrogenous Byproduct Formation

Climate change has resulted in increased use of pesticides and fertilizers in agriculture, leading to elevated pesticide and nitrate levels in aquatic ecosystems that receive agricultural runoff. In this study, we demonstrate that far-UVC (UV222) photolysis of nitrate rapidly degrades four pesticides in surface water, with a degradation rate constant 37.1-144.75 times higher than that achieved by UV254 photolysis of nitrate. The improved pesticide degradation is due not only to the enhanced direct photolysis by UV222 compared to UV254 but also to the increased generation of hydroxyl radicals (HO•) and reactive nitrogen species (e.g., NO2• and ONOO-) in the UV222/nitrate process. We determined the innate quantum yields of nitrate photolysis at 222 nm and incorporated these values into a kinetic model, allowing for the accurate prediction of nitrate photodecay and reactive species generation. While reactive nitrogen species predominantly contribute to pesticide degradation in the UV222/nitrate process, they also lead to the formation of nitration byproducts. Using stable isotope-labeled nitrate (15NO3-) combined with mass spectrometry, we confirmed that the nitration byproducts are formed from the reactive nitrogen species generated from nitrate photolysis. Additionally, we demonstrate that the UV222/nitrate process increases the formation potential of highly toxic nitrogenous chlorinated products (e.g., trichloronitromethane) during postchlorination in real surface water.

Persistent effects of larval exposure to glyphosate in mangrove rivulus fish

Glyphosate, a key ingredient in many herbicides, is increasingly present in aquatic systems due to agricultural runoff. High doses of glyphosate cause defects in organisms due to its ability to interfere with physiological processes as an endocrine disruptor. We used the mangrove rivulus fish (Kryptolebias marmoratus) to evaluate the effects of larval exposure to glyphosate on non-target species in aquatic environments. These fish produce genetically identical offspring, allowing us to evaluate phenotypic responses to toxicant exposure while controlling for genetics. We treated newly hatched larvae for 96 h with concentrations of glyphosate on the low and high end of what they would experience in the wild: control (0 mg/L), low (0.01 mg/L), and high (1.1 mg/L), and then measured behavior, morphology, and reproductive traits at 60 and 130 days. We predicted that these amphibious fish exposed to low, environmentally relevant doses would show adaptive emersion behavior to escape poor quality water conditions, and deficits in other traits would be greater with higher glyphosate dosages. We found that low doses (0.01 mg/L) of glyphosate led to lower anxiety (decreased thigmotaxis) and impaired jumping behaviors while high dose exposures to glyphosate resulted in lower activity and lower average egg yield per individual. None of these effects appeared to be adaptive at low or high doses of glyphosate. While deficits in reproductive output scaled with dosage, phenotypic effects were often dosage-specific for each trait. This study demonstrates that even environmentally relevant concentrations of herbicide may be harmful to aquatic organisms and have consequences that persist well into adulthood. Furthermore, given that environmentally relevant concentrations of glyphosate induced deficits in reproductive output, this suggests that glyphosate contamination in natural systems may have population level consequences.

Hydro-climatic extremes shift the hydrologic sensitivity regime in a cold basin

Escalating climate extreme events disrupt hydrological processes by affecting both water availability and sediment dynamics. However, the interconnection between hydrological variability and climatic extremes remains underexplored, particularly in cold regions under a changing climate. Here, we develop a yield-based dichotomy framework to examine the impact of shifted climatic extreme patterns on hydrological regimes in the Ishikari River Basin (IRB), Hokkaido, Japan, which is a crucial area for local agriculture and urban development. Utilizing a modified Soil and Water Assessment Tool (SWAT) integrated with downscaled CMIP6-GCM climate projections under Shared Socioeconomic Pathways (SSPs) scenarios, we identified significant annual variability in water and sediment yields associated with extreme climate events. Hot-dry conditions correlate with lower water and sediment yields, whereas increased cold extremes may result in higher sediment yields across the IRB. Our findings also indicate that hotter and drier patterns interact with hydrological processes, potentially establishing new hydrologic regimes and shifting climatic extremes-induced thresholds for yield classification within the IRB. Notably, under SSP585, both water availability and sediment transport are projected to intensify, increasing flood risks and exacerbating sedimentation challenges. Our study highlights the urgent need for adaptive water management strategies to address these anticipated changes in hydrological regimes in response to global climate change.

Spatiotemporal evolution and driving factors of ecosystem service value in the Upper Minjiang River of China

The stability of ecosystems in high mountain canyon areas is poor, and the interaction between humans and the land is complex, making these ecosystems more vulnerable to destruction. Quantitatively assessing the ecosystem service value (ESV) in high mountain canyon areas and revealing its spatiotemporal evolution patterns and driving factors play a crucial role in the construction of regional ecological barriers and the assurance of ecological security. This study focuses on the Upper Minjiang River as the research area, using the InVEST model and the Equivalent Factor Method to estimate ESV. This combination aims to address the inadequacy of the Equivalent Factor Method in reflecting the variability of ESV across different regions, and the sensitivity of the InVEST model to data changes that results in insufficient accuracy of ESV assessments. By harnessing spatial au-tocorrelation and the geodetector method, we unravel the spatiotemporal evolution characteristics and driving factors of ESV. The results show that: (1) From 2000 to 2020, the ESVs estimated by the two estimations increased by 31.28% and 22.47%, respectively, both indicating that the eco-environment quality of the upper Minjiang River has been continuously improved. (2) When Moran's I was greater than 0.5 (p < 0.05), the spatial clustering of "High-High" and "Low-Low" ESV was obvious. It is clear that the ESV varies geographically. High values are primarily found in the study area's center and southern regions, as well as on both banks of the Minjiang River, whereas low values are more common in the region's northern region. (3) Slope and human activity intensity (HAI) are the principal contributors to the spatial differentiation of the ESV, more than 60% of the interaction types between the two factors were classified as dual-factor enhancement. The synergistic reinforcing effects of HAI, slope, elevation, and temperature collectively shape the shifts in ESV spatial distribution. This study offers a novel evaluative lens on the ESV of the Upper Minjiang River area, supplying a sturdy data support for crafting specific ecological preservation and rejuvenation strategies in the coming years.

Divergent determinants on interannual variability of terrestrial water cycle across the globe

Intensifying variability in precipitation under a changing climate is projected to amplify fluctuation in terrestrial hydrological cycle, leading to more severe water-related disasters. The connections between interannual variability of hydrological components and factors influencing these connections have not been clearly defined yet. Based on terrestrial water budget from Climate Data Record, we identify dominant factors influencing partitioning interannual variability of precipitation (P) into that of evapotranspiration (E), runoff (Q), and water storage deviation (ΔS) across the globe by employing geographical detector model (GDM). Sensitivities of the variability partitioning to dominant factors are quantified for different hydroclimate regions by linear regression model and law of total differential. Results show that dominant factors influencing precipitation variability partitioning (VP) are different across distinct hydroclimate conditions. Comparing the statistical index (q value) of the GDM, it can be seen that surface air temperature (Ta), snow water equivalent (SWE) and water storage capacity (Smax) are dominant factors of VP in humid, semi-arid and arid regions, respectively. Changes in P variability largely can transfer into Q variability in humid region. The P variability partitioned into Q variability is dramatically reduced in semi-arid region with SWE decreasing, while P variability partitioned into ΔS variability increases with Smax increasing in arid region. Joint effects of Ta and coefficient of variation of precipitation (Pcv) are found to be the most important interaction in determining VP across the globe. Furthermore, warmer temperatures in humid region cause >90 % of the change in precipitation variability to be transferred to Q variability change. In semi-arid region with snowfall, decreased SWE has strong effect on changes in ΔS (30-40 %) and Q (20-40 %) variability. Our findings imply a changing VP and more severe impacts of hydrological extremes under future climate, where intensive changes in Ta, SWE and land cover are projected.

Sorghum drought tolerance is enhanced by cerium oxide nanoparticles via stomatal regulation and osmolyte accumulation

Sorghum [Sorghum bicolor (L.) Moench] yield is limited by the coincidence of drought during its sensitive stages. The use of cerium oxide nanoparticles in agriculture is minimal despite its antioxidant properties. We hypothesize that drought-induced decreases in photosynthetic rate in sorghum may be associated with decreased tissue water content and organelle membrane damage. We aimed to quantify the impact of foliar application of nanoceria on transpiration rate, accumulation of compatible solutes, photosynthetic rate and reproductive success under drought stress in sorghum. In order to ascertain the mechanism by which nanoceria mitigate drought-induced inhibition of photosynthesis and reproductive success, experiments were undertaken in a factorial completely randomized design or split-plot design. Foliar spray of nanoceria under progressive soil drying conserved soil moisture by restricting the transpiration rate than water spray, indicating that nanoceria exerted strong stomatal control. Under drought stress at the seed development stage, foliar application of nanoceria at 25 mg L-1 significantly improved the photosynthetic rate (19%) compared to control by maintaining a higher tissue water content (18%) achieved by accumulating compatible solutes. The nanoceria-sprayed plants exhibited intact chloroplast and thylakoid membranes because of increased heme enzymes [catalase (53%) and peroxidase (45%)] activity, which helped in the reduction of hydrogen peroxide content (74%). Under drought, compared to water spray, nanoceria improved the seed-set percentage (24%) and individual seed mass (27%), eventually causing a higher seed yield. Thus, foliar application of nanoceria at 25 mg L-1 under drought can increase grain yield through increased photosynthesis and reproductive traits.

Precision phenotyping of a barley diversity set reveals distinct drought response strategies

Plants exhibit an array of drought responses and adaptations, where the trade-off between water loss and CO2 uptake for growth is mediated by regulation of stomatal aperture in response to soil water content (SWC), among other factors. For crop yield stability, the question is how drought timing and response patterns relate to post-drought growth resilience and vigor. We earlier identified, in a few reference varieties of barley that differed by the SWC at which transpiration was curtailed, two divergent water use strategies: water-saving ("isohydric") and water-spending ("anisohydric"). We proposed that an isohydric strategy may reduce risk from spring droughts in climates where the probability of precipitation increases during the growing season, whereas the anisohydric is consistent with environments having terminal droughts, or with those where dry periods are short and not seasonally progressive. Here, we have examined drought response physiology in an 81-line barley (Hordeum vulgare L.) diversity set that spans 20th century European breeding and identified several lines with a third, dynamic strategy. We found a strong positive correlation between vigor and transpiration, the dynamic group being highest for both. However, these lines curtailed daily transpiration at a higher SWC than the isohydric group. While the dynamic lines, particularly cv Hydrogen and Baronesse, were not the most resilient in terms of restoring initial growth rates, their strong initial vigor and high return to initial transpiration rates meant that their growth nevertheless surpassed more resilient lines during recovery from drought. The results will be of use for defining barley physiological ideotypes suited to future climate scenarios.

Physiological and molecular mechanisms of plant-root responses to iron toxicity

The chemical form and physiological activity of iron (Fe) in soil are dependent on soil pH and redox potential (Eh), and Fe levels in soils are frequently elevated to the point of causing Fe toxicity in plants, with inhibition of normal physiological activities and of growth and development. In this review, we describe how iron toxicity triggers important physiological changes, including nitric-oxide (NO)-mediated potassium (K+) efflux at the tips of roots and accumulation of reactive oxygen species (ROS) and reactive nitrogen (RNS) in roots, resulting in physiological stress. We focus on the root system, as the first point of contact with Fe in soil, and describe the key processes engaged in Fe transport, distribution, binding, and other mechanisms that are drawn upon to defend against high-Fe stress. We describe the root-system regulation of key physiological processes and of morphological development through signaling substances such as ethylene, auxin, reactive oxygen species, and nitric oxide, and discuss gene-expression responses under high Fe. We especially focus on studies on the physiological and molecular mechanisms in rice and Arabidopsis under high Fe, hoping to provide a valuable theoretical basis for improving the ability of crop roots to adapt to soil Fe toxicity.

Amazon savannization and climate change are projected to increase dry season length and temperature extremes over Brazil

Land use change and atmospheric composition, two drivers of climate change, can interact to affect both local and remote climate regimes. Previous works have considered the effects of greenhouse gas buildup in the atmosphere and the effects of Amazon deforestation in atmospheric general circulation models. In this study, we investigate the impacts of the Brazilian Amazon savannization and global warming in a fully coupled ocean-land-sea ice-atmosphere model simulation. We find that both savannization and global warming individually lengthen the dry season and reduce annual rainfall over large tracts of South America. The combined effects of land use change and global warming resulted in a mean annual rainfall reduction of 44% and a dry season length increase of 69%, when averaged over the Amazon basin, relative to the control run. Modulation of inland moisture transport due to savannization shows the largest signal to explain the rainfall reduction and increase in dry season length over the Amazon and Central-West. The combined effects of savannization and global warming resulted in maximum daily temperature anomalies, reaching values of up to 14 °C above the current climatic conditions over the Amazon. Also, as a consequence of both climate drivers, both soil moisture and surface runoff decrease over most of the country, suggesting cascading negative future impacts on both agriculture production and hydroelectricity generation.

Rising rainfall intensity induces spatially divergent hydrological changes within a large river basin

Droughts or floods are usually attributed to precipitation deficits or surpluses, both of which may become more frequent and severe under continued global warming. Concurring large-scale droughts in the Southwest and flooding in the Southeast of China in recent decades have attracted considerable attention, but their causes and interrelations are not well understood. Here, we examine spatiotemporal changes in hydrometeorological variables and investigate the mechanism underlying contrasting soil dryness/wetness patterns over a 54-year period (1965-2018) across a representative mega-watershed in South China-the West River Basin. We demonstrate that increasing rainfall intensity leads to severe drying upstream with decreases in soil water storage, water yield, and baseflow, versus increases therein downstream. Our study highlights a simultaneous occurrence of increased drought and flooding risks due to contrasting interactions between rainfall intensification and topography across the river basin, implying increasingly vulnerable water and food security under continued climate change.

Transgenerational adaptation to ocean acidification determines the susceptibility of filter-feeding rotifers to nanoplastics

The adaptation of marine organisms to the impending challenges presented by ocean acidification (OA) is essential for their future survival, and mechanisms underlying OA adaptation have been reported in several marine organisms. In the natural environment, however, marine organisms are often exposed to a combination of environmental stressors, and the interactions between adaptive responses have yet to be elucidated. Here, we investigated the susceptibility of filter-feeding rotifers to short-term (ST) and long-term (LT) (≥180 generations) high CO2 conditions coupled with nanoplastic (NPs) exposure (ST+ and LT+). Adaptation of rotifers to elevated CO2 caused differences in ingestion and accumulation of NPs, resulting in a significantly different mode of action on in vivo endpoints between the ST+ and LT+ groups. Moreover, microRNA-mediated epigenetic regulation was strongly correlated with the varied adaptive responses between the ST+ and LT+ groups, revealing novel regulatory targets and pathways. Our results indicate that pre-exposure history to increased CO2 levels is an important factor in the susceptibility of rotifers to NPs.

The role of satellite remote sensing in mitigating and adapting to global climate change

Climate change has critical adverse impacts on human society and poses severe challenges to global sustainable development. Information on essential climate variables (ECVs) that reflects the substantial changes that have occurred on Earth is critical for assessing the influence of climate change. Satellite remote sensing (SRS) technology has led to a new era of observations and provides multiscale information on ECVs that is independent of in situ measurements and model simulations. This enhances our understanding of climate change from space and supports policy-making in combating climate change. However, it remains challenging to remotely retrieve ECVs due to the complexity of the climate system. We provide an update on the studies on the role of SRS in climate change research, specifically in monitoring and quantifying ECVs in the atmosphere (greenhouse gases, clouds and aerosols), ocean (sea surface temperature, sea ice melt and sea level rise, ocean currents and mesoscale eddies, phytoplankton and ocean productivity), and terrestrial ecosystems (land use and land cover change and carbon flux, water resource and hydrological hazards, solar-induced chlorophyll fluorescence and terrestrial gross primary production). The benefits and challenges of applying SRS in climate change studies are also examined and discussed. This work will help us apply SRS and recommend future SRS studies to mitigate and adapt to global climate change.

Investigating socio-ecological vulnerability to climate change via remote sensing and a data-driven ranking algorithm

The necessity for extensive historical data, variables, and weight determination still presents challenges and complexity, notwithstanding the growth in research on socio-ecological vulnerability to climate change. In order to fill in these gaps, this study used China's Fujian Province as a case study to propose a unique strategic approach for studying socio-ecological vulnerability to climate change from 2000 to 2020 by utilizing remote sensing and the framework of the Intergovernmental Panel on Climate Change. In a GIS scenario, this method employs a comprehensive framework with a wide variety of indicators and a data-driven ranking algorithm. The findings of this study revealed a moderate degree of socio-ecological vulnerability throughout the coast, with significant regional heterogeneity in its spatial distribution. Furthermore, throughout the course of the two-decade, the highly vulnerable zones expanded by 6.04%, outpacing the low-risk areas by 1116 km2 (61.41%) and 2066 km2 (123.39%), respectively, with the majority of the increase taking place in Fuzhou and Ningde. These changes in vulnerability were shown to be principally influenced by changes in vegetation, precipitation, GDP, and land use (LULC). The major influence of precipitation was highlighted further in the spatial autocorrelation analysis, which demonstrated a close correlation between growing socio-ecological vulnerability and increased precipitation. To conclude, this study's methodology differs from other socio-ecological vulnerability studies in that it is flexible and self-sufficient, offering users a choice of weight application. It also gives a more useful, accurate, and suggestive model to enable decision-makers or stakeholders build strategies or ideas for constructing more resilient coastal systems.

Modeling mass removal and sediment deposition in stormwater ponds using floating treatment islands: a computational approach

Floating treatment islands (FTIs) offer effective solutions for stormwater management, providing flood attenuation and pollutant removal capabilities. However, there remains a knowledge gap concerning their performance, specifically in terms of pollutant removal and sediment deposition. To address this gap, the present study employs computational fluid dynamics (CFD) modeling to investigate the intricate interactions within FTI systems. Various FTI configurations are analyzed, considering mass removal through FTIs and sediment deposition, the first time where these two processes were considered together in a CFD environment. The findings demonstrate that FTIs have a significant influence on flow patterns and mass removal. Notably, FTIs enhance mass removal compared to the control case, with larger sediment particles exhibiting higher removal rates. The correlation between the short-circuit index and sedimentation in FTI ponds highlights the potential of FTIs as indicators of treatment efficiency. Furthermore, the study focuses on mass removal exclusively through the FTI root zones. The positioning of FTIs within the pond has a considerable impact, resulting in differences of up to 20% in mass removal. Moreover, the FTI configuration exerts a more pronounced influence on mass removal through FTIs than through sediment deposition alone. In cases where both processes occur simultaneously, the presence of FTIs lead to higher mass removal, primarily attributed to the FTIs themselves, particularly in the initial segment. Remarkably, certain FTI configurations enable mass removal exceeding 70% for large sediment particles, even with a pond length less than half of the original.

Impacts of LULC and climate changes on hydropower generation and development: A systematic review

There is a growing concern on a global scale that the world should transition towards the utilisation of energy-efficient technologies. Hydropower plays a very significant part in the fight against climate change, and as a result, it lessens the impact that climate changewill have on our ability to achieve the Sustainable Development Goals (SDGs). Both the effectiveness of hydropower generation and the amount of streamflow are impacted by climate change as well as land use and land cover (LULC). Accordingly, the purpose of this study is to conduct a literature review on the topic of the past and future effects of climate, land use, and land cover changes on hydropower generation. This review will be based on the entries found in a number of reliable databases. A systematic literature review was carried out to analyse how LULC and climate change will affect hydropower generation and development. The research was based on 158 pieces of relevant literature that had been reviewed by experts and indexed in Scopus, Google Scholar, and ScienceDirect. The review was carried out to determine three goals in mind: the impact of climate change on hydropower generation and development; the impact of climate change on streamflow; and the combined impact of changes in climate and changes in LULC on hydropower. The findings bring to light the primary factors contributing to climate change as well as shifts in LULC which are essential to the generation of hydropower on all scales. The study identifies factors such as precipitation, temperature, floods, and droughts as examples of climate change. Deforestation, afforestation, and urbanisation are identified as the primary causes of changes in LULC over the past several decades. These changes have a negative impact on the generation and development of hydropower.

Effects of a short-term temperature increase on arthropod communities associated with pastures

The impact of climate change on islands is expected to cause dramatic consequences on native biodiversity. However, limited data are available for arthropod communities in island agroecosystems. In this study, we simulate a small-scale climatic change (average of +1.2°C), using Open Top Chambers (OTCs) in forage crops in the Azores Archipelago (Portugal) and test the responses of arthropod communities associated with intensively-managed pastures. At three sites, twenty 1 x 1 m plots were established: 10 treatment plots with OTCs and 10 control plots. Arthropods were sampled with pitfall traps on two sampling events (winter and summer of 2020). When considering all species collected, arthropods' abundance was lower in OTCs. Specific taxa, namely spiders and beetles, showed a fast response to the OTCs' presence. The assemblage of non-indigenous spiders well adapted to pastures showed a significant difference in diversity with a slightly greater richness, but lower abundance inside the warmer plots. However, the presence of OTCs resulted in a decrease in beetle richness and abundance. This decline may be attributed to the multiple effects of warming. Therefore, it is imperative to conduct further investigations to elucidate the ecological processes that underlie the observed patterns.

Large anomalies in future extreme precipitation sensitivity driven by atmospheric dynamics

Increasing atmospheric moisture content is expected to intensify precipitation extremes under climate warming. However, extreme precipitation sensitivity (EPS) to temperature is complicated by the presence of reduced or hook-shaped scaling, and the underlying physical mechanisms remain unclear. Here, by using atmospheric reanalysis and climate model projections, we propose a physical decomposition of EPS into thermodynamic and dynamic components (i.e., the effects of atmospheric moisture and vertical ascent velocity) at a global scale in both historical and future climates. Unlike previous expectations, we find that thermodynamics do not always contribute to precipitation intensification, with the lapse rate effect and the pressure component partly offsetting positive EPS. Large anomalies in future EPS projections (with lower and upper quartiles of -1.9%/°C and 8.0%/°C) are caused by changes in updraft strength (i.e., the dynamic component), with a contrast of positive anomalies over oceans and negative anomalies over land areas. These findings reveal counteracting effects of atmospheric thermodynamics and dynamics on EPS, and underscore the importance of understanding precipitation extremes by decomposing thermodynamic effects into more detailed terms.

Investigating impact of CORDEX-based predicted climatic and LCM-based LULC scenarios on hydrologic response of a semi-gauged Indian catchment

The present study aims at documenting the impact of different climate and land use change scenarios on runoff in the Kangsabati River basin. While the study relies on India Meteorological Department (IMD), National Oceanic and Atmospheric Administration's Physical Sciences Laboratory (NOAA-PSL), and a multi-model ensemble of six driving models from Coordinated Regional Downscaling Experiment-Regional Climate Models (CORDEX RCM) for climate data input, it depends on IDRISI Selva's Land Change Modeller (LCM) and Soil and Water Assessment Tool (SWAT) model to generate projected land use land change maps and simulate its streamflow response, respectively. A total of four land use and land cover (LULC) scenarios, representing four projected land use change, were modelled across three climatic scenarios, called Representative Concentration Pathways (RCPs). With runoff being predominantly impacted more by climate change than LULC, volumetric runoff is expected to be 12-46% higher than the baseline period of 1982-2017. Conversely, while surface runoff is expected to decrease by 4-28% in lower parts of the basin, it will increase by 2-39% in the rest of it, depending on the subtle alterations in land use and climatic variability.

Design Rainfall Change of Rainwater Source Control Facility to Meet Future Scenarios in Beijing

Rainwater source control facilities are essential to sponge city construction in China. Their size is determined based on historical rainfall data. However, with global warming and rapid urban development, rainfall characteristics have also changed, potentially leading to the failure of rainwater source- control facilities to manage surface water in the future. In this study, the design rainfall's change and spatial distribution are analyzed using historical (1961-2014) observation rainfall data and future (2020-2100) projection data of three CMIP6 climate models. The results show that EC-Earth3 and GFDL-ESM4 project that future design rainfall will increase. EC-Earth3 projects a significant increase, while MPI-ESM1-2 projects that the design rainfall will decrease significantly. From the perspective of space, the design rainfall isoline in Beijing has always increased from northwest to southeast. In the historical period, the difference in design rainfall in different regions has reached 19 mm, and this regional heterogeneity shows an increasing trend in the future projection of EC-Earth3 and GFDL-ESM4. The difference in design rainfall in different regions is 26.2 mm and 21.7 mm, respectively. Therefore, it is necessary to consider future rainfall changes in the design of rainwater source control facilities. The relationship curve between the volume capture ratio (VCR) of annual rainfall and design rainfall based on the rainfall data of the project site or region should be analyzed to determine the design rainfall of the rainwater source control facilities.

Assessing the contribution of vegetation variation to streamflow variation in the Lancang River Basin, China

The Lancang River Basin (LCRB) is the largest international river in Southeast Asia, and any change in its streamflow, i.e., due to the ecological environment and runoff, may lead to disputes between countries to a certain extent. However, the impact of vegetation change on streamflow in the LCRB needs to be clarified. To assess the impact of vegetation change on streamflow in the LCRB, the functional relationship between Budyko parameter (ω) and Normalized Difference Vegetation Index (NDVI) was first computed for constructing a modified Budyko formula. Finally, we quantitatively estimated the influence of different factors on streamflow variation in the LCRB using the modified Budyko formula and the elastic coefficient method. The conclusions were as follows: (1) A sudden change in streamflow at the Yunjinghong hydrological station appeared in 2005; (2) Budyko parameter (ω) has a good linear functional relationship with NDVI in the LCRB (p &lt; 0.01); ND (3) vegetation variation played the largest driving force behind streamflow variation in the LCRB, accounting for 34.47%. The contribution rates of precipitation, potential evaporation, and anthropogenic activities on streamflow variation from 1982 to 2015 were 16.83, 17.61, and 31.09%, respectively.

River ecosystem metabolism and carbon biogeochemistry in a changing world

River networks represent the largest biogeochemical nexus between the continents, ocean and atmosphere. Our current understanding of the role of rivers in the global carbon cycle remains limited, which makes it difficult to predict how global change may alter the timing and spatial distribution of riverine carbon sequestration and greenhouse gas emissions. Here we review the state of river ecosystem metabolism research and synthesize the current best available estimates of river ecosystem metabolism. We quantify the organic and inorganic carbon flux from land to global rivers and show that their net ecosystem production and carbon dioxide emissions shift the organic to inorganic carbon balance en route from land to the coastal ocean. Furthermore, we discuss how global change may affect river ecosystem metabolism and related carbon fluxes and identify research directions that can help to develop better predictions of the effects of global change on riverine ecosystem processes. We argue that a global river observing system will play a key role in understanding river networks and their future evolution in the context of the global carbon budget.

Effectiveness assessment of reservoir projects for flash flood control, water supply and irrigation in Wangmo Basin, China

Most flash floods in countries around the world occur in poor rural mountainous areas and typically cause more casualties and economic losses due to monitoring challenges and early warning difficulties. In mountainous regions, reservoir projects are a very effective measure for mitigating the risk of flash floods and can also be used for water supplies and irrigation, but there is a lack of research on the comprehensive benefit assessments of reservoirs. In this paper, we simulate the inundation extents of flash floods for the Wangmo Basin in China, where flash floods frequently occur, under different return periods using the HEC-HMS (HEC-Hydrologic Modelling System) model and FLO-2D model and compare the resulting housing losses with and without reservoirs. The results indicate that using dam and reservoir operations for flood control in the Wangmo River Basin decreases the flooded housing area in the county centre by approximately 12.9 %-30.2 %, which results in housing losses reductions of 19.7 %-45.7 %.These dams and reservoirs will begin to make a profit during the 38th year of operation, and the average annual net benefit reaches 101.76 million RMB in 50 years, which is equivalent to 1.43 % of the GDP of Wangmo County; the net benefits of flood control, water supply and irrigation accounted for 0.4 %, 1.0 % and 0.03 %, respectively. Priority should be given to planning and building these water conservation measures to help these poor mountainous areas. The construction of dams and reservoirs can contribute to decreasing losses in poverty and disaster-prone regions. The effectiveness evaluation framework for dams and reservoirs presented in this study can be applied to other mountainous basins for flood control and local development.

Shifting in the global flood timing

Climate change will have an impact on not only flood magnitude but also on flood timing. This paper studies the shifting in flood timing at 6167 gauging stations from 1970 to 2010, globally. The shift in flood timing and its relationship with three influential factors (maximum 7-day precipitation, soil moisture excess, and snowmelt) are investigated. There is a clear global pattern in the mean flooding date: winter (Dec-Feb) across the western Coastal America, western Europe and the Mediterranean region, summer (Jun-Aug) in the north America, the Alps, Indian Peninsula, central Asia, Japan, and austral summer (Dec-Feb) in south Africa and north Australia area. The shift in flood timing has a trend from - 22 days per decade (earlier) to 28 days per decade (delayed). Earlier floods were found extensively in the north America, Europe and northeast Australia while delayed floods were prevailing in the Amazon, Cerrado, south Africa, India and Japan. Earlier flood timing in the north America and Europe was caused by earlier snowmelt while delayed extreme soil moisture excess and precipitation have jointly led to delayed floods around the monsoon zone, including south Africa, India and Japan. This study provides an insight on the shifting mechanism of flood timing, and supports decisions on the global flood mitigation and the impact from future climate change.

Classification of flood-generating processes in Africa

River flooding has large societal and economic impacts across Africa. Despite the importance of this topic, little is known about the main flood generating mechanisms in Africa. This study is based on 13,815 flood events that occurred between 1981 and 2018 in 529 catchments. These flood events are classified to identify the different flood drivers: excess rains, long rains and short rains. Out of them, excess rains on saturated soils in Western Africa, and long rains for catchments in Northern and Southern Africa, are the two dominant mechanisms, contributing to more than 75% of all flood events. The aridity index is strongly related to the spatial repartition of the different flood generating processes showing the climatic controls on floods. Few significant changes were detected in the relative importance of these drivers over time, but the rather short time series available prevent a robust assessment of flood driver changes in most catchments. The major implication of these results is to underline the importance of soil moisture dynamics, in addition to rainfall, to analyze the evolution of flood hazards in Africa.

The Influence of Climate Change on Droughts and Floods in the Yangtze River Basin from 2003 to 2020

In recent decades, extreme floods and droughts have occurred frequently around the world, which seriously threatens the social and economic development and the safety of people's lives and properties. Therefore, it is of great scientific significance to discuss the causes and characteristic quantization of extreme floods and droughts. Here, the terrestrial water storage change (TWSC) derived from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) data was used to characterize the floods and droughts in the Yangtze River basin (YRB) during 2003 and 2020. To reduce the uncertainty of TWSC results, the generalized three-cornered hat and least square methods were used to fuse TWSC results from six GRACE solutions. Then combining precipitation (PPT), evapotranspiration, soil moisture (SM), runoff, and extreme climate index data, the influence of climate change on floods and droughts in the YRB was discussed and analyzed. The results show that the fused method can effectively improve the uncertainty of TWSC results. And seven droughts and seven floods occurred in the upper of YRB (UY) and nine droughts and six floods appeared in the middle and lower of YRB (MLY) during the study period. The correlation between TWSC and PPT (0.33) is the strongest in the UY, and the response time between the two is 1 month, while TWSC and SM (0.67) are strongly correlated with no delay in the MLY. The reason for this difference is mainly due to the large-scale hydropower development in the UY. Floods and droughts in the UY and MLY are more influenced by the El Niño-Southern Oscillation (ENSO) (correlation coefficients are 0.39 and 0.50, respectively) than the Indian Ocean Dipole (IOD) (correlation coefficients are 0.19 and 0.09, respectively). The IOD event is usually accompanied by the ENSO event (the probability is 80%), and the hydrological hazards caused by independent ENSO events are less severe than those caused by these two extreme climate events in the YRB. Our results provide a reference for the study on the formation, development, and recovery mechanism of regional floods and droughts on a global scale.

A Comprehensive Evaluation of Effects on Water-Level Deficits on Tomato Polyphenol Composition, Nutritional Quality and Antioxidant Capacity

Tomatoes have high nutritional value and abundant bioactive compounds. Moderate water deficit irrigation alters metabolic levels of fruits, improving composition and quality. We investigated the effects of water deficit (T1, T2, T3, and T4) treatments and adequate irrigation (CK) on tomato polyphenol composition, antioxidant capacity, and nutritional quality. Compared with CK, the total flavonoid content increased by 33.66% and 44.73% in T1 and T2, and total phenols increased by 57.64%, 72.22%, and 55.78% in T1, T2, and T3, respectively. The T2 treatment significantly enhanced antioxidant’ capacities (ABTS, HSRA, FRAP, and DPPH). There were multiple groups of significant or extremely significant positive correlations between polyphenol components and antioxidant activity. For polyphenols and antioxidant capacity, the classification models divided the treatments: CK and T4 and T1−T3. The contents of soluble solids, soluble protein, vitamin C, and soluble sugar of the treatment groups were higher than those of CK. The soluble sugar positively correlated with sugar−acid ratios. In the PCA-based model, T3 in the first quadrant indicated the best treatment in terms of nutritional quality. Overall, comprehensive rankings using principal component analysis (PCA) revealed T2 > T1 > T3 > T4 > CK. Therefore, the T2 treatment is a suitable for improving quality and antioxidant capacity. This study provides novel insights into improving water-use efficiency and quality in the context of water scarcity worldwide.

Random Forest Model Has the Potential for Runoff Simulation and Attribution

Quantifying the impact of climate change and human activities on runoff changes is beneficial for developing sustainable water-management strategies within the local ecosystem. Machine-learning models were widely used in scientific research; yet, whether it is applicable for quantifying the contribution of climate change and human activities to runoff changes is not well understood. To provide a new pathway, we quantified the contribution of climate change and human activities to runoff changes using a machine-learning method (random forest model) in two semi-humid basins in this study. Results show that the random forest model provides good performances for runoff simulation; the contributions of climate change and human activities to runoff changes from 1982 to 2014 were found between 6–9% and 91–94% in the Zijinguan basin, and 31–44% and 56–69% in the Daomaguan basin, respectively. Furthermore, the model performances were also compared with those of well-known elasticity-based and double-mass curve methods, and the results of these models are approximate in the investigated basins, which implies that the random forest model has the potential for runoff simulation and for quantifying the impact of climate change and human activities on runoff changes. This study provides a new methodology for studying the impact of climate change and human activities on runoff changes, and the limited numbers of parameters make this methodology important for further applications to other basins elsewhere. Nevertheless, the physical interpretation should be made with caution and more comprehensive comparison work must be performed to assess the model’s applicability.

A Framework to Support the Selection of an Appropriate Water Allocation Planning and Decision Support Scheme

Water is becoming a scarce resource in many parts of the world, leading to increased competition amongst water users. Optimized water allocation is increasingly important to balance the growing demand for water and the limited supply of accessible clean water. The literature on water allocation schemes and decision support systems, developed for application in specific water management areas or watersheds, was critically reviewed. Although the literature is rich in studies on the application of a broad range of water allocation schemes, there is a lack of information available on the methodology and process of selecting the most applicable scheme that balances the local realities and requirements of stakeholders while considering the local context with regard to the economic, social and environmental impact of water usage. In this article, a framework is presented that water management practitioners can use to select applicable water allocation planning schemes and associated decision support systems based on the characteristics and requirements of the specific water management situation. The framework was used to analyse the water supply situation in South Africa (SA), taking broader factors into account. Based on this, a generic conceptualized water allocation planning and decision support framework for a typical SA water management area is proposed.

Determining the drivers and rates of soil erosion on the Loess Plateau since 1901

Attributing soil erosion to land management and climatic drivers is important for global policy development to protect soils. The Chinese Loess Plateau is one of the most eroded areas in the world. However, there has been limited assessment of historic spatial changes in erosion rates on the Loess Plateau and the major contributors driving these spatial changes. In this study, the Revised Universal Soil Loss Equation was empirically validated and employed to assess spatially distributed historical erosion rates on the Loess Plateau from 1901 to 2016. A double mass curve attribution technique was then used to investigate the impact of land management and climatic drivers on the Loess Plateau. Decadal average erosion rates and the total area with intensive erosion (>5000 t km^-2 yr^-1) experienced a sharp increase from the 1930s to 1970s, followed by a decline to an historic low between the 1980s and 2000s. Mean erosion rates for the 2000s were 54.3% less than those of the 1970s. However, a recent increase in erosion rates was observed between 2010 and 2016. Land management change was the dominant driver of historical erosion rate changes before 2010. Extensive deforestation and farming, driven by population increase, were responsible for intensifying erosion between the 1930s and 1970s, while policy-driven conservation schemes and revegetation led to reduction thereafter. However, the recent increase in erosion between 2010 and 2016 was mainly driven by extreme rainfall events, a major concern given climate change projections. Advanced erosion control strategies are therefore required as part of integrated catchment management that both maintain water supplies for human use during dry periods while reducing erosion during storm events.

Investigating Impacts of Climate Change on Runoff from the Qinhuai River by Using the SWAT Model and CMIP6 Scenarios

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin’s development.

Projected changes in terrestrial water storage and associated flood potential across the Yangtze River basin

Terrestrial water storage is a crucial component in water cycle and plays an important role in flood formations process, particularly in a changing environment. In this study, we aim to examine the future variation of terrestrial water storage anomaly (TWSA) and associated flood potential in one of the most flood-prone regions, the Yangtze River basin in China. Using the Gravity Recovery and Climate Experiment (GRACE) data, we perform bias correction for seven general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 under three Shared Socio-economic Pathway (SSP) scenarios: SSP126, SSP245, and SSP585. The spatiotemporal characteristics of changes in future Flood Potential Index are projected and compared between the near (2031-2060) and far (2071-2100) future with reference to the historical period (1985-2014). The results show that GCMs-simulated TWSA generally agrees well with the GRACE results after downscaling and bias correction with the average correlation coefficient of 0.86, Nash-Sutcliffe efficiency of 0.73 and the root mean square error of 21.68 mm. We found that the total variance of projected TWSA is mainly sourced from the internal variability and model uncertainties, while the uncertainties in scenarios contribute relatively less. Moreover, the flood potential is projected to decline during the near future under various scenarios and even lower during the far future under SSP585 scenario. Our findings provide implications for flood control and management under climate change over high flood risk regions worldwide.

Carriage of antibiotic resistant bacteria in endangered and declining Australian pinniped pups

The rapid emergence of antimicrobial resistance (AMR) is a major concern for wildlife and ecosystem health globally. Genetic determinants of AMR have become indicators of anthropogenic pollution due to their greater association with humans and rarer presence in environments less affected by humans. The objective of this study was to determine the distribution and frequency of the class 1 integron, a genetic determinant of AMR, in both the faecal microbiome and in Escherichia coli isolated from neonates of three pinniped species. Australian sea lion (Neophoca cinerea), Australian fur seal (Arctocephalus pusillus doriferus) and long-nosed fur seal (Arctocephalus forsteri) pups from eight breeding colonies along the Southern Australian coast were sampled between 2016-2019. DNA from faecal samples (n = 309) and from E. coli (n = 795) isolated from 884 faecal samples were analysed for class 1 integrons using PCRs targeting the conserved integrase gene (intI) and the gene cassette array. Class 1 integrons were detected in A. p. doriferus and N. cinerea pups sampled at seven of the eight breeding colonies investigated in 4.85% of faecal samples (n = 15) and 4.52% of E. coli isolates (n = 36). Integrons were not detected in any A. forsteri samples. DNA sequencing of the class 1 integron gene cassette array identified diverse genes conferring resistance to four antibiotic classes. The relationship between class 1 integron carriage and the concentration of five trace elements and heavy metals was also investigated, finding no significant association. The results of this study add to the growing evidence of the extent to which antimicrobial resistant bacteria are polluting the marine environment. As AMR determinants are frequently associated with bacterial pathogens, their occurrence suggests that these pinniped species are vulnerable to potential health risks. The implications for individual and population health as a consequence of AMR carriage is a critical component of ongoing health investigations.

Multi-objective optimization of water resources allocation in Han River basin (China) integrating efficiency, equity and sustainability

The hydrological cycle, affected by climate change and rapid urbanization in recent decades, has been altered to some extent and further poses great challenges to three key factors of water resources allocation (i.e., efficiency, equity and sustainability). However, previous studies usually focused on one or two aspects without considering their underlying interconnections, which are insufficient for interaction cognition between hydrology and social systems. This study aims at reinforcing water management by considering all factors simultaneously. The efficiency represents the total economic interests of domesticity, industry and agriculture sectors, and the Gini coefficient is introduced to measure the allocation equity. A multi-objective water resources allocation model was developed for efficiency and equity optimization, with sustainability (the river ecological flow) as a constraint. The Non-dominated sorting genetic algorithm II (NSGA-II) was employed to derive the Pareto front of such a water resources allocation system, which enabled decision-makers to make a scientific and practical policy in water resources planning and management. The proposed model was demonstrated in the middle and lower Han River basin, China. The results indicate that the Pareto front can reflect the conflicting relationship of efficiency and equity in water resources allocation, and the best alternative chosen by cost performance method may provide rich information as references in integrated water resources planning and management.

OUP accepted manuscript

Extreme events have increased in frequency globally, with a simultaneous surge in scientific interest about their ecological responses, particularly in sensitive freshwater, coastal, and marine ecosystems. We synthesized observational studies of extreme events in these aquatic ecosystems, finding that many studies do not use consistent definitions of extreme events. Furthermore, many studies do not capture ecological responses across the full spatial scale of the events. In contrast, sampling often extends across longer temporal scales than the event itself, highlighting the usefulness of long-term monitoring. Many ecological studies of extreme events measure biological responses but exclude chemical and physical responses, underscoring the need for integrative and multidisciplinary approaches. To advance extreme event research, we suggest prioritizing pre- and postevent data collection, including leveraging long-term monitoring; making intersite and cross-scale comparisons; adopting novel empirical and statistical approaches; and developing funding streams to support flexible and responsive data collection.

Variation in Extreme Temperature and Its Instability in China

In this study, the instability of extreme temperatures is defined as the degree of perturbation of the spatial and temporal distribution of extreme temperatures, which is to show the uncertainty of the intensity and occurrence of extreme temperatures in China. Based on identifying the extreme temperatures and by analyzing their variability, we refer to the entropy value in the entropy weight method to study the instability of extreme temperatures. The results show that TXx (annual maximum value of daily maximum temperature) and TNn (annual minimum value of daily minimum temperature) in China increased at 0.18 °C/10 year and 0.52 °C/10 year, respectively, from 1966 to 2015. The interannual data of TXx’ occurrence (CTXx) and TNn’ occurrence (CTNn), which are used to identify the timing of extreme temperatures, advance at 0.538 d/10 year and 1.02 d/10 year, respectively. In summary, extreme low-temperature changes are more sensitive to global warming. The results of extreme temperature instability show that the relative instability region of TXx is located in the middle and lower reaches of the Yangtze River basin, and the relative instability region of TNn is concentrated in the Yangtze River, Yellow River, Langtang River source area and parts of Tibet. The relative instability region of CTXx instability is distributed between 105° E and 120° E south of the 30° N latitude line, while the distribution of CTNn instability region is more scattered; the TXx’s instability intensity is higher than TNn’s, and CTXx’s instability intensity is higher than CTNn’s. We further investigate the factors affecting extreme climate instability. We also find that the increase in mean temperature and the change in the intensity of the El Niño phenomenon has significant effects on extreme temperature instability.

Recent changes in heatwaves and maximum temperatures over a complex terrain in the Himalayas

The temperature response to anthropogenic global warming and forest cover changes is dependent on regional climatic characteristics. It is challenging to segregate the impacts of the two anthropogenic changes on local temperatures and heatwaves over complex mountainous regions. Here we present estimates of regional and local heat stress responses to the recent global climate change and local forest cover loss in complex terrain in the Himalayas using a satellite-based high-resolution land-surface temperature dataset. We find large-scale decreasing trends in the observed frequency of heatwaves and heat days, and localized increases in urbanized and high-elevation regions. Our results show large-scale significant decreasing trends in annual maximum and mean surface temperatures over the period 2003-2019. In locations that have witnessed large-scale forest losses, the declines in the surface temperatures were steeper compared to no-loss regions. We develop a regional multiple linear regression model to estimate the regional and local temperature responses to global climatic change and to segregate them from the response to forest cover losses. Our model estimates a regional decrease of about 2.0 °C in annual maximum temperature over the recent 2003-2019 period, which is locally modulated by the extent of urbanization, forest cover, and elevation. At the locations of intense deforestation, our model successfully predicts a steeper decrease in maximum surface temperature, and estimates the temperature response due to forest loss, after controlling for elevation and initial forest cover. The local cooling effect due to deforestation was reaffirmed by comparing the regions with contrasting forest cover losses. The results suggest that forest clearing amplifies the anthropogenic climate change over the region.

Hydrological Response of the Kunhar River Basin in Pakistan to Climate Change and Anthropogenic Impacts on Runoff Characteristics

Pakistan is amongst the most water-stressed countries in the world, with changes in the frequency of extreme events, notably droughts, under climate change expected to further increase water scarcity. This study examines the impacts of climate change and anthropogenic activities on the runoff of the Kunhar River Basin (KRB) in Pakistan. The Mann Kendall (MK) test detected statistically significant increasing trends in both precipitation and evapotranspiration during the period 1971–2010 over the basin, but with the lack of a statistically significant trend in runoff over the same time-period. Then, a change-point analysis identified changes in the temporal behavior of the annual runoff time series in 1996. Hence, the time series was divided into two time periods, i.e., prior to and after that change: 1971–1996 and 1997–2010, respectively. For the time-period prior to the change point, the analysis revealed a statistically significant increasing trend in precipitation, which is also reflected in the runoff time series, and a decreasing trend in evapotranspiration, albeit lacking statistical significance, was observed. After 1996, however, increasing trends in precipitation and runoff were detected, but the former lacked statistical significance, while no trend in evapotranspiration was noted. Through a hydrological modelling approach reconstructing the natural runoff of the KRB, a 16.1 m3/s (or 15.3%) reduction in the mean flow in the KRB was simulated for the period 1997–2010 in comparison to the period 1971–1996. The trend analyses and modeling study suggest the importance of anthropogenic activities on the variability of runoff over KRB since 1996. The changes in streamflow caused by irrigation, urbanization, and recreational activities, in addition to climate change, have influenced the regional water resources, and there is consequently an urgent need to adapt existing practices for the water requirements of the domestic, agricultural and energy sector to continue being met in the future.

Farmers’ Awareness in the Context of Climate Change: An Underutilized Way for Ensuring Sustainable Farmland Adaptation and Surface Water Quality

Simulations using the Crop Water and Irrigation Requirements model (CROPWAT), show that the projected climatic changes over the period from 2026 to 2050 in the Yanyun irrigation district, Yangzhou, China, will cause the paddy lands there to lose about 12.4% to 37.4%, and 1.6% to 45.6%, of their future seasonal rainwater in runoff under the Representative Concentration Pathways (RCP45 and RCP85), respectively. This may increase future irrigation requirements (IRs), alongside threatening the quality of adjacent water bodies. The CROPWAT simulations were re-run after increasing the Surface Storage Capacity (SSC) of the land by 50% and 100% of its baseline value. The results state that future rainwater runoff will be reduced by up to 76% and 100%, and 53% and 100% when the SSC is increased by 50% and 100%, under RCP45 and RCP85, respectively. This mitigates the future increase in IRs (e.g., under RCP45, up to about 11% and 16% of future IRs will be saved when increasing the SSC by 50% and 100%, respectively), thus saving the adjacent water bodies from the contaminated runoff from these lands. Adjusting the SSC of farmlands is an easy physical approach that can be practiced by farmers, and therefore educating them on how to follow up the rainfall forecast and then adjust the level of their farmlands’ boundaries according to these forecasts may help in the self-adaptation of vast areas of farmlands to climate change. These findings will help water users conserve agricultural water resources (by mitigating the future increase in IRs) alongside ensuring better quality for adjacent water bodies (by decreasing future runoff from these farmlands). Increasing farmers’ awareness, an underutilized approach, is a potential tool for ensuring improved agricultural circumstances amid projected climate changes and preserving the available water resources.