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Groundwater sustains human well-being and ecosystems functioning. Many regions in Europe have experienced declining groundwater levels caused by decreasing groundwater recharge (GWR) or increasing groundwater abstractions (GWAs). These changes can lead to groundwater-related stress, threatening ecosystems and water supplies. Existing groundwater stress indicators estimate stress during a given period but do not address how stress changes or show the uncertainty of future stress. We propose a novel indicator of future groundwater stress (GWSI) due to changes in GWR and GWA and, thus, the alteration of long-term mean annual groundwater discharge (GWD). Groundwater stress is defined as any alteration in GWD since ecosystems are adapted to an equilibrium state. Focusing on decreasing GWD, which is generally more harmful than increasing GWD, we quantified the future GWSI in Europe by integrating scenarios of GWR and GWA in 2070–2099. GWR was evaluated using an ISIMIP2b multi-model ensemble of eight global hydrological models driven by the output of four global climate models under two greenhouse gas emission scenarios. GWA scenarios for irrigation, domestic and manufacturing sectors were combined with the GWR projections to generate an ensemble of GWSIs, simplified into three groundwater stress scenarios (high, intermediate, low). Projected GWSIs vary significantly among the scenarios. For the high-stress scenario, 58% of Europe’s land area is projected to experience a GWD decrease of at least 25% under RCP8.5 compared to 38% under RCP2.6, while the respective values are 26 and 1% for the intermediate-stress scenario. Groundwater demand management alone might not prevent GWD declines under the high-stress and intermediate scenarios, particularly under RCP8.5. Therefore, climate change mitigation might imperative for reducing the decline of GWD, especially in Eastern and Southeastern Europe, where changes in GWR are projected to be the primary cause of declining GWD (in the high abstraction scenario under RCP8.5). Under RCP2.6, reductions in GWAs by 25–75% might balance a GWD decline in parts of Spain and Italy where GWAs are high, even in the high-stress scenario. In line with the precautionary principle, we recommend adapting to the high-stress scenario to minimize harm to the beneficiaries of groundwater.

Background/Objectives: Low back pain (LBP) is a widespread public health issue, with myofascial pain syndrome (MPS) being a common cause, affecting 67–100% of patients. However, there are significant challenges in the diagnostic process due to the subjective and unreliable nature of manual palpation. Focused Extracorporeal Shockwave Therapy (F-ESWT), traditionally used for MPS treatment, offers a reproducible and non-invasive mechanical stimulus, making it a potential diagnostic tool. This study evaluated F-ESWT’s diagnostic efficiency in chronic LBP patients by focusing on “recognition” and “referral” of pain. Methods: twenty-eight participants were screened for myofascial trigger points (MTrPs) in the lumbar, gluteal, and thigh regions. Identified MTrPs were stimulated using F-ESWT, and patient feedback was recorded. Results: data showed high diagnostic accuracy for muscles such as the quadratus lumborum, gluteus medius, and gluteus minimus muscles, achieving “referral” rates of 96%, 95%, and 92% and “recognition” rates of 84%, 86%, and 85%, respectively. Other structures like adductors, iliopsoas, erector spinae, and biceps femoris muscle showed consistent but lower diagnostic rates. Conclusions: the study’s findings indicate that F-ESWT effectively reproduces pain patterns, offering a precise, reproducible, and non-invasive diagnostic approach for MPS in chronic LBP. However, they also highlight the necessity for detailed diagnostic criteria in managing myofascial pain.

ObjectivesAlthough the Perceval sutureless aortic valve bioprosthesis presents a feasible alternative to conventional aortic valve prostheses, the extent of its applicability with respect to technical considerations for a real-world patient collective is still under debate.MethodsOne hundred patients received the Perceval prosthesis [males: 59; age: 72.5 (7.3–79) years] between December 2015 and February 2023 [EuroSCORE II: 2.8 (1.7–5.4)] for an aortic valve replacement (AVR), with additional concomitant procedures, for underlying severe aortic valve stenosis [n = 93 (93)], endocarditis [n = 5 (5)], and redo AVR [n = 7 (7)] including a prior surgical AVR [n = 4 (4)] and a failed transcatheter aortic valve implantation [n = 3 (3)]. Surgery was conducted primarily by median sternotomy [n = 71 (71)] and, alternatively, by the upper hemisternotomy approach [n = 29 (29)].ResultsOver a median follow-up time of 36.5 (16.5–53) months, eight patients (8%) underwent postoperative pacemaker implantation, with five (5%) due to high-grade atrioventricular block, while nine patients experienced a stroke (9%). The median values of maximum and mean gradients across all valve sizes were 22 (18–27.5) mmHg and 10 (13–18) mmHg, respectively. Two patients (2%) had moderate and one (1%) had severe paravalvular leakage, with the latter presenting the only case of underlying valve migration and induced redo AVR with valve explantation 2 days following initial surgery. Thirty-day mortality (and overall mortality) was 5% and 26%, respectively.ConclusionThe implantation of the Perceval bioprosthesis is feasible for a variety of indications, with excellent hemodynamic results and low complication rates in a real-world high-risk patient collective.

Abstract In recent sea level studies, discrepancies have arisen in ocean mass observations obtained from the Gravity Recovery and Climate Experiment and its successor, GRACE Follow-On, with GRACE estimates consistently appearing lower than density-corrected ocean volume observations since 2015. These disparities have raised concerns about potential systematic biases in sea-level observations, with significant implications for our understanding of this essential climate variable. Here, we reconstruct the global and regional ocean mass change through models of ice and water mass changes on land and find that it closely aligns with both GRACE and density-corrected ocean volume observations after implementing recent adjustments to the wet troposphere correction and halosteric sea level. While natural variability in terrestrial water storage is important on interannual timescales, we find that the net increase in ocean mass over 20 years can be almost entirely attributed to ice wastage and human management of water resources.

Significant regional disparities exist in the time left to prepare for unprecedented drought and how much we can buy time depending on climate scenarios. Specific regions pass this timing by the middle of 21st century even with stringent mitigation.

Global hydrological models (GHMs) are widely used to assess the impact of climate change on streamflow, floods, and hydrological droughts. For the ‘model evaluation and impact attribution’ part of the current round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a), modelling teams generated historical simulations based on observed climate and direct human forcings with updated model versions. Here we provide a comprehensive evaluation of daily and maximum annual discharge based on ISIMIP3a simulations from nine GHMs by comparing the simulations to observational data from 644 river gauge stations. We also assess low flows and the effects of different river routing schemes. We find that models can reproduce variability in daily and maximum annual discharge, but tend to overestimate both quantities, as well as low flows. Models perform better at stations in wetter areas and at lower elevations. Discharge routed with the river routing model CaMa-Flood can improve the performance of some models, but for others, variability is overestimated, leading to reduced model performance. This study indicates that areas for future model development include improving the simulation of processes in arid regions and cold dynamics at high elevations. We further suggest that studies attributing observed changes in discharge to historical climate change using the current model ensemble will be most meaningful in humid areas, at low elevations, and in places with a regular seasonal discharge as these are the regions where the underlying dynamics seem to be best represented.

River networks are among Earth’s most threatened hot-spots of biodiversity and provide key ecosystem services (e.g., supply drinking water and food, climate regulation) essential to sustaining human well-being. Climate change and increased human water use are causing more rivers and streams to dry, with devastating impacts on biodiversity and ecosystem services. Currently, more than a half of the global river networks consist of drying channels, and these are expanding dramatically. However, drying river networks (DRNs) have received little attention from scientists and policy makers, and the public is unaware of their importance. Consequently, there is no effective integrated biodiversity conservation or ecosystem management strategy of DRNs.A multidisciplinary team of 25 experts from 11 countries in Europe, South America, China and the USA will build on EU efforts to assess the cascading effects of climate change on biodiversity, ecosystem functions and ecosystem services of DRNs through changes in flow regimes and water use. DRYvER (DRYing riVER networks) will gather and upscale empirical and modelling data from nine focal DRNs (case studies) in Europe (EU) and Community of Latin American and Caribbean States (CELAC) to develop a meta-system framework applicable to Europe and worldwide. It will also generate crucial knowledge-based strategies, tools and guidelines for economically-efficient adaptive management of DRNs. Working closely with stakeholders and end-users, DRYvER will co-develop strategies to mitigate and adapt to climate change impacts in DRNs, integrating hydrological, ecological (including nature-based solutions), socio-economic and policy perspectives. The end results of DRYvER will contribute to reaching the objectives of the Paris Agreement and placing Europe at the forefront of research on climate change.

Impact models projections are used in integrated assessments of climate change. Here the authors test systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions.

Study region: Eight main river basins covering the major part of Ukraine. Study focus: The main aim of this study was to provide an assessment of climate change impacts on water availability across Ukraine using global hydrological models. Six global hydrological models were evaluated for their performance in the historical period in the basins under study. Future river discharge was simulated by using the best performing model and all available models driven by bias-corrected GCM projections from the ISIMIP project under the RCP 2.6 and RCP 8.5 scenarios. New hydrological insights for the region: The results show precipitation increase up to 10 % under RCP 2.6, and variable changes from -14 % to +10 % under RCP 8.5 by the end of the century. The projections show the decreasing mean annual river discharge in the majority of basins for the middle (2040–2070) and far future (2071–2100) periods under both RCPs, and the decrease is stronger under RCP 8.5. The seasonal changes are characterised by a decrease in summer and a small to moderate increase in winter months in most of the basins. The highest reduction of mean annual discharge was projected for the Pripyat, Southern Bug and Dniester basins, reaching up to -30 % to the end of the century under RCP 8.5.

Giant cell arteritis is an inflammatory vasculopathy of unknown etiology that typically affects the carotid artery and its branches. Symptomatic involvement of upper extremity arteries is uncommon. We report a case of a 70-year-old woman with polymyalgia rheumatica who presented with critical arm ischemia, constitutional symptoms, and elevated erythrocyte sedimentation rate. Urgent revascularization by a carotid-brachial artery bypass was performed. Histopathologic evaluation of a specimen obtained intraoperatively from the occluded axillary artery confirmed the diagnosis, and corticosteroid therapy was initiated. Large-vessel vasculitis should be considered a rare differential diagnosis in occlusive disease of the upper extremity. Keywords: Giant cell arteritis, Arm ischemia, Vasculitis

Extracorporeal Shockwaves Treatment is considered an effective therapeutic option for plantar fasciitis, but the standard application in the medial insertion of the plantar fascia on the calcaneus has provided ambiguous evidences. In this case, a 63-year man with plantar fasciitis was treated in a 3-session program and Foot and Ankle Outcome Scale and Foot Functional Index questionnaires were chosen for the clinical outcome evaluation. The therapy was focused on the active trigger or myofascial points of the leg, thigh and pelvis in order to return the correct equilibrium of the myofascial system of the whole limb. The patient has already reported an improvement after the second session (FAOS: 76 vs 33, FFI: 85%) which was confirmed in the third one and in the 1-month follow up (FAOS: 79, FFI: 6%) Results suggest that plantar fasciitis may be due to proximal rigidity or tension of the fascia and a global approach using ESWT may have a similar or better outcome respect to the standard application.

Droughts are anticipated to intensify in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought indices, makes it difficult to compare drought assessments. This issue is widely known, but its relative importance has never been quantitatively evaluated in comparison to other sources of uncertainty. Here, encompassing three drought categories (meteorological, agricultural, and hydrological droughts) with four temporal scales of interest, we evaluated changes in the drought frequency using multi-model and multi-scenario simulations to identify areas where the definition issue could result in pronounced uncertainties and to what extent. We investigated the disagreement in the signs of changes between drought definitions and decomposed the variance into four main factors: drought definitions, greenhouse gas concentration scenarios, global climate models, and global water models, as well as their interactions. The results show that models were the primary sources of variance over 82% of the global land area. On the other hand, the drought definition was the dominant source of variance in the remaining 17%, especially in parts of northern high-latitudes. Our results highlight specific regions where differences in drought definitions result in a large spread among projections, including areas showing opposite signs of significant changes. At a global scale, 7% of the variance resulted independently from the definition issue, and that value increased to 44% when 1st and 2nd order interactions were considered. The quantitative results suggest that by clarifying hydrological processes or sectors of interest, one could avoid these uncertainties in drought assessments to obtain a clearer picture of future drought change.

Future flood and drought risks have been predicted to transition from moderate to high levels at global warmings of 1.5 °C and 2.0 °C above pre-industrial levels, respectively. However, these results were obtained by approximating the equilibrium climate using transient simulations with steadily warming. This approach was recently criticised due to the warmer global land temperature and higher mean precipitation intensities of the transient climate in comparison with the equilibrium climate. Therefore, it is unclear whether floods and droughts projected under a transient climate can be systematically substituted for those occurring in an equilibrated climate. Here, by employing a large ensemble of global hydrological models (HMs) forced by global climate models, we assess the validity of estimating flood and drought characteristics under equilibrium climates from transient simulations. Differences in flood characteristics under transient and equilibrium climates could be largely ascribed to natural variability, indicating that the floods derived from a transient climate reasonably approximate the floods expected in an equally warm, equilibrated climate. By contrast, significant differences in drought intensity between transient and equilibrium climates were detected over a larger global land area than expected from natural variability. Despite the large differences among HMs in representing the low streamflow regime, we found that the drought intensities occurring under a transient climate may not validly represent the intensities in an equally warm equilibrated climate for approximately 6.7% of the global land area.

Abstract. This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Clarifying characteristics of hazards and risks of climate change at 2 °C and 1.5 °C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2 °C and 1.5 °C warming simulations. In the 2 °C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world’s population is projected to experience a present day 1-in-10 year hot day event every other year at 2 °C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO _2 emissions, low-income and high vulnerability. Limiting global warming to 1.5 °C, compared to 2 °C, is projected to lower increases in the four hazard indicators especially in those regions.

The accurate knowledge of the groundwater storage variation (ΔGWS) is essential for reliable water resource assessment, particularly in arid and semi-arid environments (e.g., Australia, the North China Plain (NCP)) where water storage is significantly affected by human activities and spatiotemporal climate variations. The large-scale ΔGWS can be simulated from a land surface model (LSM), but the high model uncertainty is a major drawback that reduces the reliability of the estimates. The evaluation of the model estimate is then very important to assess its accuracy. To improve the model performance, the terrestrial water storage variation derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is commonly assimilated into LSMs to enhance the accuracy of the ΔGWS estimate. This study assimilates GRACE data into the PCRaster Global Water Balance (PCR-GLOBWB) model. The GRACE data assimilation (DA) is developed based on the three-dimensional ensemble Kalman smoother (EnKS 3D), which considers the statistical correlation of all extents (spatial, temporal, vertical) in the DA process. The ΔGWS estimates from GRACE DA and four LSM simulations (PCR-GLOBWB, the Community Atmosphere Biosphere Land Exchange (CABLE), the Water Global Assessment and Prognosis Global Hydrology Model (WGHM), and World-Wide Water (W3)) are validated against the in situ groundwater data. The evaluation is conducted in terms of temporal correlation, seasonality, long-term trend, and detection of groundwater depletion. The GRACE DA estimate shows a significant improvement in all measures, notably the correlation coefficients (respect to the in situ data) are always higher than the values obtained from model simulations alone (e.g., ~0.15 greater in Australia, and ~0.1 greater in the NCP). GRACE DA also improves the estimation of groundwater depletion that the models cannot accurately capture due to the incorrect information of the groundwater demand (in, e.g., PCR-GLOBWB, WGHM) or the unavailability of a groundwater consumption routine (in, e.g., CABLE, W3). In addition, this study conducts the inter-comparison between four model simulations and reveals that PCR-GLOBWB and CABLE provide a more accurate ΔGWS estimate in Australia (subject to the calibrated parameter) while PCR-GLOBWB and WGHM are more accurate in the NCP (subject to the inclusion of anthropogenic factors). The analysis can be used to declare the status of the ΔGWS estimate, as well as itemize the possible improvements of the future model development.

To support implementation of the Paris Agreement, the new HAPPI ensemble of 20 bias-corrected simulations of four climate models was used to drive two global hydrological models, WaterGAP and LPJmL, for assessing freshwater-related hazards and risks in worlds approximately 1.5 °C and 2 °C warmer than pre-industrial. Quasi-stationary HAPPI simulations are better suited than transient CMIP-like simulations for assessing hazards at the two targeted long-term global warming (GW) levels. We analyzed seven hydrological hazard indicators that characterize freshwater-related hazards for humans, freshwater biota and vegetation. Using a strict definition for significant differences, we identified for all but one indicator that areas with either significantly wetter or drier conditions (calculated as percent changes from 2006–2015) are smaller in the 1.5 °C world. For example, 7 day high flow is projected to increase significantly on 11% and 21% of the global land area at 1.5 °C and 2 °C, respectively. However, differences between hydrological hazards at the two GW levels are significant on less than 12% of the area. GW affects a larger area and more people by increases—rather than by decreases—of mean annual and 1-in-10 dry year streamflow, 7 day high flow, and groundwater recharge. The opposite is true for 7 day low flow, maximum snow storage, and soil moisture in the driest month of the growing period. Mean annual streamflow shows the lowest projected percent changes of all indicators. Among country groups, low income countries and lower middle income countries are most affected by decreased low flows and increased high flows, respectively, while high income countries are least affected by such changes. The incremental impact between 1.5 °C and 2 °C on high flows would be felt most by low income and lower middle income countries, the effect on soil moisture and low flows most by high income countries.

Actual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%–40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.

Global-scale hydrological models are routinely used to assess water scarcity, flood hazards and droughts worldwide. Recent efforts to incorporate anthropogenic activities in these models have enabled more realistic comparisons with observations. Here we evaluate simulations from an ensemble of six models participating in the second phase of the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP2a). We simulate monthly runoff in 40 catchments, spatially distributed across eight global hydrobelts. The performance of each model and the ensemble mean is examined with respect to their ability to replicate observed mean and extreme runoff under human-influenced conditions. Application of a novel integrated evaluation metric to quantify the models’ ability to simulate timeseries of monthly runoff suggests that the models generally perform better in the wetter equatorial and northern hydrobelts than in drier southern hydrobelts. When model outputs are temporally aggregated to assess mean annual and extreme runoff, the models perform better. Nevertheless, we find a general trend in the majority of models towards the overestimation of mean annual runoff and all indicators of upper and lower extreme runoff. The models struggle to capture the timing of the seasonal cycle, particularly in northern hydrobelts, while in southern hydrobelts the models struggle to reproduce the magnitude of the seasonal cycle. It is noteworthy that over all hydrological indicators, the ensemble mean fails to perform better than any individual model—a finding that challenges the commonly held perception that model ensemble estimates deliver superior performance over individual models. The study highlights the need for continued model development and improvement. It also suggests that caution should be taken when summarising the simulations from a model ensemble based upon its mean output.

We performed an intercomparison of river discharge regulated by dams under four meteorological forcings among five global hydrological models for a historical period by simulation. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri–Mississippi and Green–Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the river's course to critically examine the performance of hydrological models because the performance can vary with the locations.

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971–2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.