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Water scarcity is rapidly increasing in many regions. In a novel, multi-model assessment, we examine how human interventions (HI: land use and land cover change, man-made reservoirs and human water use) affected monthly river water availability and water scarcity over the period 1971 - 2010. Here we show that HI drastically change the critical dimensions of water scarcity, aggravating water scarcity for 8.8%(7.4 - 16.5 %) ) of the global population but alleviating it for another 8.3 % (6.4 -15.8 %). Positive impacts of HI mostly occur upstream, whereas HI aggravate water scarcity downstream; HI cause water scarcity to travel downstream. Attribution of water scarcity changes to HI components is complex and varies among the hydrological models. Seasonal variation in impacts and dominant HI components is also substantial. A thorough consideration of the spatially and temporally varying interactions among HI components and of uncertainties is therefore crucial for the success of water scarcity adaptation by HI.

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge-however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

A global water scarcity assessment for the 21st century was conducted under the latest socio-economic scenario for global change studies, namely Shared Socio-economic Pathways (SSPs). SSPs depict five global situations with substantially different socio-economic conditions. In the accompanying paper, a water use scenario compatible with the SSPs was developed. This scenario considers not only quantitative socio-economic factors such as population and electricity production but also qualitative ones such as the degree of technological change and overall environmental consciousness. In this paper, water availability and water scarcity were assessed using a global hydrological model called H08. H08 simulates both the natural water cycle and major human activities such as water abstraction and reservoir operation. It simulates water availability and use at daily time intervals at a spatial resolution of 0.5° × 0.5°. A series of global hydrological simulations were conducted under the SSPs, taking into account different climate policy options and the results of climate models. Water scarcity was assessed using an index termed the Cumulative Abstraction to Demand ratio, which is expressed as the accumulation of daily water abstraction from a river divided by the daily consumption-based potential water demand. This index can be used to express whether renewable water resources are available from rivers when required. The results suggested that by 2071–2100 the population living under severely water-stressed conditions for SSP1-5 will reach 2588–2793 × 106 (39–42% of total population), 3966–4298 × 106 (46–50%), 5334–5643 × 106 (52–55%), 3427–3786 × 106 (40–45%), 3164–3379 × 106 (46–49%) respectively, if climate policies are not adopted. Even in SSP1 (the scenario with least change in water use and climate) global water scarcity increases considerably, as compared to the present-day. This is mainly due to the growth in population and economic activity in developing countries, and partly due to hydrological changes induced by global warming.

Human activity has a profound influence on river discharges, hydrological extremes and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the simulation of mean, high- and low-flows. The analysis is performed for 471 gauging stations across the globe for the period 1971-2010. We find that the inclusion of HIP improves the performance of the GHMs, both in managed and near-natural catchments. For near-natural catchments, the improvement in performance results from improvements in incoming discharges from upstream managed catchments. This finding is robust across the GHMs, although the level of improvement and the reasons for it vary greatly. The inclusion of HIP leads to a significant decrease in the bias of the long-term mean monthly discharge in 36%-73% of the studied catchments, and an improvement in the modeled hydrological variability in 31%-74% of the studied catchments. Including HIP in the GHMs also leads to an improvement in the simulation of hydrological extremes, compared to when HIP is excluded. Whilst the inclusion of HIP leads to decreases in the simulated high-flows, it can lead to either increases or decreases in the low-flows. This is due to the relative importance of the timing of return flows and reservoir operations as well as their associated uncertainties. Even with the inclusion of HIP, we find that the model performance is still not optimal. This highlights the need for further research linking human management and hydrological domains, especially in those areas in which human impacts are dominant. The large variation in performance between GHMs, regions and performance indicators, calls for a careful selection of GHMs, model components and evaluation metrics in future model applications.

A novel global water scarcity assessment for the 21st century is presented in a two-part paper. In this first paper, water use scenarios are presented for the latest global hydrological models. The scenarios are compatible with the socio-economic scenarios of the Shared Socio-economic Pathways (SSPs), which are a part of the latest set of scenarios on global change developed by the integrated assessment, the IAV (climate change impact, adaptation, and vulnerability assessment), and the climate modeling community. The SSPs depict five global situations based on substantially different socio-economic conditions during the 21st century. Water use scenarios were developed to reflect not only quantitative socio-economic factors, such as population and electricity production, but also key qualitative concepts such as the degree of technological change and overall environmental consciousness. Each scenario consists of five factors: irrigated area, crop intensity, irrigation efficiency, and withdrawal-based potential industrial and municipal water demands. The first three factors are used to estimate the potential irrigation water demand. All factors were developed using simple models based on a literature review and analysis of historical records. The factors are grid-based at a spatial resolution of 0.5° × 0.5° and cover the whole 21st century in five-year intervals. Each factor shows wide variation among the different global situations depicted: the irrigated area in 2085 varies between 2.7 × 106 and 4.5 × 106 km2, withdrawal-based potential industrial water demand between 246 and 1714 km3 yr−1, and municipal water between 573 and 1280 km3 yr−1. The water use scenarios can be used for global water scarcity assessments that identify the regions vulnerable to water scarcity and analyze the timing and magnitude of scarcity conditions.

Background:Mikulicz’s disease (MD) has been considered as one manifestation of Sjögren’s syndrome (SS). Recently, it has also been considered as an IgG4-related disorder.Objective:To determine the differences between IgG4-related disorders including MD and SS.Methods:A study was undertaken to investigate patients with MD and IgG4-related disorders registered in Japan and to set up provisional criteria for the new clinical entity IgG4-positive multiorgan lymphoproliferative syndrome (IgG4+MOLPS). The preliminary diagnostic criteria include raised serum levels of IgG4 (>135 mg/dl) and infiltration of IgG4+ plasma cells in the tissue (IgG4+/IgG+ plasma cells >50%) with fibrosis or sclerosis. The clinical features, laboratory data and pathologies of 64 patients with IgG4+MOLPS and 31 patients with typical SS were compared.Results:The incidence of xerostomia, xerophthalmia and arthralgia, rheumatoid factor and antinuclear, antiSS-A/Ro and antiSS-B/La antibodies was significantly lower in patients with IgG4+MOLPS than in those with typical SS. Allergic rhinitis and autoimmune pancreatitis were significantly more frequent and total IgG, IgG2, IgG4 and IgE levels were significantly increased in IgG4+MOLPS. Histological specimens from patients with IgG4+MOLPS revealed marked IgG4+ plasma cell infiltration. Many patients with IgG4+MOLPS had lymphocytic follicle formation, but lymphoepithelial lesions were rare. Few IgG4+ cells were seen in the tissue of patients with typical SS. Thirty-eight patients with IgG4+MOLPS treated with glucocorticoids showed marked clinical improvement.Conclusion:Despite similarities in the involved organs, there are considerable clinical and pathological differences between IgG4+MOLPS and SS. Based on the clinical features and good response to glucocorticoids, we propose a new clinical entity: IgG4+MOLPS.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Background:IgG4-related hypophysitis (IgG4-RH) represents central nervous system involvement in IgG4-related diseases (IgG4-RD). However, its diagnosis is challenging in many patients, primarily due to the difficulty in obtaining biopsies. There are few case reports of IgG4-RH, and much remains unknown about its pathology.Objectives:To discuss the clinical characteristics of 17 patients diagnosed with IgG4-RH among five institutions including our hospital.Methods:Using EZR statistical software, we analyzed the clinical characteristics of 17 IgG4-RH patients diagnosed at Kanazawa Medical University Hospital, Kanazawa University Hospital, Toyama University Hospital, Sapporo Medical University Hospital, and Nagaoka Red Cross Hospital.Results:Among 877 patients diagnosed with IgG4-RD at these centers, 17 (1.9%) were diagnosed with IgG4-RH. Of these ten (58.8%, median age 67 yrs.) were men. Pituitary lesions were present in ten patients (58.8%) upon IgG4-RD diagnosis. Diabetes insipidus was present in nine (52.9%), fatigue in six (35.3%) headache in two (11.8%), and ocular symptoms in two patients (11.8%). The median number of affected organs in IgG4-RD was four, with the salivary glands and lymph nodes (11 patients, 64.7%), and lungs (nine patients, 52.9%) being the most commonly involved. Blood tests revealed decreased ACTH, TSH, LH, or GH in eight patients (50.0%) and a decrease in ≧2 hormones in two (12.5%). ADH was decreased in all 14 measured patients. Imaging studies showed pituitary enlargement in 13 patients (81.3%). Pituitary biopsy was performed in only three patients (18.8%). A total of 12 patients (70.6%) met the comprehensive diagnostic criteria for IgG4-RD 2011, and 13 (76.5%) had an ACR/EULAR classification criteria score of ≧20. Prednisolone (PSL) treatment or increased dosage was initiated in 13 patients, with one starting hydrocortisone. The median initial PSL dose was 30 mg/day. Desmopressin treatment for diabetes insipidus was provided to six patients. Among the 16 patients receiving treatment, 14 (87.5%) showed symptom improvement. No relapses occurred during the observation period, and no patients died.Conclusion:IgG4-RH is a relatively rare lesion among IgG4-RD, and symptoms due to hormonal abnormalities are nonspecific and may be overlooked. All patients exhibited decreased ADH levels, suggesting that measuring hormone levels in IgG4-RD patients may prevent potential pituitary lesions from being overlooked. Maintenance therapy with glucocorticoids was administered to most patients, contributing to a low relapse rate.REFERENCES:NIL.Table 1.Figure 1.Acknowledgements:NIL.Disclosure of Interests:None declared.

It is now widely recognized that climate change affects multiple sectors in virtually every part of the world. Impacts on one sector may influence other sectors, including seemingly remote ones, which we call “interconnections of climate risks.” While a substantial number of climate risks are identified in the Intergovernmental Panel on Climate Change Fifth Assessment Report, there have been few attempts to explore the interconnections between them in a comprehensive way. To fill this gap, we developed a methodology for visualizing climate risks and their interconnections based on a literature survey. Our visualizations highlight the need to address climate risk interconnections in impact and vulnerability studies. Our risk maps and flowcharts show how changes in climate impact natural and socioeconomic systems, ultimately affecting human security, health, and well‐being. We tested our visualization approach with potential users and identified likely benefits and issues. Our methodology can be used as a communication tool to inform decision makers, stakeholders, and the general public of the cascading risks that can be triggered by climate change. Plain Language Summary The paper demonstrates in a most holistic manner how climate change can generate various risks and how they are actually interconnected. Based on a literature survey using the Intergovernmental Panel on Climate Change Fifth Assessment Report, we identified 91 climate risks and 253 causal relationships among them and graphically drew such interconnected risks. We found that changes in the climate system impact the natural and socioeconomic system, influencing ultimately human security, health, and well‐being. This indicates that climate change can trigger a cascade of impacts across sectors. Our findings point to the need to address the climate risk interconnections in impact and vulnerability studies. We tested our visualization approach with potential users and identified likely benefits and issues. The implications of our study go beyond science. Our study is useful to inform stakeholders of a broad yet fresh perspective of climate risks that have not been presented before. Key Points The paper developed a methodology for visualizing how climate change can generate various risks and how they can be interconnected We identified 91 climate risks and 253 causal relationships among them based on a literature survey and graphically presented the interconnected risks We found that changes in the climate system impact natural and socioeconomic systems, ultimately influencing human security, health, and well‐being

Future projections on irrigation water under a changing climate are highly dependent on meteorological data derived from general circulation models (GCMs). Since climate projections include biases, bias correction is widely used to adjust meteorological elements, such as the atmospheric temperature and precipitation, but less attention has been paid to biases in humidity. Hence, in many cases, uncorrected humidity data have been directly used to analyze the impact of future climate change. In this study, we examined how the biases remaining in the humidity data of five GCMs propagate into the estimation of irrigation water demand and consumption from rivers using the global hydrological model (GHM) H08. First, to determine the effects of humidity bias across GCMs, we ran H08 with GCM-based meteorological forcing data sets distributed by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). A state-of-the-art bias correction method was applied to the data sets without correcting biases in humidity. Differences in the monthly relative humidity amounted to 11.7 to 20.4 % RH (percentage relative humidity) across the GCMs and propagated into differences in the estimated irrigation water demand, resulting in a range between 1152.6 and 1435.5 km3 yr−1 for 1971–2000. Differences in humidity also propagated into future projections. Second, sensitivity analysis with hypothetical humidity biases of ±5 % RH added homogeneously worldwide revealed the large negative sensitivity of irrigation water abstraction in India and East China, which are heavily irrigated. Third, we performed another set of simulations with bias-corrected humidity data to examine whether bias correction of the humidity can reduce uncertainties in irrigation water across the GCMs. The results showed that bias correction, even with a primitive methodology that only adjusts the monthly climatological relative humidity, helped reduce uncertainties across the GCMs: by using bias-corrected humidity data, the uncertainty ranges of irrigation water demand across the five GCMs were successfully reduced from 282.9 to 167.0 km3 yr−1 for the present period, and from 381.1 to 214.8 km3 yr−1 for the future period (RCP8.5, 2070–2099). Although different GHMs have different sensitivities to atmospheric humidity because different types of potential evapotranspiration formulae are implemented in them, bias correction of the humidity should be applied to forcing data, particularly for the evaluation of evapotranspiration and irrigation water.