Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by biascorrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO 2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty.climate impact | global hydrology | evaporation | global warming T he global water cycle is expected to change over the 21st century due to the combined effects of climate change and increasing human intervention. In a warmer world, the waterholding capacity of the atmosphere will increase, resulting in a change in the frequency of precipitation extremes, increased evaporation and dry periods (1), and intensification of droughts (2). This process is represented by most global climate models (GCMs) by increased summer dryness and winter wetness over large areas of continental mid to high latitudes in the Northern Hemisphere (3), associated with a reduction in water availability at continental (4, 5) and global scales (6, 7). Because such changes have potentially very serious implications in some regions of the world, identifying areas where there is agreement in the direction and magnitude of changes in drought characteristics (hotspots) in response to climate change is essential information for water resource management aimed at ensuring water security in a changing climate.Most GCMs, however, are not able to reproduce the fine-scale processes governing terrestrial hydrology (and hence runoff) and suffer from systematic biases (8). As land-atmospheric feedbacks are not yet fully understood and reproduced by global models (9), and because full coupling ...

Quantifying the effects of future changes in the frequency of precipitation extremes is a key challenge in assessing the vulnerability of hydrological systems to climate change but is difficult as climate models do not always accurately simulate daily precipitation. This article compares the performance of four published techniques used to reduce the bias in a regional climate model precipitation output: (1) linear, (2) nonlinear, (3) γ -based quantile mapping and (4) empirical quantile mapping. Overall performance and sensitivity to the choice of calibration period were tested by calculating the errors in the first four statistical moments of generated daily precipitation time series and using a cross-validation technique. The study compared the 1961-2005 precipitation time series from the regional climate model HadRM3.0-PPE-UK (unperturbed version) with gridded daily precipitation time series derived from rain gauges for seven catchments spread throughout Great Britain. We found that while the first and second moments of the precipitation frequency distribution can be corrected robustly, correction of the third and fourth moments of the distribution is much more sensitive to the choice of bias correction procedure and to the selection of a particular calibration period. Overall, our results demonstrate that, if both precipitation data sets can be approximated by a γ -distribution, the γ -based quantilemapping technique offers the best combination of accuracy and robustness. In circumstances where precipitation data sets cannot adequately be approximated using a γ -distribution, the nonlinear method is more effective at reducing the bias, but the linear method is least sensitive to the choice of calibration period. The empirical quantile mapping method can be highly accurate, but results were very sensitive to the choice of calibration time period. However, it should be borne in mind that bias correction introduces additional uncertainties, which are greater for higher order moments.

This paper presents a novel framework for undertaking robust climate change impact studies, which can be used for testing the robustness of precautionary climate change allowances used in engineering design. It is illustrated with respect to fluvial flood risk in the UK. The methodology departs from conventional scenario-led impact studies because it is based on sensitivity analyses of catchment responses to a plausible range of climate changes (rather than the time-varying outcome of individual scenarios), making it scenarioneutral. The method involves separating the climate change projections (the hazard) from the catchment responsiveness (the vulnerability) expressed as changes in peak flows. By combining current understanding of likelihood of the climate change hazard with knowledge of the sensitivity of a given catchment, it is possible to evaluate the fraction of climate model projections that would not be accommodated by specified safety margins. This enables rapid appraisal of existing or new precautionary allowances for a set of climate change projections, but also for any new set of climate change projections for example arising from a new generation of climate models as soon as they are available, or when focusing on a different planning time horizon, without the need for undertaking a new climate change impact analysis with the new scenarios. The approach is demonstrated via an assessment of the UK Government's 20% allowance for climate change applied in two contrasting catchments. In these exemplars, the allowance defends against the majority of sampled climate projections for the 2080s from the IPCC-AR4 GCM and UKCP09 RCM runs but it is still possible to identify a subset of regional scenarios that would exceed the 20% threshold.

Introduction. Climate change projections indicate that droughts will become more intense in the 21 century in some areas of the world. The El Niño Southern Oscillation is associated with drought in some countries, and forecasts can provide advance warning of the increased risk of adverse climate conditions. The most recent available data from EMDAT estimates that over 50 million people globally were affected by drought in 2011. Documentation of the health effects of drought is difficult, given the complexity in assigning a beginning/end and because effects tend to accumulate over time. Most health impacts are indirect because of its link to other mediating circumstances like loss of livelihoods. Methods. The following databases were searched: MEDLINE; CINAHL; Embase; PsychINFO, Cochrane Collection. Key references from extracted papers were hand-searched, and advice from experts was sought for further sources of literature. Inclusion criteria for papers summarised in tables include: explicit link made between drought as exposure and human health outcomes; all study designs/methods; all countries/contexts; any year of publication. Exclusion criteria include: drought meaning shortage unrelated to climate; papers not published in English; studies on dry/arid climates unless drought was noted as an abnormal climatological event. No formal quality evaluation was used on papers meeting inclusion criteria. Results. 87 papers meeting the inclusion criteria are summarised in tables. Additionally, 59 papers not strictly meeting the inclusion criteria are used as supporting text in relevant parts of the results section. Main categories of findings include: nutrition-related effects (including general malnutrition and mortality, micronutrient malnutrition, and anti-nutrient consumption); water-related disease (including E coli, cholera and algal bloom); airborne and dust-related disease (including silo gas exposure and coccidioidomycosis); vector borne disease (including malaria, dengue and West Nile Virus); mental health effects (including distress and other emotional consequences); and other health effects (including wildfire, effects of migration, and damage to infrastructure). Conclusions. The probability of drought-related health impacts varies widely and largely depends upon drought severity, baseline population vulnerability, existing health and sanitation infrastructure, and available resources with which to mitigate impacts as they occur. The socio-economic environment in which drought occurs influences the resilience of the affected population. Forecasting can be used to provide advance warning of the increased risk of adverse climate conditions and can support the disaster risk reduction process. Despite the complexities involved in documentation, research should continue and results should be shared widely in an effort to strengthen drought preparedness and response activities.

Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses, i.e. additive, antagonistic and synergistic effects.Currently we know little about the spatial scale relevant for the outcome of such interactions and about effect sizes. This knowledge gap needs to be filled to underpin future land management decisions or climate mitigation interventions, for protecting and restoring freshwater ecosystems. The study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe producing 174 combinations of paired-stressor effects on a biological response variable. Generalised linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive and 33% in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes the frequency of additive and interactive effects was similar for all spatial scales addressed, while for rivers this frequency increased with scale. Nutrient enrichment was the overriding stressor for lakes, generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions.