Christel Prudhomme

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Significance Increasing concentrations of greenhouse gases in the atmosphere are widely expected to influence global climate over the coming century. The impact on drought is uncertain because of the complexity of the processes but can be estimated using outputs from an ensemble of global models (hydrological and climate models). Using an ensemble of 35 simulations, we show a likely increase in the global severity of drought by the end of 21st century, with regional hotspots including South America and Central and Western Europe in which the frequency of drought increases by more than 20%. The main source of uncertainty in the results comes from the hydrological models, with climate models contributing to a substantial but smaller amount of uncertainty. 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 bias-corrected 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 CO2 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.

Uncertainty and climate change impact on the flood regime of small UK catchments

A rigorous methodology is described for quantifying some of the uncertainties of climate change impact studies, excluding those due to downscaling techniques, and applied on a set of five catchments in Great Britain. Uncertainties in climate change are calculated from a set of 25,000 climate scenarios randomly generated by a Monte Carlo simulation, using several Global Climate Models, SRES-98 emission scenarios and climate sensitivities. Flow series representative of current and future conditions were simulated using a conceptual hydrological model. Generalised Pareto Distributions were fitted to Peak-Over-Threshold series for each scenario, and future flood scenarios were compared to current conditions for four typical flood events. Most scenarios show an increase in both the magnitude and the frequency of flood events, generally not greater than the 95% confidence limits. The largest uncertainty can be attributed to the type of GCM used, with the magnitude of changes varying by up to a factor 9 in Northern England and Scotland. It is therefore essential that climate change impact studies consider a range of climate scenarios derived from different GCMs, and that adaptation policies do not rely on results from only very few scenarios.

The Flood Characteristics of Large U.K. Rivers: Potential Effects of Changing Climate and Land Use

A continuous flow simulation model(CLASSIC) has been used to assess the potential impactof climate and land use changes on the flood regimesof large U.K. catchments. Climate change scenarios,based on the HadCM2 experiments from the HadleyCentre, are applied to the Severn and Thames rivers.The analysis shows that, for the 2050s, the climatechange scenarios result in an increase in both thefrequency and magnitude of flooding events in theserivers. The various ways of applying the rainfallscenario can have a significant effect on thesegeneral conclusions, although generally do not affecteither the direction or consistency of the changes.While ‘best guess’ land use changes show little impacton flood response, a 50% increase in forest covercould counter-act the impact of climate change. Aswould be expected, a large change in the urban coverof the catchments does have a large effect on theflood regimes, increasing both the frequency andmagnitude of floods significantly beyond the changesdue to climate alone. Further research is requiredinto the potential impacts of seasonal changes in thedaily rainfall and potential evaporation regimes, landuse changes and the interaction between the two.

Mapping extreme rainfall in a mountainous region using geostatistical techniques: a case study in Scotland

The spatial pattern of precipitation is known to be highly dependent on meteorological conditions and relief. However, the relationships between precipitation and topography in mountainous areas are not very well known, partly because of the complex topography in these regions, and partly because of the sparsity of information available to study such relationships in high elevation areas. The purpose of the investigation was to find a method of mapping extreme rainfall in the mountainous region of Scotland, which was easy to use and to understand, and which gave satisfactory results both in terms of statistical performance and consistency with meteorological mechanisms. Among the interpolation methods described in the literature, ordinary kriging and modified residual kriging have been found attractive by reason of their simplicity and ease of use. Both methods have been applied to map an index of extreme rainfall, the median of the annual maximum daily rainfall (RMED), in the mountainous region of Scotland. Rainfall records from a network of 1003 raingauges are used, covering Scotland with uneven density. A 4-parameter regression equation developed in a previous study, relating a transformed variable of RMED to topographical variables, is used in the modified residual kriging method. Comparing the relative performances of ordinary kriging and modified residual kriging shows that the use of topographical information helps to compensate for the lack of local data from which any interpolation method, such as ordinary kriging, might suffer, thus improving the final mapping. Copyright

Health Effects of Drought: a Systematic Review of the Evidence

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.

Relationships between extreme daily precipitation and topography in a mountainous region: a case study in Scotland

The spatial pattern of precipitation is known to be highly dependent on meteorological conditions and relief. But the relationships between precipitation and topography in mountainous areas are not very well known, partly because of the complex topography in these regions, and partly because of the sparsity of information available to study such relationships in high elevation areas. Moreover, studies are usually focused on mean annual precipitation, and so the patterns of extreme precipitation at short time steps, like daily, remain difficult to model. Daily annual maximum precipitation for 1003 gauges in Scotland, the most mountainous region of the United Kingdom, are studied to investigate the relationships between the median of the daily rainfall annual maximum, RMED, and the topography. A set of 14 topographical variables, some of them defined with respect to one of eight cardinal directions, are calculated from a 1×1 km digital terrain model (DTM). A particular effort has been made to improve the definition of some of the topographical variables suggested in the literature, either to provide a better physical definition or to better reflect the spatial variability of the topography. Single and multiple regression analyses have been made in some parts of the Highlands, leading to a 4-parameter model. This model is a mixture of geographical parameters (distance from the sea in opposing directions) and of topographical parameters (obstruction against the prevailing winds, and roughness between the main moisture source and the gauge). Special care has been taken to define a model whose physical sense is consistent with the meteorological conditions and whose parameters are not too interdependent.

How Well Do Large-Scale Models Reproduce Regional Hydrological Extremes in Europe?

AbstractThis paper presents a new methodology for assessing the ability of gridded hydrological models to reproduce large-scale hydrological high and low flow events (as a proxy for hydrological extremes) as described by catalogues of historical droughts [using the regional deficiency index (RDI)] and high flows [regional flood index (RFI)] previously derived from river flow measurements across Europe. Using the same methods, total runoff simulated by three global hydrological models from the Water Model Intercomparison Project (WaterMIP) [Joint U.K. Land Environment Simulator (JULES), Water Global Assessment and Prognosis (WaterGAP), and Max Planck Institute Hydrological Model (MPI-HM)] run with the same meteorological input (watch forcing data) at the same spatial 0.5° grid was used to calculate simulated RDI and RFI for the period 1963–2001 in the same European regions, directly comparable with the observed catalogues. Observed and simulated RDI and RFI time series were compared using three performance...

Characterizing Uncertainty of the Hydrologic Impacts of Climate Change

The high climate sensitivity of hydrologic systems, the importance of those systems to society, and the imprecise nature of future climate projections all motivate interest in characterizing uncertainty in the hydrologic impacts of climate change. We discuss recent research that exposes important sources of uncertainty that are commonly neglected by the water management community, especially, uncertainties associated with internal climate system variability, and hydrologic modeling. We also discuss research exposing several issues with widely used climate downscaling methods. We propose that progress can be made following parallel paths: first, by explicitly characterizing the uncertainties throughout the modeling process (rather than using an ad hoc “ensemble of opportunity”) and second, by reducing uncertainties through developing criteria for excluding poor methods/models, as well as with targeted research to improve modeling capabilities. We argue that such research to reveal, reduce, and represent uncertainties is essential to establish a defensible range of quantitative hydrologic storylines of climate change impacts.

Climate change and river flooding: part 1 classifying the sensitivity of British catchments

Effective national and regional policy guidance on climate change adaptation relies on robust scientific evidence. This two-part series of papers develops and implements a novel scenario-neutral framework enabling an assessment of the vulnerability of flood flows in British catchments to climatic change, to underpin the development of guidance for the flood management community. In this first part, the sensitivity of the 20-year return period flood peak (RP20) to changes in precipitation (P), temperature (T) and potential evapotranspiration (PE) is systematically assessed for 154 catchments. A sensitivity domain of 4,200 scenarios is applied combining 525 and 8 sets of P and T/PE mean monthly changes, respectively, with seasonality incorporated using a single-phase harmonic function. Using the change factor method, the percentage change in RP20 associated with each scenario of the sensitivity domain is calculated, giving flood response surfaces for each catchment. Using a clustering procedure on the response surfaces, the 154 catchments are divided into nine groups: flood sensitivity types. These sensitivity types show that some catchments are (very) sensitive to changes in P but others buffer the response, while the location of catchments of the same type does not show any strong geographical pattern. These results reflect the range of hydrological processes found in Britain, and demonstrate the potential importance of catchment properties (physical and climatic) in the propagation of change in climate to change in floods, and so in characterising the sensitivity types (covered in the companion paper).

Impacts of climate change, land-use change and phosphorus reduction on phytoplankton in the River Thames (UK)

Potential increases of phytoplankton concentrations in river systems due to global warming and changing climate could pose a serious threat to the anthropogenic use of surface waters. Nevertheless, the extent of the effect of climatic alterations on phytoplankton concentrations in river systems has not yet been analysed in detail. In this study, we assess the impact of a change in precipitation and temperature on river phytoplankton concentration by means of a physically-based model. A scenario-neutral methodology has been employed to evaluate the effects of climate alterations on flow, phosphorus concentration and phytoplankton concentration of the River Thames (southern England). In particular, five groups of phytoplankton are considered, representing a range of size classes and pigment phenotypes, under three different land-use/land-management scenarios to assess their impact on phytoplankton population levels. The model results are evaluated within the framework of future climate projections, using the UK Climate Projections 09 (UKCP09) for the 2030s. The results of the model demonstrate that an increase in average phytoplankton concentration due to climate change is highly likely to occur, with the magnitude varying depending on the location along the River Thames. Cyanobacteria show significant increases under future climate change and land use change. An expansion of intensive agriculture accentuates the growth in phytoplankton, especially in the upper reaches of the River Thames. However, an optimal phosphorus removal mitigation strategy, which combines reduction of fertiliser application and phosphorus removal from wastewater, can help to reduce this increase in phytoplankton concentration, and in some cases, compensate for the effect of rising temperature.