The impacts of climate change on river flood risk at the global scale

This paper presents an assessment of the implications of climate change for global river flood risk. It is based on the estimation of flood frequency relationships at a grid resolution of 0.5?×?0.5°, using a global hydrological model with climate scenarios derived from 21 climate models, together with projections of future population. Four indicators of the flood hazard are calculated; change in the magnitude and return period of flood peaks, flood-prone population and cropland exposed to substantial change in flood frequency, and a generalised measure of regional flood risk based on combining frequency curves with generic flood damage functions. Under one climate model, emissions and socioeconomic scenario (HadCM3 and SRES A1b), in 2050 the current 100-year flood would occur at least twice as frequently across 40 % of the globe, approximately 450 million flood-prone people and 430 thousand km² of flood-prone cropland would be exposed to a doubling of flood frequency, and global flood risk would increase by approximately 187 % over the risk in 2050 in the absence of climate change. There is strong regional variability (most adverse impacts would be in Asia), and considerable variability between climate models. In 2050, the range in increased exposure across 21 climate models under SRES A1b is 31–450 million people and 59 to 430 thousand km² of cropland, and the change in risk varies between ?9 and +376 %. The paper presents impacts by region, and also presents relationships between change in global mean surface temperature and impacts on the global flood hazard. There are a number of caveats with the analysis; it is based on one global hydrological model only, the climate scenarios are constructed using pattern-scaling, and the precise impacts are sensitive to some of the assumptions in the definition and application.     

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.     

Effects of climate change on the thermal structure of lakes in the Asian Monsoon Area

This research investigates the effect of climate change on the thermal structure of lakes in response to watershed hydrology. We applied a hydrodynamic water quality model coupled to a hydrological model with a future climate scenario projected by a GCM A2 emission scenario to the Yongdam Reservoir, South Korea. In the climate change scenario, the temperature will increase by 2.1°C and 4.2°C and the precipitation will increase by 178.4?mm and 464.4?mm by the 2050 and 2090, respectively, based on 2010. The pattern changes of precipitation and temperature increase due to climate change modify the hydrology of the watershed. The hydrological model results indicate that they increase both surface runoff itself and temperature. The reservoir model simulation with the hydrological model results showed that increasing air temperature is related to higher surface water temperature. Surface water temperature is expected to increase by about 1.2°C and 2.2°C from the 2050 and 2090, respectively, based on the 2010 results. The simulation results of the effects of climate warming on the thermal structure of the Asian Monsoon Area Lake showed consistent results with those of previous studies in terms of greater temperature increases in the epilimnion than in the hypolimnion, increased thermal stratification, and decreasing thermocline depths during the summer and fall. From this study, it was concluded that the hydrodynamic water quality model coupled to the hydrological model could successfully simulate the variability of the epilimnetic temperature, changed depth and magnitude of the thermocline and the changed duration of summer stratification.     

The global-scale impacts of climate change on water resources and flooding under new climate and socio-economic scenarios

This paper presents a preliminary assessment of the relative effects of rate of climate change (four Representative Concentration Pathways - RCPs), assumed future population (five Shared Socio-economic Pathways - SSPs), and pattern of climate change (19 CMIP5 climate models) on regional and global exposure to water resources stress and river flooding. Uncertainty in projected future impacts of climate change on exposure to water stress and river flooding is dominated by uncertainty in the projected spatial and seasonal pattern of change in climate. There is little clear difference in impact between RCP2.6, RCP4.5 and RCP6.0 in 2050, and between RCP4.5 and RCP6.0 in 2080. Impacts under RCP8.5 are greater than under the other RCPs in 2050 and 2080. For a given RCP, there is a difference in the absolute numbers of people exposed to increased water resources stress or increased river flood frequency between the five SSPs. With the ‘middle-of-the-road’ SSP2, climate change by 2050 would increase exposure to water resources stress for between approximately 920 and 3,400 million people under the highest RCP, and increase exposure to river flood risk for between 100 and 580 million people. Under RCP2.6, exposure to increased water scarcity would be reduced in 2050 by 22-24 %, compared to impacts under the RCP8.5, and exposure to increased flood frequency would be reduced by around 16 %. The implications of climate change for actual future losses and adaptation depend not only on the numbers of people exposed to changes in risk, but also on the qualitative characteristics of future worlds as described in the different SSPs. The difference in ‘actual’ impact between SSPs will therefore be greater than the differences in numbers of people exposed to impact.     

Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 1: baseline climate

Assessing future climate and its potential implications on river flows is a key challenge facing water resource planners. Sound, scientifically-based advice to decision makers also needs to incorporate information on the uncertainty in the results. Moreover, existing bias in the reproduction of the ‘current’ (or baseline) river flow regime is likely to transfer to the simulations of flow in future time horizons, and it is thus critical to undertake baseline flow assessment while undertaking future impacts studies. This paper investigates the three main sources of uncertainty surrounding climate change impact studies on river flows: uncertainty in GCMs, in downscaling techniques and in hydrological modelling. The study looked at four British catchments’ flow series simulated by a lumped conceptual rainfall–runoff model with observed and GCM-derived rainfall series representative of the baseline time horizon (1961–1990). A block-resample technique was used to assess climate variability, either from observed records (natural variability) or reproduced by GCMs. Variations in mean monthly flows due to hydrological model uncertainty from different model structures or model parameters were also evaluated. Three GCMs (HadCM3, CCGCM2, and CSIRO-mk2) and two downscaling techniques (SDSM and HadRM3) were considered. Results showed that for all four catchments, GCM uncertainty is generally larger than downscaling uncertainty, and both are consistently greater than uncertainty from hydrological modelling or natural variability. No GCM or downscaling technique was found to be significantly better or to have a systematic bias smaller than the others. This highlights the need to consider more than one GCM and downscaling technique in impact studies, and to assess the bias they introduce when modelling river flows.     

Evaluation of hydrological effect of stakeholder prioritized climate change adaptation options based on multi-model regional climate projections

An integrated process involving participatory and modelling approaches for prioritizing and evaluating climate change adaptation options for the Kangsabati reservoir catchment is presented here. We assess the potential effects of climate change on water resources and evaluate the ability of stakeholder prioritized adaptation options to address adaptation requirements using the Water Evaluation And Planning (WEAP) model. Two adaptation options, check dams and increasing forest cover, are prioritized using pair-wise comparison and scenario analysis. Future streamflow projections are generated for the mid-21^st century period (2021–2050) using four high resolution (~25 km) Regional Climate Models and their ensemble mean for SRES A1B scenario. WEAP simulations indicate that, compared to a base scenario without adaptation, both adaptation options reduce streamflow. In comparison to check dams, increasing forest cover shows greater ability to address adaptation requirements as demonstrated by the temporal pattern and magnitude of streamflow reduction. Additionally, over the 30 year period, effectiveness of check dams in reducing streamflow decreases by up to 40 %, while that of forest cover increases by up to 47 %. Our study highlights the merits of a comparative assessment of adaptation options and we conclude that a combined approach involving stakeholders, scenario analysis, modelling techniques and multi-model projections may support climate change adaptation decision-making in the face of uncertainty.     

Vegetation patterns in South America associated with rising CO2: uncertainties related to sea surface temperatures

Spatially precise forecasts of the impacts of climate change on the distribution of major vegetation types are essential for the implementation of effective conservation and land use policy. However, existing studies frequently omit major sources of climate variability that can significantly increase the uncertainty of projections. In this study we demonstrate how different predictions for sea surface temperature (SST) for the first half of the twenty-first century increase the uncertainty associated with forecasts of the future distribution of major ecosystems in South America. This is demonstrated through a numerical experiment using a coupled climate–vegetation model (CCM3-IBIS) for IPCC emission scenario A2 that incorporates the SST data from ten different models. The study reveals an increasing uncertainty in the ability to forecast future vegetation patterns, such that by 2050 the simulation is unable to robustly forecast the vegetation cover in an area equivalent to 28 % in South America (5?×?10⁶ km²). The future of the central and northeastern regions of Brazil is especially uncertain, with outcomes, ranging from savanna, and open shrubland to grassland. Recognizing and managing such uncertainty should be a priority for decision makers.     

Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: future climate

The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers.     

Climate change impacts on sugarcane attainable yield in southern Brazil

This study evaluated the effects of climate change on sugarcane yield, water use efficiency, and irrigation needs in southern Brazil, based on downscaled outputs of two general circulation models (PRECIS and CSIRO) and a sugarcane growth model. For three harvest cycles every year, the DSSAT/CANEGRO model was used to simulate the baseline and four future climate scenarios for stalk yield for the 2050s. The model was calibrated for the main cultivar currently grown in Brazil based on five field experiments under several soil and climate conditions. The sensitivity of simulated stalk fresh mass (SFM) to air temperature, CO₂ concentration [CO₂] and rainfall was also analyzed. Simulated SFM responses to [CO₂], air temperature and rainfall variations were consistent with the literature. There were increases in simulated SFM and water usage efficiency (WUE) for all scenarios. On average, for the current sugarcane area in the State of São Paulo, SFM would increase 24 % and WUE 34 % for rainfed sugarcane. The WUE rise is relevant because of the current concern about water supply in southern Brazil. Considering the current technological improvement rate, projected yields for 2050 ranged from 96 to 129 t?ha^?1, which are respectively 15 and 59 % higher than the current state average yield.     

Spatial impact of projected changes in rainfall and temperature on wheat yields in Australia

Climate projections over the next two to four decades indicate that most of Australia’s wheat-belt is likely to become warmer and drier. Here we used a shire scale, dynamic stress-index model that accounts for the impacts of rainfall and temperature on wheat yield, and a range of climate change projections from global circulation models to spatially estimate yield changes assuming no adaptation and no CO₂ fertilisation effects. We modelled five scenarios, a baseline climate (climatology, 1901–2007), and two emission scenarios (“low” and “high” CO₂) for two time horizons, namely 2020 and 2050. The potential benefits from CO₂ fertilisation were analysed separately using a point level functional simulation model. Irrespective of the emissions scenario, the 2020 projection showed negligible changes in the modelled yield relative to baseline climate, both using the shire or functional point scale models. For the 2050-high emissions scenario, changes in modelled yield relative to the baseline ranged from ?5 % to +6 % across most of Western Australia, parts of Victoria and southern New South Wales, and from ?5 to ?30 % in northern NSW, Queensland and the drier environments of Victoria, South Australia and in-land Western Australia. Taking into account CO₂ fertilisation effects across a North–south transect through eastern Australia cancelled most of the yield reductions associated with increased temperatures and reduced rainfall by 2020, and attenuated the expected yield reductions by 2050.     

Impacts of climate change on crop evapotranspiration with ensemble GCM projections in the North China Plain

As one of the key grain-producing regions in China, the agricultural system in the North China Plain (NCP) is vulnerable to climate change due to its limited water resources and strong dependence on irrigation for crop production. Exploring the impacts of climate change on crop evapotranspiration (ET) is of importance for water management and agricultural sustainability. The VIP (Vegetation Interface Processes) process-based ecosystem model and WRF (Weather Research and Forecasting) modeling system are applied to quantify ET responses of a wheat-maize cropping system to climate change. The ensemble projections of six General Circulation Models (GCMs) under the B2 and A2 scenarios in the 2050s over the NCP are used to account for the uncertainty of the projections. The thermal time requirements (TTR) of crops are assumed to remain constant under air warming conditions. It is found that in this case the length of the crop growth period will be shortened, which will result in the reduction of crop water consumption and possible crop productivity loss. Spatially, the changes of ET during the growth periods (ET_g) for wheat range from ?7 to 0 % with the average being ?1.5?±?1.2 % under the B2 scenario, and from ?8 to 2 % with the average being ?2.7?±?1.3 % under the A2 scenario/consistently, changes of ET_g for maize are from ?10 to 8 %, with the average being ?0.4?±?4.9 %, under the B2 scenario and from ?8 to 8 %, with the average being ?1.2?±?4.1 %, under the A2 scenario. Numerical analysis is also done on the condition that the length of the crop growth periods remains stable under the warming condition via breeding new crop varieties. In this case, TTR will be higher and the crop water requirements will increase, with the enhancement of the productivity. It is suggested that the options for adaptation to climate change include no action and accepting crop loss associated with the reduction in ET_g, or breeding new cultivars that would maintain or increase crop productivity and result in an increase in ET_g. In the latter case, attention should be paid to developing improved water conservation techniques to help compensate for the increased ET_g.     

River discharge to the Baltic Sea in a future climate

This study reports on new projections of discharge to the Baltic Sea given possible realisations of future climate and uncertainties regarding these projections. A high-resolution, pan-Baltic application of the Hydrological Predictions for the Environment (HYPE) model was used to make transient simulations of discharge to the Baltic Sea for a mini-ensemble of climate projections representing two high emissions scenarios. The biases in precipitation and temperature adherent to climate models were adjusted using a Distribution Based Scaling (DBS) approach. As well as the climate projection uncertainty, this study considers uncertainties in the bias-correction and hydrological modelling. While the results indicate that the cumulative discharge to the Baltic Sea for 2071 to 2100, as compared to 1971 to 2000, is likely to increase, the uncertainties quantified from the hydrological model and the bias-correction method show that even with a state-of-the-art methodology, the combined uncertainties from the climate model, bias-correction and impact model make it difficult to draw conclusions about the magnitude of change. It is therefore urged that as well as climate model and scenario uncertainty, the uncertainties in the bias-correction methodology and the impact model are also taken into account when conducting climate change impact studies.     

Modelling the sensitivity of wheat growth and water balance to climate change in Southeast Australia

A simulation study was carried out to assess the potential sensitivity of wheat growth and water balance components to likely climate change scenarios at Wagga Wagga, NSW, Australia. Specific processes considered include crop development, growth rate, grain yield, water use efficiency, evapotranspiration, runoff and deep drainage. Individual impacts of changes in temperature, rainfall and CO₂ concentration ([CO₂]) and the combined impacts of these three variables were analysed for 2050 ([CO₂] = 570 ppm, T +2.3°C, P ?7%) and 2070 ([CO₂] = 720 ppm, T +3.8°C, P ?10%) conditions. Two different rainfall change scenarios (changes in rainfall intensity or rainfall frequency) were used to modify historical rainfall data. The Agricultural Production Systems Simulator (APSIM) was used to simulate the growth and water balance processes for a 117 year period of baseline, 2050 and 2070 climatic conditions. The results showed that wheat yield reduction caused by 1°C increase in temperature and 10% decrease in rainfall could be compensated by a 266 ppm increase in [CO₂] assuming no interactions between the individual effects. Temperature increase had little impact on long-term average water balance, while [CO₂] increase reduced evapotranspiration and increased deep drainage. Length of the growing season of wheat decreased 22 days in 2050 and 35 days in 2070 conditions as a consequence of 2.3°C and 3.8°C increase in temperature respectively. Yield in 2050 was approximately 1% higher than the simulated baseline yield of 4,462 kg ha^???1, but it was 6% lower in 2070. An early maturing cultivar (Hartog) was more sensitive in terms of yield response to temperature increase, while a mid-maturing cultivar (Janz) was more sensitive to rainfall reduction. Janz could benefit more from increase in CO₂ concentration. Rainfall reduction across all rainfall events would have a greater negative impact on wheat yield and WUE than if only smaller rainfall events reduced in magnitude, even given the same total decrease in annual rainfall. The greater the reduction in rainfall, the larger was the difference. The increase in temperature increased the difference of impact between the two rainfall change scenarios while increase in [CO₂] reduced the difference.     

The impact of future socio-economic and climate changes on agricultural land use and the wider environment in East Anglia and North West England using a metamodel system

This paper describes a procedure to use a model interactively to investigate future land use by studying a wide range of scenarios defining climate, technological and socio-economic changes. A full model run of several hours has been replaced by a metamodel version which takes a few seconds, and provides the user with an immediate visual output and with the ability to examine easily which factors have the greatest effect. The Regional Impact Simulator combines a model of agricultural land use choices linked with models of urban growth, flooding risk, water quality and consequences for wildlife to estimate plausible futures of agricultural land on a timescale of 20–50 years. The model examines the East Anglian and North West regions of the United Kingdom at a grid resolution of 5 × 5 km, and for each scenario estimates the most likely cropping and its profitability at each location, and classifies land use as arable, intensive or extensive grassland or abandoned. From a modelling viewpoint the metamodel approach enables iteration. It is thus possible to determine how product prices change so that production meets demand. The results of the study show that in East Anglia cropping remains quite stable over a wide range of scenarios, though grassland is eliminated in scenarios with the 2050s High climate scenario – almost certainly due to the low yield in the drier conditions. In the North West there is a very much greater range of outcomes, though all scenarios suggest a reduction in grassland with the greatest in the 2050s High climate scenario combined with the “Regional Stewardship” (environmental) socio-economic scenario. The effects of the predicted changes in land use on plant species showed suitability for species to vary greatly, particularly between the socio-economic scenarios, due to detrimental effects from increases in nitrogen fertilisation. A complete simulation with the Regional Impact Simulator takes around 15 seconds (computer-dependent), which users who responded felt was adequate or better than adequate. The main areas for future improvement, such as the speed of the system, user interaction and the accuracy and detail of the modelling, are considered.     

Impacts of climate variability and human activities on decrease in streamflow in the Qinhe River,China

Under the impacts of climate variability and human activities, there are statistically significant decreasing trends for streamflow in the Yellow River basin, China. Therefore, it is crucial to separate the impacts of climate variability and human activities on streamflow decrease for better water resources planning and management. In this study, the Qinhe River basin (QRB), a typical sub-basin in the middle reach of the Yellow River, was chosen as the study area to assess the impacts of climate variability and human activities on streamflow decrease. The trend and breakpoint of observed annual streamflow from 1956 to 2010 were identified by the nonparametric Mann–Kendall test. The results showed that the observed annual streamflow decreased significantly (P?<?0.05) and a breakpoint around 1973 was detected. Therefore, the time series was divided into two periods: “natural period” (before the breakpoint) and “impacted period” (after the breakpoint). The observed annual streamflow decreased by 68.1 mm from 102.3 to 34.2 mm in the two periods. The climate elasticity method and hydrological model were employed to separate the impacts of climate variability and human activities on streamflow decrease. The results indicated that climate variability was responsible for 54.1 % of the streamflow decrease estimated by the climate elasticity method and 59.3 % estimated by the hydrological modeling method. Therefore, the climate variability was the main driving factor for streamflow decrease in the QRB. Among these driving factors of natural and anthropogenic, decrease in precipitation and increase in water diversion were the two major contributions of streamflow reduction. The finding in this study can serve as a reference for regional water resources management and planning.     

The effect of climate change on hydrological regimes in Europe: a continental perspective

This paper outlines the effects of climate change by the 2050s on hydrological regimes at the continental scale in Europe, at a spatial resolution of 0.5×0.5°. Hydrological regimes are simulated using a macro-scale hydrological model, operating at a daily time step, and four climate change scenarios are used. There are differences between the four scenarios, but each indicates a general reduction in annual runoff in southern Europe (south of around 50°N), and an increase in the north. In maritime areas there is little difference in the timing of flows, but the range through the year tends to increase with lower flows during summer. The most significant changes in flow regime, however, occur where snowfall becomes less important due to higher temperatures, and therefore both winter runoff increases and spring flow decreases: these changes occur across a large part of eastern Europe. In western maritime Europe low flows reduce, but further east minimum flows will increase as flows during the present low flow season – winter – rise. “Drought” was indexed as the maximum total deficit volume below the flow exceeded 95% of the time: this was found to increase in intensity across most of western Europe, but decrease in the east and north. The study attempted to quantify several sources of uncertainty, and showed that the effects of model uncertainty on the estimated change in runoff were generally small compared to the differences between scenarios and the assumed change in global temperature by 2050.     

A megacity in a changing climate: the case of Kolkata

Projections by the Intergovernmental Panel on Climate Change suggest that there will be an increase in the frequency and intensity of climate extremes in the 21st century. Kolkata, a megacity in India, has been singled out as one of the urban centers vulnerable to climate risks. Modest flooding during monsoons at high tide in the Hooghly River is a recurring hazard in Kolkata. More intense rainfall, riverine flooding, sea level rise, and coastal storm surges in a changing climate can lead to widespread and severe flooding and bring the city to a standstill for several days. Using rainfall data, high and low emissions scenarios, and sea level rise of 27 cm by 2050, this paper assesses the vulnerability of Kolkata to increasingly intense precipitation events for return periods of 30, 50, and 100 years. It makes location-specific inundation depth and duration projections using hydrological, hydraulic, and urban storm models with geographic overlays. High resolution spatial analysis provides a roadmap for designing adaptation schemes to minimize the impacts of climate change. The modeling results show that de-silting of the main sewers would reduce vulnerable population estimates by at least 5 %.     

An assessment of the climate change impacts on groundwater recharge at a continental scale using a probabilistic approach with an ensemble of GCMs

This study used 16 Global Climate Models and three global warming scenarios to make projections of recharge under a 2050 climate for the entire Australian continent at a 0.05° grid resolution. The results from these 48 future climate variants have been fitted to a probability distribution to enable the results to be summarised and uncertainty quantified. The median results project a reduction in recharge across the west, centre and south of Australia and an increase in recharge across the north and a small area in the east of the continent. The range of results is quite large and for large parts of the continent encompasses both increases and decreases in recharge. This makes it difficult to utilise for water resources management so the results have been analysed with a risk analysis framework; this enables the future projections for groundwater recharge to be communicated to water managers in terms of likelihood and consequence of a reduction in recharge. This highlights an important message for water resource managers that in most areas of Australia they will be making decisions on water allocations under considerable uncertainty as to the direction and magnitude of recharge change under a future climate and that this uncertainty may be irreducible.     

Water balance modelling in the Baltic Sea drainage basin – analysis of meteorological and hydrological approaches

Summary Efforts to understand and simulate the global climate in numerical models have led to regional studies of the energy and water balance. The Baltic Basin provides a continental scale test basin where meteorology, oceanography and hydrology all can meet. Using a simple conceptual approach, a large-scale hydrological model of the water balance of the total Baltic Sea Drainage Basin (HBV-Baltic) was used to simulate the basinwide water balance components for the present climate and to evaluate the land surface components of atmospheric climate models. It has been used extensively in co-operative BALTEX (The Baltic Sea Experiment) research and within SWECLIM (Swedish Regional Climate Modelling Programme) to support continued regional climate model development. This helps to identify inconsistencies in both meteorological and hydrological models. One result is that compensating errors are evident in the snow routines of the atmospheric models studied. The use of HBV-Baltic has greatly improved the dialogue between hydrological and meteorological modellers within the Baltic Basin research community. It is concluded that conceptual hydrological models, although far from being complete, play an important role in the realm of continental scale hydrological modelling. Atmospheric models benefit from the experience of hydrological modellers in developing simpler, yet more effective land surface parameterisations. This basic modelling tool for simulating the large-scale water balance of the Baltic Sea drainage basin is the only existing hydrological model that covers the entire basin and will continue to be used until more detailed models can be successfully applied at this scale. Received November 24, 2000 Revised April 4, 2001     

Bioenergy in energy transformation and climate management

This study explores the importance of bioenergy to potential future energy transformation and climate change management. Using a large inter-model comparison of 15 models, we comprehensively characterize and analyze future dependence on, and the value of, bioenergy in achieving potential long-run climate objectives. Model scenarios project, by 2050, bioenergy growth of 1 to 10 % per annum reaching 1 to 35 % of global primary energy, and by 2100, bioenergy becoming 10 to 50 % of global primary energy. Non-OECD regions are projected to be the dominant suppliers of biomass, as well as consumers, with up to 35 % of regional electricity from biopower by 2050, and up to 70 % of regional liquid fuels from biofuels by 2050. Bioenergy is found to be valuable to many models with significant implications for mitigation and macroeconomic costs of climate policies. The availability of bioenergy, in particular biomass with carbon dioxide capture and storage (BECCS), notably affects the cost-effective global emissions trajectory for climate management by accommodating prolonged near-term use of fossil fuels, but with potential implications for climate outcomes. Finally, we find that models cost-effectively trade-off land carbon and nitrous oxide emissions for the long-run climate change management benefits of bioenergy. The results suggest opportunities, but also imply challenges. Overall, further evaluation of the viability of large-scale global bioenergy is merited.