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How evaluation of global hydrological models can help to improve credibility of river discharge projections under climate change
Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections. © 2020, The Author(s).
Contribution of permafrost soils to the global carbon budget
Climate warming affects permafrost soil carbon pools in two opposing ways: enhanced vegetation growth leads to higher carbon inputs to the soil, whereas permafrost melting accelerates decomposition and hence carbon release. Here, we study the spatial and temporal dynamics of these two processes under scenarios of climate change and evaluate their influence on the carbon balance of the permafrost zone. We use the dynamic global vegetation model LPJmL, which simulates plant physiological and ecological processes and includes a newly developed discrete layer energy balance permafrost module and a vertical carbon distribution within the soil layer. The model is able to reproduce the interactions between vegetation and soil carbon dynamics as well as to simulate dynamic permafrost changes resulting from changes in the climate. We find that vegetation responds more rapidly to warming of the permafrost zone than soil carbon pools due to long time lags in permafrost thawing, and that the initial simulated net uptake of carbon may continue for some decades of warming. However, once the turning point is reached, if carbon release exceeds uptake, carbon is lost irreversibly from the system and cannot be compensated for by increasing vegetation carbon input. Our analysis highlights the importance of including dynamic vegetation and long-term responses into analyses of permafrost zone carbon budgets.
Risks for the global freshwater system at 1.5 °c and 2 °c global warming
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.
Historical and future changes in global flood magnitude - evidence from a model-observation investigation
To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maxima of 7 d streamflow are investigated, using a comprehensive streamflow archive and six global hydrological models. The models' capacity to characterise trends in annual maxima of 7 d streamflow at the continental and global scale is evaluated across 3666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and (iv) spatial pattern. Compared to observed trends, simulated trends driven by observed climate forcing generally have a higher mean, lower spread and a similar percentage of locations showing significant trends. Models show a low to moderate capacity to simulate spatial patterns of historical trends, with approximately only from 12 % to 25 % of the spatial variance of observed trends across all gauge stations accounted for by the simulations. Interestingly, there are statistically significant differences between trends simulated by global hydrological models (GHMs) forced with observational climate and by those forced by bias-corrected climate model output during the historical period, suggesting the important role of the stochastic natural (decadal, inter-annual) climate variability. Significant differences were found in simulated flood trends when averaged only at gauged locations compared to those averaged across all simulated grid cells, highlighting the potential for bias toward well-observed regions in our understanding of changes in floods. Future climate projections (simulated under the RCP2.6 and RCP6.0 greenhouse gas concentration scenarios) suggest a potentially high level of change in individual regions, with up to 35 % of cells showing a statistically significant trend (increase or decrease; at 10 % significance level) and greater changes indicated for the higher concentration pathway. Importantly, the observed streamflow database under-samples the percentage of locations consistently projected with increased flood hazards under the RCP6.0 greenhouse gas concentration scenario by more than an order of magnitude (0.9 % compared to 11.7 %). This finding indicates a highly uncertain future for both flood-prone communities and decision makers in the context of climate change. © Author(s) 2020.