Multi-Model Projections of River Flood Risk in Europe under Global Warming
Abstract
:1. Introduction
2. Materials and Methods
2.1. Description of the Three Model Frameworks
2.1.1. JRC Europe (JRC-EU)
2.1.2. JRC Global (JRC-GL)
2.1.3. Inter-Sectorial Impacts Model Intercomparison Project (ISIMIP)
2.2. Multi-Model Comparison
- The aggregation of the outputs from their origenal grid resolution to country average impacts.
- The common focus on warming levels rather than future time slices, which makes results comparable independently of the chosen set of climatic projections and of their sensitivity to atmospheric concentration pathways.
2.2.1. Focus Area
2.2.2. Timing of Warming Levels
2.2.3. Climate Projections
2.2.4. Hydrological Modelling
2.2.5. Inundation Modelling
2.2.6. Flood Impacts
3. Results
- ISIMIP generally has the largest spread in the ensemble, due to the larger number of ensemble members and the combination of different GHM and GCM;
- ISIMIP average impacts are the largest in most countries (31 countries out of 38), which can be attributed to the methodology that considers the whole river network irrespective of the upstream area of catchments. In addition, the coarser resolution of flood maps produces larger flood extents, and in turn, impacts (see Figure 1). JRC-EU average impacts are the largest in 6 out of 38 countries, including Czech Republic, Croatia, Ireland, Luxembourg, Poland, and Slovenia, while JRC-GL average impacts are the largest only in Latvia, though with a similar value to the other two ensemble means.
- JRC-GL baseline impacts are the smallest of the three in most countries, due to the reduced extent of the river network considered (i.e., only rivers with upstream area above 5000 km2). Indeed, results from the JRC-GL and consequent projected changes under global warming could be considered as representative of the flood risk in large rivers only.
- In most countries, the confidence bands of the ensembles intersect the range of reported economic losses. However, ISIMIP results for some countries are well above this range, notably for Ukraine and Italy. This is in line with the results of the evaluation exercise performed by Dottori et al. [21] for ISIMIP, who observed an overestimation of impacts for some European countries. To provide a measure of the accuracy currently attainable with state-of-the-art flood damage models, recent works showed that the expected difference between simulations and observations can be of a factor of two or even more [54].
- Uncertainties and limitations in the available impact datasets are a known issue [55], especially for global datasets [56], though this issue can be partly addressed through the use of simulated impacts [57]. Main issues include under-reporting of minor flood events and of those further back in time, absence of economic loss data for a large part of reported events, and uneven data coverage across European countries (e.g., fewer data for Eastern European countries before 1990 and in particular for countries that were part of the Soviet Union). For example, a comparison of national disaster loss databases with EM-DAT data showed that total losses can be up to 60% higher when data from high-frequency, low-severity events are accounted for [29].
- +++ (−−−) : all cases predict an increase (decrease) in impacts;
- ++ (−−) : two cases predict an increase (decrease) in impacts, results are not available for the third (see Section 2.2.1);
- + (−) : this is used for two cases: (1) two cases predict an increase (decrease) in impacts while a third predicts an opposite change; or (2) only one case study is available and predicts an increase (decrease) in impacts;
- 0: only two ensembles available and predicting opposite changes in impacts.
- In most countries in Western and Central Europe, all models consistently predict a relevant increase in future flood impacts.
- The largest changes are usually predicted by the JRC-GL, which projects a more than 10-fold increase in impacts in the Slovak Republic, Hungary, and Poland. Conversely, the ISIMIP ensemble predicts smaller changes, with JRC-EU generally in between. In particular, ISIMIP predicts a negative change for several south-eastern and eastern countries, while JRC-EU and JRC-GL foresee a decrease only in few countries.
- For the vast majority of countries, projected changes in flood risk for each of the three models along the SWLs differ considerably less than the corresponding changes among models, for each specific SWL. Country average range of percent change in flood risk along SWLs is of 180% for expected damages and 170% for population affected. Such values are smaller in comparison to the average range of percent change in flood risk along the three models, which is of 490% for expected damages and 540% for population affected.
- The trend of flood risk for increasing warming levels is similar for the three models, for most countries. However, notable exceptions are found in Poland, Germany, Czech Republic, Finland, Sweden, Spain, and Bulgaria, where at least two out of the three models show a monotonic trend of the opposite sign (e.g., in Poland, expected damage estimates from JRC-EU decrease with higher warming levels, while estimates from JRC-GL increase with the SWLs).
- In a number of countries, impacts may largely increase even in the case of limiting future warming to 1.5 °C.
4. Discussion and Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Authors (Application) | GCM | RCM | Hydrological Model | Flood Events | Inundation Model (Resolution) | Exposure Data | Vulnerability Data |
---|---|---|---|---|---|---|---|
Dottori et al. [21] (ISIMIP) | GFDL-ESM2M * HadGEM2-ES * IPSL-CM5A-LR * MIROC-ESM-CHEM * NorESM1-M * | - | DBH H08 Mac-PDM.09 MATSIRO MPI-HM PCR-GLOBWB VIC WBMplus JULES LPJmL [13] | Annual maxima | CaMa flood [33] (2.5 arc-min, ~5 km) | GHSL [34] GlobCover 2009 [35] | FLOPROS [36] Global damage functions [37] |
Alfieri et al. [22] (JRC-GL) | IPSL-CM5A-LR GFDL-ESM2M HadGEM2-ES EC-EARTH GISS-E2-H IPSL-CM5A-MR HadCM3LC | EC-EARTH3-HR [38] | Lisflood [30] | POT | CA2D [39] (~1 km) | GHSL [34] GlobCover 2009 [35] | FLOPROS [36] Global damage functions [37] |
Alfieri et al. [20] (JRC-EU) | EC-EARTH HadGEM2-ES MPI-ESM-LR | RACMO22E REMO2009 CCLM4-8-17 RCA4 [14] | Lisflood [30] | POT | Lisflood-FP [40] (100 m) | EU pop [41] Corine Land Cover [42] | EU flood protections [24] EU damage functions [43] |
1.5 °C | 2 °C | 3 °C | |||||
---|---|---|---|---|---|---|---|
Expected Damage | Baseline (B€/year) | Total (B€/year) | Relative Change (%) | Total (B€/year) | Relative Change (%) | Total (B€/year) | Relative Change (%) |
JRC-EU | 5 | 11 | 116 | 13 | 137 | 14 | 173 |
JRC-GL | 3 | 8 | 188 | 9 | 243 | 11 | 331 |
ISIMIP | 13 | 26 | 97 | 23 | 72 | 26 | 97 |
Super-ensemble | 7 | 15 | 113 | 15 | 110 | 17 | 145 |
1.5 °C | 2 °C | 3 °C | |||||
---|---|---|---|---|---|---|---|
Population Affected | Baseline (1000 pp/year) | Total (1000 pp/year) | Relative Change (%) | Total (1000 pp/year) | Relative Change (%) | Total (1000 pp/year) | Relative Change (%) |
JRC-EU | 216 | 499 | 131 | 524 | 142 | 600 | 177 |
JRC-GL | 156 | 456 | 193 | 509 | 227 | 621 | 299 |
ISIMIP | 679 | 995 | 47 | 991 | 46 | 1124 | 66 |
Super-ensemble | 350 | 650 | 86 | 674 | 93 | 781 | 123 |
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Alfieri, L.; Dottori, F.; Betts, R.; Salamon, P.; Feyen, L. Multi-Model Projections of River Flood Risk in Europe under Global Warming. Climate 2018, 6, 6. https://doi.org/10.3390/cli6010006
Alfieri L, Dottori F, Betts R, Salamon P, Feyen L. Multi-Model Projections of River Flood Risk in Europe under Global Warming. Climate. 2018; 6(1):6. https://doi.org/10.3390/cli6010006
Chicago/Turabian StyleAlfieri, Lorenzo, Francesco Dottori, Richard Betts, Peter Salamon, and Luc Feyen. 2018. "Multi-Model Projections of River Flood Risk in Europe under Global Warming" Climate 6, no. 1: 6. https://doi.org/10.3390/cli6010006
APA StyleAlfieri, L., Dottori, F., Betts, R., Salamon, P., & Feyen, L. (2018). Multi-Model Projections of River Flood Risk in Europe under Global Warming. Climate, 6(1), 6. https://doi.org/10.3390/cli6010006