Why increased extreme precipitation under climate change  negatively affects water security

Eekhout, Joris; Hunink, Johannes E.; Terink, W.; Vente, Joris de

doi:10.5194/hess-22-5935-2018

Cited by 108 publications

(52 citation statements)

References 60 publications

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“…This underlines the importance of water storage in the soil. Eekhout, J.P.C. et al (2018) presumed a considerable decline in soil water storage capacity due to climate change in Europe.…”

Section: Risky and Neutral Areas Of Changes In Intense Rainfallsmentioning

confidence: 99%

Spatial analysis of changes and anomalies of intense rainfalls in Hungary

et al. 2019

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Extreme precipitation events can trigger flash flood, mass movements, pluvial flood and accelerated soil erosion. As soil structures are highly degraded due to intensive improper cultivation water infiltration can considerably decrease during the vegetation period. Additional changes in canopy coverage on the soil surface cause relevant variability in infiltration and hence vulnerability against runoff related disasters. Most researchers agree that the frequency of extreme precipitations increases, however, in the Carpathian Basin the uncertainties are quite high. This study aims to compare daily maximum mean precipitation amounts (MMPA) predicted by the Goda-method for June and August as the most probable months of extremities. We used the CarpatClim database as input and predicted MMPAs for two periods, 1960-1985 and 1986-2010. The Goda-method uses monthly data and calculates daily results on given probability. A general increase was found between the first and second half of the period regarding daily maximum precipitation amount in both investigated months. For August the 1-day precipitation amount increased from 56.1 mm to 61.8 mm, whereas 6-days amount from 93.8 mm to 103.2 mm at 1 per cent probability (r = 0.53; p < 0.001). Beyond this change, relevant spatial differences were found. Comparing the macro regions plains had lower increase compared to the mountains, whereas the highest increase was in the Transdanubian Hills (TH). The most endangered location is the southern part of the Transdanubian Hills where parallel with the intensive increase in MMPA both in June and August the environmental conditions such as loose parent material and the high percentage of crop fields also emphasize the potential hazard.

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“…This underlines the importance of water storage in the soil. Eekhout, J.P.C. et al (2018) presumed a considerable decline in soil water storage capacity due to climate change in Europe.…”

Section: Risky and Neutral Areas Of Changes In Intense Rainfallsmentioning

confidence: 99%

Spatial analysis of changes and anomalies of intense rainfalls in Hungary

et al. 2019

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“…Precipitation is a key climate variable in the global climate system and has an important impact on the hydrological cycle and the ecological system [7][8][9]. Scientific evidence has shown that precipitation patterns change in a warmer climate, and the likelihood of extreme precipitation is expected to increase due to global warming [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Performance of CMIP5 Global Climate Models for Simulating Future Precipitation Change in the Tibetan Plateau

Kang

Ruan

Yang

et al. 2019

Water

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In this study, the performance of 33 Coupled Model Intercomparison Project 5 (CMIP5) global climate models (GCMs) in simulating precipitation over the Tibetan Plateau (TP) was assessed using data from 1961 to 2005 by an improved score-based method, which adopts multiple criteria to achieve a comprehensive evaluation. The future precipitation change was also estimated based on the Delta method by selecting the submultiple model ensemble (SMME) in the near-term and far future (2051-2095) periods under Representative Concentration Pathways (RCP) scenarios RCP4.5 and RCP8.5. The results showed that most GCMs can reasonably simulate the precipitation pattern of an annual cycle; however, all GCMs overestimated the precipitation over TP, especially in spring and summer. The GCMs generally provide good simulations of the temporal characteristics of precipitation, while they did not perform as well in reproducing its spatial distributions. Different assessment criteria lead to inconsistent results; however, the improved rank score method, which adopts multiple criteria, provided a robust assessment of GCMs performance. The future annual precipitation was projected to increase by~6% in the near-term with respect to the period 1961-2005, whereas increases of 12.3% and 16.7% are expected in the far future under RCP4.5 and RCP8.5 scenarios, respectively. Similar spatial distributions of future precipitation changes can be seen in the near-term and far future periods under the two scenarios, and indicate that the most predominant increases occurred in the north of TP. The results of this study are expected to provide valuable information on climate change, and for water resources and agricultural management in TP.

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“…No NDVI images were available for the reference and the future periods; therefore, we determined NDVI based on a land‐use‐specific log‐linear relationship between NDVI and climate conditions (precipitation and temperature) obtained from a calibration period (2000–2012) (see Eekhout et al. , , for details). The observed and bias‐corrected precipitation and temperature data were interpolated on the model grid using bivariate interpolation (Akima, ).…”

Section: Methodsmentioning

confidence: 99%

The implications of bias correction methods and climate model ensembles on soil erosion projections under climate change

Eekhout

Vente

2019

Earth Surf Processes Landf

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Climate change will most likely cause an increase in extreme precipitation and consequently an increase in soil erosion in many locations worldwide. In most cases, climate model output is used to assess the impact of climate change on soil erosion; however, there is little knowledge of the implications of bias correction methods and climate model ensembles on projected soil erosion rates. Using a soil erosion model, we evaluated the implications of three bias correction methods (delta change, quantile mapping and scaled distribution mapping) and climate model selection on regional soil erosion projections in two contrasting Mediterranean catchments. Depending on the bias correction method, soil erosion is projected to decrease or increase. Scaled distribution mapping best projects the changes in extreme precipitation. While an increase in extreme precipitation does not always result in increased soil loss, it is an important soil erosion indicator. We suggest first establishing the deviation of the bias‐corrected climate signal with respect to the raw climate signal, in particular for extreme precipitation. Furthermore, individual climate models may project opposite changes with respect to the ensemble average; hence climate model ensembles are essential in soil erosion impact assessments to account for climate model uncertainty. We conclude that the impact of climate change on soil erosion can only accurately be assessed with a bias correction method that best reproduces the projected climate change signal, in combination with a representative ensemble of climate models. © 2018 John Wiley & Sons, Ltd.

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Why increased extreme precipitation under climate change negatively affects water security

Cited by 108 publications

References 60 publications

Spatial analysis of changes and anomalies of intense rainfalls in Hungary

Spatial analysis of changes and anomalies of intense rainfalls in Hungary

Assessing the Performance of CMIP5 Global Climate Models for Simulating Future Precipitation Change in the Tibetan Plateau

The implications of bias correction methods and climate model ensembles on soil erosion projections under climate change

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