A process‐based soil erosion model ensemble to assess model uncertainty in climate change impact assessments

2021 ◽  
Author(s):  
J.P.C. Eekhout ◽  
A. Millares‐Valenzuela ◽  
A. Martínez‐Salvador ◽  
R. García‐Lorenzo ◽  
P. Pérez‐Cutillas ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Model Uncertainty ◽  
Climate Change Impact ◽  
Model Ensemble ◽  
Erosion Model ◽  
Change Impact

A process-based soil erosion model ensemble to reduce model uncertainty in climate change impact assessments

2021 ◽  
Author(s):  
Joris Eekhout ◽  
Agustín Millares-Valenzuela ◽  
Alberto Martínez-Salvador ◽  
Rafael García-Lorenzo ◽  
Pedro Pérez-Cutillas ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Model Uncertainty ◽  
Extreme Precipitation ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Model Ensemble ◽  
Erosion Model ◽  
Erosion Models ◽  
Change Impact

<p>The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are potentially an important source of uncertainty. Here we propose a soil erosion model ensemble, with the aim to reduce the model uncertainty in climate change impact assessments. The model ensemble consisted of five continuous process-based soil erosion models that run at a daily time step, i.e. DHSVM, HSPF, INCA, MMF and SHETRAN. All models simulate detachment by raindrop impact (interrill erosion), detachment by runoff (rill erosion) and immediate deposition of sediment within the cell of its origin. The models were implemented in the SPHY hydrological model. The soil erosion model ensemble was applied in a semi-arid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3 ºC). Data from two contrasting regional climate models were used to assess how an increase and a decrease in extreme precipitation affect model uncertainty. Soil loss is projected to increase and decrease under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent on the projected change in annual precipitation and extreme precipitation. This supports the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate change impact assessments.</p><p>This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities - State Research Agency (AEI) /Project CGL2017-84625-C2-1-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.</p>

Communicating water-related climate change hazards to local stakeholders

2021 ◽  
Author(s):  
Laura Müller ◽  
Petra Döll
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Climate Change Impact ◽  
Biosphere Reserve ◽  
Hydrological Models ◽  
Model Ensemble ◽  
Hydrological Hazards ◽  
Local Stakeholders ◽  
Change Impact ◽  
The Impact

<p>Due to climate change, the water cycle is changing which requires to adapt water management in many regions. The transdisciplinary project KlimaRhön aims at assessing water-related risks and developing adaptation measures in water management in the UNESCO Biosphere Reserve Rhön in Central Germany. One of the challenges is to inform local stakeholders about hydrological hazards in in the biosphere reserve, which has an area of only 2433 km² and for which no regional hydrological simulations are available. To overcome the lack of local simulations of the impact of climate change on water resources, existing simulations by a number of global hydrological models (GHMs) were evaluated for the study area. While the coarse model resolution of 0.5°x0.5° (55 km x 55 km at the equator) is certainly problematic for the small study area, the advantage is that both the uncertainty of climate simulations and hydrological models can be taken into account to provide a best estimate of future hazards and their (large) uncertainties. This is different from most local hydrological climate change impact assessments, where only one hydrological model is used, which leads to an underestimation of future uncertainty as different hydrological models translate climatic changes differently into hydrological changes and, for example, mostly do not take into account the effect of changing atmospheric CO<sub>2</sub> on evapotranspiration and thus runoff.   </p><p>The global climate change impact simulations were performed in a consistent manner by various international modeling groups following a protocol developed by ISIMIP (ISIMIP 2b, www.isimip.org); the simulation results are freely available for download. We processed, analyzed and visualized the results of the multi-model ensemble, which consists of eight GHMs driven by the bias-adjusted output of four general circulation models. The ensemble of potential changes of total runoff and groundwater recharge were calculated for two 30-year future periods relative to a reference period, analyzing annual and seasonal means as well as interannual variability. Moreover, the two representative concentration pathways RCP 2.6 and 8.5 were chosen to inform stakeholders about two possible courses of anthropogenic emissions.</p><p>To communicate the results to local stakeholders effectively, the way to present modeling results and their uncertainty is crucial. The visualization and textual/oral presentation should not be overwhelming but comprehensive, comprehensible and engaging. It should help the stakeholder to understand the likelihood of particular hazards that can be derived from multi-model ensemble projections. In this contribution, we present the communication approach we applied during a stakeholder workshop as well as its evaluation by the stakeholders.</p>

scholarly journals Climate change impact on soil erosion in the Mandakini River Basin, North India

2016 ◽  
Vol 7 (5) ◽  
pp. 2373-2383 ◽  
Author(s):  
Deepak Khare ◽  
Arun Mondal ◽  
Sananda Kundu ◽  
Prabhash Kumar Mishra
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
River Basin ◽  
Climate Change Impact ◽  
North India ◽  
Change Impact

scholarly journals Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators

2013 ◽  
Vol 120 (1-2) ◽  
pp. 211-227 ◽  
Author(s):  
Tobias Lung ◽  
Alessandro Dosio ◽  
William Becker ◽  
Carlo Lavalle ◽  
Laurens M. Bouwer
Keyword(s):  
Climate Change ◽  
Model Uncertainty ◽  
Climate Change Impact ◽  
Climate Model ◽  
Impact Indicators ◽  
Change Impact ◽  
Climate Model Uncertainty
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