| 1. |
- Towner, Jamie, et al.
(author)
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Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin
- 2019
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In: Hydrology and Earth System Sciences. - : COPERNICUS GESELLSCHAFT MBH. - 1027-5606 .- 1607-7938. ; 23:7, s. 3057-3080
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Journal article (peer-reviewed)abstract
- Extreme flooding impacts millions of people that live within the Amazon floodplain. Global hydrological models (GHMs) are frequently used to assess and inform the management of flood risk, but knowledge on the skill of available models is required to inform their use and development. This paper presents an intercomparison of eight different GHMs freely available from collaborators of the Global Flood Partnership (GFP) for simulating floods in the Amazon basin. To gain insight into the strengths and shortcomings of each model, we assess their ability to reproduce daily and annual peak river flows against gauged observations at 75 hydrological stations over a 19-year period (1997-2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) ground-water and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems.
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| 2. |
- de Bruin, Sophie P., et al.
(author)
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Projecting long-term armed conflict risk : An underappreciated field of inquiry?
- 2022
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In: Global Environmental Change. - : Elsevier. - 0959-3780 .- 1872-9495. ; 72
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Journal article (peer-reviewed)abstract
- Little research has been done on projecting long-term conflict risks. Such projections are currently neither included in the development of socioeconomic scenarios or climate change impact assessments nor part of global agenda-setting policy processes. In contrast, in other fields of inquiry, long-term projections and scenario studies are established and relevant for both strategical agenda-setting and applied policies. Although making projections of armed conflict risk in response to climate change is surrounded by uncertainty, there are good reasons to further develop such scenario-based projections. In this perspective article we discuss why quantifying implications of climate change for future armed conflict risk is inherently uncertain, but necessary for shaping sustainable future policy agendas. We argue that both quantitative and qualitative projections can have a purpose in future climate change impact assessments and put out the challenges this poses for future research.
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| 3. |
- Hoch, Jannis M, et al.
(author)
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Projecting armed conflict risk in Africa towards 2050 along the SSP-RCP scenarios : a machine learning approach
- 2021
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In: Environmental Research Letters. - : Institute of Physics Publishing (IOPP). - 1748-9326. ; 16:12
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Journal article (peer-reviewed)abstract
- In the past decade, several efforts have been made to project armed conflict risk into the future. This study broadens current approaches by presenting a first-of-its-kind application of machine learning (ML) methods to project sub-national armed conflict risk over the African continent along three Shared Socioeconomic Pathway (SSP) scenarios and three Representative Concentration Pathways towards 2050. Results of the open-source ML framework CoPro are consistent with the underlying socioeconomic storylines of the SSPs, and the resulting out-of-sample armed conflict projections obtained with Random Forest classifiers agree with the patterns observed in comparable studies. In SSP1-RCP2.6, conflict risk is low in most regions although the Horn of Africa and parts of East Africa continue to be conflict-prone. Conflict risk increases in the more adverse SSP3-RCP6.0 scenario, especially in Central Africa and large parts of Western Africa. We specifically assessed the role of hydro-climatic indicators as drivers of armed conflict. Overall, their importance is limited compared to main conflict predictors but results suggest that changing climatic conditions may both increase and decrease conflict risk, depending on the location: in Northern Africa and large parts of Eastern Africa climate change increases projected conflict risk whereas for areas in the West and northern part of the Sahel shifting climatic conditions may reduce conflict risk. With our study being at the forefront of ML applications for conflict risk projections, we identify various challenges for this arising scientific field. A major concern is the limited selection of relevant quantified indicators for the SSPs at present. Nevertheless, ML models such as the one presented here are a viable and scalable way forward in the field of armed conflict risk projections, and can help to inform the policy-making process with respect to climate security.
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| 4. |
- Scussolini, Paolo, et al.
(author)
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Global River Discharge and Floods in the Warmer Climate of the Last Interglacial
- 2020
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In: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 47:18
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Journal article (peer-reviewed)abstract
- We investigate hydrology during a past climate slightly warmer than the present: the last interglacial (LIG). With daily output of preindustrial and LIG simulations from eight new climate models we force hydrological model PCR-GLOBWB and in turn hydrodynamic model CaMa-Flood. Compared to preindustrial, annual mean LIG runoff, discharge, and 100-yr flood volume are considerably larger in the Northern Hemisphere, by 14%, 25%, and 82%, respectively. Anomalies are negative in the Southern Hemisphere. In some boreal regions, LIG runoff and discharge are lower despite higher precipitation, due to the higher temperatures and evaporation. LIG discharge is much higher for the Niger, Congo, Nile, Ganges, Irrawaddy, and Pearl and lower for the Mississippi, Saint Lawrence, Amazon, Parana, Orange, Zambesi, Danube, and Ob. Discharge is seasonally postponed in tropical rivers affected by monsoon changes. Results agree with published proxies on the sign of discharge anomaly in 15 of 23 sites where comparison is possible.
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