The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Development and evaluation of a framework for global flood hazard mapping
Open accessAbstract
Nowadays, the development of high-resolution flood hazard models have become feasible at continental and global scale, and their application in developing countries and data-scarce regions can be extremely helpful to increase preparedness of population and reduce catastrophic impacts. The present work describes the development of a novel procedure for global flood hazard mapping, based on the most recent advances in large scale flood modelling. We derive a long-term dataset of daily river discharges from the hydrological simulations of the Global Flood Awareness System (GloFAS). Streamflow data is downscaled on a high resolution river network and processed to provide the input for local flood inundation simulations, performed with a two-dimensional hydrodynamic model. All flood-prone areas identified along the river network are then merged to create continental flood hazard maps for different return periods at 30′′ resolution. We evaluate the performance of our methodology in several river basins across the globe by comparing simulated flood maps with both official hazard maps and a mosaic of flooded areas detected from satellite images. The evaluation procedure also includes comparisons with the results of other large scale flood models. We further investigate the sensitivity of the flood modelling framework to several parameters and modelling approaches and identify strengths, limitations and possible improvements of the methodology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ensemble flood risk assessment in Europe under high end climate scenarios
Alfieri, L., Feyen, L., Dottori, F., & Bianchi, A. (2015) · Global Environmental Change · doi:10.1016/j.gloenvcha.2015.09.004 · Cited by 346
Self-citation
Cited by
Mishra, K., & Sinha, R. (2020) · Geomorphology · doi:10.1016/j.geomorph.2019.106861 · Cited by 236
Das, S. (2018) · Arabian Journal of Geosciences · doi:10.1007/s12517-018-3933-4 · Cited by 203
Multi-Model Projections of River Flood Risk in Europe under Global Warming
Alfieri, L., Dottori, F., Betts, R., Salamon, P., & Feyen, L. (2018) · Climate · doi:10.3390/cli6010006 · Cited by 149
“To model inundation processes, JRC-EU and JRC-GL made use of a catalogue of model based inundation maps at the European [32] and Global [49] scales for a set of constant flood magnitudes.”
MethodSelf-citation
Metadata
- Authors
- Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., & Feyen, L.
- Venue
- Advances in Water Resources
- Publisher
- Elsevier BV
- Published
- 2016-08
- Volume
- 94
- Pages
- 87-102
- ISSN
- 0309-1708 (ISSN-L)
- OpenAlex
- W2346877152
- Cited by
- 451
- References
- 1
- FWCI
- 19.49
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Development and evaluation of a framework for global flood hazard mapping. https://app.cochat.ai/papers/10.1016/j.advwatres.2016.05.002
- The paper
- Dottori, F., Salamon, P., Bianchi, A., Alfieri, L., Hirpa, F. A., & Feyen, L. (2016). Development and evaluation of a framework for global flood hazard mapping. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2016.05.002
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.