Abstract
Flood early warning systems play a more substantial role in risk mitigation than ever before. Hydrological forecasts, which are an essential part of these systems, are used to trigger action against floods around the world. This research presents an evaluation framework, where the skills of the Global Flood Awareness System (GloFAS) are assessed in Peru for the years 2009–2015. Simulated GloFAS discharges are compared against observed ones for 10 river gauges. Forecasts skills are assessed from two perspectives: (i) by calculating verification scores at every river section against simulated discharges and (ii) by comparing the flood signals against reported events. On average, river sections with higher discharges and larger upstream areas perform better. Raw forecasts provide correct flood signals for 82% of the reported floods, but exhibit low verification scores. Post-processing of raw forecasts improves most verification scores, but reduces the percentage of the correctly forecasted reported events to 65%.
Original language | English |
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Pages (from-to) | 1171-1189 |
Number of pages | 19 |
Journal | Hydrological Sciences Journal |
Volume | 64 |
Issue number | 10 |
DOIs | |
Publication status | Published - 27 Jul 2019 |
Funding
The project was funded by NWO-VICI [Grant no. 453-13-006] and NWO New Delta [Grant no. 869.15.001];Nederlandse Organisatie voor Wetenschappelijk Onderzoek [NWO New Delta/869.15.001,NWO-VICI/453-13-006]. We thank Munich Re for providing reported flood data from the NatCatSERVICE database for the VIDI Compound Risk project by Philip Ward.
Funders | Funder number |
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Nederlandse Organisatie voor Wetenschappelijk Onderzoek | NWO-VICI /453-13-006, Delta/869.15.001 |
Keywords
- bias-correction
- early warning
- ensemble streamflow predictions
- flood
- forecast
- risk