the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Impact-based flood forecasting in the Greater Horn of Africa
Lorenzo Alfieri
Andrea Libertino
Lorenzo Campo
Francesco Dottori
Simone Gabellani
Tatiana Ghizzoni
Alessandro Masoero
Lauro Rossi
Roberto Rudari
Nicola Testa
Eva Trasforini
Ahmed Amdihun
Jully Ouma
Luca Rossi
Yves Tramblay
Huan Wu
Marco Massabò
Abstract. Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises and population displacement. Impact-based forecasting and early warning for natural hazards is recognized as a step forward in disaster risk reduction, thanks to its focus on people, livelihoods and assets at risk. Yet, the majority of the African population is not covered by any sort of early warning system. This article describes the setup of Flood-PROOFS East Africa, an impact-based riverine flood forecasting and early warning system for the Greater Horn of Africa (GHA), with a forecast range of 5 days. The system is based on a modeling cascade relying on distributed hydrological simulations forced by ensemble weather forecasts, link to inundation maps for specific return period, and application of a risk assessment framework to estimate population and assets exposed to upcoming floods. The system is operational and supports the African Union Commission and the IGAD Disaster Operation Center in the daily monitoring and early warning from hydro-meteorological disasters in Eastern Africa. Results show a first evaluation of the hydrological reanalysis at 78 river gauging stations and a semi-quantitative assessment of the impact forecasts for the catastrophic floods in Sudan and in the Nile River Basin in Summer 2020.
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Lorenzo Alfieri et al.
Status: open (until 13 Jun 2023)
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RC1: 'Comment on egusphere-2023-804', Anonymous Referee #1, 19 May 2023
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OVERVIEW
The paper describes a large-scale flood forecasting system developed for the Greater Horn of Africa. The paper describes the development of the system and results both in terms of flood forecasting and also for impact assessment.
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GENERAL COMMENTS
The paper is well written, well-structured and clear. The topic is surely of interest for the readers of Natural Hazard and Earth System Sciences (NHESS) as the paper describes an important effort to develop a large-scale flood forecasting system in an African region. The authors made a great job in developing the system and I believe the paper deserves to be published.
However, I have some major comments that, in my opinion, need to be addressed before the publication.
MAJOR COMMENTS
- The development of the system has required a number of choices with respect to input data, meteorological forecasts, and hydrological modelling. The paper only describes the system currently running without considering possible alternatives. For instance, why satellite precipitation from GSMaP? Why the GFS forecasting system? Have the authors investigated alternative options? I believe that a discussion on the decisions made to develop the system is needed.
- It is not clear how the system works in real time. If I understand correctly, the hydrological model is run every day with last day satellite precipitation from GSMaP (1 day behind now) and 5-day GFS forecast. But in the text it reads ERA5 is used. Presumably the model is run every day starting from N-days before the “now” and ERA5 is used until it is available. Something it reads at the beginning of section 2.5.1, but it seems that ERA5 is not used at all. However, this is not specified in the text and it should be clarified.
- The criteria used for parameter regionalization should be specified.
- Did the authors check the agreement between ERA5, GSMaP and GFS precipitation data? It is a very important and critical aspect in the development of a flood forecasting systems.
- The impact assessment is carried out by defining several indices. However, it is not clear how the indices are calculated and how they are integrated. I assume that normalised indices have been calculated, but this should be clarified.
- The authors say that correlation is a suitable indicator to measure the model capability to detect flood events and it is good if threshold exceedances have to be assessed. I would agree, but it should be shown in the paper. Is the model able to detect flood event correctly in terms of threshold exceedances? A dedicated paragraph should be written on this point.
SPECIFIC COMMENTS (L: line or lines)
L161: “Alfieri et al. (2022a) is missing in the references list.
L181: GEFS is not defined, please check all the acronyms.
L248: It is not clear how many stations are used for calibration and how many for validation.
L269: The Supplemental Material should be cited more clearly, which figure exactly? Which paragraph?
L325: It would be interesting to show stations located downstream large reservoirs to assess the reservoir impact.
Figure 3: The figure is too small and hardly readable. Moreover, the stations shown in the figure should be highlighted in the map. The last panel (bottom right) shows a strange behaviour of river discharge; is there any explanation for that?
L364: Do the authors have an estimation of peak river discharge? Can the authors make a comparison between observed and modelled peak discharge?
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RECOMMENDATION
On this basis, I found the topic of the paper quite relevant and I suggest a moderate revision before its publication on NHESS.
Citation: https://doi.org/10.5194/egusphere-2023-804-RC1
Lorenzo Alfieri et al.
Lorenzo Alfieri et al.
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