Integrating multi-sensor observations and rainfall-runoff inundation modeling for mapping flood extents over the Nile River basin: example from the 2020 flooding in Sudan

Figures & data

Figure 1. (a) the location of the two subbasins (the BNB and the White Nile basin) of the NRB and the streamflow stations (b) the location of Sudan and the damage and losses of their states caused by the flood event of 2020 (modified from (UNOCHA (United Nations Office for the Coordination of Humanitarian Affairs) 2020)).

Figure 2. flow chart represents the Methodology steps.

Table 1. Summary of satellite images and reanalysis data used in this study.

Datasets	Launched date	Dataset provider	Temporal resolution	Spatial resolution	Purpose	More details
MODIS	July,2002	NASA LP DAAC at the USGS EROS Center	daily	200 m	Surface area	(NASA LP DAAC 2018)
Landsat −8	April, 2013	USGS	16 days	30 m	Surface area	(Chander et al. 2009)
Sentinel-1	April 2014	European Union/ESA/ Copernicus	12 days	10 m	Flood Mapping	(Sentinel Data Access Overview; Attema et al. 2010)
Sentinel-2A	June, 2015	European Union/ESA/ Copernicus	6 days	10 m	Surface area	(SUHET 2015)
CHIRPS	February, 2015	UCSB/CHG	daily	0.25˚×0.25˚	Precipitation	(Funk et al. 2015)
ERA5	1981	Climate Data Store	monthly	0.25˚×0.25˚	Evaporation	(Muñoz Sabater 2019)

Figure 3. The hydrograph of simulated results and the observed discharge (a) Khartoum station (daily time scale) (b) Khartoum station (monthly time scale) (c) Malakal station (monthly time scale).

Table 2. Statistical indices for the evaluation of the RRI model’s performance.

Stations	Time steps	Calibration			Validation
		NSE	R^2	BIAS	NSE	R^2	BIAS
Khartoum station	Daily	0.72	0.85	−0.03	0.72	0.85	0.07
	Monthly	0.84	0.92	−0.07	0.80	0.91	16.44
Malakal station	Monthly	0.69	0.56	−0.03	0.51	0.78	0.04

Figure 4. The flood inundation extends maps using four sensors over Khartoum state (a) MODIS (b) Sentinel-1 c) Sentinel-2 d) Landsat 8.

Figure 5. Estimated flood extent by each sensor.

Figure 6. Mapping of flood inundation extent over the most affected states for two sensors (MODIS, Sentinel-2) and RRI results.

Figure 7. Categorical Statistical indicators used to evaluate the performance of sensors in detection flood inundation.

Figure 8. Flood inundation area of the two extreme flood events as estimated by two sensors and the RRI model over different states.

UNOCHA (United Nations Office for the Coordination of Humanitarian Affairs) 2020. Sudan: floods map (as of 06/09/2020).

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Data availability statement

The data that support the findings of this study are available from the corresponding author, [Hadir Abdelmoneim], upon reasonable request.