GCM-related uncertainty for river flows and inundation under climate change: the Inner Niger Delta

Figures & data

Figure 1. The Upper Niger Catchment and the Inner Niger Delta. The sub-catchments and their downstream gauging stations for which separate sub-models were developed are indicated.

Figure 2. (a) The relationship between weighted aggregate inflow to the Inner Niger Delta (Ke-Macina + Beney-Kegny) and monthly outflow (Douna), (b) comparison between observed and calculated monthly flows at Douna. Analyses are based on the period 1953–1992 using GRDC gauging station records.

Table 1. GCMs that were pattern-scaled by ClimGen and applied in this study.

GCM	Climate modelling centre and country
CCCMA CGCM3.1	Canadian Centre for Climate Modelling and Analysis (Canada)
CSIRO MK3.0	Commonwealth Scientific and Industrial Research Organisation Atmospheric Research (Australia)
IPSL CM4	Institut Pierre Simon Laplace (France)
MPI ECHAM5	Max Planck Institute for Meteorology (Germany)
NCAR CCSM30	National Centre for Atmospheric Research (USA)
UKMO HadGEM1	Hadley Centre for Climate Prediction and Research (UK)
UKMO HadCM3	Hadley Centre for Climate Prediction and Research (UK)

Figure 3. Monthly mean observed and simulated discharges for seven gauging stations within the Upper Niger for the period 1950–2000. The calibration (1950–1975), validation (1976–2000) and baseline (1961–1990) periods are indicated. Note different y-axis scales. Letters in brackets refer to the sub-catchments identified in Fig. 1.

Table 2. Model performance statistics for twelve gauging stations within the Upper Niger for the calibration (Cal. 1950–1975), baseline (BL 1961–1990) and validation (Val. 1976–2000) periods. Letters after gauging station names refer to the labels used in Fig. 1. Model performance indicators are taken from Henriksen et al. (2008).

Station	Period	Data availability^†	Dv (%)^+		NSE*		r^#
Tinkisso (a)	Cal.	13, 3, 3, 1, 6	–1.44	☆☆☆☆☆	0.860	☆☆☆☆☆	0.928
	BL	11, 3, 2, 1, 14	–3.62	☆☆☆☆☆	0.860	☆☆☆☆☆	0.928
	Val.	3, 0, 0, 0, 22	4.81	☆☆☆☆☆	0.790	☆☆☆☆	0.937
Kouroussa (b)	Cal.	14, 5, 6, 1, 0	–1.38	☆☆☆☆☆	0.846	☆☆☆☆	0.921
	BL	18, 6, 5, 2, 0	–1.65	☆☆☆☆☆	0.823	☆☆☆☆	0.908
	Val.	13, 4, 6, 2, 0	10.53	☆☆☆	0.765	☆☆☆☆	0.899
Banankoro (c)	Cal.	5, 3, 0, 1, 17	–5.46	☆☆☆☆	0.928	☆☆☆☆☆	0.965
	BL	13, 4, 5, 1, 8	0.10	☆☆☆☆☆	0.925	☆☆☆☆☆	0.962
	Val.	13, 4, 6, 1, 1	11.87	☆☆☆	0.898	☆☆☆☆☆	0.961
Kankan (d)	Cal.	24, 1, 1, 0, 0	–4.95	☆☆☆☆☆	0.857	☆☆☆☆☆	0.936
	BL	25, 5, 1, 0, 0	–3.01	☆☆☆☆☆	0.897	☆☆☆☆☆	0.954
	Val.	13, 11, 1, 0, 0	3.46	☆☆☆☆☆	0.863	☆☆☆☆☆	0.940
Sankarani (e)	Cal.	9, 2, 1, 0, 14	–3.83	☆☆☆☆☆	0.863	☆☆☆☆☆	0.931
	BL	12, 4, 3, 0, 12	–3.05	☆☆☆☆☆	0.835	☆☆☆☆	0.916
	Val.	4, 2, 2, 0, 17	–0.60	☆☆☆☆☆	0.688	☆☆☆☆	0.840
Bougouni (f)	Cal.	13, 5, 1, 0, 7	–5.00	☆☆☆☆☆	0.876	☆☆☆☆☆	0.943
	BL	18, 4, 0, 0, 9	–5.22	☆☆☆☆	0.861	☆☆☆☆☆	0.933
	Val.	8, 0, 0, 0, 17	–5.19	☆☆☆☆	0.878	☆☆☆☆☆	0.937
Pankourou (g)	Cal.	7, 11, 2, 0, 6	–4.97	☆☆☆☆☆	0.862	☆☆☆☆☆	0.932
	BL	10, 12, 1, 0, 8	–5.31	☆☆☆☆	0.839	☆☆☆☆	0.921
	Val.	6, 2, 0, 0, 17	–2.52	☆☆☆☆☆	0.819	☆☆☆☆	0.918
Koulikoro (h)	Cal.	26, 0, 0, 0, 0	–3.65	☆☆☆☆☆	0.948	☆☆☆☆☆	0.974
	BL	31, 0, 0, 0, 0	–0.34	☆☆☆☆☆	0.932	☆☆☆☆☆	0.965
	Val.	24, 1, 0, 0, 0	11.41	☆☆☆	0.879	☆☆☆☆☆	0.961
Douna (i)	Cal.	15, 5, 6, 0, 0	–9.75	☆☆☆☆	0.907	☆☆☆☆☆	0.956
	BL	24, 3, 4, 0, 0	–4.26	☆☆☆☆☆	0.882	☆☆☆☆☆	0.940
	Val.	22, 1, 2, 0, 0	16.32	☆☆☆	0.721	☆☆☆☆	0.925
Ke-Macina (j)	Cal.	16, 3, 4, 0, 3	0.01	☆☆☆☆☆	0.954	☆☆☆☆☆	0.980
	BL	16, 4, 4, 0, 7	1.33	☆☆☆☆☆	0.936	☆☆☆☆☆	0.971
	Val.	7, 2, 0, 0, 16	12.35	☆☆☆	0.874	☆☆☆☆☆	0.956
Beney-Kegny (k)	Cal.	16, 5, 4, 0, 1	–6.78	☆☆☆☆	0.897	☆☆☆☆☆	0.953
	BL	15, 4, 4, 0, 8	–9.39	☆☆☆☆	0.864	☆☆☆☆☆	0.936
	Val.	7, 0, 1, 0, 17	–9.50	☆☆☆☆	0.770	☆☆☆☆	0.883
Dire (l)	Cal.	24, 2, 0, 0, 0	–4.81	☆☆☆☆☆	0.901	☆☆☆☆☆	0.952
	BL	28, 3, 0, 0, 0	4.64	☆☆☆☆☆	0.853	☆☆☆☆☆	0.942
	Val.	20, 3, 1, 0, 1	17.81	☆☆☆	0.685	☆☆☆☆	0.893
Performance indicator	Excellent ☆☆☆☆☆	Very good ☆☆☆☆	Fair ☆☆☆	Poor ☆☆	Very poor ☆
Dv	< 5%	5–10%	10–20%	20–40%	>40%
NSE	>0.85	0.65–0.85	0.50–0.65	0.20–0.50	<0.20

^†Number of years during the calibration, baseline or validation periods for which 12, 9–11, 5–8, 1–4 and 0 months of discharge data are available, ⁺bias (Henriksen et al. 2003), *Nash-Sutcliffe coefficient (Nash and Sutcliffe, 1970), ^#Pearson correlation coefficient.

Figure 4a. Observed and simulated mean monthly discharges for 12 gauging stations within the Upper Niger for the period for the calibration (1950–1975), baseline (1961–1990) and validation (1976–2000) periods. Note different y-axis scales. Letters in brackets refer to the sub-catchments identified in Fig. 1. Symbols in square brackets indicate availability for each period: + Good, +- Medium, – Poor.

Figure 4b. Continued.

Figure 5. Flood extent within the Inner Niger Delta: (a) simulated monthly flood extent and annual maxima provided by Zwarts and Grigoras (2005); (b, c, d) simulated (S) vs Zwarts and Grigoras (2005) (ZG) annual maximum flood extents for the calibration, baseline and validation periods, respectively.

Table 3. Mean annual precipitation (Precip.) and potential evapotranspiration (PET) for the baseline (mm) and changes (%) for the climate change scenarios for sub-catchments within the Upper Niger catchment. (Shaded cells indicate negative changes compared to the baseline).

		Sub-catchments (letters refer to model sub-catchments indicated in Fig. 1)
Parameter	Scenario	a	b	c	d	e	f	g	h	i	j	k	l
Precip.	Baseline	1384.3	1677.0	1564.1	1730.2	1457.5	1282.6	1198.7	1056.3	957.8	585.2	740.7	446.1
	CCCMA	–7.7	–5.9	–5.8	–5.8	–5.6	–5.8	–5.4	–4.1	–2.7	–2.7	0.0	0.7
	CSIRO	–1.4	2.3	4.9	6.2	4.3	2.9	–0.5	–2.1	–4.8	–5.9	–5.2	–1.6
	HadCM3	–3.2	1.4	0.5	2.8	2.3	2.1	2.2	–2.2	–0.8	–6.6	3.6	–1.7
	HadGEM1	–8.6	–9.2	–6.7	–9.0	–5.3	–1.8	–1.2	–1.7	0.5	1.5	2.4	7.1
	IPSL	–31.5	–30.0	–25.9	–22.2	–17.9	–17.0	–16.1	–18.6	–5.5	–18.0	–13.2	–10.2
	MPI	–7.0	–4.0	–3.8	–2.8	–2.2	–1.6	–1.0	–6.3	–4.3	–11.9	–6.3	–11.1
	NCAR	–2.4	0.5	–0.8	0.0	0.0	0.6	1.0	–1.9	1.0	4.0	7.4	14.4
PET	Baseline	1883.9	1856.4	1920.7	1908.5	1924.3	1922.6	1924.1	1968.1	1969.7	2043.8	2015.3	2089.9
	CCCMA	6.5	5.7	5.8	5.5	5.6	5.5	5.3	6.1	5.8	5.9	5.6	5.2
	CSIRO	5.8	5.3	5.5	5.1	5.3	5.4	5.4	6.0	6.0	6.0	6.2	5.9
	HadCM3	6.4	5.8	6.3	6.2	6.7	7.0	7.0	7.2	7.3	7.4	7.3	7.0
	HadGEM1	3.4	3.1	3.3	3.0	2.9	2.7	2.2	2.8	2.4	2.8	2.6	2.9
	IPSL	6.7	6.3	6.4	6.2	6.3	6.3	6.1	6.4	6.2	6.1	6.1	5.6
	MPI	6.9	6.4	6.5	6.2	6.2	6.1	5.8	6.7	6.3	6.7	6.5	6.1
	NCAR	2.8	2.0	2.4	2.1	2.4	2.5	2.6	3.4	3.5	4.5	4.2	3.8

Figure 6. Mean monthly precipitation and PET for the baseline and the 2°C, seven GCM climate change scenarios for four representative sub-catchments within the Upper Niger. Note different y-axis scales. Letters in brackets refer to the sub-catchments identified in Fig. 1.

Table 4. Mean annual mean, Q5 and Q95 discharges for the baseline (m³s^-1) and changes (%) for the climate change scenarios for 12 gauging stations within the Upper Niger catchment. (Shaded cells indicate negative changes compared to the baseline).

		Gauging station (letters refer to gauging stations indicated in Fig. 1)
Parameter	Scenario	a	b	c	d	e	f	g	h	i	j	k	l
Mean	Baseline	138.8	194.6	924.3	163.4	299.7	86.8	164.2	1235.2	340.9	1171.2	344.8	928.8
	CCCMA	–29.0	–22.5	–23.3	–23.3	–21.0	–34.2	–33.9	–23.1	–33.1	–24.2	–32.7	–18.3
	CSIRO	–8.9	–2.5	3.1	10.8	5.5	–3.5	–17.5	3.2	–21.6	3.0	–21.1	–0.8
	HadCM3	–8.4	3.3	0.9	3.6	1.2	–0.7	–1.7	0.7	–6.1	0.6	–5.7	–1.5
	HadGEM1	–12.2	–12.4	–5.5	–2.7	8.6	22.2	23.3	–1.8	22.2	–1.5	22.0	0.3
	IPSL	–68.4	–56.7	–52.9	–45.5	–37.0	–53.9	–54.0	–49.7	–57.0	–51.8	–55.8	–42.5
	MPI	–14.3	–7.5	–6.3	–2.5	1.7	2.8	3.7	–4.6	–1.2	–4.7	–1.1	–4.0
	NCAR	–17.9	–9.1	–14.3	–16.2	–15.8	–24.5	–23.9	–15.1	–25.9	–15.9	–25.5	–11.9
Q5	Baseline	593.9	712.5	3602.2	624.5	1160.2	416.9	919.2	4726.2	1730.0	4709.5	1742.0	2128.7
	CCCMA	–22.6	–14.3	–16.0	–16.9	–17.5	–29.3	–28.4	–17.5	–26.2	–20.8	–25.5	–7.2
	CSIRO	–2.7	1.8	3.4	9.9	0.9	–5.5	–15.7	4.3	–16.2	0.3	–19.1	–1.4
	HadCM3	–2.8	6.0	2.8	7.5	2.1	0.4	–0.1	3.5	–6.8	2.5	–4.0	–0.4
	HadGEM1	–3.2	–0.1	2.8	6.2	14.0	21.3	17.1	4.0	21.3	0.2	16.7	1.4
	IPSL	–53.1	–42.2	38.7	30.8	28.9	–42.6	–44.2	–38.0	–47.1	–40.2	–46.1	–16.8
	MPI	–6.8	1.2	0.9	5.2	4.4	–2.1	3.7	0.0	–0.8	–1.7	0.8	–1.4
	NCAR	–15.9	–6.8	–10.2	–9.4	–12.9	–20.7	–20.1	–12.7	–19.6	–14.2	–18.8	–5.0
Q95	Baseline	0.6	3.4	8.0	1.5	0.2	0.1	0.1	10.3	0.5	0.0	0.8	0.0
	CCCMA	–50.0	–32.4	–30.0	–26.7	–50.0	–100.0	–100.0	–37.9	–100.0	–^†	–75.0	–^†
	CSIRO	0.0	–11.8	16.3	6.7	0.0	0.0	–100.0	–2.9	–80.0	–^†	–62.5	–^†
	HadCM3	16.7	–5.9	2.5	0.0	0.0	0.0	0.0	–14.6	–60.0	–^†	–37.5	–^†
	HadGEM1	–16.7	–32.4	–15.0	–13.3	–50.0	0.0	0.0	–26.2	80.0	–^†	150.0	–^†
	IPSL	–83.3	–67.6	–63.8	–46.7	–50.0	–100.0	–100.0	–67.0	–100.0	–^†	–75.0	–^†
	MPI	–33.3	–14.7	–12.5	–6.7	–50.0	0.0	–100.0	–21.4	–60.0	–^†	–37.5	–^†
	NCAR	0.0	–17.6	–15.0	–20.0	–50.0	–100.0	–100.0	–20.4	–100.0	–^†	–75.0	–^†

^†Baseline and scenario Q95 = 0 m³s^-1.

Figure 7. Simulated river regimes for the baseline and 2°C, seven GCM climate change scenarios for 12 gauging stations within the Upper Niger. Note different y-axis scales. Letters in brackets refer to the sub-catchments identified in Fig. 1.

Figure 8. Baseline and 2°C, seven GCM climate change scenario river inflows to the Inner Niger Delta: (a) mean monthly inflows; (b) scenario change in mean annual inflows compared to the baseline. CC = CCCMA; CS = CSIRO; H3 = HadCM3; H1 = HadGEM1; IP = IPSL; MP = MPI; NC = NCAR.

Figure 9. Flood regimes for the Inner Niger Delta for the baseline and 2°C, seven GCM climate change scenarios.

Figure 10. Impacts of the 2°C, seven GCM climate change scenarios on annual peak flood extents within the Inner Niger Delta: (a) peak flood extent-frequency for the baseline and each scenario; (b-d) change from the baseline in the maximum, mean and minimum annual peak flood extents. CC = CCCMA; CS = CSIRO; H3 = HadCM3; H1 = HadGEM1; IP = IPSL; MP = MPI; NC = NCAR.

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