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Rainfall and Water Resources Variability in Sub-Saharan Africa During the Twentieth Century

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Rainfall and Water Resources Variability in Sub-Saharan Africa During the Twentieth Century FEBRUARY 2009 C O N W A Y E T A L . 41 Rainfall and Water Resources Variability in Sub-Saharan Africa during the Twentieth Century DECLAN CONWAY School of Development Studies, and Tyndall Centre for Climate Change Research, University of East Anglia, Norwich, United Kingdom AURELIE PERSECHINO School of Development Studies, University of East Anglia, Norwich, United Kingdom SANDRA ARDOIN-BARDIN UMR HydroSciences Montpellier, Montpellier, France HAMISAI HAMANDAWANA Department of Geography and Environmental Sciences, North West University, Republic of South Africa CLAUDINE DIEULIN AND GIL MAHE´ UMR HydroSciences Montpellier, Montpellier, France (Manuscript received 21 December 2007, in final form 16 May 2008) ABSTRACT River basin rainfall series and extensive river flow records are used to characterize and improve under- standing of spatial and temporal variability in sub-Saharan African water resources during the last century. Nine major international river basins were chosen for examination primarily for their extensive, good quality flow records. A range of statistical descriptors highlight the substantial variability in rainfall and river flows [e.g., differences in rainfall (flows) of up to 214% (251%) between 1931–60 and 1961–90 in West Africa], the marked regional differences, and the modest intraregional differences. On decadal time scales, sub-Saharan Africa exhibits drying across the Sahel after the early 1970s, relative stability punctuated by extreme wet years in East Africa, and periodic behavior underlying high interannual variability in southern Africa. Central Africa shows very modest decadal variability, with some similarities to the Sahel in the adjoining basins. No consistent signals in rainfall and river flows emerge across the whole of the region. An analysis of rainfall–runoff relationships reveals varying behavior including strong but nonstationary relationships (particularly in West Africa); many basins with marked variations (temporal and spatial) in strength; weak, almost random behavior (particularly in southern Africa); and very few strong, temporally stable relationships. Twenty-year running correlations between rainfall and river flow tend to be higher during periods of greater rainfall station density; however, there are situations in which weak (strong) relationships exist even with reasonable (poor) station coverage. The authors conclude for sub-Saharan Africa that robust identification and attribution of hydrological change is severely limited by data avail- ability, conflicting behavior across basins/regions, low signal-to-noise ratios, sometimes weak rainfall–runoff relationships, and limited quantification of the magnitude and effects of land use change. Corresponding author address: Declan Conway, School of Development Studies, University of East Anglia, Norwich NR4 7TJ, United Kingdom. E-mail: [email protected] DOI: 10.1175/2008JHM1004.1 Ó 2009 American Meteorological Society Unauthenticated | Downloaded 10/01/21 03:31 AM UTC 42 JOURNAL OF HYDROMETEOROLOGY VOLUME 10 1. Introduction scale of large river basins [see Hulme et al. (2001) for African overview]. Above average and sometimes ex- a. The significance of water resources variability in treme rainfall in East Africa tends to be associated with Africa periodic circulation dipole events in the Indian Ocean Rainfall and river flows in Africa display high levels and complex interaction with the El Nin˜ o–Southern of variability across a range of spatial and temporal Oscillation (ENSO), particularly during the short Oc- scales, with important consequences for the manage- tober–December rains (Saji et al. 1999; Webster et al. ment of water resource systems (Sutcliffe and Knott 1999). The large decline in many West African river 1987; Grove 1996; Laraque et al. 2001; Conway 2002; flows is primarily related to the effects of the prolonged Ogutunde et al. 2006; Hamandawana 2007). Through- drying in the Sahel (late 1950s–late 1980s), with condi- out Africa, this variability brings significant implica- tions still drier than during the humid 1950s (L’Hoˆ te et tions for society and causes widespread acute human al. 2002; Dai et al. 2004)—though there are exceptions suffering and economic damage. Examples of variabil- (Nicholson 2005). ity include prolonged periods of high flows for rivers Despite the large influence of rainfall fluctuations on draining large parts of East and central Africa (Conway river flow variability, the response may be influenced 2002), and multidecadal anomalies in river flow regimes by other factors such as changes in land use or land in parts of West Africa where long-term mean yields of cover for the Sahel/West Africa (Mahe´ et al. 2005; Li et freshwater into the Atlantic Ocean fell by 18% between al. 2007; Leblanc et al. 2008) and southern Africa (Troy 1951–70 and 1971–89 (Mahe´ and Olivry 1999). There et al. 2007; Woyessa et al. 2006; Lørup et al. 1998). are many examples of the challenges posed by water Human abstractions and reservoir construction also resources variability in Africa: Lake Chad fisheries play a role (Vo¨ ro¨ smarty and Sahagian 2000; Haman- (Sarch and Allison 2000), reservoir management on the dawana et al. 2007) along with land surface to atmo- Senegal River (Magistro and Lo 2001), balancing sup- sphere feedbacks (Savenije 1996). ply and demand for Nile water in Egypt (Conway Depending on the actual hydrological conditions, 2005), irrigation management in the Greater Ruaha the effects of rainfall variability on the hydrologic re- River in Tanzania (Lankford and Beale 2007), and hy- sponse will generally translate into smooth and de- dropower generation in the Kafue (Sutcliffe and Knott layed responses in lake and wetland systems, whereas 1987) and Lake Victoria basins (Tate et al. 2004). semiarid river basins often exhibit low runoff coeffi- As anthropogenic climate change becomes increas- cients and high sensitivity to rainfall fluctuations ingly manifest, the prospect of shifts in flows and vari- (Nemec and Schaake 1982; Li et al. 2005; McMahon ability underscores the need for better understanding of et al. 2007). In addition, the nature of the land surface the drivers of variability and rainfall–runoff interac- itself may increase the variability of river flow re- tions. It is likely that extreme events are going to be the sponses to rainfall fluctuations. Peel et al. (2001, 2004) greatest socioeconomic challenge. Although sub- examined differences in the temporal behavior of Saharan Africa is generally associated with drought- rainfall and river flow between continents and showed related influences, anecdotally there appears to be that variability of annual river flows is higher for greater frequency and spatial extent of damaging temperate Australia, arid southern Africa, and tem- floods, particularly in East Africa and Ethiopia (e.g., perate southern Africa, than for other continents 2006 and 2007). Extreme floods have caused substantial with similar climatic zones. In addition to rainfall socioeconomic disruption in Mozambique (2000; variability, they found that the distribution of ever- Christie and Hanlon 2001) and East Africa (1961, 1978, green and deciduous vegetation in temperate regions and 1997; Conway 2002), whereas smaller floods may was a potential cause of greater river flow variability. be somewhat overlooked but locally significant, for ex- Vo¨ ro¨ smarty et al. (2005) found interesting features ample, in Nigeria (Tarhule 2005). Late 2006–07 saw of African river systems by combining biophysical and major floods of unprecedented spatial extent (and tim- social datasets to show that population distribution is ing) across Somalia, Ethiopia, and other parts of East strongly concentrated in regions exposed to high levels Africa, which is broadly in line with projections in the of interannual variability in rainfall and runoff. Intergovernmental Panel on Climate Change’s Fourth b. Aims Assessment Report for increases in autumn and winter rainfall (Christensen et al. 2007). Although much evidence exists for high interannual The main driver of much of the observed variability and decadal variability in rainfall and river flows in in river flows is—of course—rainfall, particularly at the sub-Saharan Africa, there are few detailed studies of Unauthenticated | Downloaded 10/01/21 03:31 AM UTC FEBRUARY 2009 C O N W A Y E T A L . 43 their spatial and temporal covariability. Previous at- et al. (2005) for the Okavango. Other river flow series tempts to estimate runoff at this scale have been based and some recent updates to the above series were ob- on the limited data available through international bod- tained from respective national agencies. ies; none have undertaken detailed rainfall–runoff For rainfall, we use the University of East Anglia’s analysis at the basin and subbasin scale, or taken a long Climate Research Unit (CRU) TS 2.1 0.58 resolution historical perspective to incorporate natural variability time series for 1901–2001 from New et al. (2001) and over decadal and century time scales. Rather surpris- updated in Mitchell and Jones (2005). River basin ingly, sub-Saharan Africa provides one of the best op- boundaries upstream of gauging stations were delin- portunities globally to do this type of analysis because eated using the Shuttle Radar Topography Mission many of the very large river basins possess long, rela- (SRTM) from the National Aeronautics and Space Ad- tively natural river flow records. We combine extensive ministration (NASA)/U.S. Geological Survey (USGS) databases held by international and national agencies as the digital elevation model, and ESRI’s Digital Chart to build a comprehensive picture of hydrometeorolog- of the World drainage files to delineate the catchments. ical variability during the twentieth century in large Basin rainfall series were calculated as the average of river basins comprising roughly 32% of sub-Saharan all 0.58CRU TS 2.1 grid boxes within the basin bound- Africa’s area. Our overarching aim is to contribute to ary. Detailed information on CRU TS 2.1 quality con- trol and notes on data interpretation can be found in the scientific understanding of variability in large water relevant publications, but we note here that Africa has resource systems.
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