Articles | Volume 19, issue 5
Research article
08 May 2015
Research article |  | 08 May 2015

Spatial and temporal variability of rainfall in the Nile Basin

C. Onyutha and P. Willems

Abstract. Spatiotemporal variability in annual and seasonal rainfall totals were assessed at 37 locations of the Nile Basin in Africa using quantile perturbation method (QPM). To get insight into the spatial difference in rainfall statistics, the stations were grouped based on the pattern of the long-term mean (LTM) of monthly rainfall and that of temporal variability. To find the origin of the driving forces for the temporal variability in rainfall, correlation analyses were carried out using global monthly sea level pressure (SLP) and sea surface temperature (SST). Further investigations to support the obtained correlations were made using a total of 10 climate indices. It was possible to obtain three groups of stations; those within the equatorial region (A), Sudan and Ethiopia (B), and Egypt (C). For group A, annual rainfall was found to be below (above) the reference during the late 1940s to 1950s (1960s to mid-1980s). Conversely for groups B and C, the period from 1930s to late 1950s (1960s to 1980s) was characterized by anomalies being above (below) the reference. For group A, significant linkages were found to Niño 3, Niño 3.4, and the North Atlantic Ocean and Indian Ocean drivers. Correlations of annual rainfall of group A with Pacific Ocean-related climate indices were inconclusive. With respect to the main wet seasons, the June–September rainfall of group B has strong connection to the influence from the Indian Ocean. For the March–May (October–February) rainfall of group A (C), possible links to the Atlantic and Indian oceans were found.

Short summary
Variability of rainfall in the Nile Basin was found linked to the large-scale atmosphere-ocean interactions. This finding is vital for a number of water management and planning aspects. To give just one example, it may help in obtaining improved quantiles for flood or drought/water scarcity risk management. This is especially important under conditions of (1) questionable data quality, and (2) data scarcity. These conditions are typical of the Nile Basin and inevitably need to be addressed.