It is argued in this thesis that the climate signal shows more strongly in the runoff regime of the Gambia River Basin (GRB) than the signal from deforestation. Partial and multiple regression was used to partition the effects on runoff of rainfall characteristics and deforestation over the GRB since the turn of this century. The expected shorter, higher more rapidly responding wet season flood peaks which result from deforestation have not occurred in the GRB. Rather, peak floods have fluctuated since the beginning of the century, but showing a clear declining trend similar to the rainfall regime. The large size (z 7550 km') of the sub-catchments of the GRB inhibit synchronisation of the rapid runoff that is associated with deforestation. Furthermore, deforestation, as it occurs in the GRB, takes place piece-meal as small plots of land are cleared. The nature of clearance of vegetation is important; the vegetation cleared is either replaced with another type of vegetation, for example, groundnuts or millet, or is soon allowed to recover after a cropping phase. Surface and sub-surface hydrological processes within the GRB are therefore not subjected to the severe form of alteration that characterise massive and total clearance of vegetation schemes in urban development. However, deforestation has significantly affected low flowsthere are now longer periods of lower dry season flows, and these are ascribed to the diminishing recharge of ground water. By augmenting overland flow and reducing interception and infiltration, deforestation causes a reduction in ground water recharge, which is an important component of dry season flows. Both climate change and deforestation have worked in parallel to cause a fluctuating but declining flow regime of the Gambia River. This, in turn, affects both the agricultural potential and productivity of the GRB.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:358523 |
Date | January 1993 |
Creators | Amara, Sakpa S. |
Publisher | University of Reading |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
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