Developing Sediment Yield Prediction Equations for Small Catchments in Tanzania - Advances in Data, Methods, Models and Their Applications in Geoscience - page 242

Christiansson (1981) made detailed recording of the soil erosion complex within five
selected catchments in Dodoma, the semi-arid savannah areas of central Tanzania, 4 of
which with reservoirs (Fig. 2.1). The principal methods employed include field surveying
and air photo interpretation. The main approach was physical geographical aiming at
studying the existing features of soil erosion and sedimentation and analysis of the
underlying causes of the processes. Christiansson (1981) estimated sediment yields of 260 -
900 t/km 2 /yr or 2.6 - 9 t/ha/yr as averages for the longest periods of available records.
Although, Christiansson asserted that the estimated sediment yields from his study were of
the same order of magnitude as those recorded in similar environments in other parts of
East Africa, the scope of the study was limited in-terms of spatial and climate
representation.
Mulengera and Payton (1999) in their review of the soil loss estimation equations noted that
most of the countries in the tropics have no appropriate and accurate soil erosion prediction
equations, although the Soil Loss Estimation Model for Southern Africa (SLEMSA) and the
Universal Soil Loss Equation (USLE) are used in different tropical countries. The SLEMSA(
developed in Zimbabwe) still needs some modifications and has, so far, not been widely
used or tested outside Zimbabwe and in some instances have shown to give unrealistic soil
loss values (Mulengera and Payton,1999). The USLE (developed in the USA) and widely
used throughout the world has in most cases been found to be inapplicable in the tropics.
This is due to the fact that the equation's soil erodibility nomograph commonly gives
unrealistic values for tropical soils. Although derivation of the erodibility equations for the
tropical soils have shown that soil erodibility is strongly related to texture-related soil
characteristics as has been shown for soils in temperate regions, there are differences in the
magnitudes of the characteristics for soils with relatively similar erodibility values in both
regions (Mulengera and Payton, 1999). This is due to differences in clay, silt, and sand
fractions of the soils and possibly rainfall characteristics found in the two regions. While
soils in the temperate region have all the three fractions well distributed, soils in the tropics
are mainly composed of clay and (or) sand fractions with a relatively small fraction of silt
content (Mulengera and Payton, 1999). So Mulengera and Payton concluded that it is
impossible to develop one universal soil erodibility equation. Therefore, the prediction of
soil erosion in the tropics using the USLE or its revised version (RUSLE), had been
hampered by the common inapplicability of the soil erodibilty nomograph for tropical soils.
Furthermore, the table values developed in the U.S.A. for estimating the crop and soil
management factor of the equation are not applicable for farming practices and conditions
found in the tropics (Mulengera and Payton, 1999). However, some recent studies have
shown that it can give good results, especially, when its recent version, the Modified
Universal Soil Loss Equation (MUSLE) is used (Ndomba, 2007).
Mulengera and Payton (1999) presented an equation for estimating the USLE -Soil
erodibility factor, which resulted from a wider research programme initiated to identify a
suitable soil loss prediction equation for use under Tanzanian conditions. The derived
equation based on soil texture-related parameters which is technically accurate (i.e.
explaining about 84 % of the erodibility variations) for estimating the erodibility factor of
the ( R )USLE in the tropics for soils whose physical and chemical characteristics are similar
to the soils used in the derivation. The equation is useful for soil conservation planning in
these areas currently suffering from severe soil erosion (Mulengera and Payton, 1999). The
equation was successfully used by Mtalo and Ndomba (2002) in Pangani basin, in the North-
eastern part of Tanzania.