Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → Royaume-Uni → 1996 → Soil loss prediction in the semi-arid tropical savanna zone : a tool for soil conservation planning in Tanzania.

University of Newcastle upon Tyne (1996)

Soil loss prediction in the semi-arid tropical savanna zone : a tool for soil conservation planning in Tanzania.

Mulengera, Matthew Kagorobha

Titre  : Soil loss prediction in the semi-arid tropical savanna zone : a tool for soil conservation planning in Tanzania.

Auteur : Mulengera, Matthew Kagorobha.

Université de soutenance : University of Newcastle upon Tyne

Grade : Doctor of Philosophy (Ph.D.) : 1996

Résumé
Soil erosion in Tanzania is a widespread problem and is most serious in semi-arid areas. No locally adapted equations for predicting soil loss and the consequent loss in productivity exist, although they are important tools for soil conservation planning. It is increasingly acknowledged that the existing equations developed in the temperate zone are inapplicable in the tropics.This research involved measurement of soil loss from erosion plots on contrasting soils in semi-arid Tanzania and adaptation of the Universal Soil Loss Equation (USLE) and the Soil Loss Estimation Model for Southern Africa (SLEMSA) for local use. The work led to the development of a Soil Erosion - Productivity Index Model (SEPIM). The adapted USLE and SLEMSA, together with the reduction of soil water storage capacity (a component of SEPIM), were used to assess the impact of long term soil erosion on crop production in semi-arid Tanzania through erosion hazard mapping using Geographical Information Systems.USLE - soil erodibility equations, which explain about 84% to 91% of the erodibility variations, have been developed for tropical soils. A subfactor approach for estimating the USLE - C-factor has been conceived, tested and shown to give reliable results.A method for estimating the SLEMSA - soil erodibility index for Tanzanian soils has been devised and demonstrated to give accurate results. The SLEMSA -K-submodel gives accurate predictions in areas with rainfall erosivities similar to those found where it was first developed but underpredicts soil losses in areas with low erosivities. The SLEMSA C-submodel gives reliable predictions for soils under semi-natural vegetation but is less reliable for cropped fields.

Mots clés : Agricultural engineering Soil science

Annonce : EThOS (UK)

Proquest Dissertations & Theses

Page publiée le 29 mai 2009, mise à jour le 19 octobre 2018