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An evaluation of uptake and developmental impact in the semi-arid tropics of four crop production models

Published online by Cambridge University Press:  01 March 2000

E. KEBREAB
Affiliation:
University of Reading, Department of Agriculture, Earley Gate, P.O. Box 236, Reading, RG6 6AT, UK
J. FRANCE
Affiliation:
University of Reading, Department of Agriculture, Earley Gate, P.O. Box 236, Reading, RG6 6AT, UK
R. H. ELLIS
Affiliation:
University of Reading, Department of Agriculture, Earley Gate, P.O. Box 236, Reading, RG6 6AT, UK
C. GARFORTH
Affiliation:
University of Reading, Department of Agriculture, Earley Gate, P.O. Box 236, Reading, RG6 6AT, UK

Abstract

In the last two decades, crop production models have been developed or modified for use in the semi-arid tropics. Although potential uses of crop models have been discussed in detail in the literature, examples of successful uptake and impact of those models is lacking. Four models developed specifically for the semi-arid tropics were used as a basis for evaluating uptake and impact of models in the semi-arid tropics. PARCH accounts for differences in water availability when predicting yield. PARCHED-THIRST covers water-harvesting, run-off and run-on. EMERGE identifies opportunities for successful crop establishment, and SWEAT calculates evapo-transpiration and estimates temperature and moisture throughout the soil profile. The models are dynamic, deterministic and mechanistic in nature. The equations and notations comprising them are generally well structured, meaningful and concise. The uptake and impact of these models on crop production in the semi-arid tropics was assessed using questionnaires and semi-structured interviews with the model developers. There was limited uptake. Low uptake resulted from lack of efficient dissemination and discontinuity in information transfer: from model developers to scientists in the national research institutions; and thereon to extension agents and so to farmers. Although this paper is based on a study of only four models, there are important lessons to be drawn in order to avoid similar mistakes being repeated. Guidelines for improving impact for future crop production modelling projects are proposed.

Type
Research Article
Copyright
© 2000 Cambridge University Press

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