Optimum sorghum planting dates in western Sudan by simulated water budgets

• Published in: Agricultural water management Vol. 13; no. 1; pp. 33 - 48
• Main Authors: Omer, M.A., Saxton, K.E., Bassett, D.L.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.1988; Elsevier Science; Elsevier
• Series: Agricultural Water Management
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agronomy. Soil science and plant productions; Artificial regeneration. Forest nurseries. Planting; Biological and medical sciences; Biometrics, statistics, experimental designs, modeling, agricultural computer applications; Forestry; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities. Biometrics, experimentation. Remote sensing; Sowing and planting; Vegetative propagation. Sowing and planting. Harvesting; Water balance and requirements. Evapotranspiration; Monocotyledones; Soil moisture; Rainfed agriculture; Africa; Sudan; Tropical crop; Clay soil; Agroclimatology; Water stress; Date; Cereal crop; Sowing; Vertisols; Sorghum bicolor; Gramineae; Angiospermae; Evapotranspiration; Semi arid climate; Spermatophyta; Yield; Simulation model
• ISSN: 0378-3774; 1873-2283
• DOI: 10.1016/0378-3774(88)90131-X

The Soil-Plant-Air-Water (SPAW) model previously developed and tested was used to simulate soil water budgets and crop water-stress for sorghum in the dryland region of western Sudan. Limited climatic data were combined with general observations of sorghum growth and soils to provide daily water budgets at one site for 11 years. Probability distribution of computed water budget components and water-stress index resulting from simulation of nine possible planting dates for each year were used to determine the optimum planting period for minimal crop water-stress. The water budget analysis showed a distinct optimum planting period of June 20 to July 10 with planting in early July as the most likely for best production. These results agreed well with general experience. The technique will be similarly useful for other locations, for research designs of soil water management, yield forecasting, and planning and management of agricultural resources.