The CERES-MAIZE model as a potential tool for drought assessment in South Africa
Year: 1987
Type: article
Abstract: An index to characterise drought in such a way that policy makers will have an objective measure to declare areas drought-stricken and to implement subsidy schemes on a fair basis has been sought. The Palmer Drought Severity Index (PDSI) has been found wanting in this respect and more crop specific indices are at present under investigation. A methodology employing the CERES-MAIZE model to assess drought impacts on maize at an early stage in the season has been developed. The model was verified using South African yield data collected at a wide variety of localities ranging in mean annual rainfall from 550 to 870 mm and in yield from 986 to 8 600 kg/ha. Model sensitivity to soil water parameters and planting dates was evaluated. The profile available water (PAW) capacity should preferably be known to within 50 mm to make a good assessment while planting dates as far apart as two full weeks gave similar results. In order to develop a methodology for predicting yield response to drought during the course of the growing season, temperature and rainfall data were analysed on a monthly basis. The month in the historical record which gave a monthly value nearest the value of the record was identified and used to synthesise a median year. To assess the impact of early season weather on the crop yield attained in a given season, the model was run with actual weather data up to a given date after which the year's data were used for the remainder of the growing season. Excellent correlations were found between yield predictions based on the use of observed early season data (up to as early as the end of January) in combination with data for the remainder of the season and yield predictions based on observed data over the entire season.
Source: Water SA
Author: Alejandra Pisani
Institution: South African Weather Service
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W2778548216