Evaluation of NASA satellite and modelled temperature data for simulating maize water requirement satisfaction index in the Free State Province of South Africa
Physics and Chemistry of the Earth
Agricultural Research Council, Institute for Soil, Climate and Water, Private Bag X79, Pretoria 0001, South Africa; Department of Soil, Crop and Climate Sciences, University of the Free State, PO Box 339, Bloemfontein 9300, South Africa
Low density of weather stations and high percentages of missing values of the archived climate data in most places around the world makes it difficult for decision-makers to make meaningful conclusions in natural resource management. In this study, the use of NASA modelled and satellite-derived data was compared with measured minimum and maximum temperatures at selected climate stations in the Free State Province of South Africa. The NASA temperature data-fed Hargreaves evapotranspiration estimate was compared with the Penman-Monteith estimate to obtain regional coefficients for the Free State. The maize water requirement satisfaction index (WRSI) obtained using the NASA temperature data and calibrated Hargreaves equation was evaluated against the WRSI obtained using Penman-Monteith estimate. The data used is mostly from 1999 to 2008. The results of the comparison between measured minimum temperatures and NASA minimum temperatures show overestimation of the NASA values by between a monthly mean of 1.4°C and 4.1°C. NASA maximum temperatures seem to underestimate measured temperatures by monthly values ranging from 2.2 to 3.8°C. NASA-fed Hargreaves equation in its original form underestimates Penman-Monteith evapotranspiration by between 20% and 40% and hence its coefficient was calibrated accordingly. The comparison of the maize WRSI simulated with NASA temperatures showed a good correlation and small deviations from WRSI calculated from measured data. Thus, the use of NASA satellite and modelled data is recommended in the Free State Province in places where there are no meteorological readings, with special consideration of the biasness of the data. © 2012 Elsevier Ltd.
Climate data; Climate stations; Decision makers; Free state; Good correlations; Hargreaves; Hargreaves equations; Low density; Maize; Maximum temperature; Missing values; NASA satellite; Natural resource management; Penman-Monteith; South Africa; Temperature data; Water requirements; Weather stations; WRSI; Estimation; Evapotranspiration; NASA; Natural resources management; Satellites; Water supply; Information management; computer simulation; evapotranspiration; maize; resource management; satellite data; temperature effect; Free State; South Africa; Zea mays