Swaziland is generally an arid country, with most rains falling during the period of October to March. The long term average annual rainfall ranges from 400 mm in the lowveld to 1,200 mm in the mountainous highveld. Raingauges have been used as reliable source of rainfall data, but the density of these ground based instruments is too low, offering poor spatial coverage. The use of satellite products to estimate rainfall can fill the gap created by poor spatial coverage of ground based instruments. The African Monitoring of the Environment for Sustainable Development (AMESD) project that was launched in 2007 aims to provide African Nations with resources for climate monitoring application through the use of Meteosat Second Generation (MSG) satellite data. In Swaziland, the satellite receiving station was installed in 2012. The satellite rainfall product has not been evaluated in the country. The objective of this paper was to evaluate the rainfall product by comparing it with rainfall data sourced from raingauge. Daily rainfall data were obtained for five weather stations (Big Bend, Malkerns, Matsapha, Mhlume and Nhlangano) for 1998 to 2006. These daily rainfall data were organized in 10-day (dekadal) totals. Dekadal satellite rainfall data were obtained from the local AMESD receiving station for the respective period. The data were exported to Statistical Package for Social Sciences (SPSS) computer software for analysis. Person correlation and linear regression tests were performed for average dekadals and yearly data for the five weather stations to compared gauged rainfall and satellite rainfall estimates. The correlation for average dekadal rainfall data was significant at 99% level of confidence for all weather stations. Correlation coefficients and R2 were higher for weather stations in the middleveld (Malkerns and Matsapha). The magnitude of underestimation of rainfall by satellite products was higher during the wet season for weather stations receiving relatively higher rainfall. The correlation between yearly gauged rainfall and yearly rainfall estimates from satellite product was significant at 99% level of confidence for Big Bend, Mhlume and Matsapha. It was significant at 95% level of confidence for Malkerns, and not significant for Nhlangano weather station. The regression models that were developed could be used to adjust rainfall estimates from satellite products to ground (gauged) rainfall for an area or community.
| Published in | American Journal of Agriculture and Forestry (Volume 3, Issue 3) |
| DOI | 10.11648/j.ajaf.20150303.15 |
| Page(s) | 93-98 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Correlation, Dekadal, Gauged, Regression, Satellite Data, Validation
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APA Style
Absalom Mganu Manyatsi, Ntobeko Zwane, Musa Dlamini. (2015). Evaluation of Satellite Rainfall Estimates for Swaziland. American Journal of Agriculture and Forestry, 3(3), 93-98. https://doi.org/10.11648/j.ajaf.20150303.15
ACS Style
Absalom Mganu Manyatsi; Ntobeko Zwane; Musa Dlamini. Evaluation of Satellite Rainfall Estimates for Swaziland. Am. J. Agric. For. 2015, 3(3), 93-98. doi: 10.11648/j.ajaf.20150303.15
AMA Style
Absalom Mganu Manyatsi, Ntobeko Zwane, Musa Dlamini. Evaluation of Satellite Rainfall Estimates for Swaziland. Am J Agric For. 2015;3(3):93-98. doi: 10.11648/j.ajaf.20150303.15
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Download@article{10.11648/j.ajaf.20150303.15,
author = {Absalom Mganu Manyatsi and Ntobeko Zwane and Musa Dlamini},
title = {Evaluation of Satellite Rainfall Estimates for Swaziland},
journal = {American Journal of Agriculture and Forestry},
volume = {3},
number = {3},
pages = {93-98},
doi = {10.11648/j.ajaf.20150303.15},
url = {https://doi.org/10.11648/j.ajaf.20150303.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajaf.20150303.15},
abstract = {Swaziland is generally an arid country, with most rains falling during the period of October to March. The long term average annual rainfall ranges from 400 mm in the lowveld to 1,200 mm in the mountainous highveld. Raingauges have been used as reliable source of rainfall data, but the density of these ground based instruments is too low, offering poor spatial coverage. The use of satellite products to estimate rainfall can fill the gap created by poor spatial coverage of ground based instruments. The African Monitoring of the Environment for Sustainable Development (AMESD) project that was launched in 2007 aims to provide African Nations with resources for climate monitoring application through the use of Meteosat Second Generation (MSG) satellite data. In Swaziland, the satellite receiving station was installed in 2012. The satellite rainfall product has not been evaluated in the country. The objective of this paper was to evaluate the rainfall product by comparing it with rainfall data sourced from raingauge. Daily rainfall data were obtained for five weather stations (Big Bend, Malkerns, Matsapha, Mhlume and Nhlangano) for 1998 to 2006. These daily rainfall data were organized in 10-day (dekadal) totals. Dekadal satellite rainfall data were obtained from the local AMESD receiving station for the respective period. The data were exported to Statistical Package for Social Sciences (SPSS) computer software for analysis. Person correlation and linear regression tests were performed for average dekadals and yearly data for the five weather stations to compared gauged rainfall and satellite rainfall estimates. The correlation for average dekadal rainfall data was significant at 99% level of confidence for all weather stations. Correlation coefficients and R2 were higher for weather stations in the middleveld (Malkerns and Matsapha). The magnitude of underestimation of rainfall by satellite products was higher during the wet season for weather stations receiving relatively higher rainfall. The correlation between yearly gauged rainfall and yearly rainfall estimates from satellite product was significant at 99% level of confidence for Big Bend, Mhlume and Matsapha. It was significant at 95% level of confidence for Malkerns, and not significant for Nhlangano weather station. The regression models that were developed could be used to adjust rainfall estimates from satellite products to ground (gauged) rainfall for an area or community.},
year = {2015}
}
TY - JOUR T1 - Evaluation of Satellite Rainfall Estimates for Swaziland AU - Absalom Mganu Manyatsi AU - Ntobeko Zwane AU - Musa Dlamini Y1 - 2015/05/07 PY - 2015 N1 - https://doi.org/10.11648/j.ajaf.20150303.15 DO - 10.11648/j.ajaf.20150303.15 T2 - American Journal of Agriculture and Forestry JF - American Journal of Agriculture and Forestry JO - American Journal of Agriculture and Forestry SP - 93 EP - 98 PB - Science Publishing Group SN - 2330-8591 UR - https://doi.org/10.11648/j.ajaf.20150303.15 AB - Swaziland is generally an arid country, with most rains falling during the period of October to March. The long term average annual rainfall ranges from 400 mm in the lowveld to 1,200 mm in the mountainous highveld. Raingauges have been used as reliable source of rainfall data, but the density of these ground based instruments is too low, offering poor spatial coverage. The use of satellite products to estimate rainfall can fill the gap created by poor spatial coverage of ground based instruments. The African Monitoring of the Environment for Sustainable Development (AMESD) project that was launched in 2007 aims to provide African Nations with resources for climate monitoring application through the use of Meteosat Second Generation (MSG) satellite data. In Swaziland, the satellite receiving station was installed in 2012. The satellite rainfall product has not been evaluated in the country. The objective of this paper was to evaluate the rainfall product by comparing it with rainfall data sourced from raingauge. Daily rainfall data were obtained for five weather stations (Big Bend, Malkerns, Matsapha, Mhlume and Nhlangano) for 1998 to 2006. These daily rainfall data were organized in 10-day (dekadal) totals. Dekadal satellite rainfall data were obtained from the local AMESD receiving station for the respective period. The data were exported to Statistical Package for Social Sciences (SPSS) computer software for analysis. Person correlation and linear regression tests were performed for average dekadals and yearly data for the five weather stations to compared gauged rainfall and satellite rainfall estimates. The correlation for average dekadal rainfall data was significant at 99% level of confidence for all weather stations. Correlation coefficients and R2 were higher for weather stations in the middleveld (Malkerns and Matsapha). The magnitude of underestimation of rainfall by satellite products was higher during the wet season for weather stations receiving relatively higher rainfall. The correlation between yearly gauged rainfall and yearly rainfall estimates from satellite product was significant at 99% level of confidence for Big Bend, Mhlume and Matsapha. It was significant at 95% level of confidence for Malkerns, and not significant for Nhlangano weather station. The regression models that were developed could be used to adjust rainfall estimates from satellite products to ground (gauged) rainfall for an area or community. VL - 3 IS - 3 ER -
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