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dc.contributor.advisorElfatih A. B. Eltahir.en_US
dc.contributor.authorYamana, Teresa K. (Teresa Keiko)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.en_US
dc.coverage.spatialf------en_US
dc.date.accessioned2011-04-04T16:16:47Z
dc.date.available2011-04-04T16:16:47Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/62048
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010.en_US
dc.descriptionPage 102 blank. Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 94-101).en_US
dc.description.abstractThis thesis describes studies on the use of the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) developed and tested against field data by Bomblies et al. (2008) in simulating and predicting the potential for malaria transmission in rural Africa. The first study examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 hour resolution. The second study investigated whether HYDREMATS could be effectively forced by satellite based estimates of rainfall instead of ground based observations. The CPC Morphing technique (CMORPH) (Joyce et al., 2004) precipitation estimates distributed by NOAA are available at a 30-minute temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results indicate that adjusted CMORPH rainfall estimates can be used with HYDREMATS to simulate the dynamics of mosquito populations and malaria transmission with accuracy similar to that obtained when using ground observations of rainfall. The third study tested the ability of HYDREMATS to make short term predictions about mosquito populations. A method was developed by which the rainfall forcing for HYDREMATS is constructed to suit a prediction mode. Observed rainfall is used up until the date of the prediction. The rainfall for the following two weeks (or four weeks) is assumed to be the seasonal mean for that period. HYDREMATS predictions using this method were not significantly different from simulations using observed data.This thesis describes studies on the use of the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) developed and tested against field data by Bomblies et al. (2008) in simulating and predicting the potential for malaria transmission in rural Africa. The first study examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 hour resolution. The second study investigated whether HYDREMATS could be effectively forced by satellite based estimates of rainfall instead of ground based observations. The CPC Morphing technique (CMORPH) (Joyce et al., 2004) precipitation estimates distributed by NOAA are available at a 30-minute temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results indicate that adjusted CMORPH rainfall estimates can be used with HYDREMATS to simulate the dynamics of mosquito populations and malaria transmission with accuracy similar to that obtained when using ground observations of rainfall. The third study tested the ability of HYDREMATS to make short term predictions about mosquito populations. A method was developed by which the rainfall forcing for HYDREMATS is constructed to suit a prediction mode. Observed rainfall is used up until the date of the prediction. The rainfall for the following two weeks (or four weeks) is assumed to be the seasonal mean for that period. HYDREMATS predictions using this method were not significantly different from simulations using observed data.en_US
dc.description.statementofresponsibilityby Teresa K. Yamana.en_US
dc.format.extent102 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleSimulations and predictions of mosquito populations in rural Africa using rainfall inputs from satellites and forecastsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.identifier.oclc707637476en_US


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