Understanding wetland reclamation and soil-transmitted helminths and schistosomiasis incidence patterns in Rwanda (2001 – 2012).


Data was collected from different source, organised and analysed under a four years PhD project.

Wetlands are sustaining large communities of people in Rwanda where 10 % of its surface consists of many local wetlands. Sustainable future management of these numerous wetlands requires a reliable inventory of their location and a dynamic quantitative characterization that allows assessment of their climate change sensitivity. The aim of this study was to assess the importance of climatic factors in determining wetland location at different regional scales. Wetland locations were analyzed and statistically modeled using their location factors with logistic regression. Wetland location probability was determined using topographic (elevation, slope), hydrological (contributing area) and climatic (temperature and rainfall) location factors. A wetland location probability map was made that demonstrated a calibration accuracy of 87.9 % correct at national level compared to an existing inventory, displaying even better fits at the sub-national level (reaching up to 98% correct). A validation accuracy of 86.2 % was obtained using an independently collected dataset. A sensitivity analysis was applied to the threshold values used as a cut-off value between wetland/non-wetland, demonstrating a robust performance. The developed models were used in a sensitivity scenario analysis to assess future wetland location probability to changes in temperature and rainfall. In particular, wetlands in the central regions of Rwanda demonstrate a high sensitivity to changes in temperature (1% increase causes a net probable wetland area declined by 12.4%) and rainfall (+ 1% causes a net increase by 1.6%). This potentially significant impact on wetland number and location probability indicates that climate- sensitive future planning of wetland use is required in Rwanda.

DOI http://dx.doi.org/doi:10.17026/dans-zft-5tae
Related Identifier https://webapps.itc.utwente.nl/librarywww/papers_2017/phd/nyandwi.pdf
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:113564
Creator Nyandwi, E.
Publisher Data Archiving and Networked Services (DANS)
Publication Year 2018
Rights info:eu-repo/semantics/restrictedAccess
Language English
Resource Type Dataset
Format .sav;.por;.dta
Discipline Medicine
Temporal Coverage Begin 2017-07-01T11:59:59Z
Temporal Coverage End 2018-11-12T11:59:59Z