A comparative analysis of long-term variations of temperature and rainfall in rural and urban areas, and their effects on the estimation of design storms in Kenya
| dc.contributor.advisor | Mazvimavi, Dominic | |
| dc.contributor.author | Gachahi, Lydiah Wangechi | |
| dc.date.accessioned | 2018-04-03T13:34:05Z | |
| dc.date.accessioned | 2024-11-06T10:03:55Z | |
| dc.date.available | 2018-04-03T13:34:05Z | |
| dc.date.available | 2024-11-06T10:03:55Z | |
| dc.date.issued | 2016 | |
| dc.description | Philosophiae Doctor - PhD (Earth Science) | |
| dc.description.abstract | My Thesis aimed at expanding the current knowledge on how variations of temperature characteristics including the possible existence of urban heat islands (UHI) over urban areas of Kenya could be influencing rainfall characteristics, and to examine if the stationary extreme value distributionis still suitable for modeling urban storm designs in view of the global climate change. My hypothesis was that the floodingoccurring frequently in major urban areas of Kenya are due to increased rainfall caused by global climate change, and the urban heat island (UHI) effect. To put this perception into perspective, temperature and rainfall characteristics and their inter-relationships, of four of the major urban areas in Kenya namely, Nairobi, Mombasa, Kisumu, and Nakuru, were investigated. I obtained data from meteorological stations in and around each urban area, which had at least thirty (30) years of continuous monthly (or daily) temperatures and rainfall values, from the Kenya Meteorological Department. I checked the datasets for quality and missing values and adjusted where necessary before commencing with analysis. I sourced other supporting global dataset from various websites' data banks.I used various methods of data analysis which included; i) exploratory data analysis techniques such as the continuous wavelet transform (CWT), geographical information system (GIS) maps, and visual time series plots. In particular and unique in my Thesis was the use of the CWT method as a diagnostic tool to examine non-stationaritiesand variability of temperature and rainfall time series. | |
| dc.identifier.uri | https://hdl.handle.net/10566/17652 | |
| dc.language.iso | en | |
| dc.publisher | University of the Western Cape | |
| dc.rights.holder | University of the Western Cape | |
| dc.title | A comparative analysis of long-term variations of temperature and rainfall in rural and urban areas, and their effects on the estimation of design storms in Kenya |
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