Impervious Surface Areas and Runoff in Urban Watersheds: A Case of Mihang’o Watershed, Nairobi-Kenya
| dc.contributor.author | Omwoyo, Ongaga Cyrus | |
| dc.date.accessioned | 2025-03-12T06:11:01Z | |
| dc.date.available | 2025-03-12T06:11:01Z | |
| dc.date.issued | 2024-11 | |
| dc.description | A Thesis Submitted in Partial Fulfillment of the Requirement for the Award of the Degree of Masters of Science (Integrated Watershed Management) in the School of Pure and Applied Sciences of Kenyatta University, November, 2024 | |
| dc.description.abstract | The frequency and severity of flooding in urban watersheds, including the Mihang’o watershed on the outskirts of Nairobi, has been on the rise. Over the years, Mihang’o has witnessed continuous urban expansion. This urbanization disrupts natural landscapes by replacing vegetated areas with impervious surfaces, which limit water infiltration and significantly increase surface runoff within the watershed. The overall objective of this study was to evaluate the relationship between change in impervious surface area and runoff amount of Mihang’o watershed from 2000 - 2022. The specific objectives of this study were: To determine change in impervious surface area of Mihang’o watershed, trend of precipitation amount in the watershed and the trend in runoff amount from the watershed from 2000 - 2022. Supervised classification was done on Landsat images using ArcGIS (10.4) to determine percentages of impervious surface cover for the study period and linear regression analysis was done to establish the trend. CHIRPS rainfall data was retrieved from Google Earth Engine then processed in MS Excel to produce monthly and annual rainfall totals then Mann-Kendall trend tests were used to establish the rainfall trend for the watershed. The HEC-HMS model was used to simulate runoff from the watershed with the rainfall data and impervious surface area percentages as inputs then linear regression analysis was done to establish the runoff trend. Impervious surface area increased by 87.03% from 2.78% (0.49 km2) of the total surface area of the watershed in 2000 to 22.21% (3.91 km2) in 2022. Rainfall analysis showed two rainfall seasons: short rains November to December and long rains March-April-March, with the highest annual rainfall being 1172.8 mm and the least annual rainfall being 491.7 mm, which is consistent with the Nairobi region’s climate data that shows no significant linear trend in rainfall. The Mann-Kendall trend tests results (Sen’s slope results (β = .832), Kendall’s tau results (τb = .146), and p-value (.625)) confirmed that there is no trend in rainfall time series of Mihang’o watershed. Runoff increased by 84.75% from 0.18 mm in 2000 to 1.18 mm in 2022. The regression analysis results (p < .001) supported the alternative hypothesis (H1) that there is a positive trend in the impervious surface area time series; the Mann-Kendall trend test (p > .05) supported the null hypothesis (H0) that there is no trend in the rainfall data time series; the linear regression results (p < .000) supported the alternative hypothesis (H1) that there is a positive trend in the runoff time series. Overall, correlation analysis found a significant positive relationship between impervious surface area and runoff r (6) = .99, p < .000. As the study has demonstrated a significant positive relationship between impervious surface area and runoff in the urban watershed, urban planners can leverage these findings and embrace development practices that reduce runoff, including expanding green spaces such as green roofs, permeable pavements, and urban forestry, increasing storage capacity of excess rainfall and runoff water, and constructing retention basins and infiltration trenches on the streams. | |
| dc.description.sponsorship | Kenyatta University | |
| dc.identifier.uri | https://ir-library.ku.ac.ke/handle/123456789/29768 | |
| dc.language.iso | en | |
| dc.publisher | Kenyatta University | |
| dc.title | Impervious Surface Areas and Runoff in Urban Watersheds: A Case of Mihang’o Watershed, Nairobi-Kenya | |
| dc.type | Thesis |