GIS Analysis and Spatial Modelling for Optimal Oil Pipeline Route Location. A Case Study of Proposed Isiolo Nakuru Pipeline Route
Keywords:AHP, GIS, Modeling, Pipeline Route Selection
Large reserves of commercially viable oil have been discovered in Turkana Kenya. In order to accrue benefits sustainably, optimize supply, and satisfy oil demands in the region, there is a need for an optimal oil pipeline distribution system that strikes a balance among environmental, engineering, technical and social factors. Using Isiolo and Nakuru town as start and end nodes, this study utilized spatial modeling and Geospatial Information System (GIS) analysis to come up with an optimal oil pipeline route. This involved deriving weights for the variables using Analytical Hierarchy Process (AHP) and modeling the routing process using them. A model was developed incorporating pipeline length, topography, geology, soil types, populated areas, game parks, forests, rivers, wetlands, roads, ground water points, rail-line and roads to identify an optimal route. GIS was used for spatial modeling, analysis and data overlay. The variables were weighted using AHP to determine
their relative preferences. This was achieved by running questionnaires to various stake holders and experts and professionals. The output for weighting showed high levels of preference given to environmental factors, followed by social factors and engineering factors having least preference. The mean of the weights resulted to the optimal route. The route prosed by the engineers was the best alternative identified by use of standard deviation. The optimal route realized savings by avoiding higher cost environmental and populated centers cells. The results of this
analysis demonstrated the benefits of integrating various data sources with GIS analysis as a first look for pipeline routing. The benefits of combining GIS and AHP as a decision support system for the oil pipeline routing process was depicted. This can be applied in routing of other linear structures in Kenya.
Copyright (c) 2022 Peter M. Macharia, Charles N. Mundia
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.