Browsing by Author "Makonyo, Michael"

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    Flood susceptibility mapping using GIS and multi-criteria decision analysis: a case of Dodoma region, central Tanzania
    (Elsevier, 2021) Msabi, Michael M.; Makonyo, Michael
    Floods have become common natural disasters that lead to devastating destruction to the infrastructure and natural environment. With the eminent climate change and weather variability, it might not be possible to prevent floods. However, flood prevention and mitigation can be facilitated by flood susceptibility mapping. Dodoma Region was selected due to its susceptibility to flash floods every year. The map presented in this paper is produced based on the analytical hierarchy process methodology which is an interactive decision-making approach under multi-criteria decision analysis. The method can check the consistency of the model obtained. A total of seven influencing factors are considered for mapping the flood susceptible areas within the Dodoma region, i.e. elevation, slope, geology, drainage density, flow accumulation, land-use/cover, and soil. This study established that around 40.27% of the region (17,073.323 km2) is under high to very high, whereas, 59.73% (24,517.679 km2) accounts for very low to moderate probability of flooding, respectively. The validation process of the analytical hierarchy process is executed based on the comparison of the historical flood locations of the different flood susceptible zones on the final map and AUC of 87.24% give a significant accuracy of the model. Therefore, the flood susceptibility map presented in this paper serves as a valuable tool for key stakeholders both state and non-state actors assessing flood risks in Dodoma region and the country at large.
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    Flood susceptibility mapping using GIS and multi-criteria decision analysis: a case of Dodoma region, central Tanzania
    (Elsevier, 2021) Msabi, Michael M.; Makonyo, Michael
    Floods have become common natural disasters that lead to devastating destruction to the infrastructure and natural environment. With the eminent climate change and weather variability, it might not be possible to prevent floods. However, flood prevention and mitigation can be facilitated by flood susceptibility mapping. Dodoma Region was selected due to its susceptibility to flash floods every year. The map presented in this paper is produced based on the analytical hierarchy process methodology which is an interactive decision-making approach under multi-criteria decision analysis. The method can check the consistency of the model obtained. A total of seven influencing factors are considered for mapping the flood susceptible areas within the Dodoma region, i.e. elevation, slope, geology, drainage density, flow accumulation, land-use/cover, and soil. This study established that around 40.27% of the region (17,073.323 km2) is under high to very high, whereas, 59.73% (24,517.679 km2) accounts for very low to moderate probability of flooding, respectively. The validation process of the analytical hierarchy process is executed based on the comparison of the historical flood locations of the different flood susceptible zones on the final map and AUC of 87.24% give a significant accuracy of the model. Therefore, the flood susceptibility map presented in this paper serves as a valuable tool for key stakeholders both state and non-state actors assessing flood risks in Dodoma region and the country at large.
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    GIS-based analysis of landslides susceptibility mapping: a case study of Lushoto district, north-eastern Tanzania
    (Springer Science and Business Media LLC, 2023) Makonyo, Michael; Zahor, Zahor
    Landslides are becoming increasingly widespread, claiming tens of thousands of fatalities, hundreds of thousands of injuries, and billions of dollars in economic losses each year. Thus, studies for geographically locating landslides, vulnerable areas have been increasingly relevant in recent decades. This research is aimed at integrating Geographical Information Systems (GIS) and Remote Sensing (RS) techniques to delineate landslides susceptibility areas of Lushoto district, Tanzania. RS assisted in providing remote datasets including; Digital Elevation Models (DEMs), Landsat 8 OLI imageries, and past spatially distributed landslides coordinate with the use of a handheld Global Position System (GPS) receiver, while various GIS analysis techniques were used in the preparation and analysis of landslides influencing factors hence, generating landslides susceptibility areas index values. However, rainfall, slope angle, elevation, soil type, lithology, proximity to roads, rivers, faults, and Normalized Difference Vegetation Index (NDVI) factors were found to have a direct influence on the occurrence of landslides in the study area. These factors were evaluated, weighted, and ranked using Analytical Hierarchy Process (AHP) technique in which a 0.086 (8.6%) Consistency Ratio (CR) was attained (highly accepted). Findings reveal that rainfall (29.97%), slopes’ angle (21.72%), elevation (15.68%), and soil types (11.77%) were found to have high influence on the occurrence of landslides, while proximity to faults (8.35%), lithology (4.94%), proximity to roads (3.41%), rivers (2.48%), and NDVI (1.69%) had very low influences, respectively. The overall results, obtained through Weighted Linear Combination (WLC) analysis techniques indicate that about 97669.65 Hectares (ha) of land are under very low levels of landslides susceptibility, which accounts for 24.03% of the total study area. Low susceptibility levels had 123105.84 ha (30.28%), moderate landslides susceptibility areas were found to have 140264.79 ha (34.50%), while high and very high susceptibility areas were found to cover about 45423.43 ha (11.17%) and 57.78 ha (0.01%), respectively. Furthermore, 81% overall model accuracy was obtained as computed from the Area Under the Curve (AUC) using Receiver Operating Characteristic (ROC) curve.
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    Identification of groundwater potential recharge zones using GIS-based multi-criteria decision analysis: a case study of semi-arid midlands Manyara fractured aquifer, North-Eastern Tanzania
    (Elsevier, 2021) Makonyo, Michael; Msabi, Michael M.
    The extraction of groundwater has recently increased due to water scarcity as a result of human activities including agriculture, industrial and domestic use. This has accelerated the need to spatially identify groundwater potential zones for artificial aquifer recharge and extraction through boreholes drilling. The current study is aimed at identifying groundwater potential recharge zones (GPRZ) of semi-arid midlands Manyara fractured aquifer using Geographic Information System (GIS) and Multi-criteria Decision Analysis (MCDA) based on Analytic Hierarchy Process (AHP) technique. The study area solely depends on groundwater for human survival through deep and shallow boreholes water extraction. Eight influencing factors including aquifer lithology, slopes, land use/land cover (LULC), soil types, drainage density, geological lineament density, flow accumulation, and topographic wetness index (TWI) were determined and reclassified on a scale of 1–5 in ArcGIS 10.6 environments. These factors were weighted with the help of AHP and integrated with ArcGIS pro based on the weighted linear combination (WLC) method. The results were scaled into five recharge potential classes; very high, high, moderate, low, and very low recharge potential zones. The results indicates that about 1607 km2 (14.7%) of the study area is under very high potential recharge zones, 3982 km2 (36.43%) falls under high recharge zones, 3120 km2 (28.55%) moderate, 1658 km2 (15.17%) low and 562 km2 (5.14%) under very low recharge zone. To assess the accuracy of the result a total of 66 boreholes collected from the field were used and the Receiver Operator Characteristics (ROC) curve generated. The area under the curve (AUC) was found to be 78% signifying moderate to higher accuracy of the model. The presented results provide an inventory of information for the land, water, environmental policy maker's authorities, and other stakeholders to enhancing groundwater resource management within semi-arid midlands Manyara basement fractured aquifer of the internal drainage basin North-Eastern Tanzania.
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    Potential landfill sites selection using GIS-based multi-criteria decision analysis in Dodoma capital city, central Tanzania
    (Springer Nature, 2021) Makonyo, Michael; Msabi, Michael
    Solid waste management is a global challenge, especially in developing countries due to the rapid increase in population and urbanization where the availability of sanitary landfills is inevitable. Determining suitable landfill sites is a fundamental aspect for new and rapidly growing cities. The current study is aimed at selecting potential landfill sites using GIS-based multi-criteria decision analysis in Dodoma capital city. Fifteen criteria including proximity from built-up areas, surface water, boreholes, sensitive sites including social service areas, episodic water channels, protected areas including historical sites, faults, land use/land cover, geology, soil type, elevation, slopes, airport, roads, and earthquake epicentres were integrated with the help of analytical hierarchy process (AHP). The landfill sites’ suitability map was produced based on the weighted linear combination method and assigned suitability classes as highly suitable, suitable, moderately suitable, less suitable, and unsuitable. The overall suitability results show that 41,177 ha (14.7%) of the study area is determined as highly suitable for landfills site location. The remaining 83,930 ha (30%), 84,305 ha (30.2%), and 53,508 ha (19.1%) of the area are suitable, moderately suitable, and less suitable respectively while 16,683 ha (6%) is under the unsuitable zone. From the highly suitable area, eleven candidate landfill sites were selected and prioritized using the AHP technique. The final results show landfill site 3 (10,361.94 ha), 5 (3717.85 ha), and 2 (3535.86 ha) were found to be the most highly suitable sites with eigenvector weight of 0.147, 0.122, and 0.121 respectively. Landfill sites 8, 7, and 6 were lastly considered. Field observation involving expertise from geology, hydrogeology, geophysical, and environment confirmed the suitability of selected sites. Thus, these techniques can be employed in developing countries to locate suitable landfill sites to minimize health and environmental impacts.