Using Geographical Information System (GIS), Remote Sensing (RS), and Analytic Hierarchy Process (AHP) to Map Areas Associated with Reducing Dam Safety
Niyinyitoreye V *
Department of Civil and Water Resources Engineering, School of Engineering and Technology (SoET), Sokoine University of Agriculture, P. O. Box 3003, CHUO KIKUU, Morogoro, Tanzania.
F. R. Silungwe
Department of Civil and Water Resources Engineering, School of Engineering and Technology (SoET), Sokoine University of Agriculture, P. O. Box 3003, CHUO KIKUU, Morogoro, Tanzania.
N. I. Kihupi
Department of Civil and Water Resources Engineering, School of Engineering and Technology (SoET), Sokoine University of Agriculture, P. O. Box 3003, CHUO KIKUU, Morogoro, Tanzania.
*Author to whom correspondence should be addressed.
Abstract
This study presents an integrated approach combining Geographic Information Systems (GIS), Remote Sensing (RS), and the Analytic Hierarchy Process (AHP) to assess dam conditions through multi-criteria risk analysis. Geographic Information Systems (GIS) and Remote Sensing technologies have emerged as powerful tools in the evaluation and monitoring of dam conditions. Dam management and safety compliance are critical for safeguarding infrastructure and communities in disaster-prone regions. Key criteria including topography, land use, hydrology, climatic conditions, population density, and soil stability were weighted using AHP to reflect their relative impacts on dam safety. A weighted overlay analysis in ArcMap 10.7 classified risks into three zones: high, moderate, and low. The results revealed significant spatial disparities: high-risk zones (48.27 km², 33.64%) dominate the dam’s western flank due to extreme anthropogenic pressures from uncontrolled settlements and unsustainable farming, moderate-risk zones 31.40 km², 21.88%) cluster near bushland and Mindu Mountain, where environmental factors like slope instability pose intermediate threats, and low-risk zones (63.83 km², 44.48%) prevail on the eastern side along Uluguru Mountain, where stable terrain and minimal human activity enhance resilience. The analysis emphasizes human encroachment as the primary driver of dam vulnerability, particularly on the western side, necessitating urgent land-use regulations and soil conservation measures. Conversely, the eastern low-risk zone highlights the protective role of undisturbed ecosystems. Satellite-derived RS data enabled dynamic monitoring of environmental changes, while GIS-based predictive models identified future hazards, such as sedimentation and flooding. By translating complex spatial data into actionable insights, this framework empowers policymakers, engineers, and regulators to prioritize mitigation efforts, enforce zoning laws, and implement adaptive strategies. The study demonstrates the efficacy of GIS-RS-AHP integration in achieving cost-effective, proactive dam management, balancing ecological preservation with infrastructure safety amid evolving environmental and anthropogenic challenges.
Keywords: Geographical Information System (GIS), Remote Sensing (RS), Analytic Hierarchy Process (AHP), risk potential assessment