TITLE:
Digital Mapping to Determine Sustainability of Dam Construction in Owerri North for Agricultural Productivity
AUTHORS:
Okwudili John Ugwu, Udo A. Emmanuel, Uzoeshi M. Samson, Geoffrey Ogbonna Nwodo, Anthony Okoroji
KEYWORDS:
GIS, Remote Sensing, Mapping, Dam
JOURNAL NAME:
Open Access Library Journal,
Vol.12 No.5,
May
29,
2025
ABSTRACT: Agriculture is critical for economic stability and food security, particularly in regions like Owerri North, Nigeria, where inconsistent rainfall, waterlogging, and soil erosion threaten productivity. This study leverages Geographic Information Systems (GIS) and Remote Sensing (RS) to identify suitable dam construction sites to improve agricultural productivity. Key thematic layers such as precipitation, stream density, geomorphology, geology, land use/land cover (LULC), and elevation were analyzed. Data were sourced from global satellite missions like TRMM, Earth Explorer, and CHIRPS, high-resolution DEMs (e.g., SRTM), and local geological surveys. Using the Dam Suitability Stream Model (DSSM), this study employed GIS-based Multi-Criteria Decision Making (MCDM) techniques, including the Analytic Hierarchy Process (AHP), to assign weights to criteria such as stream order, slope, and land use. The analysis generated two suitability maps: Suitability on Stream and Overall Suitability. The Suitability on Stream map highlighted highly suitable zones near high-order streams in the basin’s upper reaches, prioritizing areas with consistent water flow and favorable slopes (5% - 15%). In contrast, the Overall Suitability map expanded the scope to include broader factors like Euclidean distance from streams, identifying additional areas in the lower reaches, though many faced limitations such as lower stream orders and flood risks. Detailed evaluations of two proposed sites revealed that Dam Site 1, located on a third-order stream with a 88 km2 catchment area, was the most viable option for multipurpose use, including irrigation and flood control. Dam Site 2, with a smaller catchment area and second-order stream, showed moderate suitability for smaller-scale projects. 3D surface models and cross-sectional analyses confirmed that Dam Site 1 had higher volumetric potential and better geological stability, making it more sustainable for agricultural water management. Therefore, integrating digital mapping and AHP is an efficient method for sustainable dam site selection, directly addressing water resource challenges and enhancing agricultural resilience.