Low-lying deltaic environments are among the most environmentally vulnerable landscapes worldwide. These regions frequently experience flooding, sediment instability, and increasing exposure to coastal hazards associated with sea-level rise and climate variability. Deltaic terrains are typically characterized by extremely low relief, high water tables, dense distributary drainage networks, and complex interactions between fluvial and marine processes. Such characteristics pose considerable challenges for infrastructure development, settlement expansion, and environmental management. Although delta morphology and hydrological processes have been widely documented in the scientific literature, relatively few studies provide reproducible geospatial workflows that systematically integrate terrain analysis and drainage morphometry within a unified modelling framework for hydro-morphological vulnerability assessment. In addition, many existing modelling approaches rely on proprietary geographic information systems, which restrict transparency, limit methodological reproducibility, and constrain access to advanced spatial analysis tools. This study presents a reproducible hydro-morphological vulnerability modelling workflow implemented entirely using free and open-source geospatial (FOSS4G) technologies. The proposed framework integrates digital terrain analysis, hydrological modelling, and drainage morphometry within a transparent geospatial workflow designed to support reproducibility and methodological transferability. By combining terrain derivatives and drainage metrics within an open-source ecosystem, the study demonstrates how FOSS4G tools can support systematic vulnerability modelling in complex deltaic environments. The modelling workflow is demonstrated using the Core Niger Delta of Nigeria. The region represents a classic example of a tropical low-gradient deltaic system formed by the distributaries of the River Niger prior to their discharge into the Atlantic Ocean. The landscape consists of an extensive network of tidal creeks, floodplains, wetlands, and coastal barrier ridges formed through the combined influence of fluvial deposition and marine processes. Minimal elevation differences across the region, combined with high rainfall and tidal interactions, contribute to persistent hydro-morphological sensitivity. Instead of presenting a purely descriptive geomorphological analysis, this study proposes a structured geospatial modelling workflow that quantitatively evaluates hydro-morphological vulnerability through integration of terrain and drainage indicators within a fully open-source analytical environment. All spatial analyses are conducted within the QGIS environment, with terrain and hydrological derivatives generated using GRASS GIS and SAGA GIS algorithms accessed through the QGIS Processing Toolbox. Shuttle Radar Topography Mission (SRTM) 30-m digital elevation data serve as the primary topographic dataset. DEM preprocessing involves hydrological conditioning to remove spurious depressions and ensure consistent flow routing across the study area. Slope gradients are derived using the GRASS GIS module r.slope.aspect, enabling identification of the extremely low-relief terrain typical of deltaic landscapes. Flow direction and flow accumulation are computed using the r.watershed module, which facilitates the identification of areas where surface runoff converges and contributes to channel formation. Stream networks are extracted from the flow accumulation surface using the GRASS module r.stream.extract, with thresholds selected to represent distributary channels typical of low-gradient deltaic terrain. Drainage density is subsequently calculated using a grid-based method in which total stream length within each 1 km × 1 km grid cell is normalized by the grid area. This procedure captures spatial variability in channel concentration and landscape fragmentation. Surface moisture accumulation potential is represented using the Topographic Wetness Index (TWI), computed using SAGA GIS terrain analysis tools. TWI combines slope and upslope contributing area to identify zones where surface saturation and water accumulation are likely to occur. Six hydro-morphological indicators are derived from the terrain and hydrological analyses: elevation, slope, flow accumulation, topographic wetness index, drainage density, and distance to rivers. Because these variables differ in measurement units and magnitude, all indicators are standardized using min–max normalization to produce values ranging from 0 to 1, where higher values represent greater hydro-morphological vulnerability. A composite Hydro-Morphological Vulnerability Index (HMVI) is then generated using an equal-weight linear combination model to ensure methodological transparency and reproducibility. The HMVI integrates the standardized indicators as follows:
HMVI = (ELEV′ + SLOPE′ + FAC′ + TWI′ + DD′ + DRIV′) / 6
The resulting vulnerability surface is classified into five categories representing Very Low, Low, Moderate, High, and Very High vulnerability. This classification enables spatial identification of locations where terrain characteristics and drainage conditions combine to increase susceptibility to flooding and hydrological instability. The modelling workflow is designed to identify areas where hydro-morphological conditions converge to increase vulnerability. Within the Core Niger Delta, such conditions are expected to occur primarily in low-elevation floodplains, intertidal swamp belts, and regions characterized by minimal slope gradients and high wetness potential. The resulting vulnerability maps provide a spatial framework for identifying locations where terrain–hydrology interactions may intensify exposure to flooding and surface water accumulation.
Model performance will be evaluated through spatial comparison between HMVI outputs and documented flood-prone locations within the region. The proportion of observed flood areas occurring within high vulnerability zones will provide an initial indication of model reliability. Sensitivity analysis will also be conducted by varying indicator weights to examine the stability of vulnerability patterns under alternative weighting scenarios. The principal contribution of this research lies in demonstrating how integrated terrain and drainage modelling can be implemented entirely within a FOSS4G ecosystem to support hydro-morphological vulnerability assessment in deltaic environments. Because the workflow relies on open algorithms and globally available elevation datasets, it can be replicated in other deltaic regions where geospatial resources and technical capacity may be limited. By advancing a reproducible modelling framework grounded in open geospatial technologies, this study contributes to transparent environmental analysis and supports spatially informed climate resilience planning, sustainable infrastructure development, and water-related ecosystem risk assessment in vulnerable coastal landscapes. More broadly, the study demonstrates the capability of FOSS4G tools to support rigorous geospatial research while promoting open, accessible innovation in environmental monitoring and decision-making.
Keywords: Hydro-morphological vulnerability; FOSS4G; QGIS; GRASS GIS; SAGA GIS; Digital elevation model; Terrain analysis; Drainage morphometry; Deltaic systems