Climate change, with altered precipitation patterns and intensified extreme weather events, poses a global threat, transcending borders and impacting communities worldwide. Onitsha, Nigeria’s second-largest city and the 47th-largest built-up urban area globally, contends with flooding as a pervasive consequence of climate change (Efobi and Anierobi, 2013). Despite its prominence, Onitsha faces a pressing challenge of flooding, disrupting economies, displacing populations, and triggering humanitarian crises (Egboka et al., 2019; Egboka and Okoyeh, 2019; Umar and Gray, 2022; Nkiruka et al., 2023). This commercial hub, extending its reach into neighboring districts, must come to terms with the imperative of understanding and addressing the multifaceted dimensions of flooding to forge resilient and sustainable societies in the 21st century (UNHSP, 2012). There is need for analysis of the extensive and intensive risks in Onitsha as regards to flooding (Olanrewaju et al., 2019). Similarly, Quesada-Román and Campos-Duran (2023), emphasized the importance of disaster databases for risk assessment, land use planning, and management, while underscoring the necessity for comprehensive risk assessment at various scales in the region. This would go a long way to ensure an effective disaster risk reduction and management (Quesada-Román, 2023) in the study area and Nigeria in general.

On the other hand, Climate change further alters precipitation patterns, escalating the frequency and severity of extreme weather events, amplifying the specter of flooding. Coastal areas contend with rising sea levels, while inland regions face torrential rains and overflowing rivers, leading to repercussions extending beyond infrastructural damage. Pino and Quesada-Román (2022) discussed a bibliometric analysis of flood risk-related research in Latin America and the Caribbean (LAC), highlighting the productivity of countries like Mexico, Brazil, Chile, Peru, and Argentina in this field over the past 20 years. They emphasized the need for future research to focus on diversifying keywords, aligning titles, abstracts, and keywords better, and addressing future climatic scenarios for developing realistic solutions to disaster risks in the region.

Onitsha, situated at the mouth of the Niger River in Anambra state, Nigeria, is particularly vulnerable to flooding, primarily during the rainy seasons (Oloruntade et al., 2018; Bello et al., 2022). Over the millennia, the Niger River Basin has been altered, especially the local landscape and heightening flood dangers. In both 2012 and 2022, National Emergency Management Agency (NEMA) reported disastrous flood events in Nigeria, with Anambra state, especially Onitsha, identified as the most affected (NEMA and OCHA, 2012; PDNA, 2012; UNHSP, 2012; Agada and Nirupama, 2015; Ehiorobo and Uso, 2015; Nwachukwu et al., 2018; Mfon et al., 2022; Nkiruka et al., 2023). Severe rainfall, a critical topic among scientists and the public (Agada and Nirupama, 2015), underscores the need for integrated floodplain management methods, emphasizing water-retaining capacity (Ladislav et al., 2014). Hence, accurately mapping flood extents is vital for delineating vulnerable zones and enacting preventive measures. Besides, this study attempts to offer precise insights into the roles of soil composition in flood propagation, aiding in high-risk area identification.

Flood events, considered major destructive natural hazards globally, leave devastating consequences on lives and properties (NEMA and OCHA, 2012; PDNA, 2012; Nemine, 2015; Nkwunonwo et al., 2015; Nwachukwu et al., 2018; Komolafe et al., 2020a; Echendu, 2020). While floods may not be entirely avoidable (Koutný, 2003; Ogbodo, 2011; Komolafe et al., 2020a), their destructive effects on lives and infrastructure can be minimized (Patera and Votruba, 2004), leading to various mitigation methods, including structural measures in floodplains.

Human activities, essential for development but contributing to soil exposure and deforestation, exacerbate flood risks when it is unregulated. The alteration of the Earth through urbanization, farming, and mining impacts soil, water, and plant ecosystems, especially in regions like Onitsha (PDNA, 2012). This anthropogenic influence leads to the direct exposure of soil to precipitation, deforestation, and soil erosion, with eroded soil entering rivers, causing aggradation and sedimentation (Osakwe et al., 2014; Nemine, 2015; Komolafe et al., 2020b). More so, climate change further aggravates flood risks (Aja and Olaore, 2014; Ejenma et al., 2014; Nemine, 2015).

Soil, water, and plant ecosystem balance are crucial for human survival, but urbanization, essential for development, leads to soil exposure and deforestation, poses challenges to regions like Onitsha (PDNA, 2012). Precipitation and runoff, a consequence of anthropogenic activities, result in soil removal, waterlogging, soil compaction, and decomposition of organic matter, rendering large areas infertile. Soil erosion contributes to aggradation and sedimentation in rivers, raising floodplain levels (Mahabaleshwara and Nagabhushan, 2014). Soil porosity, vital for mitigating flooding, influences water permeation. It facilitates quicker water percolation, averting flooding (Kalantari et al., 2014). Flood hazard mapping considers elevation, soil type, and land use, hydrology data, climatic data, and disaster risk reduction approaches, among others (Ejenma et al., 2014). Soil properties, including porosity, impact flooding propensity, intensity, and water recession rate (Reynolds et al., 1985). Impacts of excessive water saturation include waterlogging, affecting the water table and soil physical properties (Sharma and Swarup, 1988). Soil type, texture, and waterlogging variations affect soil reactions (Cosentino et al., 2006). Additionally, in times of severe flooding, it is crucial to rapidly assess the scale of inundation and its impact (Quesada-Román and Villalobos-Chacón, 2020) on land use (Wang, 2002; Thalakkottukara et al., 2023). Flood mapping serves as a valuable tool for promptly organizing comprehensive relief efforts following flooding events (Quesada-Román and Villalobos-Chacón, 2020; Quesada-Román and Campos-Duran, 2022). Despite the numerous challenges associated with flood mapping, remotely sensed data offers an efficient and effective solution for its development (Nkiruka et al., 2023; Campos-Durán, 2017). This paper explores the utilization of different remote sensing techniques for flood mapping, incorporating various indices for studying flood risk, along with their specific applications.

According to the concept displayed in Figure 1, several factors such as deforestation, changes in land use and land cover, particularly urbanization, triggers urban flooding, while extreme precipitation is a natural contributor (Nkiruka et al., 2023; Agbonkhese et al., 2014). Human-induced factors, including inadequate drainage and waste disposal, also play a role. Umar and Gray (2022) identified key causes such as canal blockages, inadequate drainage, heavy rainfall, and encroachment of the natural environment, excessive precipitation being influenced by climate change and human activities. Natural causes involve intense downpours and river storms, while anthropogenic factors include broken pipes, inadequate drainage, and dam overflow.

Researchers employ various correlated variables to measure exposure to urban flooding at different scales, including physical, environmental, and socio-economic factors (Osakwe et al., 2014; Nura and Alison, 2022). Factors increasing urban flood exposure in developing countries include poverty, poor housing, inadequate flood defense management, population growth, squatter settlements in hazard-prone areas, poor drainage maintenance, inadequate awareness and limitations in early warning systems (Daffi et al., 2014; Djimesah et al., 2018). To address these challenges, proactive and holistic urban flood control approaches are crucial, advocating for the revival and enforcement of monthly environmental sanitation exercises to clear drainage channels and ensure proper waste disposal (Nkwunonwo et al., 2015; Nkiruka et al., 2023). Several studies have focused on different approaches to map flood-prone areas, manage and mitigate the menace in catchment areas.

The recurrent motif across the various approaches used, involves the application of sophisticated methodologies and models to evaluate and forecast the repercussions of climate change and extreme weather occurrences on hydrological systems and flood susceptibility across diverse geographical areas (Quesada-Román and Villalobos-Chacón, 2020; Quesada-Román, 2022; Quesada-Roman, 2023; Hidalgo et al., 2024). Each investigation utilizes intricate approaches, including the utilization of downscaled General Circulation Models (GCMs), multi-criteria decision support frameworks, and flood hazard indices, to scrutinize the plausible ramifications of climate change, accentuating the imperative for precise evaluations and effective mitigation tactics to confront the escalating adversities presented by extreme weather phenomena and flooding (Quesada-Román and Villalobos-Chacón, 2020; Ikirri et al., 2022; Aichi et al., 2024).

Kherimi et al. (2024) utilized sentinel-1 radar data to study and map vulnerable areas of the Lower Merjerda valley and identified the possible indicators of high flood risk. Geographic information analysis in Fagge, Kano State, revealed flood vulnerability factors such as elevation, drainage, geology, land use, rainfall, soil, and slope (Azua et al., 2019). Similar studies in Muscat, Oman; the Czech Republic; Gaza; England; Bellary, India; Kano and Bayelsa States in Nigeria underscore the role of soil properties in flooding (Ladislav et al., 2014; Mahabaleshwara and Nagabhushan, 2014; Timothy et al., 2017; Azua et al., 2019; Hanan and Rifaat, 2020; Achimota et al., 2021; Eshtawi et al., 2021; Temi et al., 2021).

Emmanuel, et al. (2015), used Geographic information system and remote sensing to analyze flood hazards and damages of past events in Anambra state. The result of the work revealed that 1,078 km² area were inundated and 43.40%, 19.68%, 17.20%, 11.44% and 8.29% of the area are settled in very high, high, moderately, low, and no risk areas. Odunuga et al. (2015) studied variations in flood risk in Lower Niger–Benue using historical and extreme flow rate, activities of landuse and Floodplain Vulnerability Index. The result revealed that extreme flood susceptibility of the flood prone zones of Makurdi and Lokoja indicated that strong and extreme vulnerability levels should have been the reason for the strong effects on the people along the basin. Ugoyibo and Ogbonna (2017), applied GIS and Remote Sensing methods in carrying out spatial study of flood susceptibility in Anambra East and its neighborhoods and they arrived at the results that 71% of the areas under study are sitting on the floodplain.

However, limited reports exist on flood susceptibility mapping and exposure rate aided by the impact of soil composition on flooding in the lower Niger catchments, particularly in Onitsha. This highlights the need to provide insights into soil-flooding relationships and map the susceptible zones to flooding in the Niger River Basin. Moreover, this study tends to address the following research questions: What primary elements contribute to flooding in the study area, and to what extent is the area exposed and susceptible to flooding. The corresponding hypotheses include; there is no relationship between the identified key susceptibility factors and flooding incidents in the study area and, the study area exhibits uniform levels of flood risk, susceptibility, and exposure rates across the area.

The study from the soil texture analysis shown in Table 2 displayed the analysis of proportions of the soil compositions and the area coverages in Hectares. The sampled 10 sub-locations showed that the dominant soil structures in the study area are mainly sandy with average percentage of (84.8%), silt (8.1%) and clayey (7.1%), respectively. Moreover, a table of analyses of the sampled soil types (Table 1) were plotted in bar charts in Figures 6A–C. Table 2 presents the proportions of the compositions and textures of the soils in the study area displayed according to the sampled locations. While Figure 6D presented the susceptibilities of the study area to flooding as a result of the dominant sandy soils.

Table 2 is the general soil texture analysis while, Figures 3–5 showcase the map of the supervised classification for sandy soil, silt, and clay, respectively. From Table 3, the Southern and North-western part of the study area appears to be highly prone to flooding than other regions due to the high composition of sandy soil in the area, followed by moderately high percentage of sandy soil in those regions. These regions are also known to have very low proportions of clayey soil (Figures 3, 6D) which suggests a minimal water retention capacity in the area, but very porous.

Using the significant flood event of 2018, the flood extent map of the study area (Figure 7), depicts the submerged regions during that period. Notably, a considerable proportion of the commercial zones experienced severe flooding during this event, indicating their susceptibility to floods and the high risk of recurrent inundation. The flood extent map for 2018, as revealed in Figure 7, underscores the imperative to highlight the levels of susceptibility and exposure of these areas to flooding, quantified by their sizes in hectares. Table 4 presents the risk levels and exposure rates (%) of these regions to flooding, emphasizing the urgent need for proactive measures in disaster management and mitigation, particularly in the Onitsha catchment area. Table 5 indicates that a significant portion of the catchment area and population are under threat, with an alarming 2,926.2 ha (58.5%) categorized as extremely or strongly susceptible to future flooding, a trend further corroborated by Figure 10.

Figure 8 is the graphical representation of the levels of risks and susceptibility of the population to flooding. This indicates that majority of the zones are strongly at risk followed by extremely risk. However, the moderately and less at risk are also threatened but not to the degree of the majority at risk.

Meanwhile, the importance of this information depends on the interest of the administrative authorities in the area. More so, it will serve as a guide to the policymakers and implementers in the creation of zoned areas for flood disaster risk reduction and management.

This study has identified the areas that lie within sandy soils terrain (Figure 3) to be the most vulnerable due to its high pososity and poor water retention properties. However, for the purpose of relating the sizes and proportions of areas underlaid by the soil to their levels of susceptibilities, Table 4 displays the analysis of these areas and their sizes (Ha) in terms of their levels of susceptibilities. On the other hand, Table 5 displays the levels of susceptibilities in relation to the population of the Thirteen (13) major business locations in the study area.

Figure 9 shows the mapped flood risk/vulnerable zones of the study area in color codes. The analysis was further shown in Table 5 relating the degree of their susceptibilities according to the locations and their respective populations. Table 5 further linked the business locations along with their respective population to their levels of vulnerabilities to flooding.

Relating the analysis to the business location, Figure 8A displayed the population vulnerability chart and their rates of exposure. From Table 5, it is observed that Biafran Market, Bridge Head Market, Harbor Market and Textile Market are extremely threatened by flooding in the study area. Figure 8C is the graphical representation showcasing the vulnerable business populations and their respective rates of exposure. This indicates that at 18.6% and 39.9% exposure rate, the population are extremely and strongly susceptible to flooding in the catchment posing a threat to an area of 2,926.2 Ha and a population of 79, 426 (Table 6). Table 6 also shows the levels of vulnerability according elevations mapped in Figure 10, while Figure 9 display the mapped areas according the flood risk zones and their susceptibilities to flooding, respectively.

On the other hand, Ochanja, Federal Low Cost Housing, OgboEfele, Plastic Wares, and Relief Markets are captured as being moderately at risk, while Electronic International Market and Okpoko Market are at less risk of flooding. Figures 6C, D are charts linking the range of soil compositions in the catchment to their levels of vulnerability to flooding.

Nevertheless, the digital elevation models (Figure 10) delineates the undulating patterns of the topography or landscape, defining the slopes and elevations in the study area.

The maps displayed in Figures 7–10 serve as valuable tools in tackling a range of issues pertaining to both natural and man-made environments. They facilitate the simulation of water movement, forecast erosion, and predict flood patterns. Additionally, they furnish data regarding water bodies, elevation, slope, and contours of the terrain. The flood extent map (Figure 7), flood risk zones (Figure 9), susceptibility map (Figure 8) and elevation map in Figure 10 were employed to gauge the susceptibility of the study area to flooding by identifying the slopes or flow patterns of the terrain. Furthermore, Figure 6D illustrates the correlation between elevations and their corresponding levels of susceptibility in a descriptive analysis.

In sub-Saharan West Africa, Nigeria confronts recurrent devastating floods due to heavy rains, causing extensive damage and loss of life, notably in Onitsha. Nkiruka et al. (2023) underscore the critical role of flood risk and susceptibility mapping for disaster mitigation. Their study underscores the effectiveness of remote sensing and photogrammetry in pinpointing flood-prone areas. Understanding and addressing flood risk requires a multifaceted strategy, incorporating a range of tools and evaluations. Flood-risk zones, digital elevation models (DEMs), flood extent maps, threat analyses, and exposure assessments each provide valuable and unique insights into the intricate issue of flood vulnerability. To comprehensively assess the persistent flooding in the lower Niger Catchment, it is imperative to have a deeper understanding of the existing phenomenon.

This study comprised comprehensive analysis of soil classification and flood susceptibility analysis in Onitsha, encompassing Onitsha South and Onitsha North Local Government Areas. The primary objective was to provide valuable insights and add to the extant volume of flood data on the Onitsha Niger River Catchment. Utilizing ground-truthing techniques, soil samples were collected from ten locations with precise Global Positioning System (GPS) coordinates. Administrative maps of Anambra state and satellite images from Landsat’s enhanced thematic mapper (ETM+) were employed to delineate the political boundaries and extract feature classes for the analysis. Supervised classification techniques facilitated the extraction of meaningful information from the imagery, with IDRISI software utilized for data analysis.

The analysis revealed that the predominant soil composition in the research region consists predominantly of sand (84.8%), followed by silt (8.1%) and clay (7.1%). This composition aligns with reports of recurrent flooding in the area and the higher proportions of sandy soil observed during in-situ surveys. The susceptibility of sandy soil to flooding was further underscored, attributed to its ability to facilitate rapid infiltration of rainwater coupled with its low water-holding capacity, leading to swift saturation and substantial inundation.

The research further demonstrates elevated levels of susceptibility and exposure in specific areas within the catchment, a fact reinforced by the flood extent map. Additionally, various tools such as DEM, flood extent maps, vulnerability maps, and flood-risk maps were employed to highlight and visualize vulnerable regions and flood-prone zones within the studied area, showcasing the considerable jeopardy faced by businesses and communities within the Niger River catchment, Onitsha.

The integration of these findings into flood risk assessments offers critical insights into the dynamics of flood susceptibility within the Onitsha Niger River catchment. By elucidating the relationship between soil composition and flood susceptibility, this study contributes essential to the existing knowledge for devising effective flood mitigation strategies. More so, future research endeavors could explore the incorporation of hydraulic models to enhance understanding of flood patterns and inform proactive measures for flood risk management in the region.