Understanding the Challenges and Gaps in Flood Vulnerability Assessment and Mitigation Strategies in Nigeria

Understanding the Challenges and Gaps in Flood Vulnerability Assessment and Mitigation Strategies in Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding the Challenges and Gaps in Flood Vulnerability Assessment and Mitigation Strategies in Nigeria Ololade Sophiat Alaran, Abdulahi Opejin, Adewunmi Aderonke Oluwabunmi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6952249/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Flooding is among the most destructive environmental hazards, leading to significant socioeconomic losses, infrastructural damage, and displacement. Floods are becoming more frequent and intense due to climate change, increased urbanization, inadequate drainage systems, and inadequate flood risk management measures. Many empirical studies utilized various advanced tools and methods to understand the extent of flood vulnerability in flood-prone areas. The combination of the datasets for flood mapping, the choice of methods, and the flood modeling approach varies from one researcher to another, and they often neglect social-ecological dynamics, which can influence flood risks. Additionally, flood vulnerability, risk preparedness, and adaptive management practices varied, sidelining the integration of community-based science and consideration for crucial stakeholders. However, this study seeks to assess flood vulnerability assessment and mitigation approaches to understand current modeling methods and existing adaptive methods in developing countries like Nigeria. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline summarized the literature from 28 journals. The study's findings revealed that environmental contexts are crucial in determining flood risk mapping parameters and suggest integrating those factors with social-ecological factors. The review also suggests addressing primary barriers to flood data collection and accessibility, using cost-effective, community-driven, or crowdsourced methods, and interdisciplinary collaboration to improve flood risk assessment and mitigation strategies in urban and rural Nigerian communities. The study proposes a multidisciplinary approach encompassing capacity-building programs, regulatory reforms, and technological advancements to enhance resilience against flooding. Flooding disaster management flood data resilience environmental management hydrologic models 1. Introduction Floods are common hydrometeorological disasters with potential loss of lives, economic damage, and environmental degradation (Koko et al., 2021; Zhang et al., 2023). Natural disasters increased significantly between 1990 and 2020, with flooding as the most prominent disaster (Abbas et al., 2023; Rahman et al., 2023). Flooding represents one of the most devastating types of natural disasters, inflicting considerable damage to life, property, and the environment (Ibrahim et al., 2024). Floods happen when the rivers overflow their banks, caused by heavy rainfall, and the impacts intensify globally every year (Zhao & Zhang, 2013; Khan et al., 2016). According to the World Health Organization (WHO), flooding affected more than two billion people globally from 1998 to 2017, and those living in floodplains in poor housing or with limited knowledge about the dangers of flooding are especially vulnerable to disaster (World Health Organization, 2020). Cities in Egypt and Nigeria are purportedly more susceptible to flood risk in Africa, potentially due to the population increase in those nations (Nicholls et al., 2008). Economic development and population growth may have encouraged people to live along the river overflow, despite the adverse effects of flooding, especially in some Nigerian cities like Ibadan, Lagos, Kano, and Lokoja (Amangabara & Obenade, 2015; Ademola et al., 2021 ). More people in Nigeria have been impacted and displaced by flooding than by any other disaster, which disrupts sources of income and causes property loss and destruction. In 2012, the river Niger overflowed, causing floods in Lokoja, making it the most catastrophic natural disaster in Nigeria's history (Popoola et al., 2022 ). Due to this disaster and its socio-economic consequences, an assessment and action plan for flood risk is needed. More flood events have highlighted the need for mapping flood-prone areas, which is an aspect of flood mitigation (Chakrabortty et al., 2018; Yu et al., 2023). Roy et al. (2020) Appropriately, recognized that concern for eco-friendly disaster management is growing in diverse fields, no less so than amongst global teams from various ventures, researchers, geographers, climatologists, and regional planners engaged to control and alleviate disaster impacts. Developing a model for measuring vulnerability presents essential opportunities to boost flood management methods (Ruidas et al., 2022). Protecting vulnerable areas from flood damage requires complete understanding of flood vulnerability for both risk assessments and mitigation plans and resilient strategies (Wang et al., 2022; Vignesh et al., 2021). The rise in flood occurrences has led to greater national awareness while speeding up flood vulnerability assessment and management endeavors across Nigeria. Multiple flood mitigation projects exist in Nigeria, yet the country faces shortcomings related to its missing integrated and sustainable methods for risk management (Onoh, 2023). Research demonstrates that Nigeria has insufficient methods for flood vulnerability assessment and implementing flood mitigation strategies (Echendu, 2020; Ndimele et al., 2024). Various obstacles limit the success of flood mitigation in Nigeria, including policies that lack stable direction, along with weak institutional structures and shortages in funding for studies and infrastructure expansions (Anifowose & Rollason, 2024). Neighborhoods across various locations experience significant flood risks from climate change, its effects, human-caused incidents of rapid population growth without planning, and inadequate urban development (Popoola, 2022; Wu, 2021). Post-modern flood assessment techniques and mitigation strategies through GIS, hydrological modeling, and remote sensing technology give better chances to manage risk by improving flood prediction capabilities (Gyang et al., 2024). Nigeria faces significant barriers to implementing new flood risk management technologies due to difficulties with data accessibility, insufficient technical expertise, and poor inter-agency cooperation, and the solution requires multiple governmental organizations, community groups, and private investors to collaborate and meet these requirements (Okunola, 2025 ; Okunola & Werners, 2024). Researchers acknowledge adaptive flood mitigation techniques as a vital method for improving the assessment and response to flood risks (Klijn et al., 2015; Qi et al., 2024). Since flood risks are constantly changing, adaptive flood mitigation design uses flexible response strategies that use real-time data collection, community involvement, and technological advancements to lessen the effects of floods. This approach will allow officials and local stakeholders to create resilient, and sustainable flood measures (Emami, 2020). Empirical studies have identified significant gaps in present flood risk assessment approaches. Research has shown that none of the current modeling approaches produces adequate results for tracking complete flood hydrodynamic conditions in every location. For instance, Nkwunonwo et al. (2020) observed that a perfect model or general approach that can capture all components of flood hydrodynamics in an ideal form within the research areas is still unachievable. The study by Malgwi et al. (2021) on the approach to rebuilding flood scenarios using field interviews and hydrodynamic modeling in Nigeria. The study emphasizes the prospect of using interview data for hydrodynamic modeling applications in data-scarce locales to enhance regional flood risk assessment. However, it has been noted that this modeling is not viable. The multiple modeling procedures used in Nigeria have failed to provide an all-encompassing remedy to forecast floods and determine their intensity levels. The advanced tools for flood risk management, including remote sensing methods and ensemble-based hydrological modeling with extreme value distribution analysis, are underutilized in developing countries. Therefore, progressive flood risk administration must efficiently integrate scientific research tools, including satellite systems, GIS mapping, social-ecological data, and machine learning capability, to assess or predict flood vulnerability. The lack of coordination among concerned stakeholders (e.g., communities, researchers, policymakers, and governmental agencies that handle flood risk management) impedes effective flood mitigation and adaptive management practices. To resolve these shortcomings, policies should create changes that enhance data transparency and establish active assistance between different professions while creating changes that enhance data transparency and establish synergistic assistance between different professions, stakeholders, communities, and government agencies while conducting studies to understand the effects of floods and flood mitigation procedures. Therefore, adaptive measures such as crowdsourcing and community engagement are employed by locals to gather flood data in collaboration with different stakeholders (Helmrich et al., 2021). This review evaluates primary barriers to flood data collection and accessibility in Nigeria and how cost-effective, community-driven, and crowdsourced methods can bridge this gap. It also addresses interdisciplinary collaboration and multi-source data integration to enhance flood risk assessment and mitigation strategies in urban and rural Nigerian communities. Given the study’s objectives, we reviewed challenges, innovations, and the role of the adaptive flood mitigation approach by identifying the primary obstacles that hinder the assessment and mitigation process for flooding in Nigeria. The research focused on analyzing essential issues related to flood data collection challenges, the potential benefits of community-based and crowdsourced approaches, and the value of interdisciplinary collaboration in risk evaluation and defense strategies, through which we answered the following research questions. What are the primary barriers to flood data collection and accessibility in Nigeria, and how can cost-effective, community-driven, and/or crowdsourced methods bridge this gap? How can interdisciplinary collaboration and multi-source data integration enhance flood risk assessment and mitigation strategies in urban and rural Nigerian communities? Understanding these issues is crucial to developing effective policies and frameworks that reduce the socioeconomic and environmental impacts of floods in Nigeria. 2. Method This paper employed the systematic review approach to investigate barriers, innovations, and the role of adaptive flood mitigation strategies to aid the upgrading of flood vulnerability assessment and reduction in Nigeria. The methodological framework aimed to address the research questions through an interdisciplinary approach and by reviewing existing literature on flood risk management. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist serves as a basis for achieving a transparent and complete review procedure for this study. Research questions were selected to solve three main problems: data collection and accessibility issues, cost-effective community flood mitigation calculations, and collaboration between experts in flood risk assessments. The study extensively evaluates the Nigerian context of operational viability for different models and systems in the Nigerian context by examining hydrological modeling, remote sensing, GIS applications, and machine learning approaches. Stakeholder participation was focused on alongside collaboration between public service departments, researchers, and local communities to develop better flood prevention techniques. 2.1 Search Strategy The research followed a systematic approach by searching databases to gather flood vulnerability assessment and mitigation literature from research platforms, including Web of Science, Scopus, Google Scholar, Science Direct, and SpringerLink. The research team utilized predetermined keywords to swiftly identify pertinent studies. This study examines key phrases such as “flood risk mitigation,” “flood vulnerability assessment,” “barriers to flood data collection,” “adaptive flood management,” “remote sensing and GIS for flood prediction,” “interdisciplinary collaboration in flood risk assessment,” and “community-driven flood mitigation strategies.” The reference lists of relevant studies are reviewed to identify additional literature that aligns with the research goals. A systematic assessment method summarizes the studies obtained during the search process. The initial research screening occurs in two stages: studies without matches are rejected during title and abstract screening, and the remaining studies undergo full-text review for objective compliance. This method of selecting high-quality research ensures strong insights, which enhance strategies for flood mitigation. Scribbr and Mendeley were used to manage citations and references properly. This paper documented its literature selection process through a PRISMA flow diagram, providing greater transparency and reproducibility. The research employs this structured system to deliver valuable findings that enhance Nigeria's flood vulnerability assessments and mitigation efforts by integrating innovative methodologies and team collaboration. 2.2 Relevance screening and eligibility criteria In order to ensure the inclusion of high-quality and relevant literature to the themes of this study, we adopted a structured relevance screening and eligibility evaluation adapted from the PRISMA guidelines and framework (see Appendix 1) established in Sayyed et al. 2014. The abstracts of the considered journals were downloaded and examined to determine the study's relevance to the secondary data used. We evaluated these studies for quality assessment to ensure they are pertinent to this research by skimming the full-text articles to assess their quality and eligibility. The studies included any journal articles, dissertations, or those released by authors from known, adequately referenced sources. The first level of screening assessed the abstracts and titles with a focus on the four thematic areas: Barriers to flood data collection and accessibility, Impact of cost-effective, community-driven, and crowdsourced methods on flood, Interdisciplinary Collaboration and Multi-Source Data Integration Enhance Flood Risk Assessment and Mitigation strategies with emphasis on studies in Nigeria. Studies that do not meet these criteria were excluded at this point. During the second level screening, the full text was examined, journals between 2015 and 2025 were considered, while others were excluded. Other details, such as literature providing clear methodology, and the publications were limited to peer-reviewed journal articles, dissertations, and those from reputable sources, were used as selection criteria for inclusion and exclusion were established to ensure the validity of the data. 2.3 Data Analysis From each paper, information was extracted on the following: (i) Barriers to flood data collection and accessibility in Nigeria; (ii) Impact of cost-effective, community-driven, and crowdsourced methods on flood; (iii) How interdisciplinary collaboration and multi-source data integration enhance flood risk assessment (iv) Mitigation strategies in urban and rural Nigerian communities. The study synthesized all extracted secondary data, provided a narrative summary of the findings, and highlighted the relationships between the studies. 3. Result The results were gathered through a systematic review under the following section: 3.1 Barriers to flood data collection and accessibility in Nigeria Nations experience reduced flood management effectiveness because of barriers, including institutional challenges, technical limitations, and socioeconomic obstacles, that limit flood data collection and accessibility. Institutional challenges cause nations to struggle with flood response management because they lack appropriate hydrological data management, sufficient political will, and legal frameworks (Ekeu-Wei, 2018 ; Sola et al., 2020 ). A national flood management policy would not improve the situation since different regions use separate approaches (Adelekan & Asiyanbi, 2016). Also, the slowness of governmental processes and weak governance delays data exchange between different agencies (Ekeu-Wei, 2018 ). Different problems arise from the use of technology; these include the breakdown of hydrological infrastructures as a result of flooding and restricted access to advanced radar or sonar data acquisition systems, leading to a reduction in the performance of flood monitoring systems (Ekeu-Wei, 2018 ; Ebekozien et al., 2023 ). Nigeria's early warning system cannot monitor real-time flood situations (Atijosan et al., 2017); this lack of adequate assessment of floods is a result of using substandard remote sensing technology and inadequate meteorological station deployment (Nkwunonwo et al., 2020). Three studies identified a lack of inter-agency collaboration, substandard and poor infrastructures as challenges to flood data collection (Ekeu-Wei, 2018 ; Lamond et al., 2019 ; Oladokun & Proverbs, 2016 ). In one study on the evaluation of Hydrological Data Collection Challenges and Flood Estimation Uncertainties in Nigeria, the author analyzed challenges of collecting flood data along the Ogun-Osun River using data through interviews from 5 collection officers. Ekeu-Wei ( 2018 ) discovered that errors in flood frequency estimates result from improper maintenance of hydrological infrastructures. The lack of unification between research groups and government agencies on the standard of data collection results in forecasting and flood record challenges. The authors therefore recommended improved management, data collection methods, and utilization of flood data and infrastructures. The lack of coordination between government agencies, technical experts, and local stakeholders results in a lack of unified data collection methods, which in turn causes duplicate work and operational inefficiencies, hindering thorough flood risk assessments (Lamond et al., 2019 ). Moreover, poor and substandard decisions made on flood preparation and emergency response by local authorities and stakeholders are due to inadequate capacity development (Adelekan & Asiyanbi, 2016). Agencies should enhance cooperative efforts amongst all stakeholders and implement a capacity-building program encouraging community-level flood observation for effective flood risk management (Nkwunonwo et al., 2020; Okunola, 2025 ). Social and economic circumstances also create significant barriers to accessing flood data. Flood-related information remains inaccessible to marginalized communities primarily because rural and low-income urban areas lack sufficient investment in resilience technologies and adequate infrastructure, and face financial limitations. (Ebekozien et al., 2023 ; Sola et al., 2020 ). People in numerous communities do not understand the flood warning networks available, which decreases their capacity to adopt protective actions (Adelekan & Asiyanbi, 2016). The unreliable power supply and inadequate internet connectivity prevent vulnerable populations from accessing and using thematic categorization to analyze the data collected on barriers to using flood resilience technologies. Three studies have highlighted socioeconomic constraints like financial limitations as affecting flood data management (Adeoti, 2020 ; Ebekozien et al., 2023 ; Sola et al., 2020 ). One of the literatures identified other barriers groups, including socio-economic differences. Ebekozien et al. ( 2023 ) conducted virtual interviews with 30 stakeholders in the six geopolitical zones of Nigeria. The authors grouped the barriers into technical, socio-economic, institutional, financial, and infrastructure. They found out that infrastructure and funding are important to flood resilience. National-scale risk assessments heavily depend on meteorological data but lack sufficient detailed local-scale information. The potential solution of open-access remotely sensed data faces ongoing logistical and organizational obstacles when implementing this data into national flood management plans (Lamond et al., 2019 ; Ekeu-Wei & Blackburn, 2018 ). Many flood control measures rely on generalized models rather than local flood patterns, as area-specific model calibration is often not readily available (Nkwunonwo et al., 2020). The combination of citizen science procedures and participatory methods creates a connection that combines local on-ground observations with the national flood management systems, according to Alemu et al. (2023). Resolving these barriers requires a multifaceted approach, which includes integrating national resources into flood management, infrastructure development alongside stakeholder communication enhancement, and technological and data management system funding expansion. Geospatial mapping is an essential method for detecting coastal flood hazards and assessing vulnerability distributions in urban areas of Lagos, particularly in Nigeria. The enhancement of flood management in Nigeria is possible through technological investments, like GIS, inter-institutional cooperation, and data sharing across all stakeholders to protect vulnerable communities from economic and social flood impacts. New investigations must merge indigenous knowledge techniques with present-day computational hydrologic models since their combination would boost flood prediction capacities and adaptation mechanisms (Nkwunonwo et al., 2020). Literature has supported using remote sensing and GIS to easily access real-time flood data and detect risks (Ekeu-wei & Blackburn, 2018 ; Otokiti et al., 2019 ; Popoola et al., 2022 ). Otokiti et al. ( 2019 ) examined the geospatial mapping of flood risk in the coastal megacity of Lagos, Nigeria. They used data from the United States Geological Survey (USGS) archive to generate parameters on Digital Elevation Model (DEM), slope, drainage density, land cover type, curvature, Normalized Difference Water Index, and flow accumulation. The authors explained that remote sensing and GIS help identify flood risks through their discovery that using precise spatial data improves model accuracy for flood forecasting. Popoola et al. ( 2022 ) demonstrated that GIS with multiple criteria helps discover hazardous locations and supports the formulation of flood management policies for urban districts bordering the Niger River. According to Gyang et al. (2024), flood predictions and response planning reach higher accuracy when organizations use advanced technologies such as Geographic Information Systems (GIS) and real-time flood mapping. The authors Ekeu-wei and Blackburn ( 2018 ) discuss flood modelling and mapping in Nigeria under challenges like the unavailability of datasets due to financial, technical, and organizational challenges. They advocate for open-source remote sensing platforms to enhance ground-based information networks, transboundary flood analysis, and flood management in developing nations. According to Adelekan and Asiyanbi (2016), developing a stronger flood management framework in Nigeria requires policy reforms to improve flood governance structures and data-sharing systems through investment in technology. The warning capabilities of flood-prone areas can be improved by installing geographic information systems technology, low-cost sensors to detect signals, and mobile tracking applications (Otokiti et al, 2019 ). 3.2 Impact of cost-effective, community-driven, and crowdsourced methods on flood Floods represent one of the most catastrophic natural events that result in massive human casualties, severe structural damage, and substantial economic losses, necessitating proper management (Helmrich et al., 2021; Wolf et al., 2022 ). Traditional flood control systems do not work adequately for developing nations because these methods lack data-based characteristics, have limited budget reach, and have accessibility challenges. Developing low-cost, crowd-based solutions is a contemporary method that supports risk assessment activities, flood warning creation, and response implementation. Numerous experts agree that crowdsourcing enables the collection of valuable flood data (Helmrich et al., 2021; Songcho, 2023). Organizations that link crowd-based data systems with traditional processes can develop cost-effective solutions that deliver accurate flood spatial information and fast data analysis capacities (Helmrich et al., 2021; Songcho et al., 2023). The price of hydrological monitoring systems decreased through the use of economical digital equipment such as smartphones and social media platforms (Helmrich et al., 2021). Users gather flood information swiftly from Twitter, Facebook, and YouTube to enhance their assessment results during urban flood investigations (Re et al., 2022; Songchon et al., 2021). Social media platforms, webcams, and citizen science successfully generate proper data records (Helmrich et al., 2021). Residents collaborate with professionals under citizen science initiatives to gather flood data, which leads to successful engagement in flood monitoring (Assumpção et al., 2018). Elega et al. ( 2024 ) examined the Eco Nai + platform, consisting of a web and mobile app for accessing geo-journalism data. The authors used a multi-method approach to analyze platform data, interviews, and documents. They explored the importance of crowdsourcing and opined that the integration of geo-journalism with participatory mapping helps research findings establish effective networks between scientists, public servants, and at-risk residents. According to them, these initiatives let distant community members actively participate in developing measures to reduce disaster risks and improve flood preparedness while establishing personal ownership of the developed strategies. However, with the numerous merits of crowdsourcing and community-based flood management systems, these systems may encounter various obstacles in data quality assessment, reliability, and testing accuracy. Due to its inherent nature, multiple verification mechanisms must be established to solve accuracy and consistency issues arising from unstructured crowdsourced information (Songchon et al., 2021; Helmrich et al., 2021). The combination of artificial intelligence and machine learning technology helps validate crowd-sourced flood data by conducting analyses of different information sources, satellite data, and hydrological inputs (Songchon et al., 2021). It is important to protect contributors' privacy; data must be balanced through proper ethical practices that maintain clear data usage transparency. Okunola's study (2025) analyzed multilevel governance arrangements in disaster recovery in Lagos, Nigeria, using document reviews and semi-structured interviews. The study revealed poor collaboration between public departments caused difficulties during post-flood building reconstruction efforts, and top-down decision-making limited community participation. Therefore, recovery and resilience from a disaster such as a flood would succeed when multi-level governance is fully implemented. They recommended collaboration and coordination among stakeholders. Some opportunities noted for crowd sourcing and citizen science are setting up models using land cover maps that can be validated with citizen science, validating data collected through social media, and using applications and websites developed that could be shared for public use. However, an additional layer of verification should be done to avoid duplication (Assumpção et al., 2018). The challenges of citizen science include using citizens as interpreters, improving estimation methods from pictures gathered, quantifying uncertainties, and harmonizing distributions and time frequencies from other data sources alongside citizen science. Modern advancements in remote sensing technology, IoT systems, and blockchain-based data verification protocols would also improve the efficiency of crowdsourced data. Water level sensors and IoT drone technology are used in community-based monitoring to collect real-time flood information. Implementing transparent and immutable blockchain record-keeping for crowdsourced flooding data increases system trust by eliminating ghost data issues (Ebekozien et al., 2023 ). 3.3 How Has Interdisciplinary Collaboration and Multi-Source Data Integration Enhanced Flood Risk Assessment? Flood disasters that have struck Nigeria require better assessment tools for identifying flood risks in the affected regions. This section reviews studies on how interdisciplinary collaboration and multi-source data integration can enhance flood risk assessment. The flood vulnerability mapping project involving Geographic Information System (GIS) and Remote Sensing and Fuzzy Logic System emerged from Atemoagbo et al. ( 2024 ) to assess flood risk areas in Suleja Local Government of Niger State North Central Nigeria. This research uses GIS and satellite datasets to create the Flood Zonation Mapping of Suleja. The identification of flood-prone areas utilizes rainfall data from the Nigeria Meteorological Agency (NiMET) together with Climate Hazards Group InfraRed Precipitation with Station Data (CHRPS), Global Satellite Mapping of Precipitation (GSMaP), slope elevation, and nearness to water bodies, along with land use and drainage density parameters. The geographic area faces various flood risks categorized into five zones based on the flood vulnerability map and these risk areas are organized as Very Low Risk (40.9%), Low Risk (18.9%), Medium Risk (27.6%), High Risk (7.1%), and Very High Risk (5.5%). According to this research, developing data-driven techniques enables improved flood risk evaluation for Nigeria. The study enables stakeholders and policymakers to make strategic decisions to protect infrastructure and communities from flooding risks. A geospatial multi-criteria model for flood risk assessment was developed by Gambo et al. ( 2024 ) for Jigawa, Nigeria. The research incorporated data from multiple origins through assets provided by the National Population Commission (NPC) and National Bureau of Statistics (NBS) with land use and Digital Elevation Model (DEM) details obtained from Shuttle Radar Topography Mission (SRTM) and Sentinel-2 as well as precipitation data retrieved from Climate Hazards Group Infrared Precipitation with Station (CHIRPS). The integration of different data sources enables the development of a complete method to assess flood-risk prone areas across Jigawa. Flood danger areas in the region span 3–13% of the total landscape, indicating severe flood danger. Flood disasters affect 40% of the population within this region. These research outcomes demonstrate that combining multi-source data collections with geospatial software enhances Nigerian disaster risk management systems. Aladejana and Ebijuoworih (2024) performed work that had similarities to Gambo et al. ( 2024 ) study. Researchers applied multiple methods to produce statewide flood risk mapping by investigating flood hazard and flood vulnerability factors. A flood risk assessment of Kogi State was carried out by integrating satellite remote sensing with GIS technology and field observations from original and existing data sources. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data underwent reprojecting and mosaicking functions, which produced Kogi State's digital elevation model (DEM) at a resolution of 30 m. The previous five years of weather data came from the Climate Hazards Group's Infrared Precipitation with Stations (CHIRPS). Information about road networks and health centers/hospitals’ locations is derived from OpenStreetMap (OSM). Statistics on population density, female population data, literacy, and employment rate information were obtained from the National Bureau of Statistics (NBS) archives. The researchers applied FAHP with a Fuzzy approach to weight and rank drainage length and the other six flood hazard factors, along with seven vulnerability factors, to assess flooding contributions in Kogi State. Analysis of collected data resulted in the development of the Flood Hazard Index (FHI) and two other index models as part of risk zone assessment in Kogi State. This indicates that collaboration between multiple bodies enabled the development of the Flood Hazard Index (FHI) and two other index models as part of risk zone assessment in Kogi State. A flood risk assessment and mapping developed by Shuaibu et al. ( 2022 ) assessed flood risk and vulnerability throughout the Hadejia River basin, Nigeria, to decrease flood vulnerability and risk in the region. Agency data used in the analysis includes 36 years of daily rainfall records obtained from NiMet stations and HJRBDA facilities in Nigeria. The National Population Commission (NPC) 's official website and the National Bureau of Statistics (NBS) provided population census data for the years 2006 and 2011 at the LGA level. Data analysis revealed high-to-very high flood risk in a basin section spanning 43.4% of the area where the downstream and central upstream locations exist. This suggests that collaboration between different agencies enhanced flood risk assessment in the areas. Nkechi et al. ( 2024 ) applied an integrated research method by uniting remote sensing technology with GIS techniques to control flooding effectively. The research objective was to identify flood-vulnerable zones located in Oguta LGA within Imo State. The research investigators implemented flood-prone zone mapping through their analysis of Landsat ETM + of 2023, along with Digital Elevation Model (DEM) Shuttle Radar Topographic Mission (SRTM) combined with geological data and meteorological data obtained from the USGS Earth Explorer website and Tropical Rainfall Measuring Mission satellite. All gathered data served to identify factors that lead to flooding incidents in the region studied. The assessment technique successfully determined areas at high risk of flooding in Oguta LGA of Imo State. 3.4 Flood Mitigation Strategies in Urban and Rural Nigerian Communities Perception of risk is a significant factor in the preparation and mitigation of disasters. Over time, understanding the flood risk, likelihood, and possible related disasters has affected the selection of what flood risk management approach to choose and apply (Danladi et al., 2024 ). Given the significant flood catastrophes in Nigeria during the last two decades, it is imperative to develop mitigation techniques. Flood mitigation strategies used in urban and rural Nigerian communities are categorized as structural and non-structural. Nkwunonwo et al. ( 2016 ) reported that Lagos's flood risk management strategies have been built on preventing and controlling floods, with primary measures being the development of structural methods. Flood mitigation strategies used in Ibadan are mainly structural and non-structural methods. Structural methods are channelization, dredging, and construction/widening of culverts and bridge throughways, and non-structural measures are improved waste management systems (Egbinola et al., 2017 ). Channelization of the Ogunpa River and the Awba Stream within the University of Ibadan helped stop flooding in Ibadan. In addition, dredging of all the streams within the city helped to mitigate flooding in the affected areas by the floods across all the 11 local government areas of Ibadan (Egbinola et al., 2017 ). These strategies corroborate the Ifeanyi ( 2024 ) investigation on flood resilience and mitigation strategies in Maiduguri, Nigeria. The highlight is effective flood mitigation strategies in Maiduguri, Nigeria, including upgrading drainage systems, enhancing early warning systems, and implementing green infrastructure. In research conducted by Obeta and Ochege ( 2018 ), the research compared flooding in Warri and Port Harcourt urban areas of the Niger Delta region in southern Nigeria. It was revealed that mitigation strategies used in the two states are urban drainage systems. However, this strategy is inadequate for protecting floodplain occupants in these areas. Barau and Wada ( 2021 ) studied Do-It-Yourself flood risk adaptation strategies in the neighborhoods of Kano City, Nigeria. It was revealed that Do-It-Yourself (DIY) adaptation manifests in using sandbags, de-siltation of drainage, construction of fences, and drainage diversions, indicating that DIY is a practical mitigation approach for flood protection. Obi et al. ( 2021 ) examined indigenous flood control and management knowledge to identify its effectiveness in preventing flood disasters in Nigeria's coastal communities. The finding shows that indigenous flood control and management practices are the major flood risk reduction strategies in coastal communities in Nigeria. The federal, state, and local governments have contributed to flood mitigation plans in Nigeria. The Ministry of Environment, alongside additional relevant agencies, functions under the federal government to oversee flood governance activities, provide risk reduction initiatives, perform monitoring operations, and implement management strategies. The government worked toward three primary objectives: raising public awareness and demonstrating people's relationship to their environment, as well as establishing partnerships with environmental NGOs, MDAs, and the corporate sector (Danhassan et al., 2023). The Ministry of Environment exists in each of the 36 states, which handles flood regulation and environmental threats. The Ministry of Environment and several state regulatory bodies operate to manage and oversee flood regulation according to Danhassan et al. (2023). LASEPA and JISEPA, under Lagos State and Jigawa State, respectively, represent a few among the multiple environmental protection agencies (Adelekan, 2016; Tariq et al., 2020 ). Numerous governments created state emergency management agencies (SEMA) to produce regulations while leading disaster response initiatives. The government at the local level maintains crucial responsibility to handle and prevent floods affecting rural areas. The government is responsible for disaster reactions, local disaster plan approval and rapid notification of local disaster information to the local flood disaster coordinator. Local flood disaster management groups should be established to assist governments in creating flood management plans while assessing and developing successful flood control practices (Sinthumule & Mudau, 2019 ). Symmetrical flood operation management should incorporate mutual integration with all involved departments, including state disaster management and local flood disaster management (Vaughan & Hillier, 2019). The government needs to identify resources dedicated to flood mitigation, control the response operations through proper coordination, and maintain flood readiness for the community. Local governments within Nigeria face poor financial capacity when it comes to flood response due to the joint financial management system between states and local governments (Danhassan et al., 2023). 4. Discussion The literature reveals that multiple substantial barriers hinder flood data collection and accessibility in Nigeria, reducing flood management and mitigation effectiveness. Institutional challenges, technical limitations, and socioeconomic obstacles were found to be the main barriers to flood data collection and accessibility. The literature shows that a lack of data will affect the flood vulnerability assessment. All these barriers were highlighted in Ekeu-Wei ( 2018 ); Sola et al. ( 2020 ); Ademola et al. ( 2021 ); and Adelekan and Asiyanbi (2016). The findings of this study align with the results of Waterman et al. (2021) on an investigation into barriers for sharing geospatial and resilience flood data in the UK. The study identified barriers and constraints when sharing data between organizations, which include technological, security, privacy, cultural, and commercial barriers across different use cases and data points. The study reviews the impact of cost-effective, community-driven, and crowdsourced methods on floods. It was determined that these methods are crucial for assessing flood vulnerability and developing mitigation strategies for flood protection in Nigeria. The study conforms with Degrossi (2014) on Flood Citizen Observatory: a crowdsourcing-based approach for flood risk management in Brazil. The result established that crowdsourcing is effective in obtaining useful and accurate information from the citizens, since citizens can easily provide information about the water level in the riverbed through the platform categories. In addition, the findings of this study affirm Danraka et al.'s (2024) investigation on community-based adaptation to floods in Malaysia. The study findings discovered that a wide range of community mobilization strategies exist, ranging from early warning systems and hazard forecasts to livelihood-based adaptation. Furthermore, this study investigated how interdisciplinary collaboration and multi-source data integration enhance flood risk assessment through the literature. The study found that developing data-driven methods through interdisciplinary collaboration and multi-source data integration enhances Nigeria's flood risk assessment. This study's findings confirm the approach that Ibrahim et al. (2025) used on an integrated approach to flood risk assessment using multi-criteria decision analysis and geographic information systems in a flood-prone region of Pakistan. The study established that combining methods enabled the creation of accurate, data-driven flood risk maps. The hazard map of the area serves as a valuable tool for decision-making, resource allocation, and the development of flood risk management strategies. The study reviewed the flood mitigation strategies in urban and rural Nigerian communities. Significant flood mitigations in Nigeria's urban and rural communities include upgrading drainage systems and channeling rivers. Non-structural mitigation creates awareness by collaborating with environmental NGOs and MDAs. Compared to the flood mitigation method used in the US, research by Slotter et al. (2021) explored a range of mitigation strategies used in the US. Slotter et al. (2021) recorded over 25 policy interventions for flood risk reduction. These interventions are aggregated into five categories: insurance, land use planning, property acquisition (buyout program), financial assistance, and community engagement. The flood mitigation strategies used in Nigeria are quite different from those in the US. These strategies can be incorporated into the flood mitigation strategies used in Nigeria. Study of Davids et al. (2024) showed that Nature-based solutions (NBS) are another flood risk mitigation strategy that complements conventional ‘grey’ infrastructure for stormwater management (dams and dikes) in reducing flood risks. 5. Conclusion This study is delimited to enhancing flood vulnerability assessment and mitigation in Nigeria. The study reviewed challenges, innovations, and the role of the adaptive flood mitigation approach. The study employed a systematic review, which may not apply to other studies. The study reviewed studies that related to this study with significant findings. Based on the findings, the study concluded that institutional challenges, technical limitations, and socioeconomic obstacles were found to be the main barriers to flood data collection and accessibility; cost-effective, community-driven, and crowdsourced flood methods are crucial for assessing flood vulnerability and developing mitigation strategies for flood protection in Nigeria; the development of data-driven methods through interdisciplinary collaboration and multi-source data integration enhances Nigeria's flood risk assessment; and the significant flood mitigations used in urban and rural communities in Nigeria is structural (upgrading of drainage system and channeling of river) and non-structural mitigation (creating awareness). Because of the dearth of relevant literature, the study faced some challenges. The number of literature works selected in the first screening level was drastically reduced due to the unavailability of literature specific to Nigeria. Literature assessing barriers to flood data collection and crowd sourcing was rampant in countries like India and Pakistan, but was excluded due to our selection criteria. Other limitations include inconsistencies in the quality of some papers, reliance on English language databases, and restrictions due to a lack of access to full texts due to paywalls and institutional access. Declarations Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships that may be considered potential competing interests: References Adelekan IO, Asiyanbi AP (2015) Flood risk perception in flood-affected communities in Lagos. Nigeria Environ Urbanization 27(2):1–18. 10.1007/s11069-015-1977-2 Ademola F, Ifeanyi AM, Richard U, Opejin, Abdulahi (2021) An Assessment of Flood Vulnerability Areas in ETI-OSA Local Government Area, Lagos State, Nigeria. Semantic Scholar. https://api.semanticscholar.org/CorpusID:249011027 Adeoti A (2020) Constraints on data collection implementation at the river basin level in Nigeria. J Water Resour Environ Eng 12(3):45–56 Aladejana JA, Oluwafemi I, Oduwole A (2024) Flood risk assessment in Kogi State Nigeria through the integration of hazard and vulnerability factors. Environ Hazards 23(1):56–74 Atemoagbo C, Chinedu E, Salisu H (2024) Metropolitan flood risk characterization using remote sensing, GIS, and fuzzy logic (RS-GIS-FL) approach: Suleja, Nigeria. Nat Hazards Rev 25(2):88–103 Barau AS, Wada AC (2021) Do-it-yourself flood risk adaptation strategies in the neighborhoods of Kano City, Nigeria. Int J Disaster Risk Reduct 54:102050. https://doi.org/10.1016/j.ijdrr.2020.102050 Danhassan I (2023) Flood policy and governance: A pathway for policy coherence in Nigeria. Environ Policy Gov 33(1):12–27. https://doi.org/10.1002/eet.1980 Danladi MA, Abubakar A, Yusuf K (2024) Pre-disaster preparedness/prevention and mitigation strategies for floods: A use case of Lagos, Nigeria. Disaster Prev Manage 33(2):75–91 Ebekozien A, Olatunji O, Akinola M (2023) Appraising the role of flood resilience technologies in developing cities: How prepared are the professional stakeholders? J Urban Manage 12(1):19–33 Egbinola CN, Olaniran HD, Amanambu AC (2017) Flood management in cities of developing countries: The example of Ibadan, Nigeria. Int J Disaster Risk Reduct 23:311–318. https://doi.org/10.1016/j.ijdrr.2017.05.004 Ekeu-Wei IT (2018) Evaluation of hydrological data collection challenges and flood estimation uncertainties in Nigeria. Hydrology 5(3):45–58 Ekeu-Wei IT, Blackburn GA (2018) Remote Sens Applications: Soc Environ 11:40–52. https://doi.org/10.1016/j.rsase.2018.06.004 . Applications of open-access remotely sensed data for flood modelling and mapping in developing regions Elega AA, Adewale SA, Bamidele AF (2024) Geojournalism, data journalism, and crowdsourcing: The case of Eco-Nai + in Nigeria. J Afr Media Stud 16(1):95–110 Gambo M, Musa A, Kabir A (2024) Unveiling and modelling the flood risk and multidimensional poverty determinants using a geospatial multi-criteria approach: Evidence from Jigawa, Nigeria. Geoj Environ Risk 18(1):61–79 Ifeanyi O (2024) Assessing natural disaster and sustainable infrastructure development: A case study of flood resilience and mitigation strategies in Maiduguri, Nigeria. Int J Environ Stud 81(2):201–218 Lamond J, Proverbs D, Hammond F, Oloke D (2019) Information for adaptation and response to flooding: Multi-stakeholder perspectives in Nigeria. J Flood Risk Manag 12(3):e12467. https://doi.org/10.1111/jfr3.12467 Nkechi FU, Emeka PC, Okoro J (2024) GIS-based multi-criteria analysis for mapping flood-prone areas in Oguta L.G.A, Imo State, Nigeria. Appl Geomatics 16(2):67–82 Nkwunonwo UC, Whitworth M, Baily B (2016) A review and critical analysis of the efforts towards urban flood risk management in the Lagos region of Nigeria. Nat Hazards Earth Syst Sci 16(2):349–362 Obeta MC, Ochege FU (2018) A comparative analysis of flooding in Warri and Port Harcourt urban areas of the Niger Delta region in southern Nigeria. GeoJournal 83(3):405–420 Obi RN, Okorie S, Chukwu M (2021) Indigenous flood control and management knowledge and flood disaster risk reduction in Nigeria’s coastal communities: An empirical analysis. Int J Disaster Risk Reduct 60:102276. https://doi.org/10.1016/j.ijdrr.2021.102276 Okunola A (2025) Exploring multi-level governance arrangements in disaster recovery: A study of Lagos. Nigeria Disaster Gov Rev 14(1):15–33 Oladokun VO, Proverbs DG (2016) Flood risk management in Nigeria: A review of the challenges and opportunities. Nat Hazards Rev 17(3):05016001 Otokiti AA, Adebayo RA, Aluko AO (2019) Geospatial mapping of flood risk in the coastal megacity of Nigeria. J Environ Manage 234:404–417 Popoola AA, Adeoti RO, Jimoh RA (2022) Indicators for disaster vulnerability to the overflowing of the Niger River in adjoining settlements in the confluence city of Lokoja. Nigeria Environ Earth Sci 81(9):366 Shuaibu A, Musa I, Nuhu S (2022) Flood risk assessment and mapping in the Hadejia River Basin, Nigeria, using a hydro-geomorphic approach and multi-criterion decision-making method. Hydrol Res 53(6):857–872 Sinthumule N, Mudau MJ (2019) Participatory approach to flood disaster management in Thohoyandou. Jàmbá: Journal of Disaster Risk Studies, 11(1), 1–8. https://doi.org/10.4102/jamba.v11i1.633 Sola AO, Eniola A, Bamgbose M (2020) Adaptation to climate change effects on water resources: Understanding institutional barriers in Nigeria. Climate Dev 12(4):295–307 Tariq MAUR, van de Giesen N, Ahmad S (2020) A critical review of flood risk management and the selection of suitable measures. Water 12(5):1420. https://doi.org/10.3390/w12051420 Vaughan E (2019) Ensuring impact: The role of civil society organizations in strengthening World Bank disaster risk financing. World Bank Policy Research Working Paper Series, (WPS8897) Wolf K, Dawson R, Mills J, Morley J (2022) Beyond conventional hazard maps: Assessing flood impacts using real-time data from smart device. https://doi.org/10.5281/zenodo.6410100 Supplementary Files Appendix.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 30 Jul, 2025 Reviewers invited by journal 30 Jul, 2025 Editor invited by journal 25 Jul, 2025 Editor assigned by journal 23 Jun, 2025 First submitted to journal 22 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6952249","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493257629,"identity":"f3bcd336-d1fa-44a7-b74b-5e7c7742f0a7","order_by":0,"name":"Ololade Sophiat Alaran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYDACdgglZ9/eAGYwNhDUwgyhjA14DpCoJXGDRAKRWvibmZ99+LnDhnG75OODn3kYbGQ3HCCgReIwm/HM3jNpzJaz05KleRjSjAlqYTjMYMzA23aYjeF2jhkzD8PhRIJa5A+zf2b823aYh+Hm+W9ALf8JazE4zGPMDLRFwuAGDxtQywHCWgwP8xQzy7alGUj2pBlLzjFINp5JSIvc8fbNjG/bbOr72Q8//PCmwk62j5AWdHeSpnwUjIJRMApGAQ4AANDDPm/9KE8VAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0005-0720-5249","institution":"East Carolina University","correspondingAuthor":true,"prefix":"","firstName":"Ololade","middleName":"Sophiat","lastName":"Alaran","suffix":""},{"id":493257630,"identity":"3974018b-f7d3-4abe-b5d3-7afaa8fbd3b5","order_by":1,"name":"Abdulahi Opejin","email":"","orcid":"","institution":"East Carolina University","correspondingAuthor":false,"prefix":"","firstName":"Abdulahi","middleName":"","lastName":"Opejin","suffix":""},{"id":493257631,"identity":"3f618434-1563-405b-b33c-34d95b6a9e11","order_by":2,"name":"Adewunmi Aderonke Oluwabunmi","email":"","orcid":"","institution":"Osun State University","correspondingAuthor":false,"prefix":"","firstName":"Adewunmi","middleName":"Aderonke","lastName":"Oluwabunmi","suffix":""},{"id":493257632,"identity":"4d357a3c-dd62-4407-b1d2-b1dff1adc813","order_by":3,"name":"Olamilekan Ademola Ademosu","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Olamilekan","middleName":"Ademola","lastName":"Ademosu","suffix":""},{"id":493257633,"identity":"59f36840-9a90-4df9-be77-19cc71dea3a7","order_by":4,"name":"Olusegun Ayokunle Osundina","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Olusegun","middleName":"Ayokunle","lastName":"Osundina","suffix":""}],"badges":[],"createdAt":"2025-06-23 03:14:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6952249/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6952249/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88270450,"identity":"dd302252-d97f-4961-85c4-fd97e711d036","added_by":"auto","created_at":"2025-08-04 17:00:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":548479,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6952249/v1/792abb7c-b207-4339-862d-3fb050ef125a.pdf"},{"id":88268999,"identity":"46b6b58d-aaeb-47b8-b87e-688d417b3ef1","added_by":"auto","created_at":"2025-08-04 16:52:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54491,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-6952249/v1/b427a2103ddf07b09a0bb748.docx"}],"financialInterests":"","formattedTitle":"Understanding the Challenges and Gaps in Flood Vulnerability Assessment and Mitigation Strategies in Nigeria","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eFloods are common hydrometeorological disasters with potential loss of lives, economic damage, and environmental degradation (Koko et al., 2021; Zhang et al., 2023). Natural disasters increased significantly between 1990 and 2020, with flooding as the most prominent disaster (Abbas et al., 2023; Rahman et al., 2023). Flooding represents one of the most devastating types of natural disasters, inflicting considerable damage to life, property, and the environment (Ibrahim et al., 2024). Floods happen when the rivers overflow their banks, caused by heavy rainfall, and the impacts intensify globally every year (Zhao \u0026amp; Zhang, 2013; Khan et al., 2016). According to the World Health Organization (WHO), flooding affected more than two billion people globally from 1998 to 2017, and those living in floodplains in poor housing or with limited knowledge about the dangers of flooding are especially vulnerable to disaster (World Health Organization, 2020). Cities in Egypt and Nigeria are purportedly more susceptible to flood risk in Africa, potentially due to the population increase in those nations (Nicholls et al., 2008).\u003c/p\u003e\u003cp\u003eEconomic development and population growth may have encouraged people to live along the river overflow, despite the adverse effects of flooding, especially in some Nigerian cities like Ibadan, Lagos, Kano, and Lokoja (Amangabara \u0026amp; Obenade, 2015; Ademola et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). More people in Nigeria have been impacted and displaced by flooding than by any other disaster, which disrupts sources of income and causes property loss and destruction. In 2012, the river Niger overflowed, causing floods in Lokoja, making it the most catastrophic natural disaster in Nigeria's history (Popoola et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Due to this disaster and its socio-economic consequences, an assessment and action plan for flood risk is needed. More flood events have highlighted the need for mapping flood-prone areas, which is an aspect of flood mitigation (Chakrabortty et al., 2018; Yu et al., 2023). Roy et al. (2020) Appropriately, recognized that concern for eco-friendly disaster management is growing in diverse fields, no less so than amongst global teams from various ventures, researchers, geographers, climatologists, and regional planners engaged to control and alleviate disaster impacts. Developing a model for measuring vulnerability presents essential opportunities to boost flood management methods (Ruidas et al., 2022). Protecting vulnerable areas from flood damage requires complete understanding of flood vulnerability for both risk assessments and mitigation plans and resilient strategies (Wang et al., 2022; Vignesh et al., 2021).\u003c/p\u003e\u003cp\u003eThe rise in flood occurrences has led to greater national awareness while speeding up flood vulnerability assessment and management endeavors across Nigeria. Multiple flood mitigation projects exist in Nigeria, yet the country faces shortcomings related to its missing integrated and sustainable methods for risk management (Onoh, 2023). Research demonstrates that Nigeria has insufficient methods for flood vulnerability assessment and implementing flood mitigation strategies (Echendu, 2020; Ndimele et al., 2024). Various obstacles limit the success of flood mitigation in Nigeria, including policies that lack stable direction, along with weak institutional structures and shortages in funding for studies and infrastructure expansions (Anifowose \u0026amp; Rollason, 2024). Neighborhoods across various locations experience significant flood risks from climate change, its effects, human-caused incidents of rapid population growth without planning, and inadequate urban development (Popoola, 2022; Wu, 2021).\u003c/p\u003e\u003cp\u003ePost-modern flood assessment techniques and mitigation strategies through GIS, hydrological modeling, and remote sensing technology give better chances to manage risk by improving flood prediction capabilities (Gyang et al., 2024). Nigeria faces significant barriers to implementing new flood risk management technologies due to difficulties with data accessibility, insufficient technical expertise, and poor inter-agency cooperation, and the solution requires multiple governmental organizations, community groups, and private investors to collaborate and meet these requirements (Okunola, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Okunola \u0026amp; Werners, 2024). Researchers acknowledge adaptive flood mitigation techniques as a vital method for improving the assessment and response to flood risks (Klijn et al., 2015; Qi et al., 2024). Since flood risks are constantly changing, adaptive flood mitigation design uses flexible response strategies that use real-time data collection, community involvement, and technological advancements to lessen the effects of floods. This approach will allow officials and local stakeholders to create resilient, and sustainable flood measures (Emami, 2020).\u003c/p\u003e\u003cp\u003eEmpirical studies have identified significant gaps in present flood risk assessment approaches. Research has shown that none of the current modeling approaches produces adequate results for tracking complete flood hydrodynamic conditions in every location. For instance, Nkwunonwo et al. (2020) observed that a perfect model or general approach that can capture all components of flood hydrodynamics in an ideal form within the research areas is still unachievable. The study by Malgwi et al. (2021) on the approach to rebuilding flood scenarios using field interviews and hydrodynamic modeling in Nigeria. The study emphasizes the prospect of using interview data for hydrodynamic modeling applications in data-scarce locales to enhance regional flood risk assessment. However, it has been noted that this modeling is not viable.\u003c/p\u003e\u003cp\u003eThe multiple modeling procedures used in Nigeria have failed to provide an all-encompassing remedy to forecast floods and determine their intensity levels. The advanced tools for flood risk management, including remote sensing methods and ensemble-based hydrological modeling with extreme value distribution analysis, are underutilized in developing countries. Therefore, progressive flood risk administration must efficiently integrate scientific research tools, including satellite systems, GIS mapping, social-ecological data, and machine learning capability, to assess or predict flood vulnerability. The lack of coordination among concerned stakeholders (e.g., communities, researchers, policymakers, and governmental agencies that handle flood risk management) impedes effective flood mitigation and adaptive management practices. To resolve these shortcomings, policies should create changes that enhance data transparency and establish active assistance between different professions while creating changes that enhance data transparency and establish synergistic assistance between different professions, stakeholders, communities, and government agencies while conducting studies to understand the effects of floods and flood mitigation procedures. Therefore, adaptive measures such as crowdsourcing and community engagement are employed by locals to gather flood data in collaboration with different stakeholders (Helmrich et al., 2021).\u003c/p\u003e\u003cp\u003eThis review evaluates primary barriers to flood data collection and accessibility in Nigeria and how cost-effective, community-driven, and crowdsourced methods can bridge this gap. It also addresses interdisciplinary collaboration and multi-source data integration to enhance flood risk assessment and mitigation strategies in urban and rural Nigerian communities.\u003c/p\u003e\u003cp\u003eGiven the study\u0026rsquo;s objectives, we reviewed challenges, innovations, and the role of the adaptive flood mitigation approach by identifying the primary obstacles that hinder the assessment and mitigation process for flooding in Nigeria. The research focused on analyzing essential issues related to flood data collection challenges, the potential benefits of community-based and crowdsourced approaches, and the value of interdisciplinary collaboration in risk evaluation and defense strategies, through which we answered the following research questions.\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eWhat are the primary barriers to flood data collection and accessibility in Nigeria, and how can cost-effective, community-driven, and/or crowdsourced methods bridge this gap?\u003c/span\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHow can interdisciplinary collaboration and multi-source data integration enhance flood risk assessment and mitigation strategies in urban and rural Nigerian communities?\u003c/span\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eUnderstanding these issues is crucial to developing effective policies and frameworks that reduce the socioeconomic and environmental impacts of floods in Nigeria.\u003c/span\u003e\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"2. Method","content":"\u003cp\u003eThis paper employed the systematic review approach to investigate barriers, innovations, and the role of adaptive flood mitigation strategies to aid the upgrading of flood vulnerability assessment and reduction in Nigeria. The methodological framework aimed to address the research questions through an interdisciplinary approach and by reviewing existing literature on flood risk management. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist serves as a basis for achieving a transparent and complete review procedure for this study.\u003c/p\u003e\u003cp\u003eResearch questions were selected to solve three main problems: data collection and accessibility issues, cost-effective community flood mitigation calculations, and collaboration between experts in flood risk assessments. The study extensively evaluates the Nigerian context of operational viability for different models and systems in the Nigerian context by examining hydrological modeling, remote sensing, GIS applications, and machine learning approaches. Stakeholder participation was focused on alongside collaboration between public service departments, researchers, and local communities to develop better flood prevention techniques.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Search Strategy\u003c/h2\u003e\u003cp\u003eThe research followed a systematic approach by searching databases to gather flood vulnerability assessment and mitigation literature from research platforms, including Web of Science, Scopus, Google Scholar, Science Direct, and SpringerLink. The research team utilized predetermined keywords to swiftly identify pertinent studies. This study examines key phrases such as \u0026ldquo;flood risk mitigation,\u0026rdquo; \u0026ldquo;flood vulnerability assessment,\u0026rdquo; \u0026ldquo;barriers to flood data collection,\u0026rdquo; \u0026ldquo;adaptive flood management,\u0026rdquo; \u0026ldquo;remote sensing and GIS for flood prediction,\u0026rdquo; \u0026ldquo;interdisciplinary collaboration in flood risk assessment,\u0026rdquo; and \u0026ldquo;community-driven flood mitigation strategies.\u0026rdquo; The reference lists of relevant studies are reviewed to identify additional literature that aligns with the research goals.\u003c/p\u003e\u003cp\u003eA systematic assessment method summarizes the studies obtained during the search process. The initial research screening occurs in two stages: studies without matches are rejected during title and abstract screening, and the remaining studies undergo full-text review for objective compliance. This method of selecting high-quality research ensures strong insights, which enhance strategies for flood mitigation.\u003c/p\u003e\u003cp\u003eScribbr and Mendeley were used to manage citations and references properly. This paper documented its literature selection process through a PRISMA flow diagram, providing greater transparency and reproducibility. The research employs this structured system to deliver valuable findings that enhance Nigeria's flood vulnerability assessments and mitigation efforts by integrating innovative methodologies and team collaboration.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003e2.2 Relevance screening and eligibility criteria\u003c/h3\u003e\n\u003cp\u003eIn order to ensure the inclusion of high-quality and relevant literature to the themes of this study, we adopted a structured relevance screening and eligibility evaluation adapted from the PRISMA guidelines and framework (see Appendix 1) established in Sayyed et al. 2014. The abstracts of the considered journals were downloaded and examined to determine the study's relevance to the secondary data used. We evaluated these studies for quality assessment to ensure they are pertinent to this research by skimming the full-text articles to assess their quality and eligibility. The studies included any journal articles, dissertations, or those released by authors from known, adequately referenced sources.\u003c/p\u003e\u003cp\u003eThe first level of screening assessed the abstracts and titles with a focus on the four thematic areas: Barriers to flood data collection and accessibility, Impact of cost-effective, community-driven, and crowdsourced methods on flood, Interdisciplinary Collaboration and Multi-Source Data Integration Enhance Flood Risk Assessment and Mitigation strategies with emphasis on studies in Nigeria. Studies that do not meet these criteria were excluded at this point.\u003c/p\u003e\u003cp\u003eDuring the second level screening, the full text was examined, journals between 2015 and 2025 were considered, while others were excluded. Other details, such as literature providing clear methodology, and the publications were limited to peer-reviewed journal articles, dissertations, and those from reputable sources, were used as selection criteria for inclusion and exclusion were established to ensure the validity of the data.\u003c/p\u003e\n\u003ch3\u003e2.3 Data Analysis\u003c/h3\u003e\n\u003cp\u003eFrom each paper, information was extracted on the following: (i) Barriers to flood data collection and accessibility in Nigeria; (ii) Impact of cost-effective, community-driven, and crowdsourced methods on flood; (iii) How interdisciplinary collaboration and multi-source data integration enhance flood risk assessment (iv) Mitigation strategies in urban and rural Nigerian communities. The study synthesized all extracted secondary data, provided a narrative summary of the findings, and highlighted the relationships between the studies.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003eThe results were gathered through a systematic review under the following section:\u003c/p\u003e\n\u003ch3\u003e3.1 Barriers to flood data collection and accessibility in Nigeria\u003c/h3\u003e\n\u003cp\u003eNations experience reduced flood management effectiveness because of barriers, including institutional challenges, technical limitations, and socioeconomic obstacles, that limit flood data collection and accessibility. Institutional challenges cause nations to struggle with flood response management because they lack appropriate hydrological data management, sufficient political will, and legal frameworks (Ekeu-Wei, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sola et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A national flood management policy would not improve the situation since different regions use separate approaches (Adelekan \u0026amp; Asiyanbi, 2016). Also, the slowness of governmental processes and weak governance delays data exchange between different agencies (Ekeu-Wei, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferent problems arise from the use of technology; these include the breakdown of hydrological infrastructures as a result of flooding and restricted access to advanced radar or sonar data acquisition systems, leading to a reduction in the performance of flood monitoring systems (Ekeu-Wei, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ebekozien et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nigeria's early warning system cannot monitor real-time flood situations (Atijosan et al., 2017); this lack of adequate assessment of floods is a result of using substandard remote sensing technology and inadequate meteorological station deployment (Nkwunonwo et al., 2020).\u003c/p\u003e\u003cp\u003eThree studies identified a lack of inter-agency collaboration, substandard and poor infrastructures as challenges to flood data collection (Ekeu-Wei, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lamond et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Oladokun \u0026amp; Proverbs, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In one study on the evaluation of Hydrological Data Collection Challenges and Flood Estimation Uncertainties in Nigeria, the author analyzed challenges of collecting flood data along the Ogun-Osun River using data through interviews from 5 collection officers. Ekeu-Wei (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) discovered that errors in flood frequency estimates result from improper maintenance of hydrological infrastructures. The lack of unification between research groups and government agencies on the standard of data collection results in forecasting and flood record challenges. The authors therefore recommended improved management, data collection methods, and utilization of flood data and infrastructures. The lack of coordination between government agencies, technical experts, and local stakeholders results in a lack of unified data collection methods, which in turn causes duplicate work and operational inefficiencies, hindering thorough flood risk assessments (Lamond et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, poor and substandard decisions made on flood preparation and emergency response by local authorities and stakeholders are due to inadequate capacity development (Adelekan \u0026amp; Asiyanbi, 2016). Agencies should enhance cooperative efforts amongst all stakeholders and implement a capacity-building program encouraging community-level flood observation for effective flood risk management (Nkwunonwo et al., 2020; Okunola, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSocial and economic circumstances also create significant barriers to accessing flood data. Flood-related information remains inaccessible to marginalized communities primarily because rural and low-income urban areas lack sufficient investment in resilience technologies and adequate infrastructure, and face financial limitations. (Ebekozien et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sola et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). People in numerous communities do not understand the flood warning networks available, which decreases their capacity to adopt protective actions (Adelekan \u0026amp; Asiyanbi, 2016). The unreliable power supply and inadequate internet connectivity prevent vulnerable populations from accessing and using thematic categorization to analyze the data collected on barriers to using flood resilience technologies.\u003c/p\u003e\u003cp\u003eThree studies have highlighted socioeconomic constraints like financial limitations as affecting flood data management (Adeoti, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ebekozien et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sola et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). One of the literatures identified other barriers groups, including socio-economic differences. Ebekozien et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) conducted virtual interviews with 30 stakeholders in the six geopolitical zones of Nigeria. The authors grouped the barriers into technical, socio-economic, institutional, financial, and infrastructure. They found out that infrastructure and funding are important to flood resilience.\u003c/p\u003e\u003cp\u003eNational-scale risk assessments heavily depend on meteorological data but lack sufficient detailed local-scale information. The potential solution of open-access remotely sensed data faces ongoing logistical and organizational obstacles when implementing this data into national flood management plans (Lamond et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ekeu-Wei \u0026amp; Blackburn, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Many flood control measures rely on generalized models rather than local flood patterns, as area-specific model calibration is often not readily available (Nkwunonwo et al., 2020). The combination of citizen science procedures and participatory methods creates a connection that combines local on-ground observations with the national flood management systems, according to Alemu et al. (2023).\u003c/p\u003e\u003cp\u003eResolving these barriers requires a multifaceted approach, which includes integrating national resources into flood management, infrastructure development alongside stakeholder communication enhancement, and technological and data management system funding expansion. Geospatial mapping is an essential method for detecting coastal flood hazards and assessing vulnerability distributions in urban areas of Lagos, particularly in Nigeria.\u003c/p\u003e\u003cp\u003eThe enhancement of flood management in Nigeria is possible through technological investments, like GIS, inter-institutional cooperation, and data sharing across all stakeholders to protect vulnerable communities from economic and social flood impacts. New investigations must merge indigenous knowledge techniques with present-day computational hydrologic models since their combination would boost flood prediction capacities and adaptation mechanisms (Nkwunonwo et al., 2020). Literature has supported using remote sensing and GIS to easily access real-time flood data and detect risks (Ekeu-wei \u0026amp; Blackburn, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Otokiti et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Popoola et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOtokiti et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) examined the geospatial mapping of flood risk in the coastal megacity of Lagos, Nigeria. They used data from the United States Geological Survey (USGS) archive to generate parameters on Digital Elevation Model (DEM), slope, drainage density, land cover type, curvature, Normalized Difference Water Index, and flow accumulation. The authors explained that remote sensing and GIS help identify flood risks through their discovery that using precise spatial data improves model accuracy for flood forecasting.\u003c/p\u003e\u003cp\u003ePopoola et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) demonstrated that GIS with multiple criteria helps discover hazardous locations and supports the formulation of flood management policies for urban districts bordering the Niger River. According to Gyang et al. (2024), flood predictions and response planning reach higher accuracy when organizations use advanced technologies such as Geographic Information Systems (GIS) and real-time flood mapping. The authors Ekeu-wei and Blackburn (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) discuss flood modelling and mapping in Nigeria under challenges like the unavailability of datasets due to financial, technical, and organizational challenges. They advocate for open-source remote sensing platforms to enhance ground-based information networks, transboundary flood analysis, and flood management in developing nations.\u003c/p\u003e\u003cp\u003eAccording to Adelekan and Asiyanbi (2016), developing a stronger flood management framework in Nigeria requires policy reforms to improve flood governance structures and data-sharing systems through investment in technology. The warning capabilities of flood-prone areas can be improved by installing geographic information systems technology, low-cost sensors to detect signals, and mobile tracking applications (Otokiti et al, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Impact of cost-effective, community-driven, and crowdsourced methods on flood\u003c/h2\u003e\u003cp\u003eFloods represent one of the most catastrophic natural events that result in massive human casualties, severe structural damage, and substantial economic losses, necessitating proper management (Helmrich et al., 2021; Wolf et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Traditional flood control systems do not work adequately for developing nations because these methods lack data-based characteristics, have limited budget reach, and have accessibility challenges. Developing low-cost, crowd-based solutions is a contemporary method that supports risk assessment activities, flood warning creation, and response implementation. Numerous experts agree that crowdsourcing enables the collection of valuable flood data (Helmrich et al., 2021; Songcho, 2023). Organizations that link crowd-based data systems with traditional processes can develop cost-effective solutions that deliver accurate flood spatial information and fast data analysis capacities (Helmrich et al., 2021; Songcho et al., 2023).\u003c/p\u003e\u003cp\u003eThe price of hydrological monitoring systems decreased through the use of economical digital equipment such as smartphones and social media platforms (Helmrich et al., 2021). Users gather flood information swiftly from Twitter, Facebook, and YouTube to enhance their assessment results during urban flood investigations (Re et al., 2022; Songchon et al., 2021). Social media platforms, webcams, and citizen science successfully generate proper data records (Helmrich et al., 2021). Residents collaborate with professionals under citizen science initiatives to gather flood data, which leads to successful engagement in flood monitoring (Assump\u0026ccedil;\u0026atilde;o et al., 2018).\u003c/p\u003e\u003cp\u003eElega et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) examined the Eco Nai\u0026thinsp;+\u0026thinsp;platform, consisting of a web and mobile app for accessing geo-journalism data. The authors used a multi-method approach to analyze platform data, interviews, and documents. They explored the importance of crowdsourcing and opined that the integration of geo-journalism with participatory mapping helps research findings establish effective networks between scientists, public servants, and at-risk residents. According to them, these initiatives let distant community members actively participate in developing measures to reduce disaster risks and improve flood preparedness while establishing personal ownership of the developed strategies.\u003c/p\u003e\u003cp\u003eHowever, with the numerous merits of crowdsourcing and community-based flood management systems, these systems may encounter various obstacles in data quality assessment, reliability, and testing accuracy. Due to its inherent nature, multiple verification mechanisms must be established to solve accuracy and consistency issues arising from unstructured crowdsourced information (Songchon et al., 2021; Helmrich et al., 2021). The combination of artificial intelligence and machine learning technology helps validate crowd-sourced flood data by conducting analyses of different information sources, satellite data, and hydrological inputs (Songchon et al., 2021). It is important to protect contributors' privacy; data must be balanced through proper ethical practices that maintain clear data usage transparency.\u003c/p\u003e\u003cp\u003eOkunola's study (2025) analyzed multilevel governance arrangements in disaster recovery in Lagos, Nigeria, using document reviews and semi-structured interviews. The study revealed poor collaboration between public departments caused difficulties during post-flood building reconstruction efforts, and top-down decision-making limited community participation. Therefore, recovery and resilience from a disaster such as a flood would succeed when multi-level governance is fully implemented. They recommended collaboration and coordination among stakeholders.\u003c/p\u003e\u003cp\u003eSome opportunities noted for crowd sourcing and citizen science are setting up models using land cover maps that can be validated with citizen science, validating data collected through social media, and using applications and websites developed that could be shared for public use. However, an additional layer of verification should be done to avoid duplication (Assump\u0026ccedil;\u0026atilde;o et al., 2018). The challenges of citizen science include using citizens as interpreters, improving estimation methods from pictures gathered, quantifying uncertainties, and harmonizing distributions and time frequencies from other data sources alongside citizen science.\u003c/p\u003e\u003cp\u003eModern advancements in remote sensing technology, IoT systems, and blockchain-based data verification protocols would also improve the efficiency of crowdsourced data. Water level sensors and IoT drone technology are used in community-based monitoring to collect real-time flood information. Implementing transparent and immutable blockchain record-keeping for crowdsourced flooding data increases system trust by eliminating ghost data issues (Ebekozien et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003e3.3 How Has Interdisciplinary Collaboration and Multi-Source Data Integration Enhanced Flood Risk Assessment?\u003c/h3\u003e\n\u003cp\u003eFlood disasters that have struck Nigeria require better assessment tools for identifying flood risks in the affected regions. This section reviews studies on how interdisciplinary collaboration and multi-source data integration can enhance flood risk assessment.\u003c/p\u003e\u003cp\u003eThe flood vulnerability mapping project involving Geographic Information System (GIS) and Remote Sensing and Fuzzy Logic System emerged from Atemoagbo et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) to assess flood risk areas in Suleja Local Government of Niger State North Central Nigeria. This research uses GIS and satellite datasets to create the Flood Zonation Mapping of Suleja. The identification of flood-prone areas utilizes rainfall data from the Nigeria Meteorological Agency (NiMET) together with Climate Hazards Group InfraRed Precipitation with Station Data (CHRPS), Global Satellite Mapping of Precipitation (GSMaP), slope elevation, and nearness to water bodies, along with land use and drainage density parameters. The geographic area faces various flood risks categorized into five zones based on the flood vulnerability map and these risk areas are organized as Very Low Risk (40.9%), Low Risk (18.9%), Medium Risk (27.6%), High Risk (7.1%), and Very High Risk (5.5%). According to this research, developing data-driven techniques enables improved flood risk evaluation for Nigeria. The study enables stakeholders and policymakers to make strategic decisions to protect infrastructure and communities from flooding risks.\u003c/p\u003e\u003cp\u003eA geospatial multi-criteria model for flood risk assessment was developed by Gambo et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) for Jigawa, Nigeria. The research incorporated data from multiple origins through assets provided by the National Population Commission (NPC) and National Bureau of Statistics (NBS) with land use and Digital Elevation Model (DEM) details obtained from Shuttle Radar Topography Mission (SRTM) and Sentinel-2 as well as precipitation data retrieved from Climate Hazards Group Infrared Precipitation with Station (CHIRPS). The integration of different data sources enables the development of a complete method to assess flood-risk prone areas across Jigawa. Flood danger areas in the region span 3\u0026ndash;13% of the total landscape, indicating severe flood danger. Flood disasters affect 40% of the population within this region. These research outcomes demonstrate that combining multi-source data collections with geospatial software enhances Nigerian disaster risk management systems.\u003c/p\u003e\u003cp\u003eAladejana and Ebijuoworih (2024) performed work that had similarities to Gambo et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) study. Researchers applied multiple methods to produce statewide flood risk mapping by investigating flood hazard and flood vulnerability factors. A flood risk assessment of Kogi State was carried out by integrating satellite remote sensing with GIS technology and field observations from original and existing data sources. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data underwent reprojecting and mosaicking functions, which produced Kogi State's digital elevation model (DEM) at a resolution of 30 m. The previous five years of weather data came from the Climate Hazards Group's Infrared Precipitation with Stations (CHIRPS). Information about road networks and health centers/hospitals\u0026rsquo; locations is derived from OpenStreetMap (OSM). Statistics on population density, female population data, literacy, and employment rate information were obtained from the National Bureau of Statistics (NBS) archives. The researchers applied FAHP with a Fuzzy approach to weight and rank drainage length and the other six flood hazard factors, along with seven vulnerability factors, to assess flooding contributions in Kogi State. Analysis of collected data resulted in the development of the Flood Hazard Index (FHI) and two other index models as part of risk zone assessment in Kogi State. This indicates that collaboration between multiple bodies enabled the development of the Flood Hazard Index (FHI) and two other index models as part of risk zone assessment in Kogi State.\u003c/p\u003e\u003cp\u003eA flood risk assessment and mapping developed by Shuaibu et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) assessed flood risk and vulnerability throughout the Hadejia River basin, Nigeria, to decrease flood vulnerability and risk in the region. Agency data used in the analysis includes 36 years of daily rainfall records obtained from NiMet stations and HJRBDA facilities in Nigeria. The National Population Commission (NPC) 's official website and the National Bureau of Statistics (NBS) provided population census data for the years 2006 and 2011 at the LGA level. Data analysis revealed high-to-very high flood risk in a basin section spanning 43.4% of the area where the downstream and central upstream locations exist. This suggests that collaboration between different agencies enhanced flood risk assessment in the areas.\u003c/p\u003e\u003cp\u003eNkechi et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) applied an integrated research method by uniting remote sensing technology with GIS techniques to control flooding effectively. The research objective was to identify flood-vulnerable zones located in Oguta LGA within Imo State. The research investigators implemented flood-prone zone mapping through their analysis of Landsat ETM\u0026thinsp;+\u0026thinsp;of 2023, along with Digital Elevation Model (DEM) Shuttle Radar Topographic Mission (SRTM) combined with geological data and meteorological data obtained from the USGS Earth Explorer website and Tropical Rainfall Measuring Mission satellite. All gathered data served to identify factors that lead to flooding incidents in the region studied. The assessment technique successfully determined areas at high risk of flooding in Oguta LGA of Imo State.\u003c/p\u003e\n\u003ch3\u003e3.4 Flood Mitigation Strategies in Urban and Rural Nigerian Communities\u003c/h3\u003e\n\u003cp\u003ePerception of risk is a significant factor in the preparation and mitigation of disasters. Over time, understanding the flood risk, likelihood, and possible related disasters has affected the selection of what flood risk management approach to choose and apply (Danladi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given the significant flood catastrophes in Nigeria during the last two decades, it is imperative to develop mitigation techniques. Flood mitigation strategies used in urban and rural Nigerian communities are categorized as structural and non-structural. Nkwunonwo et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) reported that Lagos's flood risk management strategies have been built on preventing and controlling floods, with primary measures being the development of structural methods. Flood mitigation strategies used in Ibadan are mainly structural and non-structural methods. Structural methods are channelization, dredging, and construction/widening of culverts and bridge throughways, and non-structural measures are improved waste management systems (Egbinola et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eChannelization of the Ogunpa River and the Awba Stream within the University of Ibadan helped stop flooding in Ibadan. In addition, dredging of all the streams within the city helped to mitigate flooding in the affected areas by the floods across all the 11 local government areas of Ibadan (Egbinola et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These strategies corroborate the Ifeanyi (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) investigation on flood resilience and mitigation strategies in Maiduguri, Nigeria. The highlight is effective flood mitigation strategies in Maiduguri, Nigeria, including upgrading drainage systems, enhancing early warning systems, and implementing green infrastructure.\u003c/p\u003e\u003cp\u003eIn research conducted by Obeta and Ochege (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the research compared flooding in Warri and Port Harcourt urban areas of the Niger Delta region in southern Nigeria. It was revealed that mitigation strategies used in the two states are urban drainage systems. However, this strategy is inadequate for protecting floodplain occupants in these areas. Barau and Wada (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) studied Do-It-Yourself flood risk adaptation strategies in the neighborhoods of Kano City, Nigeria. It was revealed that Do-It-Yourself (DIY) adaptation manifests in using sandbags, de-siltation of drainage, construction of fences, and drainage diversions, indicating that DIY is a practical mitigation approach for flood protection. Obi et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) examined indigenous flood control and management knowledge to identify its effectiveness in preventing flood disasters in Nigeria's coastal communities. The finding shows that indigenous flood control and management practices are the major flood risk reduction strategies in coastal communities in Nigeria.\u003c/p\u003e\u003cp\u003eThe federal, state, and local governments have contributed to flood mitigation plans in Nigeria. The Ministry of Environment, alongside additional relevant agencies, functions under the federal government to oversee flood governance activities, provide risk reduction initiatives, perform monitoring operations, and implement management strategies. The government worked toward three primary objectives: raising public awareness and demonstrating people's relationship to their environment, as well as establishing partnerships with environmental NGOs, MDAs, and the corporate sector (Danhassan et al., 2023). The Ministry of Environment exists in each of the 36 states, which handles flood regulation and environmental threats. The Ministry of Environment and several state regulatory bodies operate to manage and oversee flood regulation according to Danhassan et al. (2023). LASEPA and JISEPA, under Lagos State and Jigawa State, respectively, represent a few among the multiple environmental protection agencies (Adelekan, 2016; Tariq et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Numerous governments created state emergency management agencies (SEMA) to produce regulations while leading disaster response initiatives.\u003c/p\u003e\u003cp\u003eThe government at the local level maintains crucial responsibility to handle and prevent floods affecting rural areas. The government is responsible for disaster reactions, local disaster plan approval and rapid notification of local disaster information to the local flood disaster coordinator. Local flood disaster management groups should be established to assist governments in creating flood management plans while assessing and developing successful flood control practices (Sinthumule \u0026amp; Mudau, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Symmetrical flood operation management should incorporate mutual integration with all involved departments, including state disaster management and local flood disaster management (Vaughan \u0026amp; Hillier, 2019). The government needs to identify resources dedicated to flood mitigation, control the response operations through proper coordination, and maintain flood readiness for the community. Local governments within Nigeria face poor financial capacity when it comes to flood response due to the joint financial management system between states and local governments (Danhassan et al., 2023).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003cp\u003eThe literature reveals that multiple substantial barriers hinder flood data collection and accessibility in Nigeria, reducing flood management and mitigation effectiveness. Institutional challenges, technical limitations, and socioeconomic obstacles were found to be the main barriers to flood data collection and accessibility. The literature shows that a lack of data will affect the flood vulnerability assessment. All these barriers were highlighted in Ekeu-Wei (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); Sola et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); Ademola et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); and Adelekan and Asiyanbi (2016). The findings of this study align with the results of Waterman et al. (2021) on an investigation into barriers for sharing geospatial and resilience flood data in the UK. The study identified barriers and constraints when sharing data between organizations, which include technological, security, privacy, cultural, and commercial barriers across different use cases and data points.\u003c/p\u003e\u003cp\u003eThe study reviews the impact of cost-effective, community-driven, and crowdsourced methods on floods. It was determined that these methods are crucial for assessing flood vulnerability and developing mitigation strategies for flood protection in Nigeria. The study conforms with Degrossi (2014) on Flood Citizen Observatory: a crowdsourcing-based approach for flood risk management in Brazil. The result established that crowdsourcing is effective in obtaining useful and accurate information from the citizens, since citizens can easily provide information about the water level in the riverbed through the platform categories. In addition, the findings of this study affirm Danraka et al.'s (2024) investigation on community-based adaptation to floods in Malaysia. The study findings discovered that a wide range of community mobilization strategies exist, ranging from early warning systems and hazard forecasts to livelihood-based adaptation.\u003c/p\u003e\u003cp\u003eFurthermore, this study investigated how interdisciplinary collaboration and multi-source data integration enhance flood risk assessment through the literature. The study found that developing data-driven methods through interdisciplinary collaboration and multi-source data integration enhances Nigeria's flood risk assessment. This study's findings confirm the approach that Ibrahim et al. (2025) used on an integrated approach to flood risk assessment using multi-criteria decision analysis and geographic information systems in a flood-prone region of Pakistan. The study established that combining methods enabled the creation of accurate, data-driven flood risk maps. The hazard map of the area serves as a valuable tool for decision-making, resource allocation, and the development of flood risk management strategies.\u003c/p\u003e\u003cp\u003eThe study reviewed the flood mitigation strategies in urban and rural Nigerian communities. Significant flood mitigations in Nigeria's urban and rural communities include upgrading drainage systems and channeling rivers. Non-structural mitigation creates awareness by collaborating with environmental NGOs and MDAs. Compared to the flood mitigation method used in the US, research by Slotter et al. (2021) explored a range of mitigation strategies used in the US. Slotter et al. (2021) recorded over 25 policy interventions for flood risk reduction. These interventions are aggregated into five categories: insurance, land use planning, property acquisition (buyout program), financial assistance, and community engagement. The flood mitigation strategies used in Nigeria are quite different from those in the US. These strategies can be incorporated into the flood mitigation strategies used in Nigeria. Study of Davids et al. (2024) showed that Nature-based solutions (NBS) are another flood risk mitigation strategy that complements conventional \u0026lsquo;grey\u0026rsquo; infrastructure for stormwater management (dams and dikes) in reducing flood risks.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003cp\u003eThis study is delimited to enhancing flood vulnerability assessment and mitigation in Nigeria. The study reviewed challenges, innovations, and the role of the adaptive flood mitigation approach. The study employed a systematic review, which may not apply to other studies. The study reviewed studies that related to this study with significant findings. Based on the findings, the study concluded that institutional challenges, technical limitations, and socioeconomic obstacles were found to be the main barriers to flood data collection and accessibility; cost-effective, community-driven, and crowdsourced flood methods are crucial for assessing flood vulnerability and developing mitigation strategies for flood protection in Nigeria; the development of data-driven methods through interdisciplinary collaboration and multi-source data integration enhances Nigeria's flood risk assessment; and the significant flood mitigations used in urban and rural communities in Nigeria is structural (upgrading of drainage system and channeling of river) and non-structural mitigation (creating awareness).\u003c/p\u003e\u003cp\u003eBecause of the dearth of relevant literature, the study faced some challenges. The number of literature works selected in the first screening level was drastically reduced due to the unavailability of literature specific to Nigeria. Literature assessing barriers to flood data collection and crowd sourcing was rampant in countries like India and Pakistan, but was excluded due to our selection criteria. Other limitations include inconsistencies in the quality of some papers, reliance on English language databases, and restrictions due to a lack of access to full texts due to paywalls and institutional access.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDeclaration of interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships that may be considered potential competing interests:\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdelekan IO, Asiyanbi AP (2015) Flood risk perception in flood-affected communities in Lagos. Nigeria Environ Urbanization 27(2):1\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11069-015-1977-2\u003c/span\u003e\u003cspan address=\"10.1007/s11069-015-1977-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAdemola F, Ifeanyi AM, Richard U, Opejin, Abdulahi (2021) An Assessment of Flood Vulnerability Areas in ETI-OSA Local Government Area, Lagos State, Nigeria. 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World Bank Policy Research Working Paper Series, (WPS8897)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWolf K, Dawson R, Mills J, Morley J (2022) Beyond conventional hazard maps: Assessing flood impacts using real-time data from smart device. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.6410100\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.6410100\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Flooding, disaster management, flood data, resilience, environmental management, hydrologic models","lastPublishedDoi":"10.21203/rs.3.rs-6952249/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6952249/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFlooding is among the most destructive environmental hazards, leading to significant socioeconomic losses, infrastructural damage, and displacement. Floods are becoming more frequent and intense due to climate change, increased urbanization, inadequate drainage systems, and inadequate flood risk management measures. Many empirical studies utilized various advanced tools and methods to understand the extent of flood vulnerability in flood-prone areas. The combination of the datasets for flood mapping, the choice of methods, and the flood modeling approach varies from one researcher to another, and they often neglect social-ecological dynamics, which can influence flood risks. Additionally, flood vulnerability, risk preparedness, and adaptive management practices varied, sidelining the integration of community-based science and consideration for crucial stakeholders. However, this study seeks to assess flood vulnerability assessment and mitigation approaches to understand current modeling methods and existing adaptive methods in developing countries like Nigeria. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline summarized the literature from 28 journals. The study's findings revealed that environmental contexts are crucial in determining flood risk mapping parameters and suggest integrating those factors with social-ecological factors. The review also suggests addressing primary barriers to flood data collection and accessibility, using cost-effective, community-driven, or crowdsourced methods, and interdisciplinary collaboration to improve flood risk assessment and mitigation strategies in urban and rural Nigerian communities. The study proposes a multidisciplinary approach encompassing capacity-building programs, regulatory reforms, and technological advancements to enhance resilience against flooding.\u003c/p\u003e","manuscriptTitle":"Understanding the Challenges and Gaps in Flood Vulnerability Assessment and Mitigation Strategies in Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-04 16:47:33","doi":"10.21203/rs.3.rs-6952249/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-07-30T15:36:39+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-30T14:38:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Natural Hazards","date":"2025-07-25T09:38:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T09:11:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Natural Hazards","date":"2025-06-22T23:13:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"natural-hazards","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nhaz","sideBox":"Learn more about [Natural Hazards](https://www.springer.com/journal/11069)","snPcode":"11069","submissionUrl":"https://submission.nature.com/new-submission/11069/3","title":"Natural Hazards","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"69bd0751-48bf-4d5f-81e2-3cfd796f8a5f","owner":[],"postedDate":"August 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-04T10:17:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-04 16:47:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6952249","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6952249","identity":"rs-6952249","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}