The role of geology in flood risk assessments: a systematic literature review and a comprehensive bibliometric analysis

The role of geology in flood risk assessments: a systematic literature review and a comprehensive bibliometric analysis | 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 The role of geology in flood risk assessments: a systematic literature review and a comprehensive bibliometric analysis Cemre Erbil, Berna Ayat, Cengiz Zabcı This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5866366/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Floods have emerged as a critical global issue due to climate change, leading to increased research interest across various fields. However, the complex relationship between floods and geological factors remains insufficiently explored in the literature. This bibliometric analysis addresses this gap by examining the intellectual structure of research on floods and geology through a systematic review of 71 articles published between 1989 and 2024. The study reveals that environmental science dominates the field (44%), followed by earth and planetary sciences (16%), engineering (12%), and computer sciences (7%). Analysis of research terms demonstrates the field's breadth, with hydrology-related keywords comprising 58.4% of total terms, while flood-related and geology-related terms represent 21.9% and 19.7%, respectively. This study was conducted using data from the Scopus database, and co-word, co-citation, and co-author network analysis were performed through VOSviewer software. Key topics, influential publications, citation patterns, and international collaborations were identified and visualized using VOSviewer. The United States leads with 22 publications and 771 citations, followed by China with 15 publications and 117 citations. The analysis identified seven distinct international collaboration clusters, highlighting the global nature of flood research while also revealing geographical disparities in coverage. Notably, previous research demonstrates that integrating geological layers into hydrological models yields results closely matching real flood measurements, even in basins lacking measurement stations. This finding emphasizes the significance of understanding lithological characteristics for enhanced flood risk assessment. The analysis highlights an increasing application of advanced technologies, such as remote sensing, GIS, and machine learning, particularly in post-2020 studies, marking a shift toward data-driven approaches. flood geology bibliometric analysis literature review Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. INTRODUCTION Reviewing the literature is fundamental in academic research as it consolidates existing insights and evaluates the progression of a specific discipline (Cropanzano, 2009 ; Kunisch et al., 2018 ). Bibliometric analysis, which provides a systematic approach to examining academic publications, is instrumental in forecasting future trends and identifying new directions within fields. This analysis is widely applied to assess the current landscape, cutting-edge research, and evolving patterns across different domains (Wang and Li, 2016 ; Koskinen et al., 2008). The method relies on detailed measurement and examination of research outputs, utilizing indicators such as publication counts, impact factors (IF), and citation metrics (Garfield, 1986 ; Nieminen and Isohanni, 1998 ). Despite its importance, bibliometric research within specific areas like flood-related studies remains limited. Recent analyses have revealed that only a handful precisely five bibliometric evaluations exist that investigate the intersection of flood and hydrology research. Furthermore, there is currently no bibliometric analysis that specifically addresses the overlap between flood and geology research. Key examples of bibliometric work in hydrology and flood research include Salvati et al.'s ( 2024 ) systematic review of Muskingum flood routing techniques, which highlighted advancements in hydrological modelling. Lu et. al. ( 2023 ) explored urban flood vulnerability in Water (Switzerland) , detailing the development trends and knowledge domain in this area. Additionally, Almheiri et al. (2023) reviewed hydrological studies in the United Arab Emirates, providing insight into regional water challenges. Ahmed et. al. ( 2023 ) conducted a bibliometric overview of regional flood frequency analysis, while Rahman et al. (2022) analysed water research, development, and management in Bangladesh, contributing valuable perspectives on the country's water sector. Floods are one of the natural disasters with the most significant impacts on human life, the environment, and the economy. Geological structures, regional geomorphology, and climatic conditions are crucial factors determining the frequency and severity of floods (Yadav et al., 2007 ; Tetzlaff et al., 2007 ; Oudin et al., 2010 ). These events are typically precipitated by sudden downpours, riverine inundation, or heightened flows within and over differential lithological units, which have the capacity to severely impact agricultural lands, residential areas, and infrastructure, often resulting in significant human and economic losses. Geological formations play a decisive role in flood formation (Vannier et al., 2016 ). Permeable and porous geological materials, such as limestone, sandstone and/or conglomerates, facilitate rainwater infiltration, thereby reducing flood risk. Conversely, unplanned construction in floodplains can exacerbate this risk. A comprehensive approach that integrates natural and anthropogenic factors is essential for mitigating flood impacts. This should include flood risk assessments, protective measures, and resilience strategies, ultimately minimizing damage and enhancing community resilience. The interaction between floods and geological formations and structures is a significant focus of hydrological research, crucial for understanding how these features influence flood occurrence and severity. For instance, a study in the Cévennes-Vivarais region highlighted that the thickness and hydraulic conductivity of weathered rock strata significantly impact streamflow dynamics (Vannier et al., 2016 ). Another study emphasized the importance of geological features in hydrological modelling, introducing the Drainable Storage Capacity Index (DSCI) to better represent water transfer in regions with complex geological structures (Vannier et al., 2014 ). Additionally, the SIMPLEFLOOD model demonstrated the influence of geological characteristics on hydrological responses in the Ardèche basin (Adomovic et al., 2016). These studies collectively underscore the necessity of understanding geological factors in flood modelling to improve prediction accuracy and develop effective management strategies. This study evaluates previous research on the impact of geological factors on flood formation through a bibliometric approach, proposing an interdisciplinary methodology to better integrate geological features into hydrological modelling and flood risk management. Specifically, it aims to contribute to the development of methods with higher accuracy compared to traditional models by introducing data-driven approaches to comprehensively understand the contributions of complex geological structures to flood formation. 2. METHODS 2.1 Research questions This section describes the approach taken to review the literature concerning the effects of geology on floods. The goal of this review is to investigate trends in research findings related to how geology impacts floods over the past 20 years. The following research questions will be explored: 1. What is the intellectual framework of this research area, and how has it developed over time? 2. Which authors and publications have had the most significant impact? What is the nature of collaborative patterns in this field? 3. What are the existing research gaps and future challenges in studying the impact of geology on floods? 2.2 Data Acquisition A bibliometric analysis examining the relationship between floods and geology was conducted using the Elsevier’s SCOPUS database. General methodology is summarized in Fig. 1 . SCOPUS was chosen due to its extensive and multidisciplinary coverage, which offers superior journal coverage compared to other databases. The analyses were performed using VOSviewer software. The literature search was conducted using the keywords "flood", "hydrology", "geology" and "model." The data acquisition process involved a two-stage search protocol to comprehensively investigate the relationship between floods and geology. In the first stage, a broad search was conducted in the SCOPUS database using the specified keywords, targeting studies that included the terms "flood", "hydrology", "geology", and "model." In the second stage, the obtained data were analysed in detail using VOSviewer software. This software is an important tool for identifying relationships and trends within literature. The search method was designed to cover content areas such as titles, abstracts, and keywords. This approach was implemented to select the most comprehensive and relevant publications related to floods and geology. The obtained data provided a significant foundation for identifying and analysing the relevant literature. 3. RESULTS AND DISCUSSION 3.1 Trend of documents Figure 2 illustrates the progression of both publications and citations from 1989 to 2024. Between 1989 and 2015, the number of documents remained relatively low, but a steady increase can be seen. A notable peak in 2005 may be related to Hurricane Katrina, which led a widespread flood along the U.S. Gulf Coast. Furthermore, National Science Foundation’s (NSF) increased funding for flood-related research during this period may have contributed to the rise in publications, as evidenced by the fact that two out of four publications in 2005 received support from the NSF. The increase in publications and citations around 2016 can be attributed to the growing interest following major flooding events, such as intense monsoon rains in Asia and hurricanes in the Caribbean. These events likely triggered research on flood risk management and geological analysis, making 2016 a significant year for environmental disaster studies. During this time, there was a notable publication related to flooding in the Caribbean and two publications focusing on the severe floods in France in 2008. The research on the French floods was particularly influenced by initiatives such as the HyMeX (Hydrological Cycle in the Mediterranean Experiment) program and the FloodScale project. These projects aimed to enhance the understanding of flash flood processes through comprehensive observation and modelling efforts conducted during the Enhanced Observation Period (EOP) from 2012 to 2015. As a result, the publications released in 2016 reflect the culmination of years of data collection, analysis, and modelling. This body of research highlights the importance of understanding flood impacts and improving flood management strategies. The increase in scientific publications in 2021 can be seen as a reflection of the growing awareness and research demand regarding global issues such as climate change, urbanization, and natural disasters. Among the publications, themes such as flood risk assessment, hydrological modeling, multi-criteria decision analysis, and data mining are prominent, indicating a global search for solutions in disaster management and natural resource conservation. Despite the decline in publications in 2022, the increase in publication numbers in the following years indicates growing awareness and research interest in this field. 3.2 Citation analysis Figure 3 illustrates a citation network of publications within the research field. Each node on the map represents a publication, and the size of the node is proportional to the number of citations that publication has received. This map demonstrates the impact and reach of certain publications within the field. For instance, the publication by Bevis et al. ( 2005 ) is represented by one of the larger nodes, indicating its significant impact with a high number of citations. Similarly, other influential works, such as those by Kirkby (2002), Pham et al. ( 2021 ), and Nandi et al. ( 2016 ), are also prominently displayed. However, it should be noted that these nodes do not have any relationships with each other and do not cite one another. This indicates that while each publication is impactful on its own, there are no direct citation connections among them. The citation network provides a visual summary of key contributions in the field, with the most cited works standing out. This analysis helps in understanding the significance and academic influence of various studies, revealing how specific research has shaped and contributed to the overall discourse in the domain. The absence of connections among the 71 papers in the citation network indicates that the studies have largely been conducted independently or that there has been a lack of frequent cross-referencing in the literature. This suggests a lack of deep collaboration or information sharing within the research field, and that there may be no widely recognized common ground or reference work. The diversity of disciplines could also contribute to this lack of citation; studies from different fields may be examined in isolation from one another. 3.3 Co-authorship analysis and research collaboration Figure 4 illustrates the co-authorship network among researchers examining the intersection of floods and geology. This network visualizes the collaborations and interactions among researchers, revealing how they come together in specific thematic areas. Notably, each author appears only once in the network, indicating that no single author is involved in multiple publications. The clusters within the network represent groups of authors who frequently work together on particular topics. These groups focus on areas such as hydrological modelling, geological impact assessment, and flood risk management. The involvement of 331 authors from 35 different countries indicates that research in this field has an international dimension. This situation allows experts from different countries to share their knowledge and experiences, leading to the development of more effective solutions. The collaboration of authors from various disciplines emphasizes the importance of interdisciplinary approaches in addressing complex environmental issues. Such collaborations contribute to the development of more comprehensive and effective strategies for managing flood risk. Out of the 71 papers, 49 involve multiple authors, meaning that in the majority of these papers, more than one person has collaborated and contributed, rather than just a single author. This suggests that the research typically addresses topics that require teamwork, drawing on a broader range of knowledge and expertise. Additionally, such multi-author studies allow experts from different disciplines to come together, enabling more comprehensive and in-depth investigations. Table 1 presents the top ten most cited articles related to flood research, along with citation counts and keywords. The countries listed in the table represent the countries of the institutions where the studies were conducted. The countries where the research was dominantly applied are: Brazil, Spain, Vietnam, Jamaica, the United States, Poland, and Portugal. These countries represent the geographical areas where the studies were implemented. For example, these articles, covering a wide range from the Amazon River in Brazil to the Caribbean in Jamaica, provide a comprehensive understanding of flood hazards, hydraulic processes, and risk assessments. The most cited study about flood and mantle dynamics is by Bevis et al. ( 2005 ) (Table 1), which examines vertical ground movements in the Amazon River basin, highlighting the effects of elastic water oscillations and seasonal fluctuations. Furthermore, it assesses the relationship between these phenomena and structural geology and tectonic movements, making significant contributions to understanding the dynamics of water movements. By employing techniques such as time series analysis and hydrological modelling, it sheds light on other studies in the fields of geoscience and hydrology. In second place is the study by Kirkby et al. ( 2002 ), which has received 136 citations. This research focuses on slope hydrology and surface runoff in mountainous regions, emphasizing the importance of water connectivity across the landscape and investigating its role in flood formation. Insights like these are critical for developing environmental management strategies and mitigating the impacts of natural disasters. The study by Pham et al. ( 2021 ), which conducts flood risk assessments in Quang Nam, Vietnam, has garnered 123 citations. It presents innovative approaches to flood risk management and forecasting using machine learning and multi-criteria decision analysis. Other significant studies include the GIS-based risk assessment of geological hazards by Mejia-Navarro et al. (1994) and the research on channel deepening and river engineering by Wyzga (2001). These works provide essential data for developing more effective engineering solutions to reduce flood risks. Pelletier (2005) focuses on alluvial fan formation and surface geology, receiving 67 citations. This research offers important insights into soil and water management, contributing to the health of ecosystems. Turner-Gillespie et al. ( 2003 ) investigate the effects of urban development on flood responses, highlighting that urbanization can increase flood risks. Lastly, Hettiarachchi (2019) analyses the impacts of climate change on urban flooding, providing a valuable resource for developing strategies in this area. Table 1 also offers a detailed content analysis of these influential works. This table summarizes the main objectives, identified hazards, and key criteria used in each study. For instance, Bevis et al. ( 2005 ) employs geodesy and elastic oscillations within a tectonic context, utilizing time series analysis as a fundamental criterion. This approach prioritizes connectivity criteria, similar to the research by Kirkby et al. ( 2002 ) in studying slope hydrology. Pham et al. ( 2021 ) emphasizes methodological diversity by using machine learning and multi-criteria decision frameworks. Nandi et al. ( 2016 ) focus on flood hazard assessments using ArcGIS and statistical analysis, while Mejia-Navarro et al. (1994) examine geological hazards through risk assessments. Pelletier et al. ( 2005 ) investigate alluvial fan dynamics using numerical modelling and remote sensing techniques. In this context, Wyzga (2001) studies channel dynamics and sediment transport, providing the necessary information to mitigate flood risks. The interdisciplinary approach and methodological diversity found in flood research offer a deeper perspective on the topic. Techniques from fields such as geology, hydrology, remote sensing, and statistical analysis play a critical role in assessing and understanding flood risks. However, the limited collaboration networks among authors indicate a need for more partnerships to comprehensively examine the relationships between flooding and geology. In this regard, comparing geological and hydro-meteorological processes across different regions is vital for developing more effective flood management strategies. Although the study by Bevis et al. ( 2005 ) has accumulated the most citations overall, Table 2 highlights the top 10 most influential papers based on annual citation counts. This distinction arises because the Bevis et al. ( 2005 ) study has had more time to accumulate citations, whereas the influential papers are measured by their yearly citation rates. The works of Pham et al. ( 2021 ) and Nandi et al. ( 2016 ) are particularly noteworthy due to their use of innovative and powerful methods. Pham et al. ( 2021 ) utilized modern statistical and analytical techniques such as machine learning and multi-criteria decision analysis (MCDA) for flood risk assessment. These advanced methods allow for more accurate and effective risk predictions through the analysis of large datasets. MCDA, in particular, enables the integration of multiple factors and assesses their relative importance, contributing to a more comprehensive flood risk model. Similarly, Nandi et al. ( 2016 ) employed statistical and analytical techniques that extract meaningful insights from extensive datasets, enhancing the impact of his research. These modern approaches, unlike traditional methods, provide more precise and adaptable analyses, resulting in broader engagement and greater influence within the scientific community. Higher-impact journals generally offer greater visibility and credibility, leading to a higher number of citations. However, certain studies have managed to achieve significant citation counts even when published in journals with lower impact factors, owing to their innovative methodologies and valuable findings. This demonstrates that the quality and novelty of the research, rather than the journal's impact factor alone, play crucial roles in driving the scientific impact and recognition of a study. 3.4 Countries network map The countries network was created to examine the relationship between floods and geology reveals the global distribution of publications from different countries in this field and their collaboration patterns (Fig. 5 ). This network consists of seven different country clusters, each reflecting the level of collaboration in research conducted by those countries. In the visualization, the colours represent different years. Darker colours (e.g., blue shades) indicate that countries have been conducting studies in this field since earlier years, while lighter and brighter colours (e.g., yellow shades) represent more recent studies. For example, the United States and China have been active in this field for a long time and have extensive collaboration networks. Countries like Australia and Portugal have shown an increase in research in more recent years. Cluster 1 France, India, Iran, Norway, Singapore, Vietnam. The countries in this cluster have made significant contributions to research on floods and geology. France stands out with 9 publications and 140 citations. India also plays an important role with 3 publications and 145 citations. Iran has achieved 2 publications with 27 citations. Norway has 1 publication with 17 citations, while Singapore has 1 publication with 26 citations, and Vietnam has 3 publications with 166 citations. Cluster 2 Australia, Montenegro, Morocco, Portugal, Romania. Despite consisting of fewer countries, this cluster highlights Australia’s contributions with 4 publications and 73 citations. Montenegro and Morocco each have 1 publication with limited citations. Portugal has 2 publications with 60 citations, while Romania has only 1 publication with just 1 citation. Cluster 3 Canada, China, Thailand. In this cluster, Canada has 2 publications with 15 citations, while China continues to be a significant player with 15 publications and 117 citations. Thailand has only 1 publication with just 5 citations. Cluster 4 Brazil, Colombia, Germany, Sweden. Brazil and Colombia each have 4 publications with 181 and 2 citations, respectively. Germany has 5 publications with 42 citations, while Sweden has 2 publications with 43 citations. Cluster 5 Greece, Italy, Japan, Netherlands. Greece has 1 publication with 35 citations, while Italy has 3 publications with 43 citations. Japan has 1 publication with 7 citations, and the Netherlands has 2 publications with 7 citations. Cluster 6 Nepal, Poland, United Kingdom, United States. The United States emerges as the leading contributor in this cluster with 22 publications and 771 citations. The United Kingdom has 3 publications with 196 citations, while Poland has 4 publications with 100 citations. Nepal has 1 publication with 4 citations. Cluster 7 Jamaica, Trinidad and Tobago. Jamaica stands out with 1 publication and 118 citations. Trinidad and Tobago also have 1 publication with the same number of citations. These seven clusters illustrate how research on floods and geology is distributed on an international scale and highlight the importance of collaborations in this field. Collaborations between countries play a critical role in understanding the relationship between flood events and geological processes in different geographical regions and in developing effective management strategies. The United States stands out as the largest node on the map, demonstrating significant collaboration with institutions from 9 different countries. This indicates that the U.S.A holds a central position in international academic endeavours. China has a broad network of collaborations and establishes strong ties with countries across Asia, Europe, and the U.S.A.; the color of the lines signifies that these collaborations are relatively new, having been established at the beginning of 2020. European countries like France, Germany, and the United Kingdom engage in intense collaborations with one another and with the U.S. For instance, relationships between the U.S.A, Portugal, and Australia are more recent, represented by yellow tones, while collaborations with European countries are more established, depicted in blue tones. Smaller nodes like Vietnam, Jamaica, and Greece typically engage in collaboration with one country. Figure 6 shows the distribution of flood risk and geological studies across countries and highlights the countries with the most research. The USA, with 21 studies, is at the top of the list, indicating the intensity of flood risk assessment and geological studies related to flooding in the country. The USA stands out as a country with extensive flood research due to its large geographical area, diverse climate conditions, and advanced research infrastructure. China, with 14 studies, ranks second. China's large population and vast territory contribute to the widespread occurrence of flood and geological studies. The country's geographical diversity and frequent flooding events are significant factors driving the need for research in this field. France, with 5 studies, ranks third and is an important center for flood and geological research in Europe. Studies on flooding events and water management in France contribute to Europe's leadership in flood risk management and water governance. Brazil, with 4 studies, is prominent, as it has vast water systems like the Amazon basin, making it an important area for flood risk analysis and geological studies in flood-prone regions. Vietnam, with 3 studies, along with Poland and India, each with 2 studies, is also notable. These countries are significantly affected by floods, making local flood risk assessments and management an important research focus in these regions. Other countries with only one study include Bulgaria-Greece, Korea, Morocco, Iran, Indonesia, Nigeria, Italy, Laos, Australia, Colombia, Thailand, Portugal, Netherlands, Canada, Belgium, Germany, Turkey, the United Kingdom, and Jamaica. Research in these countries is generally more focused on local flood impacts and geological processes in smaller areas. Overall, studies conducted in larger countries like the USA and China are more intense and comprehensive due to their large geographical areas and significant data on flooding events. In other countries, the studies focus more on local flood risks and water management, addressing specific regional issues. 3.5 Co-word analysis and research evolution Co-word analysis results are shown in Fig. 7 . The relationship between flooding and geology holds significant importance in research on water management and flood control. Figure 6 clearly establishes a direct correlation between the keywords “flood” and “geology.” The keyword "hydrology" acts as a bridge between flood and geology, highlighting the impact of water management and geological structures on flood events. This demonstrates how hydrological processes interact with geological formations to increase flood risks. Figure 7 shows which topics have emerged over the years and how these topics have evolved over time. The colour scale indicates the time period during which each keyword was studied in greater depth. During the 1989–2015 period, represented by blue tones, older studies focused on themes such as “water resource management”, “hydrology”, and “natural disasters”. During this time, fundamental topics like "hydrology," "flood" and "geology" held a significant place in the literature. The terms related to Flood include approximately 30 terms, such as Flood, Flood forecasting, Flood hazard, Flood risk, Flood wave, Flood damage, Flood control, Flash floods, Flood frequency, Flood hydrology, Flood magnitude, Flood analysis, Flood prediction, Flooded area, Floodplain, Flood disaster prediction, Flash-floods, and Flood hazard map. These account for approximately 21.9% of the total terms. The terms related to Geology include approximately 27 terms, such as Geomorphology, Geology, Geological hazards, Geological structures, Surficial geology, Karst, Fracture flow, Geotechnologies, Fracture mapping, Permeability distribution, Groundwater flow, Rocks, Landslide-prone areas, Landslides, Geodesy, Structural geology, Crustal movement, Displacement, Groundwater, Groundwater-surface water interactions, and Geology-Ecology. These make up about 19.7% of the total terms. The terms related to Hydrology include approximately 80 terms, such as Hydrology, Hydrological model, Hydrological prediction model, Hydrological data, Hydrological simulation, Hydrological modelling, Hydrological evaluation, Hydrological forecasting, Rainfall-runoff simulation, Stormwater management, Urban stormwater management, Watershed hydrology, Low Impact Development (LID), Storm Water Management Model (SWMM), Hydrological models, Watershed management, Hydrological errors, Distributed hydrological modelling, Flash flood, Flood risk modelling, and Stormwater infrastructure. These represent about 58.4% of the total terms. From 1989 to 2025, research on environmental and hydrological topics has evolved significantly, with countries focusing on a wide range of issues based on their specific challenges and needs. In the early 2000s, countries like the United States, the United Kingdom, and Poland concentrated on foundational hydrological and geological research, while more recent studies from 2015 onward have seen a shift toward urban planning, sustainable water management, and the impacts of climate change. From 2005 to 2015, research represented by green tones concentrated on water management in cities and infrastructure development. Concepts such as "stormwater management," "urban hydrology," and "sponge city" became more prominent. These studies focused on improving stormwater management systems and reinforcing infrastructure to minimize flooding in urban areas. Urban hydrology became a central field of study, particularly to understand how urbanization affects the natural water cycle. The concept of "sponge cities" emerged as a sustainable solution to enhance the ability of urban environments to absorb rainwater, mitigating the effects of heavy rainfall and floods. During this period, studies on urban flooding, river basin management, and flood risk evaluation continued to be important topics, particularly in countries like the United States, Vietnam, and the United Kingdom. In the 2020–2025 period, represented by yellow tones, the research shifted towards urban planning, sustainable water management, and the effects of climate change. Concepts such as "climate change," "sponge city," "urban hydrology," and "flood control" became more prominent. Climate change, with its impact on the water cycle, flood risks, and water management strategies, has become one of the most significant research topics. Studies on flood control, particularly in urban areas, have risen, focusing on strategies to reduce the impacts of flooding in cities. The innovative "sponge city" concept has gained traction as part of sustainable urban management, providing new ways to manage stormwater and mitigate urban flooding. Research on urbanization and flood response, with a particular focus on managing the adverse effects of climate change, became central in countries like the United States, Australia, and Vietnam. Looking at the evolution of research topics, from 2010 to 2015, studies primarily focused on fundamental and broad topics aimed at understanding natural processes and the physical behaviour of hydrological systems. Between 2015 and 2020, research began to concentrate on urban challenges and solutions, particularly concerning water management in cities. By 2020, the increasing focus on the effects of climate change and the application of innovative urban solutions marked a significant shift in the literature, addressing the growing concerns of urban flooding, sustainability, and the resilience of water systems in the face of climate change. The collaboration of advanced technologies such as machine learning, GIS, and numerical modelling in flood risk assessment and water management has also been notable in the later years, especially in countries like Vietnam, Jamaica, and Australia. Overall, these periods reflect the growing importance of sustainable and resilient water management practices, particularly in urban settings, to address the ongoing challenges posed by climate change and urbanization. The integration of new technologies, such as machine learning and GIS, with traditional methods of flood risk assessment and management, continues to advance the field and contribute to global efforts in mitigating the impact of water-related disasters. The rise of innovative approaches in recent years is particularly linked to the need for sustainability and adaptation to climate change (such as machine learning, GIS, remote sensing, big data analytics, sponge city concept, and sustainable urban water management solutions). These approaches are becoming crucial in developing effective strategies for flood risk management, urban water management, and climate change adaptation, helping cities become more resilient to the impacts of flooding and environmental changes. Researchers have increasingly turned toward producing more effective solutions for stormwater management, flood control, and urban infrastructure development. These types of solutions aimed at improving water management in cities are receiving great attention in the literature and are likely to shape future studies. This analysis demonstrates that topics like sustainable water management and urban infrastructure have gained importance over time, and innovative approaches have increasingly found their place in research. The relationship between flooding and geology plays a crucial role in water management and flood control research, with geological factors significantly impacting flood risks. Research indicates that with climate change and the increasing frequency of flood events, geological structures are being studied more intensively, and new techniques and strategies are being developed in this area. The map visually represents the intellectual structure of this research field and how it has evolved over time. 4. REVIEW OF LITERATURE AND DEFINITION OF RESEARCH GAPS Floods and their interaction with geological factors have been the focus of various interdisciplinary studies, highlighting significant advancements while uncovering areas that remain underexplored. Existing research underscores the role of geological structures, such as lithology and deformation-related structures, in shaping hydrological processes and flood risks. Studies like those by Bevis et al. and Pham et al. emphasize the importance of integrating geological data into hydrological models to improve flood risk assessments. Recent advancements in geographic information system (GIS), remote sensing, and machine learning technologies have enhanced conventional methodologies, facilitating more precise predictions and comprehensive risk management strategies. Concurrently, innovative urban planning concepts, such as sponge cities, have emerged as pioneering solutions for mitigating the deleterious effects of urban flooding by augmenting water absorption and diminishing runoff. Despite these advancements, notable gaps persist in the literature. One major issue is the limited integration of complex geological features in current hydrological models, which often fail to account for lithological diversity and the unique characteristics of geological structures. The representation of regional morphogenesis is another concern, as research is heavily concentrated in regions like the United States, China, and France, leaving areas in the Global South significantly underrepresented. This imbalance restricts the applicability of findings to diverse geological and climatic contexts. Furthermore, the concentration of studies on floods and geological factors across different disciplines highlights the interdisciplinary nature of this field. Various areas, such as environmental science (44%), earth and planetary sciences (16%), engineering (12%), and social science (6%), contribute to understanding and addressing this complex issue (Fig. 8 ). However, despite this diversity, greater integration and collaboration in interdisciplinary studies could lead to more comprehensive solutions for mitigating flood risks. The challenge of data accessibility also hinders progress, particularly in underrepresented regions where high-quality and region-specific data are scarce. While advanced technologies have been applied in some studies, the use of historical geological data to predict long-term flood trends has been limited. Additionally, as climate change continues to influence flood frequency and intensity, there is an insufficient focus on adaptive strategies tailored to specific geological conditions. Understanding the dynamic interaction between climate-induced changes and geological factors is critical for developing effective mitigation and adaptation measures. Addressing these gaps requires a multi-faceted approach. Future research should prioritize the integration of geological insights into hydrological modelling, expanding the geographic focus to include underrepresented regions and fostering greater interdisciplinary collaboration. Leveraging advanced technologies like AI, big data analytics, and geological records, such as the spatial distribution of lithological formations and structures, can enhance predictive accuracy and provide localized solutions. Emphasis should also be placed on designing climate-resilient strategies that address both immediate flood risks and long-term adaptation needs. By bridging these gaps, researchers can contribute to the development of sustainable and globally applicable flood risk management strategies, fostering resilience against the growing challenges posed by climate change and urbanization. 5. CONCLUSIONS The bibliometric analysis of the studies on the relationship between floods and geology provides important insights into the global distribution of research, influential publications, and the evolution of research themes. This analysis highlights the interdisciplinary nature of the field, where hydrology, geology, urban planning, and climate change intersect to provide a comprehensive understanding of flood risks and mitigation strategies. The importance of the GIS is increasing on a daily basis, as it is utilized in the assessment of flood risk based on hydrological modelling and geological studies. For example, Bevis et al. ( 2005 ) focuses on geophysical and hydrological processes in the Amazon River basin, emphasizing the importance of integrating geological structures and hydrological systems to understand the complex dynamics of flood events. Similarly, Pham et al. ( 2021 ) and Nandi et al. ( 2016 ) highlight the importance of modern, data-driven techniques for flood risk assessment, particularly in vulnerable regions. These studies demonstrate how traditional methods are being enriched with technology-assisted tools. The global collaboration network in flood and geology research shows how international partnerships have developed across various geographical regions. Countries such as the United States, China, and France play significant roles, while underrepresented regions like Nepal, Vietnam, and Jamaica also make important contributions. This international collaboration is crucial for understanding flood risks in diverse geological environments and for developing global solutions for flood mitigation. The evolution of the research field shows a shift from traditional hydrological studies to more applied areas, particularly in urban environments. Initially, studies focused on fundamental hydrological processes, but over time, urban water management, infrastructure development, and climate change adaptation have become more prominent. Concepts like "sponge cities" reflect this shift toward infrastructure-based, sustainable solutions for urban resilience in the face of extreme weather events. In recent years, with the increasing impact of climate change, research has shifted toward long-term, climate-resilient strategies for managing flood risks. While there has been progress in flood and geology research, several challenges remain. There is a need for greater interdisciplinary collaboration among geologists, hydrologists, urban planners, and policymakers. As research increasingly focuses on urban resilience and climate adaptation, managing flood risks in diverse regions with unique geological structures requires innovative, context-specific solutions. Additionally, the uneven distribution of research efforts, with underrepresentation in regions like the Global South, highlights the need for more international collaboration to create globally applicable solutions. In conclusion, the relationship between floods and geology is a critical area of study that plays a vital role in water management, urban resilience, and climate adaptation. As the field continues to evolve, fostering interdisciplinary collaboration, expanding research in underrepresented regions, and focusing on sustainable, long-term strategies for flood risk management are essential. The evolution of research over the past decade shows that addressing the complex interplay between geological structures and flood events is key to building resilient communities in the face of growing environmental challenges. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interest The authors have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Cemre Erbil. Berna Ayat and Cengiz Zabcı contributed to the conceptual development and writing of the document. The first draft of the manuscript was written by Cemre Erbil and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. References Adamovic, M., Branger, F., Braud, I., & Kralisch, S. (2016). Development of a data-driven semi-distributed hydrological model for regional scale catchments prone to Mediterranean flash floods. Journal of Hydrology, 541 (Part A), 173–189. https://doi.org/10.1016/j.jhydrol.2016.03.032 Ahmed, A., Yildirim, G., Haddad, K., & Rahman, A. (2023). Regional Flood Frequency Analysis: A Bibliometric Overview. Water, 15 (9), 1658. https://doi.org/10.3390/w15091658 Bevis, M., Alsdorf, D., Kendrick, E., Fortes, P., Forsberg, B., Smalley, B., Becker, J., & Fortes, L. (2005). Seasonal fluctuations in the mass of the Amazon River system and Earth's elastic response. Geophysical Research Letters, 32 (1). https://doi.org/10.1029/2005GL023491 Brandão, C., Cameira, M. R., Valente, F., Cruz de Carvalho, R., & Paço, T. A. (2017). Wet season hydrological performance of green roofs using native species under Mediterranean climate. Ecological Engineering, 102 , 596–611. https://doi.org/10.1016/j.ecoleng.2017.02.025 Cropanzano, R. (2009). Writing Nonempirical Articles for Journal of Management: General Thoughts and Suggestions. Journal of Management, 35 (6), 1304–1311. https://doi.org/10.1177/0149206309344118 Garfield, E. (1986). Which medical journals have the greatest impact? Annals of Internal Medicine, 105 , 313–320. Hettiarachchi, S., Wasko, C., & Sharma, A. (2019). Can antecedent moisture conditions modulate the increase in flood risk due to climate change in urban catchments? Journal of Hydrology, 571 , 11–20. https://doi.org/10.1016/j.jhydrol.2019.01.039 Kirkby, M., Bracken, L., & Reaney, S. (2002). The influence of land use, soils, and topography on the delivery of hillslope runoff to channels in SE Spain. Earth Surface Processes and Landforms, 27 (13), 1459–1473. https://doi.org/10.1002/esp.441 Kosinen, J., Isohanni, M., Paajala, H., Jääskeläinen, E., Nieminen, P., Koponen, H., Tienari, P., & Miettunen, J. (2008). How to use bibliometric methods in evaluation of scientific research? An example from Finnish schizophrenia research. Nordic Journal of Psychiatry, 62 (2), 136–143. https://doi.org/10.1080/08039480801961667 Kunisch, S., Menz, M., Bartunek, J. M., Cardinal, L. B., & Denyer, D. (2018). Feature Topic at Organizational Research Methods: How to Conduct Rigorous and Impactful Literature Reviews? Organizational Research Methods, 21 (3), 519–523. https://doi.org/10.1177/1094428118770750 Lu, S., Huang, J., & Wu, J. (2023). Knowledge Domain and Development Trend of Urban Flood Vulnerability Research: A Bibliometric Analysis. Water, 15 (10), 1865. https://doi.org/10.3390/w15101865 Mejía-Navarro, M., Wohl, E. E., & Oaks, S. D. (1994). Geological hazards, vulnerability, and risk assessment using GIS: model for Glenwood Springs, Colorado. In M. Morisawa (Ed.), Geomorphology and Natural Hazards (pp. 331–354). Elsevier. https://doi.org/10.1016/B978-0-444-82012-9.50025-6 Nandi, A., Mandal, A., Wilson, M., et al. (2016). Flood hazard mapping in Jamaica using principal component analysis and logistic regression. Environmental Earth Sciences, 75 , 465. https://doi.org/10.1007/s12665-016-5323-0 Nieminen, P., & Isohanni, M. (1998). Bibliometric analysis on Finnish psychiatric research in years 1994–1997. Sosiaalilääkäri Aikakauslehti, 35 , 152–162. Oudin, L., Kay, A., Andréassian, V., & Perrin, C. (2010). Are seemingly physically similar catchments truly hydrologically similar? Water Resources Research, 46 (11). https://doi.org/10.1029/2009WR008887 Pelletier, J. D., Mayer, L., Pearthree, P. A., House, P. K., Demsey, K. A., Klawon, J. E., & Vincent, K. R. (2005). An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing. GSA Bulletin, 117 (9–10), 1167–1180. https://doi.org/10.1130/B25544.1 Pham, B. T., Luu, C., Phong, T. V., Nguyen, H. D., Le, H. V., Tran, T. Q., Ta, H. T., & Prakash, I. (2021). Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam. Journal of Hydrology, 592 , 125815. https://doi.org/10.1016/j.jhydrol.2020.125815 Salvati, A., Moghaddam Nia, A., Salajegheh, A., Shirzadi, A., Shahabi, H., Ahmadisharaf, E., Han, D., & Clague, J. J. (2024). A Systematic Review of Muskingum Flood Routing Techniques. Hydrological Sciences Journal, 69 , 810–831. https://doi.org/10.1080/02626667.2024.00000 Tetzlaff, D., Waldron, S., Malcolm, I., Bacon, P., Dunn, S., Lilly, A., & Youngson, A. (2007). Conceptualization of runoff processes using a geographical information system and tracers in a nested mesoscale catchment. Hydrological Processes, 21 (10), 1221–1239. https://doi.org/10.1002/hyp.6309 Turner-Gillespie, D. F., Smith, J. A., & Bates, P. D. (2003). Attenuating reaches and the regional flood response of an urbanizing drainage basin. Advances in Water Resources, 26 (6), 673–684. https://doi.org/10.1016/S0309-1708(03)00017-4 Vannier, O., Anquetin, S., & Braud, I. (2016). Investigating the role of geology in the hydrological response of Mediterranean catchments prone to flash-floods: Regional modelling study and process understanding. Journal of Hydrology, 541 (Part A), 158–172. https://doi.org/10.1016/j.jhydrol.2016.04.001 Vannier, O., Braud, I., & Anquetin, S. (2014). Regional estimation of catchment-scale soil properties by means of streamflow recession analysis for use in distributed hydrological models. Hydrological Processes, 28 (26), 6276–6291. https://doi.org/10.1002/hyp.10101 Wang, Q., & Li, R. (2016). Natural gas from shale formation: A research profile. Renewable and Sustainable Energy Reviews, 57 , 1–6. https://doi.org/10.1016/j.rser.2015.12.093 Wyżga, B. (2001). A geomorphologist's criticism of the engineering approach to channelization of gravel-bed rivers: Case study of the Raba River, Polish Carpathians. Environmental Management, 28 , 27–41. https://doi.org/10.1007/s0026702454 Yadav, M., Wagener, T., & Gupta, H. (2007). Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins. Advances in Water Resources, 30 (8), 1756–1774. https://doi.org/10.1016/j.advwatres.2007.01.005 Tables Table 1. Content analysis of top influential papers. Paper Citation Keyword Country Objective Hazard Method Bevis et al. (2005) 154 Amazon River; South America; Western Hemisphere; World; Floods; Geodesy; Geophysics; Hydrology; Mathematical models; Rivers; Structural geology; Time series analysis; crustal movement; displacement; river basin; vertical movement; water; Crustal oscillation; Elastic oscillations; Hydrological model; Seasonal fluctuations; Vertical displacement; Tectonics USA Flood analysis Ground deformation; Infrastructure damage risk; Hydraulic loading Time series analysis; Hydrological model Kirkby et al. (2002) 136 Connectivity; Hill slope hydrology; Runoff United Kingdom Runoff connectivity Increased erosion; Flood risk Runoff measurement; Hydrological modeling Pham et al. (2021) 123 Flood risk assessment; Machine learning; multi-criteria decision analysis; Quang Nam, Vietnam Vietnam Risk assessment Flood risk Machine learning, multi-criteria decision Nandi et al. (2016) 118 ArcGIS; Caribbean; Flood hazard evaluation; Statistical analysis; Validation USA,Jamaica Hazard evaluation Flood hazard ArcGIS; Statistical analysis Mejia-Navarro et al. (1994) 94 Geological hazards; Vulnerability; Risk assessment; GIS USA Vulnerability study Geological hazards GIS; Risk assessment Pelletier et al. (2005) 67 Alluvial fan, Flood hazard, Numerical modeling, Remote sensing, Surficial geology USA Modeling flood hazard Flood risk Numerical modeling; Remote sensing Wyzga(2001) 61 Channel incision; Channelization; Environmental change; Gravel-bed rivers; River engineering; Sediment transport Poland Channel dynamics Channel incision; Sediment imbalance; Channel instability Bedload transport calculations; Sedimentological studies; Brandao et al. (2017) 59 Mosses; Plant selection; Sustainability; Urban hydrology; Urban stormwater management Portual Sustainability Flooding; Drainage system overload Plant selection; Urban hydrology Turner-Gillespie at al. (2003) 50 Attenuating reach; Flood response; Urbanization USA, United Kingdom Urbanization impact Flood risk Attenuating reach; Flood response Hettiarachchi et al. (2019) 44 Antecedent moisture conditions; Climate change; Continuous simulation; Urban flooding Australia Climate change effects Urban flooding Continuous simulation; Antecedent moisture Table 2. The top 10 most impactful articles Paper Citations per Year Sources Impact Factor Pham et al. (2021) 41.00 Journal of Hydrology 6.37 Nandi et al. (2016) 14.75 Earth Surface Processes and Landforms 2.8 Hettiarachchi et al. (2019) 8.80 Journal of Hydrology 6.37 Brandao et al. (2017) 8.43 Ecological Engineering 3.9 Bevis et al. (2005) 8.11 Geophysical Research Letters 4.55 Kirkby et al. (2002) 6.18 Earth Surface Processes and Landforms 2.8 Pelletier et al. (2005) 3.53 Bulletin of the Geological Society of America 4.27 Mejia-Navarro et al. (1994) 3.13 Geomorphology 3.1 Wyzga (2001) 2.65 Environmental Management 2.7 Turner-Gillespie at al. (2003) 2.38 Advances in Water Resources 4.26 Additional Declarations No competing interests reported. Supplementary Files ErbiletalNaturalHazardsAppendix.docx Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5866366","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":405616294,"identity":"90522ff6-3493-4c12-a5d9-541b12270787","order_by":0,"name":"Cemre Erbil","email":"","orcid":"","institution":"Istanbul Technical University","correspondingAuthor":false,"prefix":"","firstName":"Cemre","middleName":"","lastName":"Erbil","suffix":""},{"id":405616295,"identity":"6ba23176-5260-42b6-a064-85a48db01cc0","order_by":1,"name":"Berna Ayat","email":"","orcid":"","institution":"Yıldız Technical University","correspondingAuthor":false,"prefix":"","firstName":"Berna","middleName":"","lastName":"Ayat","suffix":""},{"id":405616296,"identity":"c677dabe-5810-4191-9ba7-aae659992291","order_by":2,"name":"Cengiz Zabcı","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYFACHgaGhAoJMFOCBC1nJCSgWgyI1MLYxkCCFvn2swc/PJxnUWdwgPngbR6GP/kEtTD25CVLJG6TkDA4wJZszcNgYNlASAszQ44ZA0QLj5k0UAthl7HxvwFqmQPSwv+NOC08EiBbGsC2sBGnRULiXbJEwjEJyZmH2Ywt5xgYE9Yi35978OOPmjp+vuPND2+8qZAjKmKggBlEkKJhFIyCUTAKRgFuAABJ0y3zkgdMEwAAAABJRU5ErkJggg==","orcid":"","institution":"Istanbul Technical University","correspondingAuthor":true,"prefix":"","firstName":"Cengiz","middleName":"","lastName":"Zabcı","suffix":""}],"badges":[],"createdAt":"2025-01-20 13:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5866366/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5866366/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74650905,"identity":"1f432b26-91cf-4a14-a38c-5102731a75b4","added_by":"auto","created_at":"2025-01-24 10:44:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":220271,"visible":true,"origin":"","legend":"\u003cp\u003eResearch Methodology Framework.\u003c/p\u003e","description":"","filename":"Fig01.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/b41c87c76f83a8f41cd87271.jpg"},{"id":74650904,"identity":"db6fa1aa-5f28-4bae-b50e-93d88dac4d63","added_by":"auto","created_at":"2025-01-24 10:44:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":336531,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of Documents and Citations Over Time\u003c/p\u003e","description":"","filename":"Fig02.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/89579a4afdd9ad973f53ed5a.jpg"},{"id":74651227,"identity":"a323c456-5663-4b88-a9a4-bf6945d0b235","added_by":"auto","created_at":"2025-01-24 10:52:39","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":140581,"visible":true,"origin":"","legend":"\u003cp\u003eCitation network\u003c/p\u003e","description":"","filename":"Fig03.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/7cb656f49cae87ca8d3f6a79.jpg"},{"id":74650906,"identity":"69f084df-9263-4dc6-8d7d-23f7cb314839","added_by":"auto","created_at":"2025-01-24 10:44:39","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":132524,"visible":true,"origin":"","legend":"\u003cp\u003eCo-author network. The increasing number of circles are proportional to the number of cooperation.\u003c/p\u003e","description":"","filename":"Fig04.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/c108364e9d1a06cb8bb5b518.jpg"},{"id":74650913,"identity":"f4865bd5-ac33-4f79-8834-e936baf6e7e0","added_by":"auto","created_at":"2025-01-24 10:44:39","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":97865,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of countries co-authorship. The size of circles is proportional to the number of incorporations between countries.\u003c/p\u003e","description":"","filename":"Fig05.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/4a8417490450caaa5f0aaee6.jpg"},{"id":74651232,"identity":"18253ef6-88e0-44ff-8812-f6279fedceea","added_by":"auto","created_at":"2025-01-24 10:52:39","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":27916,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of flood risk and geological studies by country\u003c/p\u003e","description":"","filename":"Fig06.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/940be248597c3715cf8311ec.jpg"},{"id":74650939,"identity":"25412111-5872-4258-813d-6e8b16a7009e","added_by":"auto","created_at":"2025-01-24 10:44:40","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":72390,"visible":true,"origin":"","legend":"\u003cp\u003eKeyword evolution overtime.\u003c/p\u003e","description":"","filename":"Fig07.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/f939b4c3e2ad85871812362b.jpg"},{"id":74652462,"identity":"a5bd39fc-66cc-4bf3-aa34-6e57f20d5585","added_by":"auto","created_at":"2025-01-24 11:00:39","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":206559,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of research disciplines in studies examining the relationship between floods and geological factors\u003c/p\u003e","description":"","filename":"Fig08.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/f661780fb73875343f064826.jpg"},{"id":79005840,"identity":"dd58745b-0cfe-4763-94d6-37bf4ec440c5","added_by":"auto","created_at":"2025-03-22 08:01:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1930346,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/2f647a44-5646-4a3f-9a9e-222c0bea0f99.pdf"},{"id":74650942,"identity":"aaa37064-7c7f-427f-8b6b-dd60dea1732c","added_by":"auto","created_at":"2025-01-24 10:44:41","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21244,"visible":true,"origin":"","legend":"","description":"","filename":"ErbiletalNaturalHazardsAppendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-5866366/v1/a35386ead1949156c6e131b9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The role of geology in flood risk assessments: a systematic literature review and a comprehensive bibliometric analysis","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eReviewing the literature is fundamental in academic research as it consolidates existing insights and evaluates the progression of a specific discipline (Cropanzano, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Kunisch et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Bibliometric analysis, which provides a systematic approach to examining academic publications, is instrumental in forecasting future trends and identifying new directions within fields. This analysis is widely applied to assess the current landscape, cutting-edge research, and evolving patterns across different domains (Wang and Li, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Koskinen et al., 2008). The method relies on detailed measurement and examination of research outputs, utilizing indicators such as publication counts, impact factors (IF), and citation metrics (Garfield, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Nieminen and Isohanni, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite its importance, bibliometric research within specific areas like flood-related studies remains limited. Recent analyses have revealed that only a handful precisely five bibliometric evaluations exist that investigate the intersection of flood and hydrology research. Furthermore, there is currently no bibliometric analysis that specifically addresses the overlap between flood and geology research.\u003c/p\u003e \u003cp\u003eKey examples of bibliometric work in hydrology and flood research include Salvati et al.'s (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) systematic review of Muskingum flood routing techniques, which highlighted advancements in hydrological modelling. Lu et. al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) explored urban flood vulnerability in \u003cem\u003eWater (Switzerland)\u003c/em\u003e, detailing the development trends and knowledge domain in this area. Additionally, Almheiri et al. (2023) reviewed hydrological studies in the United Arab Emirates, providing insight into regional water challenges. Ahmed et. al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) conducted a bibliometric overview of regional flood frequency analysis, while Rahman et al. (2022) analysed water research, development, and management in Bangladesh, contributing valuable perspectives on the country's water sector.\u003c/p\u003e \u003cp\u003eFloods are one of the natural disasters with the most significant impacts on human life, the environment, and the economy. Geological structures, regional geomorphology, and climatic conditions are crucial factors determining the frequency and severity of floods (Yadav et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Tetzlaff et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Oudin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These events are typically precipitated by sudden downpours, riverine inundation, or heightened flows within and over differential lithological units, which have the capacity to severely impact agricultural lands, residential areas, and infrastructure, often resulting in significant human and economic losses. Geological formations play a decisive role in flood formation (Vannier et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Permeable and porous geological materials, such as limestone, sandstone and/or conglomerates, facilitate rainwater infiltration, thereby reducing flood risk. Conversely, unplanned construction in floodplains can exacerbate this risk.\u003c/p\u003e \u003cp\u003eA comprehensive approach that integrates natural and anthropogenic factors is essential for mitigating flood impacts. This should include flood risk assessments, protective measures, and resilience strategies, ultimately minimizing damage and enhancing community resilience.\u003c/p\u003e \u003cp\u003eThe interaction between floods and geological formations and structures is a significant focus of hydrological research, crucial for understanding how these features influence flood occurrence and severity. For instance, a study in the C\u0026eacute;vennes-Vivarais region highlighted that the thickness and hydraulic conductivity of weathered rock strata significantly impact streamflow dynamics (Vannier et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother study emphasized the importance of geological features in hydrological modelling, introducing the Drainable Storage Capacity Index (DSCI) to better represent water transfer in regions with complex geological structures (Vannier et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Additionally, the SIMPLEFLOOD model demonstrated the influence of geological characteristics on hydrological responses in the Ard\u0026egrave;che basin (Adomovic et al., 2016).\u003c/p\u003e \u003cp\u003eThese studies collectively underscore the necessity of understanding geological factors in flood modelling to improve prediction accuracy and develop effective management strategies. This study evaluates previous research on the impact of geological factors on flood formation through a bibliometric approach, proposing an interdisciplinary methodology to better integrate geological features into hydrological modelling and flood risk management. Specifically, it aims to contribute to the development of methods with higher accuracy compared to traditional models by introducing data-driven approaches to comprehensively understand the contributions of complex geological structures to flood formation.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Research questions\u003c/h2\u003e\n \u003cp\u003eThis section describes the approach taken to review the literature concerning the effects of geology on floods. The goal of this review is to investigate trends in research findings related to how geology impacts floods over the past 20 years. The following research questions will be explored:\u003c/p\u003e\n \u003cp\u003e\u003cspan\u003e1. What is the intellectual framework of this research area, and how has it developed over time?\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e2. Which authors and publications have had the most significant impact? What is the nature of collaborative patterns in this field?\u003cbr\u003e\u003c/span\u003e \u003cspan\u003e3. What are the existing research gaps and future challenges in studying the impact of geology on floods?\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Data Acquisition\u003c/h2\u003e\n \u003cp\u003eA bibliometric analysis examining the relationship between floods and geology was conducted using the Elsevier\u0026rsquo;s SCOPUS database. General methodology is summarized in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. SCOPUS was chosen due to its extensive and multidisciplinary coverage, which offers superior journal coverage compared to other databases. The analyses were performed using VOSviewer software. The literature search was conducted using the keywords \u0026quot;flood\u0026quot;, \u0026quot;hydrology\u0026quot;, \u0026quot;geology\u0026quot; and \u0026quot;model.\u0026quot;\u003c/p\u003e\n \u003cp\u003eThe data acquisition process involved a two-stage search protocol to comprehensively investigate the relationship between floods and geology. In the first stage, a broad search was conducted in the SCOPUS database using the specified keywords, targeting studies that included the terms \u0026quot;flood\u0026quot;, \u0026quot;hydrology\u0026quot;, \u0026quot;geology\u0026quot;, and \u0026quot;model.\u0026quot; In the second stage, the obtained data were analysed in detail using VOSviewer software. This software is an important tool for identifying relationships and trends within literature.\u003c/p\u003e\n \u003cp\u003eThe search method was designed to cover content areas such as titles, abstracts, and keywords. This approach was implemented to select the most comprehensive and relevant publications related to floods and geology. The obtained data provided a significant foundation for identifying and analysing the relevant literature.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Trend of documents\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the progression of both publications and citations from 1989 to 2024. Between 1989 and 2015, the number of documents remained relatively low, but a steady increase can be seen. A notable peak in 2005 may be related to Hurricane Katrina, which led a widespread flood along the U.S. Gulf Coast. Furthermore, National Science Foundation\u0026rsquo;s (NSF) increased funding for flood-related research during this period may have contributed to the rise in publications, as evidenced by the fact that two out of four publications in 2005 received support from the NSF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe increase in publications and citations around 2016 can be attributed to the growing interest following major flooding events, such as intense monsoon rains in Asia and hurricanes in the Caribbean. These events likely triggered research on flood risk management and geological analysis, making 2016 a significant year for environmental disaster studies.\u003c/p\u003e \u003cp\u003eDuring this time, there was a notable publication related to flooding in the Caribbean and two publications focusing on the severe floods in France in 2008. The research on the French floods was particularly influenced by initiatives such as the HyMeX (Hydrological Cycle in the Mediterranean Experiment) program and the FloodScale project. These projects aimed to enhance the understanding of flash flood processes through comprehensive observation and modelling efforts conducted during the Enhanced Observation Period (EOP) from 2012 to 2015. As a result, the publications released in 2016 reflect the culmination of years of data collection, analysis, and modelling. This body of research highlights the importance of understanding flood impacts and improving flood management strategies.\u003c/p\u003e \u003cp\u003eThe increase in scientific publications in 2021 can be seen as a reflection of the growing awareness and research demand regarding global issues such as climate change, urbanization, and natural disasters. Among the publications, themes such as flood risk assessment, hydrological modeling, multi-criteria decision analysis, and data mining are prominent, indicating a global search for solutions in disaster management and natural resource conservation. Despite the decline in publications in 2022, the increase in publication numbers in the following years indicates growing awareness and research interest in this field.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Citation analysis\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrates a citation network of publications within the research field. Each node on the map represents a publication, and the size of the node is proportional to the number of citations that publication has received.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis map demonstrates the impact and reach of certain publications within the field. For instance, the publication by Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) is represented by one of the larger nodes, indicating its significant impact with a high number of citations. Similarly, other influential works, such as those by Kirkby (2002), Pham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and Nandi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), are also prominently displayed. However, it should be noted that these nodes do not have any relationships with each other and do not cite one another. This indicates that while each publication is impactful on its own, there are no direct citation connections among them.\u003c/p\u003e \u003cp\u003eThe citation network provides a visual summary of key contributions in the field, with the most cited works standing out. This analysis helps in understanding the significance and academic influence of various studies, revealing how specific research has shaped and contributed to the overall discourse in the domain.\u003c/p\u003e \u003cp\u003eThe absence of connections among the 71 papers in the citation network indicates that the studies have largely been conducted independently or that there has been a lack of frequent cross-referencing in the literature. This suggests a lack of deep collaboration or information sharing within the research field, and that there may be no widely recognized common ground or reference work. The diversity of disciplines could also contribute to this lack of citation; studies from different fields may be examined in isolation from one another.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Co-authorship analysis and research collaboration\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the co-authorship network among researchers examining the intersection of floods and geology. This network visualizes the collaborations and interactions among researchers, revealing how they come together in specific thematic areas. Notably, each author appears only once in the network, indicating that no single author is involved in multiple publications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe clusters within the network represent groups of authors who frequently work together on particular topics. These groups focus on areas such as hydrological modelling, geological impact assessment, and flood risk management. The involvement of 331 authors from 35 different countries indicates that research in this field has an international dimension. This situation allows experts from different countries to share their knowledge and experiences, leading to the development of more effective solutions.\u003c/p\u003e \u003cp\u003eThe collaboration of authors from various disciplines emphasizes the importance of interdisciplinary approaches in addressing complex environmental issues. Such collaborations contribute to the development of more comprehensive and effective strategies for managing flood risk. Out of the 71 papers, 49 involve multiple authors, meaning that in the majority of these papers, more than one person has collaborated and contributed, rather than just a single author. This suggests that the research typically addresses topics that require teamwork, drawing on a broader range of knowledge and expertise. Additionally, such multi-author studies allow experts from different disciplines to come together, enabling more comprehensive and in-depth investigations.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1 presents the top ten most cited articles related to flood research, along with citation counts and keywords. The countries listed in the table represent the countries of the institutions where the studies were conducted. The countries where the research was dominantly applied are: Brazil, Spain, Vietnam, Jamaica, the United States, Poland, and Portugal. These countries represent the geographical areas where the studies were implemented.\u003c/p\u003e \u003cp\u003eFor example, these articles, covering a wide range from the Amazon River in Brazil to the Caribbean in Jamaica, provide a comprehensive understanding of flood hazards, hydraulic processes, and risk assessments.\u003c/p\u003e \u003cp\u003eThe most cited study about flood and mantle dynamics is by Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) (Table\u0026nbsp;1), which examines vertical ground movements in the Amazon River basin, highlighting the effects of elastic water oscillations and seasonal fluctuations. Furthermore, it assesses the relationship between these phenomena and structural geology and tectonic movements, making significant contributions to understanding the dynamics of water movements. By employing techniques such as time series analysis and hydrological modelling, it sheds light on other studies in the fields of geoscience and hydrology.\u003c/p\u003e \u003cp\u003eIn second place is the study by Kirkby et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), which has received 136 citations. This research focuses on slope hydrology and surface runoff in mountainous regions, emphasizing the importance of water connectivity across the landscape and investigating its role in flood formation. Insights like these are critical for developing environmental management strategies and mitigating the impacts of natural disasters.\u003c/p\u003e \u003cp\u003eThe study by Pham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which conducts flood risk assessments in Quang Nam, Vietnam, has garnered 123 citations. It presents innovative approaches to flood risk management and forecasting using machine learning and multi-criteria decision analysis. Other significant studies include the GIS-based risk assessment of geological hazards by Mejia-Navarro et al. (1994) and the research on channel deepening and river engineering by Wyzga (2001). These works provide essential data for developing more effective engineering solutions to reduce flood risks.\u003c/p\u003e \u003cp\u003ePelletier (2005) focuses on alluvial fan formation and surface geology, receiving 67 citations. This research offers important insights into soil and water management, contributing to the health of ecosystems. Turner-Gillespie et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) investigate the effects of urban development on flood responses, highlighting that urbanization can increase flood risks. Lastly, Hettiarachchi (2019) analyses the impacts of climate change on urban flooding, providing a valuable resource for developing strategies in this area.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;1 also offers a detailed content analysis of these influential works. This table summarizes the main objectives, identified hazards, and key criteria used in each study. For instance, Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) employs geodesy and elastic oscillations within a tectonic context, utilizing time series analysis as a fundamental criterion. This approach prioritizes connectivity criteria, similar to the research by Kirkby et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) in studying slope hydrology.\u003c/p\u003e \u003cp\u003ePham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) emphasizes methodological diversity by using machine learning and multi-criteria decision frameworks. Nandi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) focus on flood hazard assessments using ArcGIS and statistical analysis, while Mejia-Navarro et al. (1994) examine geological hazards through risk assessments. Pelletier et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) investigate alluvial fan dynamics using numerical modelling and remote sensing techniques. In this context, Wyzga (2001) studies channel dynamics and sediment transport, providing the necessary information to mitigate flood risks.\u003c/p\u003e \u003cp\u003eThe interdisciplinary approach and methodological diversity found in flood research offer a deeper perspective on the topic. Techniques from fields such as geology, hydrology, remote sensing, and statistical analysis play a critical role in assessing and understanding flood risks. However, the limited collaboration networks among authors indicate a need for more partnerships to comprehensively examine the relationships between flooding and geology. In this regard, comparing geological and hydro-meteorological processes across different regions is vital for developing more effective flood management strategies.\u003c/p\u003e \u003cp\u003eAlthough the study by Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) has accumulated the most citations overall, Table\u0026nbsp;2 highlights the top 10 most influential papers based on annual citation counts. This distinction arises because the Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) study has had more time to accumulate citations, whereas the influential papers are measured by their yearly citation rates. The works of Pham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Nandi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) are particularly noteworthy due to their use of innovative and powerful methods. Pham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) utilized modern statistical and analytical techniques such as machine learning and multi-criteria decision analysis (MCDA) for flood risk assessment. These advanced methods allow for more accurate and effective risk predictions through the analysis of large datasets. MCDA, in particular, enables the integration of multiple factors and assesses their relative importance, contributing to a more comprehensive flood risk model.\u003c/p\u003e \u003cp\u003eSimilarly, Nandi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) employed statistical and analytical techniques that extract meaningful insights from extensive datasets, enhancing the impact of his research. These modern approaches, unlike traditional methods, provide more precise and adaptable analyses, resulting in broader engagement and greater influence within the scientific community.\u003c/p\u003e \u003cp\u003eHigher-impact journals generally offer greater visibility and credibility, leading to a higher number of citations. However, certain studies have managed to achieve significant citation counts even when published in journals with lower impact factors, owing to their innovative methodologies and valuable findings. This demonstrates that the quality and novelty of the research, rather than the journal's impact factor alone, play crucial roles in driving the scientific impact and recognition of a study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Countries network map\u003c/h2\u003e \u003cp\u003eThe countries network was created to examine the relationship between floods and geology reveals the global distribution of publications from different countries in this field and their collaboration patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This network consists of seven different country clusters, each reflecting the level of collaboration in research conducted by those countries. In the visualization, the colours represent different years. Darker colours (e.g., blue shades) indicate that countries have been conducting studies in this field since earlier years, while lighter and brighter colours (e.g., yellow shades) represent more recent studies. For example, the United States and China have been active in this field for a long time and have extensive collaboration networks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCountries like Australia and Portugal have shown an increase in research in more recent years.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 1\u003c/strong\u003e \u003cp\u003eFrance, India, Iran, Norway, Singapore, Vietnam. The countries in this cluster have made significant contributions to research on floods and geology. France stands out with 9 publications and 140 citations. India also plays an important role with 3 publications and 145 citations. Iran has achieved 2 publications with 27 citations. Norway has 1 publication with 17 citations, while Singapore has 1 publication with 26 citations, and Vietnam has 3 publications with 166 citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 2\u003c/strong\u003e \u003cp\u003eAustralia, Montenegro, Morocco, Portugal, Romania. Despite consisting of fewer countries, this cluster highlights Australia\u0026rsquo;s contributions with 4 publications and 73 citations. Montenegro and Morocco each have 1 publication with limited citations. Portugal has 2 publications with 60 citations, while Romania has only 1 publication with just 1 citation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 3\u003c/strong\u003e \u003cp\u003eCanada, China, Thailand. In this cluster, Canada has 2 publications with 15 citations, while China continues to be a significant player with 15 publications and 117 citations. Thailand has only 1 publication with just 5 citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 4\u003c/strong\u003e \u003cp\u003eBrazil, Colombia, Germany, Sweden. Brazil and Colombia each have 4 publications with 181 and 2 citations, respectively. Germany has 5 publications with 42 citations, while Sweden has 2 publications with 43 citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 5\u003c/strong\u003e \u003cp\u003eGreece, Italy, Japan, Netherlands. Greece has 1 publication with 35 citations, while Italy has 3 publications with 43 citations. Japan has 1 publication with 7 citations, and the Netherlands has 2 publications with 7 citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 6\u003c/strong\u003e \u003cp\u003eNepal, Poland, United Kingdom, United States. The United States emerges as the leading contributor in this cluster with 22 publications and 771 citations. The United Kingdom has 3 publications with 196 citations, while Poland has 4 publications with 100 citations. Nepal has 1 publication with 4 citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCluster 7\u003c/strong\u003e \u003cp\u003eJamaica, Trinidad and Tobago. Jamaica stands out with 1 publication and 118 citations. Trinidad and Tobago also have 1 publication with the same number of citations.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eThese seven clusters illustrate how research on floods and geology is distributed on an international scale and highlight the importance of collaborations in this field. Collaborations between countries play a critical role in understanding the relationship between flood events and geological processes in different geographical regions and in developing effective management strategies.\u003c/p\u003e \u003cp\u003eThe United States stands out as the largest node on the map, demonstrating significant collaboration with institutions from 9 different countries. This indicates that the U.S.A holds a central position in international academic endeavours. China has a broad network of collaborations and establishes strong ties with countries across Asia, Europe, and the U.S.A.; the color of the lines signifies that these collaborations are relatively new, having been established at the beginning of 2020. European countries like France, Germany, and the United Kingdom engage in intense collaborations with one another and with the U.S. For instance, relationships between the U.S.A, Portugal, and Australia are more recent, represented by yellow tones, while collaborations with European countries are more established, depicted in blue tones. Smaller nodes like Vietnam, Jamaica, and Greece typically engage in collaboration with one country.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the distribution of flood risk and geological studies across countries and highlights the countries with the most research. The USA, with 21 studies, is at the top of the list, indicating the intensity of flood risk assessment and geological studies related to flooding in the country. The USA stands out as a country with extensive flood research due to its large geographical area, diverse climate conditions, and advanced research infrastructure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eChina, with 14 studies, ranks second. China's large population and vast territory contribute to the widespread occurrence of flood and geological studies. The country's geographical diversity and frequent flooding events are significant factors driving the need for research in this field.\u003c/p\u003e \u003cp\u003eFrance, with 5 studies, ranks third and is an important center for flood and geological research in Europe. Studies on flooding events and water management in France contribute to Europe's leadership in flood risk management and water governance.\u003c/p\u003e \u003cp\u003eBrazil, with 4 studies, is prominent, as it has vast water systems like the Amazon basin, making it an important area for flood risk analysis and geological studies in flood-prone regions.\u003c/p\u003e \u003cp\u003eVietnam, with 3 studies, along with Poland and India, each with 2 studies, is also notable. These countries are significantly affected by floods, making local flood risk assessments and management an important research focus in these regions.\u003c/p\u003e \u003cp\u003eOther countries with only one study include Bulgaria-Greece, Korea, Morocco, Iran, Indonesia, Nigeria, Italy, Laos, Australia, Colombia, Thailand, Portugal, Netherlands, Canada, Belgium, Germany, Turkey, the United Kingdom, and Jamaica. Research in these countries is generally more focused on local flood impacts and geological processes in smaller areas.\u003c/p\u003e \u003cp\u003eOverall, studies conducted in larger countries like the USA and China are more intense and comprehensive due to their large geographical areas and significant data on flooding events. In other countries, the studies focus more on local flood risks and water management, addressing specific regional issues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Co-word analysis and research evolution\u003c/h2\u003e \u003cp\u003eCo-word analysis results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The relationship between flooding and geology holds significant importance in research on water management and flood control. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e clearly establishes a direct correlation between the keywords \u0026ldquo;flood\u0026rdquo; and \u0026ldquo;geology.\u0026rdquo; The keyword \"hydrology\" acts as a bridge between flood and geology, highlighting the impact of water management and geological structures on flood events. This demonstrates how hydrological processes interact with geological formations to increase flood risks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows which topics have emerged over the years and how these topics have evolved over time. The colour scale indicates the time period during which each keyword was studied in greater depth. During the 1989\u0026ndash;2015 period, represented by blue tones, older studies focused on themes such as \u0026ldquo;water resource management\u0026rdquo;, \u0026ldquo;hydrology\u0026rdquo;, and \u0026ldquo;natural disasters\u0026rdquo;. During this time, fundamental topics like \"hydrology,\" \"flood\" and \"geology\" held a significant place in the literature. The terms related to Flood include approximately 30 terms, such as Flood, Flood forecasting, Flood hazard, Flood risk, Flood wave, Flood damage, Flood control, Flash floods, Flood frequency, Flood hydrology, Flood magnitude, Flood analysis, Flood prediction, Flooded area, Floodplain, Flood disaster prediction, Flash-floods, and Flood hazard map. These account for approximately 21.9% of the total terms.\u003c/p\u003e \u003cp\u003eThe terms related to Geology include approximately 27 terms, such as Geomorphology, Geology, Geological hazards, Geological structures, Surficial geology, Karst, Fracture flow, Geotechnologies, Fracture mapping, Permeability distribution, Groundwater flow, Rocks, Landslide-prone areas, Landslides, Geodesy, Structural geology, Crustal movement, Displacement, Groundwater, Groundwater-surface water interactions, and Geology-Ecology. These make up about 19.7% of the total terms.\u003c/p\u003e \u003cp\u003eThe terms related to Hydrology include approximately 80 terms, such as Hydrology, Hydrological model, Hydrological prediction model, Hydrological data, Hydrological simulation, Hydrological modelling, Hydrological evaluation, Hydrological forecasting, Rainfall-runoff simulation, Stormwater management, Urban stormwater management, Watershed hydrology, Low Impact Development (LID), Storm Water Management Model (SWMM), Hydrological models, Watershed management, Hydrological errors, Distributed hydrological modelling, Flash flood, Flood risk modelling, and Stormwater infrastructure. These represent about 58.4% of the total terms.\u003c/p\u003e \u003cp\u003eFrom 1989 to 2025, research on environmental and hydrological topics has evolved significantly, with countries focusing on a wide range of issues based on their specific challenges and needs. In the early 2000s, countries like the United States, the United Kingdom, and Poland concentrated on foundational hydrological and geological research, while more recent studies from 2015 onward have seen a shift toward urban planning, sustainable water management, and the impacts of climate change.\u003c/p\u003e \u003cp\u003eFrom 2005 to 2015, research represented by green tones concentrated on water management in cities and infrastructure development. Concepts such as \"stormwater management,\" \"urban hydrology,\" and \"sponge city\" became more prominent. These studies focused on improving stormwater management systems and reinforcing infrastructure to minimize flooding in urban areas. Urban hydrology became a central field of study, particularly to understand how urbanization affects the natural water cycle. The concept of \"sponge cities\" emerged as a sustainable solution to enhance the ability of urban environments to absorb rainwater, mitigating the effects of heavy rainfall and floods. During this period, studies on urban flooding, river basin management, and flood risk evaluation continued to be important topics, particularly in countries like the United States, Vietnam, and the United Kingdom.\u003c/p\u003e \u003cp\u003eIn the 2020\u0026ndash;2025 period, represented by yellow tones, the research shifted towards urban planning, sustainable water management, and the effects of climate change. Concepts such as \"climate change,\" \"sponge city,\" \"urban hydrology,\" and \"flood control\" became more prominent. Climate change, with its impact on the water cycle, flood risks, and water management strategies, has become one of the most significant research topics. Studies on flood control, particularly in urban areas, have risen, focusing on strategies to reduce the impacts of flooding in cities. The innovative \"sponge city\" concept has gained traction as part of sustainable urban management, providing new ways to manage stormwater and mitigate urban flooding. Research on urbanization and flood response, with a particular focus on managing the adverse effects of climate change, became central in countries like the United States, Australia, and Vietnam.\u003c/p\u003e \u003cp\u003eLooking at the evolution of research topics, from 2010 to 2015, studies primarily focused on fundamental and broad topics aimed at understanding natural processes and the physical behaviour of hydrological systems. Between 2015 and 2020, research began to concentrate on urban challenges and solutions, particularly concerning water management in cities. By 2020, the increasing focus on the effects of climate change and the application of innovative urban solutions marked a significant shift in the literature, addressing the growing concerns of urban flooding, sustainability, and the resilience of water systems in the face of climate change. The collaboration of advanced technologies such as machine learning, GIS, and numerical modelling in flood risk assessment and water management has also been notable in the later years, especially in countries like Vietnam, Jamaica, and Australia.\u003c/p\u003e \u003cp\u003eOverall, these periods reflect the growing importance of sustainable and resilient water management practices, particularly in urban settings, to address the ongoing challenges posed by climate change and urbanization. The integration of new technologies, such as machine learning and GIS, with traditional methods of flood risk assessment and management, continues to advance the field and contribute to global efforts in mitigating the impact of water-related disasters.\u003c/p\u003e \u003cp\u003eThe rise of innovative approaches in recent years is particularly linked to the need for sustainability and adaptation to climate change (such as machine learning, GIS, remote sensing, big data analytics, sponge city concept, and sustainable urban water management solutions). These approaches are becoming crucial in developing effective strategies for flood risk management, urban water management, and climate change adaptation, helping cities become more resilient to the impacts of flooding and environmental changes. Researchers have increasingly turned toward producing more effective solutions for stormwater management, flood control, and urban infrastructure development. These types of solutions aimed at improving water management in cities are receiving great attention in the literature and are likely to shape future studies. This analysis demonstrates that topics like sustainable water management and urban infrastructure have gained importance over time, and innovative approaches have increasingly found their place in research.\u003c/p\u003e \u003cp\u003eThe relationship between flooding and geology plays a crucial role in water management and flood control research, with geological factors significantly impacting flood risks. Research indicates that with climate change and the increasing frequency of flood events, geological structures are being studied more intensively, and new techniques and strategies are being developed in this area. The map visually represents the intellectual structure of this research field and how it has evolved over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. REVIEW OF LITERATURE AND DEFINITION OF RESEARCH GAPS","content":"\u003cp\u003eFloods and their interaction with geological factors have been the focus of various interdisciplinary studies, highlighting significant advancements while uncovering areas that remain underexplored. Existing research underscores the role of geological structures, such as lithology and deformation-related structures, in shaping hydrological processes and flood risks. Studies like those by Bevis et al. and Pham et al. emphasize the importance of integrating geological data into hydrological models to improve flood risk assessments. Recent advancements in geographic information system (GIS), remote sensing, and machine learning technologies have enhanced conventional methodologies, facilitating more precise predictions and comprehensive risk management strategies. Concurrently, innovative urban planning concepts, such as sponge cities, have emerged as pioneering solutions for mitigating the deleterious effects of urban flooding by augmenting water absorption and diminishing runoff.\u003c/p\u003e \u003cp\u003eDespite these advancements, notable gaps persist in the literature. One major issue is the limited integration of complex geological features in current hydrological models, which often fail to account for lithological diversity and the unique characteristics of geological structures. The representation of regional morphogenesis is another concern, as research is heavily concentrated in regions like the United States, China, and France, leaving areas in the Global South significantly underrepresented. This imbalance restricts the applicability of findings to diverse geological and climatic contexts. Furthermore, the concentration of studies on floods and geological factors across different disciplines highlights the interdisciplinary nature of this field. Various areas, such as environmental science (44%), earth and planetary sciences (16%), engineering (12%), and social science (6%), contribute to understanding and addressing this complex issue (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). However, despite this diversity, greater integration and collaboration in interdisciplinary studies could lead to more comprehensive solutions for mitigating flood risks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe challenge of data accessibility also hinders progress, particularly in underrepresented regions where high-quality and region-specific data are scarce. While advanced technologies have been applied in some studies, the use of historical geological data to predict long-term flood trends has been limited. Additionally, as climate change continues to influence flood frequency and intensity, there is an insufficient focus on adaptive strategies tailored to specific geological conditions. Understanding the dynamic interaction between climate-induced changes and geological factors is critical for developing effective mitigation and adaptation measures.\u003c/p\u003e \u003cp\u003eAddressing these gaps requires a multi-faceted approach. Future research should prioritize the integration of geological insights into hydrological modelling, expanding the geographic focus to include underrepresented regions and fostering greater interdisciplinary collaboration. Leveraging advanced technologies like AI, big data analytics, and geological records, such as the spatial distribution of lithological formations and structures, can enhance predictive accuracy and provide localized solutions. Emphasis should also be placed on designing climate-resilient strategies that address both immediate flood risks and long-term adaptation needs. By bridging these gaps, researchers can contribute to the development of sustainable and globally applicable flood risk management strategies, fostering resilience against the growing challenges posed by climate change and urbanization.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eThe bibliometric analysis of the studies on the relationship between floods and geology provides important insights into the global distribution of research, influential publications, and the evolution of research themes. This analysis highlights the interdisciplinary nature of the field, where hydrology, geology, urban planning, and climate change intersect to provide a comprehensive understanding of flood risks and mitigation strategies.\u003c/p\u003e \u003cp\u003eThe importance of the GIS is increasing on a daily basis, as it is utilized in the assessment of flood risk based on hydrological modelling and geological studies. For example, Bevis et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) focuses on geophysical and hydrological processes in the Amazon River basin, emphasizing the importance of integrating geological structures and hydrological systems to understand the complex dynamics of flood events. Similarly, Pham et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Nandi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) highlight the importance of modern, data-driven techniques for flood risk assessment, particularly in vulnerable regions. These studies demonstrate how traditional methods are being enriched with technology-assisted tools.\u003c/p\u003e \u003cp\u003eThe global collaboration network in flood and geology research shows how international partnerships have developed across various geographical regions. Countries such as the United States, China, and France play significant roles, while underrepresented regions like Nepal, Vietnam, and Jamaica also make important contributions. This international collaboration is crucial for understanding flood risks in diverse geological environments and for developing global solutions for flood mitigation.\u003c/p\u003e \u003cp\u003eThe evolution of the research field shows a shift from traditional hydrological studies to more applied areas, particularly in urban environments. Initially, studies focused on fundamental hydrological processes, but over time, urban water management, infrastructure development, and climate change adaptation have become more prominent. Concepts like \"sponge cities\" reflect this shift toward infrastructure-based, sustainable solutions for urban resilience in the face of extreme weather events. In recent years, with the increasing impact of climate change, research has shifted toward long-term, climate-resilient strategies for managing flood risks.\u003c/p\u003e \u003cp\u003eWhile there has been progress in flood and geology research, several challenges remain. There is a need for greater interdisciplinary collaboration among geologists, hydrologists, urban planners, and policymakers. As research increasingly focuses on urban resilience and climate adaptation, managing flood risks in diverse regions with unique geological structures requires innovative, context-specific solutions. Additionally, the uneven distribution of research efforts, with underrepresentation in regions like the Global South, highlights the need for more international collaboration to create globally applicable solutions.\u003c/p\u003e \u003cp\u003eIn conclusion, the relationship between floods and geology is a critical area of study that plays a vital role in water management, urban resilience, and climate adaptation. As the field continues to evolve, fostering interdisciplinary collaboration, expanding research in underrepresented regions, and focusing on sustainable, long-term strategies for flood risk management are essential. The evolution of research over the past decade shows that addressing the complex interplay between geological structures and flood events is key to building resilient communities in the face of growing environmental challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Cemre Erbil. Berna Ayat and Cengiz Zabcı contributed to the conceptual development and writing of the document. The first draft of the manuscript was written by Cemre Erbil and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdamovic, M., Branger, F., Braud, I., \u0026amp; Kralisch, S. (2016). Development of a data-driven semi-distributed hydrological model for regional scale catchments prone to Mediterranean flash floods. \u003cem\u003eJournal of Hydrology, 541\u003c/em\u003e(Part A), 173\u0026ndash;189. https://doi.org/10.1016/j.jhydrol.2016.03.032\u003c/li\u003e\n\u003cli\u003eAhmed, A., Yildirim, G., Haddad, K., \u0026amp; Rahman, A. (2023). 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An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing. \u003cem\u003eGSA Bulletin, 117\u003c/em\u003e(9\u0026ndash;10), 1167\u0026ndash;1180. https://doi.org/10.1130/B25544.1\u003c/li\u003e\n\u003cli\u003ePham, B. T., Luu, C., Phong, T. V., Nguyen, H. D., Le, H. V., Tran, T. Q., Ta, H. T., \u0026amp; Prakash, I. (2021). Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam. \u003cem\u003eJournal of Hydrology, 592\u003c/em\u003e, 125815. https://doi.org/10.1016/j.jhydrol.2020.125815\u003c/li\u003e\n\u003cli\u003eSalvati, A., Moghaddam Nia, A., Salajegheh, A., Shirzadi, A., Shahabi, H., Ahmadisharaf, E., Han, D., \u0026amp; Clague, J. J. (2024). 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A geomorphologist\u0026apos;s criticism of the engineering approach to channelization of gravel-bed rivers: Case study of the Raba River, Polish Carpathians. \u003cem\u003eEnvironmental Management, 28\u003c/em\u003e, 27\u0026ndash;41. https://doi.org/10.1007/s0026702454\u003c/li\u003e\n\u003cli\u003eYadav, M., Wagener, T., \u0026amp; Gupta, H. (2007). Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins. \u003cem\u003eAdvances in Water Resources, 30\u003c/em\u003e(8), 1756\u0026ndash;1774. https://doi.org/10.1016/j.advwatres.2007.01.005\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eContent analysis of top influential papers.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1011\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKeyword\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHazard\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eBevis et al. (2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eAmazon River; South America; Western Hemisphere; World; Floods; Geodesy; Geophysics; Hydrology; Mathematical models; Rivers; Structural geology; Time series analysis; crustal movement; displacement; river basin; vertical movement; water; Crustal oscillation; Elastic oscillations; Hydrological model; Seasonal fluctuations; Vertical displacement; Tectonics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eFlood analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGround deformation; Infrastructure damage risk; Hydraulic loading\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eTime series analysis; Hydrological model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eKirkby et al. (2002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eConnectivity; Hill slope hydrology; Runoff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUnited Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eRunoff connectivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eIncreased erosion; Flood risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eRunoff measurement; Hydrological modeling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003ePham et al. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eFlood risk assessment; Machine learning; multi-criteria decision analysis; Quang Nam, Vietnam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eVietnam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eRisk assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFlood risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eMachine learning, multi-criteria decision\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eNandi et al. (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eArcGIS; Caribbean; Flood hazard evaluation; Statistical analysis; Validation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUSA,Jamaica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eHazard evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFlood hazard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eArcGIS; Statistical analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eMejia-Navarro et al. (1994)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eGeological hazards; Vulnerability; Risk assessment; GIS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eVulnerability study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eGeological hazards\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eGIS; Risk assessment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003ePelletier et al. (2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eAlluvial fan, Flood hazard, Numerical modeling, Remote sensing, Surficial geology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eModeling flood hazard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFlood risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eNumerical modeling; Remote sensing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eWyzga(2001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eChannel incision; Channelization; Environmental change; Gravel-bed rivers; River engineering; Sediment transport\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003ePoland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eChannel dynamics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eChannel incision; Sediment imbalance; Channel instability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eBedload transport calculations; Sedimentological studies;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eBrandao et al. (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eMosses; Plant selection; Sustainability; Urban hydrology; Urban stormwater management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003ePortual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eSustainability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFlooding; Drainage system overload\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003ePlant selection; Urban hydrology\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eTurner-Gillespie at al. (2003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eAttenuating reach; Flood response; Urbanization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eUSA, United Kingdom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eUrbanization impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFlood risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eAttenuating reach; Flood response\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 204px;\"\u003e\n \u003cp\u003eHettiarachchi et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 275px;\"\u003e\n \u003cp\u003eAntecedent moisture conditions; Climate change; Continuous simulation; Urban flooding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eAustralia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eClimate change effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eUrban flooding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eContinuous simulation; Antecedent moisture\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e The top 10 most impactful articles\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"613\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitations per Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSources\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImpact Factor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003ePham et al. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e41.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eJournal of Hydrology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eNandi et al. (2016)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e14.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eEarth Surface Processes and Landforms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eHettiarachchi et al. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eJournal of Hydrology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eBrandao et al. (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eEcological Engineering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eBevis et al. (2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eGeophysical Research Letters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eKirkby et al. (2002)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e6.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eEarth Surface Processes and Landforms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003ePelletier et al. (2005)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eBulletin of the Geological Society of America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eMejia-Navarro et al. (1994)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eGeomorphology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eWyzga (2001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eEnvironmental Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003eTurner-Gillespie at al. (2003)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 228px;\"\u003e\n \u003cp\u003eAdvances in Water Resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"flood, geology, bibliometric analysis, literature review","lastPublishedDoi":"10.21203/rs.3.rs-5866366/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5866366/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFloods have emerged as a critical global issue due to climate change, leading to increased research interest across various fields. However, the complex relationship between floods and geological factors remains insufficiently explored in the literature. This bibliometric analysis addresses this gap by examining the intellectual structure of research on floods and geology through a systematic review of 71 articles published between 1989 and 2024. The study reveals that environmental science dominates the field (44%), followed by earth and planetary sciences (16%), engineering (12%), and computer sciences (7%). Analysis of research terms demonstrates the field's breadth, with hydrology-related keywords comprising 58.4% of total terms, while flood-related and geology-related terms represent 21.9% and 19.7%, respectively. This study was conducted using data from the Scopus database, and co-word, co-citation, and co-author network analysis were performed through VOSviewer software. Key topics, influential publications, citation patterns, and international collaborations were identified and visualized using VOSviewer. The United States leads with 22 publications and 771 citations, followed by China with 15 publications and 117 citations. The analysis identified seven distinct international collaboration clusters, highlighting the global nature of flood research while also revealing geographical disparities in coverage. Notably, previous research demonstrates that integrating geological layers into hydrological models yields results closely matching real flood measurements, even in basins lacking measurement stations. This finding emphasizes the significance of understanding lithological characteristics for enhanced flood risk assessment. The analysis highlights an increasing application of advanced technologies, such as remote sensing, GIS, and machine learning, particularly in post-2020 studies, marking a shift toward data-driven approaches.\u003c/p\u003e","manuscriptTitle":"The role of geology in flood risk assessments: a systematic literature review and a comprehensive bibliometric analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-24 10:44:32","doi":"10.21203/rs.3.rs-5866366/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a22b428f-6e3a-4c07-a0d4-d24f82162af2","owner":[],"postedDate":"January 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-22T07:53:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-24 10:44:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5866366","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5866366","identity":"rs-5866366","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}