Flood Prevention Measures Research Articles

A novel urban flood risk assessment framework based on refined numerical simulation technology

Due to urbanization and climate change, urban areas are becoming more susceptible to flooding, posing significant risks to human life and property. Numerical simulation techniques can provide valuable support in mitigating urban flood risks. The objective of this study is to establish a novel framework for flood risk assessment based on refined urban flood simulations. To achieve refined urban flood simulations, the Torricelli’s law is incorporated into a two-dimensional fluid dynamics model, and a numerical analysis model is developed to estimate the inundation within buildings and accurately simulate the entire inundation process. The model was used to reproduce a real flood event in Omihachiman City, Japan, with the Nash-Sutcliffe Efficiency (NSE) values of 0.6488 and 0.7182, demonstrating the credibility of the model. Based on the simulation results, the hydrological causes of the flood event were analyzed, and flood prevention measures were proposed. After implementing these measures, the maximum water depths at the study area were reduced to 0.14 m, 0.62 m, and 0.12 m, respectively, proving the effectiveness of the flood prevention measures. To address the issue of inundation depth not fully reflecting flood risk, the instability of human bodies in floodwaters is conducted to evaluate flood risk for adults and children in the target area. In response to increasingly frequent extreme rainfall events, the extreme precipitation events of three different return periods (10-year, 50-year, and 100-year) are used to assess the flood risk and the effectiveness of flood prevention measures. Based on the assessment results, the flood prevention measures not only reduced the flood risk levels but also decreased the flood risk area, further confirming their effectiveness.

Adaptation and Adversity Acceptance as Resilience to Flooding at World Heritage Sites: A Case Study of Hoi An Ancient Town, Vietnam

ABSTRACT This article investigates long-term adaptation and resilience to floods at World Heritage sites through a case study of Hoi An Ancient Town, Quang Nam, Vietnam. Drawing on fieldwork observation, document review, and unstructured interviews conducted in Hoi An, we examine the enduring processes and experiences of co-living with floods. The article considers residents’ ability to comprehend, acknowledge, and address the challenges of flooding using the conceptual lens of adaptation and adversity acceptance as resilience. Our findings reveal an inseparable bond between residents and their built environment, encompassing invaluable lessons and experiences, local beliefs, resource availability, and adaptive strategies aimed at harmonious cohabitation with flooding described as ‘leaning into nature’. Strikingly, residents have developed their own practices and identities shaped by the town’s inundation by flood waters over a few centuries. Various modern flood prevention measures trace their origins to historical efforts, underscoring the vital role of traditional knowledge and practices in coping with the impacts of climate change. Those efforts are also framed within the local policy context such as Heritage Management Plan, Disaster Risk Management Plan, and Regulation for the Protection of the UNESCO-listed Hoi An Ancient Town.

Frequency Analysis of Annual One Day Maximum Rainfall at Faisalabad, Lahore and Multan (Punjab)

Effective management of water systems and seepage projects depends on accurate precipitation data, particularly annual daily maximum precipitation, which is essential for designing hydraulic structures. This study conducts a frequency analysis of annual daily maximum precipitation for Faisalabad, Lahore, and Multan in Punjab, Pakistan, using over 50 years of historical data from these three stations. The analysis, performed with RAINBOW software, evaluates five probability distributions—normal, log-normal, weibull, gamma, and exponential. The fit of these distributions was assessed using Chi-square, Kolmogorov-Smirnov, and Anderson-Darling tests at significance levels of 5%, 10%, and 20%. Results indicate that the Weibull and Log-normal distributions most accurately represent the precipitation data. Based on this analysis, the study estimates the magnitude of maximum annual precipitation for return periods of 2, 5, 10, 25, 50, and 100 years. The findings aim to improve water management strategies, enhance flood and drought prevention measures, and optimize the hydraulic design of seepage structures, contributing to more effective planning and resilience in the face of extreme weather events.

Study on the Driving Mechanism of Ecohydrological Regime in the Wandering Section of the Lower Yellow River

Climate change and human activities exert significant impacts on runoff generation and convergence mechanisms. Understanding the evolution mechanisms and driving forces of runoff is crucial for the sustainable development of water resources. This study is based on the runoff data of the Huayuankou (HYK), Jiahetan (JHT), and Gaocun (GC) stations in the lower reaches of the Yellow River from 1951 to 2019. The objectives are to identify and quantify the hydrological pattern and its driving mechanism of the three stations by the Mann–Kendall test, cumulative deviation method, wavelet analysis, the IHA-RVA method, SCRCO method, and the Budyko method. Our study revealed that the runoff disturbance points at all three stations occurred in 1985. During the two periods before and after the disturbance, the trends and periodicities within the year exhibited high consistency, showing an overall downward trend, with runoff increasing in October and decreasing in June and the primary cycles being 5 and 7 years. All three stations experienced high-degree changes in their hydrological situations, with the high-degree change occupying the largest proportion. At the HYK, JHT, and GC stations, human activities accounted for 66.05%, 71.94%, and 74.38% of runoff changes, respectively. Furthermore, we verified the attribution conclusion of runoff at HYK using the Budyko model, confirming that human activities are the primary factor influencing runoff. Finally, we explored the interactive relationships along the spatial trajectory of runoff at the three stations, analyzed 32 hydrological indicators, and detailed the land use changes in the Yellow River Basin. Our research findings complement the understanding of hydrological change mechanisms in the lower reaches of the Yellow River Basin and provide a scientific basis for future water resource management and flood prevention measures.

지방정부의 댐 하천관리의 물공급에 관한 사례분석: 유지유량 관리를 중심으로

The purpose of this study was to find solutions for local government dam river management and water supply for maintenance flow. For this purpose, based on data collected and organized on items to be included in the system related to the environment around Unmun Dam and Dongchang Stream, a comparative review of the policy status of other local governments and environmental facilities was conducted, and case analysis was conducted focusing on domestic and international cases. The local government's maintenance flow management plan for water supply in dam river management is, first, to manage the river flow in a stable manner throughout the year in order to perform the smooth function of the river, and second, to pump water to maintain the basic flow rate of the river. A reverse pumping method that sends water from downstream to upstream, and third, artificial supply of soil through flooding or flushing discharge to improve the environment of the river downstream of the dam were proposed. As a result, we tracked changes in the natural ecological environment of Dongchang Stream after the construction of Unmun Dam and proposed dam operation plans and flood control policies to derive implications such as ecological environment restoration, flood prevention measures in downstream areas, and local economy revitalization measures.

‘When it floods, we work on our own’: Exploring factors influencing collective efficacy appraisals for community‐level flood measures among urban informal settlements in Suva, Fiji

AbstractMore than one billion people worldwide are living in urban informal settlements where flood risks are high. Positive collective efficacy beliefs can facilitate community‐level adaptive action. This sub‐study of the Revitalizing Informal Settlements and their Environments (RISE) trial, aimed to identify social and contextual factors influencing residents' collective efficacy appraisals about their settlement's ability to implement community‐level flood prevention, protection and response measures. Forty‐two in‐depth interviews were conducted in 10 settlements in Suva, Fiji using a photovoice methodology. Thematic analysis was used to elicit key themes, which were then interpreted and contextualized collaboratively with the local field team. The most salient influencing factors were formal leadership, shared needs or benefits, collective identity (whether via shared religion, ethnicity or regional/kinship group), past performance experiences and expectations around collective action. While the data revealed some between‐settlement variation on these factors, there was also a large degree of within‐settlement variation concerning perceptions of these factors. Community‐based flood programming should not be undertaken without first assessing the degree to which participants believe that programme objectives reflect shared needs or will yield shared benefits and whether those objectives warrant collective action according to the community's social expectations for participation and contribution.

Flood‑Induced Health Vulnerability: A Case Study of Nirmal Char in Murshidabad District, West Bengal

The chars (riverine sand bars) are poorly connected to the mainland and are prone to natural hazards like floods. Char lands are occupied by people from lower-income groups who have been living in an ecologically fragile landscape. The frequent floods affect the char dwellers’ health and health infrastructures and limit access to health care services. A study has been conducted to assess the health vulnerability of char dwellers in Nirmal Char in the Murshidabad district. The current study explores the impact of floods on the health of char dwellers during pre-flood season which differs from or is similar to flood season. The health vulnerability of the char dwellers was measured in terms of flood exposure, flood sensitivity and flood adaptive capacity. The primary data collected from selected households reveals that the livelihood conditions of most of the char dwellers have been severely affected during the flood, introducing different health-related diseases (i.e. typhoid fever, malaria, diarrhea and dengue) catalysed due to the lack of accessibility to health care facilities. The present study showed that up to 97.87% of households had a high level of vulnerability and 2.13% had a moderate level of vulnerability. We concluded that early flood warning, flood prevention measures and long-term mitigation strategies must be strengthened for char dwellers as they face greater health problems. Therefore, a context-specific sustainable health policy intervention is required to improve the adaption capacity of char dwellers.

Flood susceptibility assessment of the Agartala Urban Watershed, India, using Machine Learning Algorithm.

Frequent floods are a severe threat to the well-being of people the world over. This is particularly severe in developing countries like India where tropical monsoon climate prevails. Recently, flood hazard susceptibility mapping has become a popular tool to mitigate the effects of this threat. Therefore, the present study utilized four distinctive Machine Learning algorithms i.e., K-Nearest Neighbor, Decision Tree, Naive Bayes, and Random Forest to estimate flood susceptibility zones in the Agartala Urban Watershed of Tripura, India. The latter experiences debilitating floods during the monsoon season. A multicollinearity test was conducted to examine the collinearity of the chosen flood conditioning factors, and it was seen that none of the factors were compromised by multicollinearity. Results showed that around three-fourths of the AUW area was classified as moderate to very high flood-prone zones, while over 20 percent was between low and very low flood-prone zones. The models applied performed well with ROC-AUC scores greater than 70 percent and MAE, MSE, and RMSE scores less than 30 percent. DT and RF algorithms were suggested for places with similar physical characteristics based on their outstanding performance and the training datasets. The study provides valuable insights to policymakers, administrative authorities, and local stakeholders to cope with floods and enhance flood prevention measures as a climate change adaptation strategy in the AUW.

Ensuring the protection of Abay region from the threat of mudflows

This article describes mudflows, a special category of hydrological threats that pose a threat to human life. Factors and types of mudflows are recorded. Mudflow hazard zones in the Abay region, conditions for mudflows, and natural factors contributing to mudflows are listed. It is characterized by the slope of the channel and the fact that, depending on the presence of channel deposits in it, the mass and speed of movement of the mudflow are subject to changes, and the mudflow is divided by the power of impact on the slope and the volume of the transported mass. An example of mudflows that occurred in Kazakhstan is given. Mudflow protection involves predicting the occurrence of mudflows and conducting special events. Therefore, the need for the construction of protective structures used in flood prevention, agroforestry and reclamation measures for special measures to protect against mudflows and special hydraulic structures is outlined. Such structures are designed to contain protected facilities with high mudflow emissions, to divert mudflow away from facilities, as well as to protect the facility from the impact of mudflow.The need to plan the terrain in the mudflow zone, install drains, divert surface and groundwater, carry out forest reclamation works and safety measures in areas with a risk of mudflows are outlined.

The impacts of rainfall and soil moisture to flood hazards in a humid mountainous catchment: a modeling investigation

Floods pose a significant threat to the safety of countries with severe societal, economic, and environmental consequences, especially the flash floods in mountainous regions. Previous studies have shown that many floods were caused by intense rainfall with highly saturated soil. In this study, we applied a physically-based distributed hydrological model (Integrated Hydrology Model, InHM) to a warm humid mountainous catchment in Southwest China, the Shouxi River. The main objective of our research is to investigate the relative importance of rainfall and antecedent soil moisture on flood generation in our study region. Our results show that an increase in rainfall return period and antecedent soil saturation ratio significantly increased peak flow and shortened peak time. There is a correlation between the ratio of antecedent soil saturation ratio to rainfall (SPR) and peak flow. When SPR <1, there is a positive correlation; when SPR >1, there is a negative correlation. Additionally, with the increase in drainage area, the relative importance of rainfall tends to decrease, while the relative contribution of soil saturation ratio tends to increase. The findings could provide support for the determination of the dominant factors influencing runoff generation in humid regions, offering scientific support for the timely and effective flood prevention and mitigation measures in mountainous regions.

Flood Risk Assessment Based on Hydrodynamic Model—A Case of the China–Pakistan Economic Corridor

Under global warming, flooding has become one of the most destructive natural disasters along the China–Pakistan Economic Corridor (CPEC), which significantly jeopardizes the construction and ongoing stability of the CPEC. The assessment of regional flood potential is, therefore, crucial for effective flood prevention and relief measures. In light of this, our study applied MIKE 11 hydrodynamic model for the Indus River Basin of Pakistan to achieve a comprehensive analysis of the flood-affected locations and depths under typical scenarios. The flood risk zones along the CPEC were evaluated using the indicator system method in conjunction with the combination weighting method. The results show that the hydrodynamic model has a Nash–Sutcliffe efficiency of 0.86, allowing for the investigation of floods at more precise temporal and spatial scales. Punjab, Sindh, and Balochistan Provinces are the main inundation areas under a 100-year flood scenario, with inundation depths ranging from 1 to 4 m. The coastal regions of Sindh and Hafizabad in Punjab witnessed the most severe floods, with maximum inundation depths exceeding 8 m. Flooding predominantly impacts the southeastern region of the CPEC. The medium- to high-risk zones comprise 25.56% of the region, while high-risk areas constitute 4.18%. Particularly, the eastern and southern regions of Punjab, along with the central and southern regions of Sindh, have been pinpointed as high-risk areas, primarily due to their dense population and riverine characteristics. Overall, our findings provide a scientific basis for informed decision making pertaining to disaster reduction and flood prevention.

ANALISIS DAYA TAMPUNG AIR PADA SALURAN DRAINASE DI LINGKUNGAN ART CENTRE KOTA DENPASAR

Flood is a natural event that can have a negative impact, for example, causing health problems and the safety of living things. The drainage channel studied in this study is the Tukad Kelandis River which stretches from Jl. Katrangan to Jl. Nusa Indah which crosses the Denpasar City Art Center. In 2021 there was a flood at the Art Center, the impact was flooding under the Ksiranawa Building where the art exhibition was held. For this problem, it is necessary to conduct a study (research) on the profile of the flood front as a flood prevention measure. Before modeling the water level profile with HEC-RAS, when estimating the capacity of the drainage channel, a quantitative method must be calculated, namely by measuring the condition of the canal in the case study. From the results of flood simulations with return times of 2, 5, 10, 20 and 25 years. The results of the evaluation of the current channel discharge at all points of the channel experienced flooding with return periods of 2, 5, 10, 20 - 25 years because the results of the current channel discharge and water level exceeded. The profile is shown in the results at all channel points where the sum of the actual water level (E.G., level) and water level feet (W.S. level) is greater than the capacity of the water discharge in the channel. In addition, at the water level (Crit. W.S.) in the Sta. 2 is 5.05 m, which is less than (W.S. level) which is 6.69 m, so the flow is supercritical.

Estimating the Socioeconomic Impacts of Flooding on Regional Economies With a Computable General Equilibrium Model

AbstractThe growing number of flood events in urban areas is causing far‐reaching economic losses and social disruptions. To implement suitable flood risk management strategies and measures for flood prevention and mitigation, it is paramount to adequately assess economy‐wide losses associated with potential flood events. The assessment of potential flood damage in the USA relies significantly on the Federal Emergency Management Agency (FEMA) Hazus Flood Model. A primary requirement to reduce uncertainty is to empirically gather user input data. Consequently, there is a need to integrate publicly accessible business data for accurate evaluation of losses in business activities. We present a novel approach for estimating both the direct losses in business activities during a flood and the total economy‐wide impact that arise from these disruptions. First, we integrate the FEMA Hazus Flood Model with Reference Solutions business‐level data to estimate the reduction in business activities (i.e., direct losses) following a 100‐year flood event in New Hanover County, North Carolina. Second, we estimate the broader economy‐wide impact these business activity losses have on total industry output, employment, value‐added and household income using a regional computational general equilibrium model. The advantage of our approach is the easy replicability of the business loss estimation process for US cities and regions of interest, which, when used in a follow‐up economic impact study, leads to estimating the total economy‐wide losses in economic activities. Policy makers relying solely on direct physical and economic damages would, by ignoring indirect losses, underestimate the benefits of investing in flood mitigation and protection.

Spatial Flood Forecasting Modeling under Lack of Data Using RS and Optimized Support Vector Machine: A Case Study of the Zahedan Watershed

This research was conducted with the aim of producing flood susceptible area maps of the Zahedan catchment in Iran during lack of data using remote sensing. To determine the factors to be included in the model, factors identified in previous studies were prepared using remote sensing and were evaluated by the information gain ratio (IGR) method and the multicollinearity diagnostic test, and ultimately 10 factors with the highest IGR values were chosen as the most effective factors in the region. The flood inventory map was produced by processing the Sentinel-1 satellite data. The gathered data were used to map flood susceptibility maps with the SVM model optimized with IWO and ACO. The prediction accuracy of the models was evaluated in terms of root mean square error (RMSE), mean absolute error (MAE), and the area under the receiver operating characteristic (ROC) curve (AUC). While both optimization algorithms are effective in improving the performance of SVM, the hybrid of SVM with IWO shows the best performance in terms of statistical measures and Friedman test results. The results of the study confirm the good performance of the proposed models in spatial prediction of flood susceptible areas. Since over half of the urban lands of the city of Zahedan are at moderate to very high risk of flooding, this area needs more attention in terms of flood prevention and control measures.

Risk Assessment Mmodel of Karst Tunnel Flood Based on Distance Discriminant Weighting and Set Pair Cloud

Flood has become the main hidden threat to the safety of the karst tunnel. Scientific and reasonable flood classification assessment and prevention measures have also become the main problems to be solved urgently in the construction and operation of tunnels. Aiming at the problems of multiple influencing factors, complex index systems, and linear processing of the connection degree of set pair analysis, a set pair cloud model based on cloud theory eigenvalues is proposed to optimize the connection degree of set pair analysis. Regarding the uncertainty of the evaluation system and the ambiguity of the evaluation grade boundary, firstly, the ridge-type membership function is used to determine the basic probability distribution of each measured index. Secondly, the distance discrimination weighting theory based on the index distance is also established, so that each measured index can assign the dynamic weight of the evaluation system. It can comprehensively determine the weight of the cloud connection degree for the system, and draw the cloud level diagram to determine the tunnel flood risk level. Finally, the proposed model is verified with tunnel flood. The results show that the evaluation results are consistent with other evaluation models and actual tunnel conditions. This model can provide guidance for flood prediction and prevention in karst tunnels.

Urban flood risk assessment characterizing the relationship among hazard, exposure, and vulnerability.

Risk assessment is an effective means to alleviate urban flood disasters and has attracted the attention of many studies. However, most previous studies about urban flood risk assessment often focused more on urban inundation area and depth, less on the inter-relationship of the components of risk. In this study, an urban flood risk assessment approach that characterizes the relationship among the three components of risk "hazard-exposure-vulnerability" (H-E-V) is developed. Firstly, eleven flood risk indicators are selected based on the flood simulation results of urban flood model and statistical data to establish the urban flood risk assessment index system. Then, the combination of analytic hierarchy process (AHP) and entropy weight method is employed to determine the weight of each indicator and the comprehensive urban flood risk is assessed. Most importantly, the coupling coordination degree model (CCDM) is used to reveal the relationship among H-E-V. After applying this method to Haikou city, China, the results show that the comprehensive effect and the coupling coordination degrees among H-E-V have a multidimensional impact on urban flood risk. For example, some sub-catchments, although at high risk of flooding, may experience a potential waste of resources. Urban flood assessment can be made more detailed and three-dimensional by comparing hazard, exposure, and vulnerability horizontally. Understanding and grasping the internal relationships among these three risk components can help implement flood prevention measures, optimize the allocation of flood prevention resources, and effectively reduce urban flood risks.

Spatial-temporal evolution of influencing mechanism of urban flooding in the Guangdong Hong Kong Macao greater bay area, China

Extreme weather has been more frequent in recent years. Urban agglomerations, as areas with a high density of human activities, have been plagued by storm flooding. Historically, the main focus of attention on flood control in urban agglomerations has gradually shifted from underground pipe networks to the impervious surface, reflecting profound changes in the influencing mechanism of urban flooding. Exploring the evolution of the mechanisms influencing urban flooding in the Guangdong Hong Kong Macao Greater Bay Area (GBA) urban agglomeration is of great reference significance for formulating flood prevention and control measures and promoting high-quality development of the GBA city cluster. In this paper, we fully use the collected information on urban flooding events from 1980 to 2018 in the GBA city cluster. Correlation analysis and geographically weighted regression (GWR) are used to analyze the influence of impervious surface percentage (ISP), impervious surface aggregation index (AI), impervious surface mean shape index (Shape_MN), vegetation cover (FVC), water surface ratio (WSR), relative elevation (RE) and slope on flooding in urban clusters and their evolution characteristics over time from a global perspective and spatial heterogeneity, respectively. The results show that: 1) ISP, AI, Shape_MN, and WSR are positively correlated with urban flooding, while FVC, RE, and Slope are negatively correlated with urban flooding. The correlations of each factor showed a general trend of gradual strengthening over time, and the increase rate slowed down after 2000, while the correlation of WSR showed a relatively noticeable decrease. 2) The GWR results show that each factor’s influence on urban flooding has pronounced spatial-temporal heterogeneity, and each factor shows different distribution characteristics. This study uses long time series of urban flooding point data to explore the spatial-temporal evolution of the influencing mechanism of urban flooding in the GBA urban agglomeration. We hope to provide a scientific basis for an in-depth understanding of the causes of urban flooding in the GBA, intending to provide auxiliary decision-making support for the formulation of waterlogging prevention and control measures.

Short-term Runoff Prediction Optimization Method Based on BGRU-BP and BLSTM-BP Neural Networks

Runoff forecasting is one of the important non-engineering measures for flood prevention and disaster reduction. The accurate and reliable runoff forecasting mainly depends on the development of science and technology, many machine learning models have been proposed for runoff forecasting in recent years. Considering the non-linearity and real-time of hourly rainfall and runoff data. In this study, two runoff forecasting models were proposed, which were the combination of the bidirectional gated recurrent unit and backpropagation (BGRU-BP) neural network and the bidirectional long short-term memory and backpropagation (BLSTM-BP) neural network. The two models were compared with the gated recurrent unit (GRU), long short-term memory (LSTM), bidirectional gated recurrent unit (BGRU), and bidirectional long short-term memory (BLSTM) models. The research methods were applied to simulate runoff in the Yanglou hydrological station, Northern Anhui Province, China. The results show that the bidirectional models were superior to the unidirectional model, and the backpropagation (BP) based bidirectional models were superior to the bidirectional models. The bidirectional propagation was conducive to improving the generalization ability of the model, and BP neural network could better guide the model to find the optimal nonlinear relationship. The results also show that the BGRU-BP model performs equally well as the BLSTM-BP model. The BGRU-BP model has few parameters and a short training time, so it may be the preferred method for short-term runoff forecasting.

With the Measuring Rod against the Floods: Ferdinand Verbiest and His Forgotten Introduction of Benedetto Castelli’s River Hydraulics to China

The monumental <italic>Studies to Fathom Principles</italic> (<italic>Qiongli xue</italic> 窮理學; 1683) by Ferdinand Verbiest S. J. (Nan Huairen 南懷仁, 1623-1688) was never printed, and its exact content is not known. A section of the only extant, though incomplete, manuscript deals with fluvial flood prevention and river control measures, a subject that until then had not cropped up in any Chinese-language work of the Jesuits. In this section, Verbiest not only described the already well-known Aristotelian theory of the origin of rivers, but also introduced to China new scientific propositions, concepts, and numerical examples originating from the seminal Renaissance work <italic>Della misura dell’acque correnti</italic> (<italic>Of the Mensuration of Running Waters</italic>; 1628) by Benedetto Castelli (1578-1643). In addition, Verbiest presented to his readers some noteworthy examples of pertinent Western achievements such as the pound-lock with miter gate, and he provided them with a simple economic analysis of flood control options. The significance and possible influence of Verbiest’s text on further developments in Chinese approaches to water engineering are discussed, highlighting a hitherto largely disregarded facet of Western science and technology transfer in the field of river hydraulics and flood management.

Earth Science, Art and Coastal Engineering at the Seaside: Envisioning an Open Exploratorium or Geo-Promenade at Weston-super-Mare, Somerset, United Kingdom

The paper outlines how an outdoor ‘exploratorium’ can be curated to place field observations, together with some knowledge of the local environment, in a manner that relates to geology, geomorphology and artistic aesthetics. The exploratorium can also be used to help explain what is seen, touched or felt as part of ‘sensory geology’. The locations used are on an accessible walk, a geo-promenade, along the sea front of a coastal town, Weston-super-Mare, England. Sites, such as a sea wall and recent engineering structures, are linked to flood prevention measures and sculpture and stone promenade furniture relate to various aspects of geoheritage. Notions of consilience and decision-making in the behavioural environment are introduced, together with ways in which perceptions of the landscape can be shared with visually impaired visitors. Notes are provided to illustrate the additional information (metadata) that might be supplied in constructing a geo-promenade. The use of mobile technologies for recording observations, providing locations (using decimal Latitude Longitude designations) and general information is also discussed with respect to accessible visits. Attention is also given to cognition and educational models of experiential discussion and knowledge sharing that can be used in exploratoria and geoheritage in general.