Flooded Areas Research Articles

Conservation Priorities for Threatened Fish to Withstand Climate Crisis: Sustainable Capture and Protection of Inland Hydrographic Ecosystems

Globally, suitable freshwater habitats are undergoing alterations and fish population declines, primarily attributed to the swift changes in climate and land use. Developing an effective conservation policy for freshwater fish necessitates careful consideration of the impacts of climatic and spatial factors. This study focuses on the analysis of 64 threatened freshwater fish in Bangladesh to anticipate their current and future climatically suitable habitats, utilizing the bioclim() species distribution model. Additionally, this study examines existing inland hydrographic networks and their corresponding harvest rates. The findings indicate that approximately 75% of the area of occupancy for the studied species is currently climatically suitable, but this is expected to decrease to 13% under future climate scenarios. Notably, 27 threatened species are at risk of lacking climatically suitable habitats in the future within their current area of occupancy. The three components of hydrographic networks—floodplains, rivers, and natural lakes—play varying roles in providing a climatically suitable habitat for the studied species. For instance, only 34% of threatened fish species are projected to find a suitable habitat over flood areas, 23% over rivers, and 16% over lakes. Existing protected areas presently offer limited protection (21% suitable area), expected to decline to 6% in the future, with no dedicated protected areas for freshwater fish. Floodplains are highlighted for providing habitat connectivity and facilitating brood fish dispersal. However, the unregulated and unmonitored annual harvest of freshwater fish from floodwater and rivers poses a potential silent cause for rapid population decline. Prioritizing the management of hydrographic components to maintain habitat connectivity, legal protection for threatened fish species, and establishing permanent protected areas for fish are crucial aspects in developing a conservation policy to mitigate the impact of future climate scenarios on threatened freshwater species.

Multilevel data simplification methods for flood process visualizations based on visual perceptions

ABSTRACT Visualizations of flood processes require a balance between scientific authenticity and realistic expressions. As the flood area increases, the amounts of time-series data that are produced by flood models often exceed the capacity of computer rendering, leading to poor user experiences and low visualization effectiveness. Therefore, this study carried out visual perception experiments and proposed a multilevel simplification and scheduling method for flood process data based on visual perceptions. This method first simplifies flood data by flood feature point selection according to conclusions related to visual perception, then triangulated irregular networks are built, and finally, flood data scheduling and rendering are achieved through multiple levels of detail combined with visual ranges. An experimental analysis using a 3D visualization prototype system shows that the proposed method can improve the efficiency of visual expressions while preserving flood morphology features.

Mapping the Lava Flood Hazard Using the Flood Discharge Approach and 2D Hydrodynamic Modeling at the Rejali River, Mount Semeru

In December 2021, Mount Semeru experienced an eruption accompanied by extreme rainfall, which resulted in lava floods, known as lahars or debris flows. The lava flood destroyed infrastructure, resulting in loss of life. Various rivers surrounding Mount Semeru, including the Rejali River, experienced the effects of this phenomenon. To address this, a study is needed to analyze the occurrence and frequency of lava floods over specific time intervals through the creation of a hazard map. This study aims to map the hazard of lava floods for various return periods using a coupled HEC-HMS and HEC-RAS software alongside a lava flood discharge approach. The HEC-HMS software is used to simulate hydrological processes, to obtain the lava flood discharge, while the HEC-RAS is used to model a two-dimensional (2D) lava flood hazard map. The input parameters of the modeling in this study are rainfall intensity, soil type, land cover, river distance, slope, and elevation. The results show that the flood area covers 9.55% of the total study area by 2 year return period (Q2), 11.80% by Q10, 14.10% by Q50, and 15.72% by Q200 with an overall validation Root Mean Square Error (RMSE) of 0.16. These changes are determined by the discharge volume from each return phase and the river's shallow depth, which causes overflow beyond the river's ability to accommodate the flow. Thus, this study suggests that the models successfully generated a reliable model for mapping the risk of lava floods on the Rejali River. These findings can help the government reduce disaster losses through adequate adaptation and mitigation initiatives.

Autecology of the extant ostracod fauna of Lake Ohrid and adjacent waters - a key to paleoenvironmental reconstruction

Understanding the ecology of bioindicators such as ostracods is essential in order to reconstruct past environmental and climate change from analysis of fossil assemblages preserved in lake sediment cores. Knowledge of the ecology of ancient Lake Ohrid’s ostracod fauna is very limited and open to debate. In advance of the Ohrid ICDP-Drilling project, which has potential to generate high-resolution long-term paleoenvironmental data of global importance in paleoclimate research, we sampled Lake Ohrid and a wide range of habitat types in its surroundings to assess 1) the composition of ostracod assemblages in lakes, springs, streams, and short-lived seasonal water bodies, 2) the geographical distribution of ostracods, and 3) the ecological characteristics of individual ostracod species. In total, 40 species were collected alive, and seven species were preserved as valves and empty carapaces. Of the 40 ostracod species, twelve were endemic to Lake Ohrid. The most common genus in the lake was Candona, represented by 13 living species, followed by Paralimnocythere, represented by five living species. The most frequent species was Cypria obliqua. Species with distinct distributions included Heterocypris incongruens, Candonopsis kingsleii, and Cypria lacustris. The most common species in shallow, flooded areas was H. incongruens, and the most prominent species in ditches was C. kingsleii. C. lacustris was widely distributed in channels, springs, lakes, and rivers. Statistical analyses were performed on a “Lake Ohrid” dataset, comprising the subset of samples from Lake Ohrid alone, and an “entire” dataset comprising all samples collected. The unweighted pair group mean average (UPGMA) clustering was mainly controlled by species-specific depth preferences. Canonical Correspondence Analysis (CCA) with forward selection identified water depth, water temperature, and pH as variables that best explained the ostracod distribution in Lake Ohrid. The lack of significance of conductivity and dissolved oxygen in CCA of Ohrid data highlight the uniformity across the lake of the well-mixed waters. In the entire area, CCA revealed that ostracod distribution was best explained by water depth, salinity, conductivity, pH, and dissolved oxygen. Salinity was probably selected by CCA due to the presence of Eucypris virens and Bradleystrandesia reticulata in short-lived seasonal water bodies. Water depth is an important, although indirect, influence on ostracod species distribution, which is probably associated with other factors such as sediment texture and food supply. Some species appeared to be indicators for multiple environmental variables, such as lake level and water temperature.

Structure and vulnerability of the ichthyochory network in wetland forests of Central Amazonia

AbstractThe interaction between fish and plants is vital for the dynamics of ecosystems since it influences plant distribution and regeneration patterns. In the floodable areas of the Amazon, these interactions are mainly structured by the flood pulse, which enables seed dispersal via water (hydrochory) and fish (ichthyochory), and which contributes to the formation of complex mutualistic networks. Our study evaluated the structure (modularity, nestedness, specialisation, and robustness) of the network of dispersal of seeds by frugivorous fish in a floodplain forest in Central Amazonia. We expect the binary network to have a nested pattern, while the weighted network is expected to have a non‐nested structure; that generalist frugivorous species should constitute the core of the network, while specialist frugivorous species will be peripheral; that the size of fish and seeds is related to specialisation, and that the robustness of the network weakens as generalist frugivorous fish are removed. We found 5012 intact seeds from 49 plant species in the digestive tracts of 11 species of frugivorous fish. A nested and modular pattern was found for the binary and weighted networks, albeit with a low degree of nestedness. Our network proved relatively robust when the frugivores were removed, whereby all the fish and plant species became peripheral. No relationship was found between the size of the fish and the seeds and the degree of specialisation. Considering the anthropogenic impacts that can cause modifications in seed dispersal networks, knowing the structure of mutualistic networks is fundamental in order to be able infer the vulnerability of the interactions as a result of changes in the ecosystem.

Malaria transmission heterogeneity in different eco-epidemiological areas of western Kenya: a region-wide observational and risk classification study for adaptive intervention planning

BackgroundUnderstanding of malaria ecology is a prerequisite for designing locally adapted control strategies in resource-limited settings. The aim of this study was to utilize the spatial heterogeneity in malaria transmission for the designing of adaptive interventions.MethodsField collections of clinical malaria incidence, asymptomatic Plasmodium infection, and malaria vector data were conducted from 108 randomly selected clusters which covered different landscape settings including irrigated farming, seasonal flooding area, lowland dryland farming, and highlands in western Kenya. Spatial heterogeneity of malaria was analyzed and classified into different eco-epidemiological zones.ResultsThere was strong heterogeneity and detected hot/cold spots in clinical malaria incidence, Plasmodium prevalence, and vector abundance. The study area was classified into four zones based on clinical malaria incidence, parasite prevalence, vector density, and altitude. The two irrigated zones have either the highest malaria incidence, parasite prevalence, or the highest malaria vector density; the highlands have the lowest vector density and parasite prevalence; and the dryland and flooding area have the average clinical malaria incidence, parasite prevalence and vector density. Different zones have different vector species, species compositions and predominant species. Both indoor and outdoor transmission may have contributed to the malaria transmission in the area. Anopheles gambiae sensu stricto (s.s.), Anopheles arabiensis, Anopheles funestus s.s., and Anopheles leesoni had similar human blood index and malaria parasite sporozoite rate.ConclusionThe multi-transmission-indicator-based eco-epidemiological zone classifications will be helpful for making decisions on locally adapted malaria interventions.

DETERMINATION OF RISK AREAS IN THE CIMAHI CITY DRAINAGE ASPECT BASED ON 2018 CITY SANITATION STRATEGY GUIDELINES

Cimahi City is one of the cities that participated in the Accelerated Habitation Sanitation Development Program in 2011. This was done because the Cimahi City Government realized that the sanitation conditions in Cimahi City were still of concern. In 2015, the coverage of drainage system services reached 89.87%. Meanwhile, inundation and flood area in 2018 in Cimahi City reached 36.4 hectares or equal to 0.76% of the total area of Cimahi City. Inundation and floods that occur resulting in displaced residents as well as financial losses. Based on the following problems, this study was conducted to calculate the level of risk in each urban village in Cimahi City. The level of risk is expressed in scores ranging from 1 - 4. A score of 1 means very low risk, a score of 2 means low risk, a score of 3 means high risk, and a score of 4 means very high risk. Determination of risk scores involves exposure factors and impact factors Exposure factors consist of inundation area percentage, sanitation risk index (IRS) score based on EHRA, and OPD perceptions. While the impact factors consist of population, population density, poverty rate, and urban / rural function.

Towards Development: The Yellow River project and UNRRA’s technical assistance to China, 1944–1947

Abstract This article examines an international endeavour to manage the 1938 Yellow River dyke breach and to bring mechanized farming to the flooded area, as part of the UNRRA China Programme (1944–1947). It reveals why a Chinese Nationalist vision of international aid entailed technical assistance, and how this call for development was received by UNRRA’s multi-national, albeit predominantly American, cadre of experts at a transitional period from war to reconstruction. This article argues that technical assistance is integral to understanding the history of UNRRA and its role in negotiating different visions for the post-war world, especially a developmental one. Development did not emerge as a united concept; instead, the ambiguity created a space for experts with different backgrounds to fit themselves into the post-war programme. Focusing on those recipients and fieldworkers that shaped the UNRRA aid on the ground, it offers a non-European perspective for understanding how development thoughts gained momentum through a post-war programme, leading the way to global proliferation of development projects.

Using geomorphologic indicators in preparation for flood zoning and flood risk maps in the Kashafroud basin, Iran

AbstractThe risk of flooding has become more significant in many parts of the world due to climate change and increased urbanization. Flood has devastating effects on infrastructure, and communities, causing damage to property and loss of life. Simulation of flood extent in a particular area is done by using various mathematical models, hydrologic‐hydraulic models, and datasets. Flood modeling using hydraulic‐hydrological models has many errors due to the lack of hydraulic‐hydrologic data and insufficient statistical period length. This study demonstrates the fact that the geomorphological index (GI) method, which is based on the digital elevation model and requires little hydraulic‐hydrologic data, is an effective method for flood modeling. Flood zoning based on GI was performed within the Kashafroud basin with 25, 100, and 200‐year return periods by using geomorphic flood area (GFA) plugin in QGIS software. The true positive rates were 0.985, 0.989, and 0.992, respectively, which showed the high accuracy of flood zoning based on the GI method. Here proposed method showed that using the GFA plugin offers a good way for the flood risk assessment in a basin with the lack of measured data as an alternative to the hydraulic‐hydrological methods.

HUMAN RIGHTS TO HEALTH AND WELLBEING FOR VULNERABLE GROUPS IN TIDAL FLOOD AREAS: A POLICY BRIEF

Objective: Mental health problems in vulnerable groups in tidal flood areas include impaired self-concept, stress, and anxiety. Many policies regulate flood management especially to manage mental health problems in disaster areas. However, during tidal floods, the implementation of programs to handle psychosocial problems was not optimal. This research aims to develop policy recommendations to meet the need for the right to a healthy and prosperous life among vulnerable groups in tidal flood areas. Method: This research is a review type of research that examines the policies and legal norms that apply in Indonesia and is related to the tidal flood disaster situation. Prescriptive analysis is carried out by researchers so that researchers can describe problems based on the perspective of policy studies and legal norms that have been studied and analyzed using literature studies. Result: Various efforts to deal with tidal floods have been carried out, but they still focus on improving the physical environment and dealing with physical health problems. Mental health problems are still ignored because they tend not to be studied and presented by society and the government. Fulfillment of the right to health is unequal because it is not implemented holistically. Conclusion: Exposure to tidal floods that cannot be changed and prevented requires the existence of policies that regulate the prevention and treatment of mental health problems. Existing policies need to be integrated with each other so that they can be implemented technically by carrying out continuous mental health efforts.

ANALISIS PENGETAHUAN MITIGASI BANJIR PADA MASYARAKAT KABUPATEN BANJAR DENGAN PENDEKATAN METODE REGRESI LOGISTIK BINER

The largest flood condition in South Kalimantan Province occurred in 2021. The worst flooded area is Banjar Regency with 27,249 fatalities. Floods also affected the agriculture and fisheries sectors, causing agricultural land productivity to decrease to 87,598 tons from 2021 to 2020. A total of 1,838 aquaculture businesses suffered losses of up to 70 billion rupiah. The causes of flooding do not only come from natural factors but can come from other factors such as a lack of knowledge of flood mitigation, resulting in huge losses for the community. Previous research states that the factors that influence flood disaster mitigation are the level of education and income. This study aims to determine the factors that influence flood mitigation knowledge in Banjar Regency communities using the binary logistic regression method. The results of the study provide differences from previous studies, namely the environmental factor with category 1, the implementation of environmental management by the community affects flood mitigation knowledge with a p value (0.027) < α (0.05) and a value of W (2.2198) > Z_table (1.960). The odds ratio value shows that the probability of the Banjar Regency community having flood mitigation knowledge is 2.79 times greater than other variable categories. The model explains an influence of 31.6% with an AIC value of 125. The respondents flood mitigation knowledge in managing the environment includes all types and stages of flood disaster mitigation related to local wisdom in the respondents location, namely several terms such as "Apar-Apar, Jukung Terpal, Galangan, Kelambu Kolam". There are still some things that need to be maximized for flood mitigation knowledge, namely the formation of disaster resilient villages in Martapura City, East and West Sub-districts. Dissemination of information on climate-smart agriculture training to farmers. Realization of temporary waste bin facilities in Banjar Regency.

Social learning about climate risks

AbstractWith a social network adjacency matrix constructed from the Facebook Social Connectedness Index (SCI), this paper examines whether social learning facilitates climate risk perception updates to inform climate adaptation. We find that Hurricanes Harvey and Irma‐induced regional flooding increased flood insurance policies nationwide to the extent of each county's social network proximity to the flooded areas, with a corresponding update in climate risk perception. Social learning resulted in an additional 250,000 policies in flooded counties and 81,000 policies in unflooded counties over 3 years. We find evidence of the salience effect but no support for adverse selection or over‐insurance.

Proposal of rescue strategies and evaluation of their effectiveness in long-term flooded areas considering the effect of drainage processing

In response to the intensification of floods, the limits of rescue activities for people in need of rescue are being stressed. To solve such a situation, the request for residents to evacuate voluntarily has been considered, but the evacuation awareness of residents has not been improved yet. Therefore, it is necessary to enhance the performance of rescue operations and to provide more specific and critical evacuation instructions to those residents who cannot be rescued. In this paper, we propose a new rescue operation model that incorporates the effect of drainage treatment work in the flooded area, which is not a function of rescue operation. Specifically, we introduced new rescue strategies such as relocation of advancing bases and temporary transport sites, taking into account the fact that the inundated area changes. Based on the proposed rescue strategy, a full-scale rescue simulation was conducted, and it was confirmed that more residents could be rescued than with the conventional strategy. By comparing various strategic scenarios, we have identified the characteristics of rescue strategies that take wastewater treatment into account. The results also provide knowledge for future flood countermeasures, such as the importance of strengthening drainage treatment capacity and improving the reliability of its operation in order to take advantage of the strengths of rescue strategies, and the introduction of more focused countermeasures based on the specific residential areas and flooding conditions for those residents who cannot be rescued even with the above-mentioned measures.

A novel machine learning tool for current and future flood susceptibility mapping by integrating remote sensing and geographic information systems

Flood mapping is essential for managing and mitigating the risks associated with flood events. This study integrates weighted overlay analysis and analytical network process to create a flood susceptibility map. Twelve factors were selected to assess flood risk in the region, and an analytical network process was used to derive weights of factors. Weighted overlay analysis was then used to apply weights to the flood conditioning factors to prepare the flood susceptibility map. The most prominent historical flood extent was derived by using Landsat 8, Sentinel-2 and Sentinel-1 satellite imageries, spectral indices and decision tree model to generate a flood inventory map. The flood susceptibility map was assessed for accuracy using the flood inventory map, achieving an overall accuracy rate of 88.3 %. The primary factors affecting flood risk were elevation, slope, and distance from the stream, with high-risk areas mainly located downstream. To develop the flood risk assessment model, the essential factors were classified into four main categories: topographical, environmental, hydrological, and anthropological. All possible input combinations were checked using the outlier robust extreme learning machine for one to twelve input variables, and the best model was selected using the outlier robust extreme learning machine with the input combination of five variables (i.e., normalizes difference vegetation index, geology, precipitation, elevation, and slope). Based on the Sixth Intergovernmental Panel on climate change report, the developed outlier robust extreme learning machine was used to project potential flood areas in the next 78 years. Based on the different scenarios, the results indicated that 10.93 %, 8.55 %, 8.09 %, 11.99 %, and 16.28 % of all areas are projected to be highly and very highly flood susceptible. The tools and methods outlined in this study can assist decision-makers in preparing for and responding to floods. Moreover, the method developed in this study can be implemented in watersheds and urban areas and help manage flood risk in urban drainage systems.

Informing the Conservation of Ephemerally Flooded Wetlands Using Hydrologic Regime and LiDAR-Based Habitat Assessments

Integrated assessments of wetland hydrologic regimes and other environmental factors are key to understanding the ecology of species breeding in ephemerally flooded wetlands, and reproductive success is often directly linked to suitable flooding regimes, both temporally and spatially. We used high-resolution Light Detection and Ranging (LiDAR) data to develop bathymetric stage–flooded area relationships, predict spatial extent of flooding, and assess vegetation structure in 30 pine flatwoods wetlands. For a subset of wetlands with monitoring wells, we then integrated bathymetric and water level data to create multi-year time series of daily flooded areas. We then related the observed flooded areas to topographic and landscape metrics to develop models predicting flooded extents in wetlands without monitoring wells. We found that stage–area curves varied depending on wetland size and bathymetry, such that a one-cm increase in water depth could generate flooded area increases ranging from hundreds to thousands of square meters. Flooded areas frequently fragmented into discrete flooded patches as wetlands dried, and there was a weak positive correlation between hydroperiod and mean flooded area across multiple years (r = 0.32). To evaluate the utility of using LiDAR-derived data to support the conservation of wetland-breeding species, we combined metrics of flooding and vegetation to map potentially suitable habitat for the imperiled reticulated flatwoods salamander (Ambystoma bishopi). Overall, projects focusing on the ecology of wetland-breeding species could gain a broader understanding of habitat effects from coupled assessments of bathymetry, water level dynamics, and other wetland characteristics.

Real-time flood forecasting using an integrated hydrologic and hydraulic model for the Vamsadhara and Nagavali basins, Eastern India

AbstractDue to recent rainfall extremes and tropical cyclones that form over the Bay of Bengal during the pre- and post-monsoon seasons, the Nagavali and Vamsadhara basins in India experience frequent floods, causing significant loss of human life and damage to agricultural lands and infrastructure. This study provides an integrated hydrologic and hydraulic modeling system that is based on the Soil and Water Assessment Tool model and the 2-Dimensional Hydrological Engineering Centre-River Analysis System, which simulates floods using Global Forecasting System rainfall forecasts with a 48-h lead time. The integrated model was used to simulate the streamflow, flood area extent, and depth for the historical flood events (i.e., 1991–2018) with peak discharges of 1200 m3/s in the Nagavali basin and 1360 m3/s in the Vamsadhara basin. The integrated model predicted flood inundation depths that were in good agreement with observed inundation depths provided by the Central Water Commission. The inundation maps generated by the integrated modeling system with a 48-h lead time for tropical cyclone Titli demonstrated an accuracy of more than 75%. The insights gained from this study will help the public and government agencies make better decisions and deal with floods.

Refined analysis of flood-regional composition under changing environment in the middle reach of Hanjiang River

To investigate the flood-regional composition under changing environmental conditions in the middle reach of Hanjiang River (MHR), a data-driven hydrological simulation model and its related quantitative methods were developed. The flood-regional composition of Huangzhuang(HZ) in the MHR was quantitatively analyzed, and the influence of environmental changes on river flood routing was discussed. The primary research findings are as follows: ① A hydrological simulation model based on support vector regression machine (SVRM) is constructed to simulate the daily average flow process of HZ from 1965 to 2021. The Nash-Sutcliffe Efficiency (NSE) coefficient achieved values above 0.95, and the overall relative error (RE) was within ± 1 %, indicating excellent simulation performance. ② A quantitative analysis method has been proposed to identify the composition of flood areas. The results indicate that the upper reach of Hanjiang River (UHR) is the primary contributor to floods in the MHR, accounting for 60.62 % to 78.05 % of the total. The Tangbai River (TR) contributed between 14.1 % and 27.4 %, whereas the Nan River had a smaller contribution of only 6.83 % to 8.85 %. ③ Trend analysis indicates that the proportion of floods originating from the UHR increases in the summer flood season and decreases in the autumn flood season, while those changes of TR and Nanhe River (NR) are coincidental, especially in the autumn flood season, the proportion of floods in the TR increases significantly. The impact of floods from the UHR and TR cannot be ignored when implementing flood control measures. ④ A comprehensive analysis method has been proposed to quantify the integrated impacts of environmental changes. The results show that environmental changes had a relatively minor impact on flood routing and its flood-regional composition. However, they did affect the flood propagation process, resulting in earlier occurrences in peak flow, increased in peak discharge, and rapid rise and fall of floodwaters for floods exceeding 12,000 m3/s. These research findings provide strong foundational support for designing flood-regional, as well as flood control and disaster reduction systems in the MHR.

Impacts of anthropocene sea-level rise on people, environments, and archaeological sites in Marajó Island, Brazilian Amazonia

Coastal marine systems worldwide present several risks through the global sea-level rise (SLR) trends. The Amazon Delta and Estuary (ADE) in Pará state, Brazil, is a mainland archipelago with variable landscapes and vulnerable archaeological sites in the context of global climate change. We aimed to recognize the human and environmental conditions knowledge for support directives to mitigate possible consequences of climate change in the lower Amazonia drainage basin system, in support of the Sustainable Development Goals (SDGs) of the United Nations. We map landscapes, estimated floodable areas of 2, 3, and 6 m of SLR using DSAS 5.0 (Digital Shoreline Analysis System), investigated coastline morphology changes between 1973 and 2019 (46 years), sampled soils at East Marajó Island, and suggested mitigation actions. The results indicate that several environments and archaeological sites are at heavy risk in front of climate change, mainly in the lowlands most submitted to the waterlogging process. Mangrove revealed several SLR effects with aggressive erosion at the coastline. The results provide spatial information regarding important aspects of SLR impacts in the ADE and its environmental, people, and archaeological fragilities.

A heterogeneous robots collaboration for safety, security, and rescue robotics: e-ASIA joint research program for disaster risk and reduction management

In the face of humanitarian crises such as torrential rainfall, resulting floods, and landslides, rapid rescue operations are often imperative. However, owing to the inherent dangers and unpredictability of such circumstances, immediate on-site aid delivery is frequently unfeasible. In such challenging scenarios, mobile robot systems have emerged as the optimal solution for aiding search and rescue efforts. The 'Informational system for management of flood and landslide disaster areas using a distributed heterogeneous robotic team' project, initiated by the International e-ASIA Joint Research Program, united research teams from Japan, Russia, and Thailand, each contributing unique expertize and experience towards common objectives. Drawing upon our extensive theoretical and practical knowledge in disaster response research, we developed an integrated international operational framework for disaster site management, centered on dispersed, heterogeneous semi-autonomous Unmanned Aerial Vehicles (UAVs), Semi-Autonomous Rough Terrain Vehicles (UGVs), and Semi-Autonomous Surface Vehicles (USVs). This paper provides an overview of the methodologies, models, and algorithms employed throughout the successful three-year project conducted by the Thailand team while also directing interested readers to supplementary research papers for in-depth insights.

I-CVSSDM: IoT Enabled Computer Vision Safety System for Disaster Management

INTRODUCTION: Around the world, individuals experience flooding more frequently than any other natural calamity.
 OBJECTIVES: The motivation behind this research is to provide an Internet of Things (IoT)-based early warning assistive system to enable monitoring of water logging levels in flood-affected areas. Further, the SSD-MobiNET V2 model is used in the developed system to detect and classify the objects that prevail in the flood zone.
 METHODS: The developed research is validated in a real-time scenario. To enable this, a customized embedded module is designed and developed using the Raspberry Pi 4 model B processor. The module uses (i) a pi-camera to capture the objects and (ii) an ultrasonic sensor to measure the water level in the flood area.
 RESULTS: The measured data and detected objects are periodically ported to the cloud and stored in the cloud database to enable remote monitoring and further processing.
 CONCLUSION: Also, whenever the level of waterlogged exceeds the threshold, an alert is sent to the concerned authorities in the form of an SMS, a phone call, or an email.