Flood Hazard Mapping Research Articles

Geographic Information System application in flood risks prevention, hazards reduction and planning

The effects of Flood hazard mapping and flood inundation modelling in saving lives and properties in our societies cannot be overemphasized. Haphazard land use planning and lack of compliance to rules and regulations concerning setbacks have been observed to worsen the impacts of flooding and equally pose as major contributing factors to the exposure of people to flood risks in the study area. The study aimed at determining the built areas within the floodable area. Integrated Geographic Information System (GIS) and Remote Sensing were utilized to analyze the topographic data and the land use data generated from the satellite imagery of the area. The study revealed that nearly half of the buildings and infrastructures in the study area lie within the flood plain. Applications of GIS and Satellite Imagery analysis techniques were used to estimate the population at risk of flooding in the study area. We submit that space based and Geospatial data analysis and applications in flood risks assessment and planning prior to infrastructural development would go a long way in the preservation of lives and properties and prevent great economic loss as a result of flooding.

Novel ensemble machine learning models in flood susceptibility mapping

The research aims to propose the new ensemble models by combining the machine learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k-nearest neighbour (KNN), boosted regression tree (BRT), and logitboost (LB) with the base classifier adabag (AB) for flood susceptibility mapping (FSM). The proposed models were implemented in the central west coast of India, which is vulnerable to flood events. For flood inventory mapping, a total of 210 flood localities were identified. Twelve effective factors were selected using the boruta algorithm for FSM. The area under the receiver operating characteristics (AUROC) curve and other statistical measures (sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and mean absolute error (MAE)) were employed to estimate and compare the success rate of the approaches. The validation results of the individual models in terms of AUC value were AB (92.74%) >RF (91.50%) >BRT (90.75%) >LB (89.07%) >NSC (88.97%) >KNN (83.88%), whereas the ensemble models showed that the AB-RF (94%) was of the highest prediction efficiency followed by, AB-KNN (93.33%), AB-NSC (93.02%), AB-LB (92.83%), and AB-BRT (92.64%). The outcomes of the ensemble models established that the AB is more appropriate to increase the accuracy of different single models. Therefore, this study can be useful for proper planning and management of the study area and flood hazard mapping in alike geographic environment.

Local Participatory Flood Hazard Mapping’s Assessment and Coping: A Conceptual Model of Sustainability in Downstream Area of Belu Regency in the Western Timor Island, East Nusa Tenggara Province, Indonesia

This study applies interview, Focus Group Discussion (FGDs), Participatory Geographical Information Systems (pGIS), and a conceptual model of sustainability (CMS) using risk perception of local community to map flood hazard and assess the social and cultural copings to cope with river flooding in downstream areas i.e., Lasaen, Umatoos, and Fafoe villages of West Malaka Subdistrict of Belu Regency, Indonesia. The results of this study indicate that the rural-river flooding was inundated at all three villages. The cycle of flood is twenty-years per event (1939, 1959, 1975, 1999 through 2000), and from 2000 its occurrence was each year until 2012. Based on interviews and FGDs, the information of flood characteristics of Lasaen and Fafoe villages were similar, but Umatoos village was not. The single longevity of flood inundation was in Fafoe village (1 week-1 month). Whilst Lasaen and Umatoos villages were experiencing less duration of flood inundations (0-7 days to 14-21 days). Lasaen and Umatoos Villages were dealing with flood depth’s variation from the lowest depth (0-50cm) to its deepest (251-300cm). For CMS, the most invaluable coping that might be sustainable was cultural capital. Both social and cultural coping enhancements were implemented by local community. The minimum and lack of both these transformable sub-copings were still the problem in the discourse unit of sustainability. As each sub-coping would be overlapped if there has no sufficient distribution of it, utilized by the local community. The genuineness local knowledge of community in applying their social and cultural copings in sustainability is seen as a unique reference and a useful form of local wisdom which can be highlighted and adopted as an effective and/or example discourse analysis by the other rural villages in developing nations that are also still struggling and coping with flood disaster.

Hydrologic Model for Flooding in Manupali Watershed and Its Implications to Land-Use Policies

Flooding has become a recurring event in the Province of Bukidnon causing severe destruction to houses, buildings, infrastructure and livelihood. Since the province is not exempted to flooding events as an impact of the typhoon, understanding the watershed hydrologic behavior is essential for vulnerability and risk assessment as to disaster preparedness and risk reduction. The study aims to analyze the hydrologic response of Manupali watershed through flood hazard maps, hydrologic and hydraulic models. This paper presents the combination of geographic information system, high -resolution digital elevation model, land cover, observed hydro-meteorological data and the combined Hydrologic Engineering Center-Hydrologic Modeling System and River Analysis System models. The hydrologic model assesses the relationship between rainfall and discharge of the watershed and the hydraulic model computes the flood depth and flow pattern in the floodplain. Upon calibration, the over-all performance of the hydrologic model is “very good” performance rating based on the standards set by Moriasi et.al. (2015) with index values of 0.89, 0.75, 0.46 for Nash-Sutcliffe Coefficient of Model Efficiency, Percentage Bias, and Root Mean Square Error, respectively. The calibrated hydrographs were used to produce flood hazard maps in 2, 5, 10, 25, 50, and 100-year return periods as well as determined the number of flooded buildings in each flood hazard level per return period. The flood hazard maps may contribute to science-based land-use policy formulation, land-use zoning, planning and management to mitigate extreme rainfall-induced flood risks in the affected Barangays in the Manupali watershed.

Hydrologic Model for Flooding in Manupali Watershed and Its Implications to Land-Use Policies

Flooding has become a recurring event in the Province of Bukidnon, causing severe destruction to houses, buildings, infrastructure, and livelihood. Since the province is not exempted in flooding events as an impact of typhoons, understanding the watershed hydrologic behavior is essential for vulnerability and risk assessment as to disaster preparedness and risk reduction. The study aims to analyze the hydrologic response of Manupali watershed through flood hazard maps, hydrologic, and hydraulic models. This paper presents the combination of geographic information system, high -resolution digital elevation model (DEM), land cover, observed hydro-meteorological data, and the combined hydrologic engineering center-hydrologic modeling system and river analysis system models. The hydrologic model assesses the relationship between rainfall and discharge of the watershed and the hydraulic model computes the flood depth and flow pattern in the floodplain. Upon calibration, the over-all performance of the hydrologic model was rated very good in its performance based on the standards set by Moriasi et al. (2015) with index values of 0.89, 0.75, 0.46. The calibrated hydrographs were used to produce flood hazard maps in 2, 5, 10, 25, 50, and 100-year return periods, and assessed the number of flooded buildings in each flood hazard level per return period. The flood hazard maps may contribute to science-based land-use policy formulation, land-use zoning, planning, and management to mitigate extreme rainfall-induced flood risks in the affected barangays in the Manupali watershed.

Urban flood hazard mapping using machine learning models: GARP, RF, MaxEnt and NB

Rapid urban development, increasing impermeable surfaces, poor drainage system and changes in extreme precipitations are the most important factors that nowadays lead to increased urban flooding and it has become an urban problem. Urban flood mapping and its use in making an urban development plan can reduce flood damages and losses. Constantly producing urban flood hazard maps using models that rely on the availability of detailed hydraulic-hydrological data is a major challenge especially in developing countries. In this study, urban flood hazard map was produced with limited data using three machine learning models: Genetic Algorithm Rule-Set Production, Maximum Entropy (MaxEnt), Random Forest (RF) and Naive Bayes for Kermanshah city, Iran. The flood hazard predicting factors used in modeling were: slope, land use, precipitation, distance to river, distance to channel, curve number (CN) and elevation. Flood inventory map was produced based on available reports and field surveys, that 117 flooded points and 163 non-flooded points were identified. Models performance was evaluated based on area under the receiver-operator characteristic curve (AUC-ROC), Kappa statistic and hits and miss analysis. The results show that RF model (AUC-ROC = 99.5%, Kappa = 98%, Accuracy = 90%, Success ratio = 99%, Threat score = 90% and Heidke skill score = 98%) performed better than other models. The results also showed that distance to canal, land use and CN have shown more contribution among others for modeling the flood and precipitation had the least effect among other factors. The findings show that machine learning methods can be a good alternative to distributed models to predict urban flood-prone areas where there are lack of detailed hydraulic and hydrological data.

Flood Mapping Proposal in Small Watersheds: A Case Study of the Rebollos and Miranda Ephemeral Streams (Cartagena, Spain)

Anthropogenic landscape changes cause significant disturbances to fluvial system dynamics and such is the case of the watersheds studied near the Spanish Mediterranean coast (Cartagena). Economic growth resulted in the addition of external water resources from the Tajo River (1979) as part of the National Water Plan (1933). Irrigation water has caused the water table to rise since 1979. Furthermore, water resources have boosted urban touristic expansion, industrial estates, and road infrastructures. This study presents a diagnosis of the official flood hazard maps by applying remote sensing techniques that enable the identification of (i) areas flooded during recent events; and (ii) the possible effects of anthropogenic actions on fluvial processes affecting flooding (land use and land cover change—LULCC). The flooded areas were identified from a multispectral satellite image taken by a sensor on Sentinel-2. A multi-temporal analysis of aerial photographs (1929, 1956, 1981, 2009, and 2017) showing the fluvial and anthropic environment at a detailed scale (1:25,000) was used to define the fluvial geomorphology and the main anthropic alterations on the Rebollos ephemeral stream. Official inputs from geographical information repositories about land use were also gathered (LULC). The result was compared to the official flood hazard maps (SNCZI) and this revealed floodable areas that had not been previously mapped because official maps rely only on the hydraulic method. Finally, all the recent changes that will have increased the disastrous consequences of flooding have been detected, analyzed, and mapped for the study area.

GIS-based multi-criteria analysis for flood prone areas mapping in the trans-boundary Shatt Al-Arab basin, Iraq-Iran

Severe flood events in the trans-boundary Shatt Al-Arab basin (Iraq-Iran) claim hundreds of human lives and cause damage to the economy and environment. Therefore, developing a flood hazard model to recognize the basin’s susceptible areas to flooding is important for decision makers for comprehensive flood risk management. The flood hazard map was prepared using geographical information systems (GIS) and multi-criteria decision analysis (MCDA) along with the application of analytical hierarchy process (AHP) method to identify the optimal selection of weights for the factors that contribute to flood risk. The flooding causative factors used in this study were rainfall, distance to the river, digital elevation model (DEM), slope, land use/land cover (LULC), drainage density, soils, and lithology. The derived flood hazard map consisted of four distinct categories (zones). These zones that depict high, intermediate, low, and very low flood hazard cover around 20%, 40%, 39%, and 2% of the basin area, respectively. The produced flood hazard map was further verified using a historical flood event in the study area. The results were found to be consistent with the historical data of flood events, revealing the model’s effectiveness in the realistic representation of flood hazard mapping.

Effects of return periods on flood hazard mapping: an analysis of the UFSC Campus Basin, Florianópolis city, Brazil

ABSTRACT The development of urban areas exacerbates flood risk by increasing both runoff and the exposure of population and infrastructure. In this study, we highlight the importance of return period choice on flood hazard degree and flood hydraulics characteristics. We use the UFSC campus basin as a test bed and combine a hydrological and a hydrodynamic model to define the flood hazard intensity and flood hazard degree. Six hazard intensity maps were elaborated using different return periods (2, 10, 25, 50, 100 and 500-years) that characterize low and high recurrence scenarios. The low recurrence hazard map can be ideal to verify hazard effects on buildings, while the high recurrence hazard map helps to identify people security. All variables related to the rainfall effect and its consequences (e.g. rainfall intensity, flood mean velocity, and total flood area) follow a logarithmic relationship, with a small variation for higher return periods. We highlight how different return periods can influence flood hydraulics and flood hazard and should therefore be considered in flood hazard mapping.

Multi-Hazard Evaluation Using Cluster Analysis—For Designated Evacuation Centers of Yokohama

Hazard maps are usually prepared for each disaster, including seismic hazard maps, flood hazard maps, and landslide hazard maps. However, when the general public attempts to check their own disaster risk, most are likely not aware of the specific types of disaster. So, first of all, we need to know what kinds of hazards are important. However, the information that integrates multiple hazards is not well maintained, and there are few such studies. On the other hand, in Japan, a lot of hazard information is being released on the Internet. So, we summarized and assessed hazard data that can be accessed online regarding shelters (where evacuees live during disasters) and their catchments (areas assigned to each shelter) in Yokohama City, Kanagawa Prefecture. Based on the results, we investigated whether a grouping by cluster analysis would allow for multi-hazard assessment. We used four natural disasters (seismic, flood, tsunami, sediment disaster) and six parameters of other population and senior population. However, since the characteristics of the population and the senior population were almost the same, only population data was used in the final examination. From the cluster analysis, it was found that it is appropriate to group the designated evacuation centers in Yokohama City into six groups. In addition, each of the six groups was found to have explainable characteristics, confirming the effectiveness of multi-hazard creation using cluster analysis. For example, we divided, all hazards are low, both flood and Seismic hazards are high, sediment hazards are high, etc. In many Japanese cities, disaster prevention measures have been constructed in consideration of ground hazards, mainly for earthquake disasters. In this paper, we confirmed the consistency between the evaluation results of the multi-hazard evaluated here and the existing ground hazard map and examined the usefulness of the designated evacuation center. Finally, the validity was confirmed by comparing this result with the ground hazard based on the actual measurement by the past research. In places where the seismic hazard is large, the two are consistent with the fact that the easiness of shaking by actual measurement is also large.

Mapping flood prone and Hazards Areas in rural landscape using landsat images and random forest classification: Case study of Nasia watershed in Ghana

Floods are hazard which poses immense threat to life and property. Identifying flood-prone areas, will enhance flood mitigation and proper land use planning of affected areas. However, lack of resources, the sizable extent of rural settlements, and the evolving complexities of contemporary flood models have hindered flood hazard mapping of the rural areas in Ghana. This study used supervised Random Forest (RF) classification, Landsat 8 OLI, and Landsat 7 ETM + images to produce flood prone, Land Use Land Cover (LULC), and flood hazard maps of the Nasia Watershed in Ghana. The results indicated that about 418.82 km2 area of the watershed is flooded every 2–3 years (normal flooding) and about 689.61 km2 is flooded every 7–10 years (extreme flooding). The LULC classification produced an overall accuracy of 92.31% and kappa of 0.9. The flood hazard map indicated that land areas within hazard zones of the river include the Nasia community, Flood Recession Agricultural (FRA), rainfed and woodlands. When compared with a Modified Normalized Difference Water Index (MNDWI), the RF supervised classification had an edge over the MNDWI in estimating the flooded areas. The results from this study can be used by local administrators, national flood disaster management and researchers for flood mitigation and land use planning within the watershed.

A rapid flood inundation model in the floodplain area due to an extreme rainfall event

Extreme rainfall in East Jakarta on February 19, 2021 caused flooding in a number of subdistricts. The research was conducted in the central part of Kali Sunter, which flows through three subdistricts, namely Cipinang Melayu, Cipinang Muara, and Pondok Bambu. The purpose of the study was to do flood hazard modeling and analyze the characteristics of flood-affected areas based on land use and topography. Inundation and flood hazard maps is done by: calculating the flood discharge using the SCS-CN method, flood inundation modelling using HEC-RAS, and analyzing the characteristics of the inundated area. This combination is effective for rapid modeling during extreme rainfall events. Based on the research, the distribution of the highest flood hazard area is in RW 004 Cipinang Melayu, with the widest inundation affecting small and medium-sized houses. The characteristics of the affected area are that there is green and empty land which reduces the potential for water to inundate buildings or other land uses. Buildings located in low-hazard housing areas tend to be more organized and relatively medium to large in size. While the types of housing in the Cipinang Melayu with a high level of danger tend to be dense and small to medium in size, but the majority have two floors as a form of flood adaptation.

Flood Hazard Mapping in Rural Area: Case of Ephemeral Watercourses in SidiBoulenouar Zone

The eastern region of Morocco is characterized by an arid to semi-arid climate. It is often confronted with heavy rainfall episodes that can generate floods that can cause adverse human and property damage. This work studies hydrological risk in the SidiBoulenouar area (Oujda province) to model floods and map risk areas. The method used is to determine the watersheds and their watercourses, then to calculate the flows with the mathematical formulas. Topographic data were extracted from a 12.5-m resolution DEM derived from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). GDEM (Global DEM). The DEM was used to delimit the hydrographic network with ArcMap software. The use of HEC RAS 1D was necessary to delimit the flooding area. The results of the 1D hydraulic modeling of the centennial flood showed that four ephemeral watercourses landlock the rural area of SidiBoulenouar at the time of the floods.

GIS Based Method for Flood Hazard Assesment in Kobe River Watershed - North Maluku Province

The objectives of this study are to mapping the hazard-prone area and to analyse the flood vulnerability index in Kobe Watershed, Central Halmahera District. In order to determine the optimal selection of weights for the factors that contribute to flood risk, GIS and multi-criteria decision analysis (MCDA) were used in conjunction with the application of the analytical hierarchy process (AHP) method to create the flood hazard map. The flood hazard map was generated by using selected hazard factors including land use, topography, slope, and rainfall pattern. The result shows that the Kobe River basin is a flood-prone area, with 77.46 percent of its land classified as less prone to flooding and 21.41 percent classified as flood-prone. However, only 21.41 percent of its land is classified as flood-prone. Only 1.13 percent of the land is protected from the danger of floods, compared to the whole country. The altitude factor is the most important element influencing flood susceptibility in Weda District, where the majority of the land (16.34 percent) is located at or below sea level, making it particularly vulnerable to flooding.

Use of HAND terrain descriptor for estimating flood-prone areas in river basins

The flood hazard mapping in a river basin is crucial for flooding risk management, mitigation strategies, and flood forecasting and warning systems, among other benefits. One approach for this mapping is based on the HAND (Height Above Nearest Drainage) terrain descriptor, directly derived from the Digital Elevation Model (DEM), in which each pixel represents the elevation difference of this point in relation to the river drainage network to which it is connected. Considering the Mamanguape river basin (3,522.7 km²; state of Paraíba, Brazil) as the study location, the present research applied this method and verified it as for five aspects: consideration of a spatially variable minimum drainage area for denoting the river drainage initiation; the impact of considering a depressionless DEM; evaluation of hydrostatic condition; effect of incorporating an existing river vector network; and comparative analysis of basin morphology regarding longitudinal river profiles. According to the results, adopting a uniform minimum drainage area for the river network initiation is a simplification that should be avoided, using a spatially variable approach, which influences the amount and spatial distribution of flooded areas. Additionally, considering the depressionless DEM leads to higher values of HAND and to a smaller flooded area (difference ranging between 3% and 99%), when compared with the use of DEM with depression, despite 3.1% of the pixels representing depressions. The use of the depressionless DEM is recommended, whereas the DEM pre-processing by incorporating a vector network (stream burning) generates dubious results regarding the relation between HAND and the morphological pattern presented in the DEM. Moreover, the estimation of flooded areas based on HAND does not guarantee the hydrostatic condition, but this disagreement comprises a negligible area for practical purposes.

Current Status of Creating Flood Hazard Maps by Local Residents and Factors Affecting the Information on Maps

Current Status of Creating Flood Hazard Maps by Local Residents and Factors Affecting the Information on Maps

Flood Modelling of Pamba River Using MIKE FLOOD

Flood hazard mapping and flood risk zoning are very effective in the monitoring and risk management of floods. For this flood inundation maps are required. Different computational models are available, such as one-dimensional (1D), two-dimensional (2D) and 1D-2D-coupled model. In this study a coupled 1D-2D hydrodynamic model, MIKE FLOOD was used to simulate flood inundation extent, water levels at different location of the river. MIKE FLOOD is a platform that combines the MIKE 11 and MIKE 21 models into a single modeling framework that is dynamically coupled. Using a coupled approach makes it possible to use the best features of all two versions of software. The study area considered is Pamba river in Kerala which is most effected region in 2018 flood. So flood modelling of Pamba river is necessary. The time series of daily discharge and water level of different gauging station of Centre Water Commission at Kallooppara, Malakkara, Thumpamon and water level data of Thottappalli spillway are used for the study. The SRTM DEM was used to generate the flood model for the period June to August 2010. At the downstream of the river, the maximum water level obtained is 1.48 m in 1D model and water depth obtained is in the range of 0.6 to 1.2 in 2D modelling. The correlation coefficient values ranges 0.52 to 0.96. This study will assist policy makers in the field of water management to achieve effective mitigation step

FLOOD RISK, COASTAL MEGACITIES, AND URBAN POOR: ASSESSING THE FUTURE URBAN FLOOD RISK IN THE H/E WARD OF MUMBAI

In India, Mumbai city is highly vulnerable to the threats posed by climate change, such as sealevel rise, storm, and floods. The vulnerability of the city was demonstrated on the 26 July 2005 when thousands of houses were submerged in the water, and assets worth billions of rupees were damaged. The flood severely impacted the residents in informal settlements known as slums, which incurred substantial financial losses. With the increasing vulnerability of coastal megacities to urban floods, there is a need for an effective risk assessment and Adaptation Planning. Hence this study aims to assess the current amd future Flood Risk faced by the H/E Ward (study area) of Mumbai. The flood risk assessment is performed using the standard catastrophe Risk modeling, which combines Hazard, exposure, and vulnerability. Various data sources such as Historical rainfall data, Elevation Data, Soil Database, Landsat Imagery, and census data were collected from multiple online sources to achieve this objective. The data processing is done using GIS, Hydrological and Hydraulic Processes. As the H/E ward lies in the Mithi River catchment area, we processed the DEM and used the SCS-Curve Number and kinematic routing method to generate the peak discharge at the River Sub basins in HEC-HMS software. The River geometry is prepared in HEC-RAS software, and Flood Hazard Maps were prepared. The current & future Risk analysis shows an increase in the inundation extent for the 100 year return period in the H/E Ward, which highlights that there would be an increase in the total affected Population and losses incurred by them. The study also highlights that the people's adaptive capacity is deficient. Most of the affected Population are poor people, employed in menial jobs, chosen to stay in the riskier site because of proximity to work. Hence this study highlights an urgent need for an effective Risk Management and Adaptation planning in the H/E ward of Mumbai.

An ice jam flood hazard assessment of a lowland river and its terminus inland delta

Flooding is one of the most frequent and most costly natural disasters that occur throughout Canada, and although there is ongoing work to update and improve flood hazard assessments and mapping of high flood risk rivers throughout the country, most studies only delve into open water flooding. However, many rivers in Canada experience higher peak water levels due to ice jamming, resulting in severe flooding of surrounding areas. Hence, there is an urgency to expand current flood hazard assessments to include ice jam flooding for better flood management practices. One area that is often plagued with ice jam flooding is the lowest reach of Manitoba’s Red River. The Lower Red River is a low-lying river with a terminus inland delta where water levels are governed by Lake Winnipeg. Ice jam floods often divert water into the lower Red River’s floodplain that is continually being encroached by development. RIVICE, Environment Canada’s one-dimensional ice hydraulic model, was set up within a Monte Carlo framework to simulate an envelope of backwater level profiles that result from ice jams within the study site. Non-exceedance probability profiles were created from the envelope of backwater level profiles to assess ice jam flood hazard.

Flash flood hazard mapping based on AHP with GIS and satellite information in Kampong Speu Province, Cambodia

Purpose Cambodia is considered one of the countries that are most vulnerable to adverse effects of climate change, particularly floods and droughts. Kampong Speu Province is a frequent site of calamitous flash floods. Reliable sources of flash flood information and analysis are critical in efforts to minimize the impact of flooding. Unfortunately, Cambodia does not yet have a comprehensive program for flash flood hazard mapping, with many places such as Kampong Speu Province having no such information resources available. The purpose of this paper is, therefore, to determine flash flood hazard levels across all of Kampong Speu Province using analytical hierarchy process (AHP) and geographical information system (GIS) with satellite information. Design/methodology/approach The integrated AHP–GIS analysis in this study encompasses ten parameters in the assessment of flash flood hazard levels across the province: rainfall, geology, soil, elevation, slope, stream order, flow direction, distance from drainage, drainage density and land use. The study uses a 10 × 10 pairwise matrix in AHP to compare the relative importance of each parameter and find each parameter’s weight. Finally, a flash flood hazard map is developed displaying all areas of Kampong Speu Province classified into five levels, with Level 5 being the most hazardous. Findings This study reveals that high and very high flash flood hazard levels are identified in the northwest part of Kampong Speu Province, particularly in Aoral, Phnum Srouch and Thpong districts and along Prek Thnot River and streams. Originality/value The flash flood hazard map developed here provides a wealth of information that can be invaluable for implementing effective disaster mitigation, improving disaster preparedness and optimizing land use.