Flood Risk Mapping using GIS
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Flooding is a recurring phenomenon in Kumasi which has caused damage to properties and financial loss over the years. The risk of flooding is projected to increase due to the annual rise in rainfall and conversion of floodplains to... more
Flooding is a recurring phenomenon in Kumasi which has caused damage to properties and financial loss over the years. The risk of flooding is projected to increase due to the annual rise in rainfall and conversion of floodplains to settlement. Many kinds of research have been made to assess the risk of flood and map out the vulnerable zones using diverse methodologies. This gives the idea of flood prediction, mitigation, and prevention. To achieve the objective of flood risk assessment in Kumasi, the GIS modeling approach was used to produce a flood risk map with the help of Quantum GIS software. In this research, a digital elevation model which is important data for hydrological modeling was obtained from the Shuttle Radar Topography Mission (SRTM). Four hydrological factors which include digital elevation, slope, proximity to the river, and topographic wetness index were derived from the depressionless DEM of the study area. The hydrological factors were further reclassified and overlaid to produce the flood risk map. The flood risk map showed five risk zones – very high, high, moderate, low, and very low zones in the study area. The results showed that 30% of the study area lies within the very high and high-risk zones. These areas are considered very highly susceptible to flooding. However, only 2% of the very high and high population density areas fall within the high susceptible flood zones. This is because most of the highly susceptible flood zones fall in the southern and north-eastern parts of the study area. These areas cover the very low and low population density regions. Moreover, floods will be likely to occur during the rainy season. To further demonstrate and visualize the risk of flood in the high susceptible zones, a flood simulation method was adopted. With the aid of Quantum GIS geoalgoritms and a digital elevation model, a resampled DEM was used to produce a flood simulation map showing the areas at risk in a given flood depth along the Susan river at Atonsu-Junction in Kumasi. This was further overlaid on a georeferenced google earth image of the area to aid visualize the affected areas. The flood simulation map showed that areas that have experienced extensive flooding fall within the predicted flood depths. The research has proved that the application of GIS for hydrological modeling and flood risk simulation is important for the assessment of flood risk.
Flood is becoming the most environmental challenge menacing Ado-Ekiti in recent times. The aim of this study is to evaluate and map flood risk in the study area, using GIS techniques, to achieve this aim, the study has the following... more
Flood is becoming the most environmental challenge menacing Ado-Ekiti in recent times. The aim of this study is to evaluate and map flood risk in the study area, using GIS techniques, to achieve this aim, the study has the following objectives, assess the extent and magnitude of flooding in the study area, also it assesses elements at risk in the study area, hence integrate the outcome of these analysis in a GIS environment. Primary data was sourced with the use of structured questionnaires, while the secondary data sources are from Google earth map and literatures. Simple statistics was use to analyse the data to help develop indicators of vulnerability. A hazard and vulnerability maps were produced based on the perception the population living in the area, the map was then combined with the hazard map, and thus to produce an integrated risk map for the study area. Results reveal that from Vulnerability, Hazard and Risk maps showed that buildings closer to rivers and stream all have higher index. The impact of flood on households sampled revealed that some of the household believed that flood occurrence in the study area have some of impacts on their properties and expenditure. The methodology has proven to be a suitable tool to provide a first overview of spatial distribution of risk which is considered by the households
During the last decade, many local governments have launched initiatives to reduce CO2 emissions and the potential impact of hydro-climatic disasters. Nonetheless, today barely 11% of subtropical and tropical cities with over 100,000... more
During the last decade, many local governments have launched initiatives to reduce CO2 emissions and the potential impact of hydro-climatic disasters. Nonetheless, today barely 11% of subtropical and tropical cities with over 100,000 inhabitants have a climate plan. Often this tool neither issues from an analysis of climate change or hydro climatic risks, nor does it provide an adequate depth of detail for the identified measures (cost, funding mode, implementation), nor a sound monitoring-evaluation device. This book aims to improve the quality of climate planning by providing 19 examples of analysis and assessments in eleven countries. It is intended for local operators in the fields of climate, hydro-climatic risks, physical planning, besides researchers and students of these subjects. The first chapter describes the status of climate planning in large subtropical and tropical cities. The following six chapters discuss the hazards (atmospheric drought, intense precipitations, sea level rise, sea water intrusion) and early warning systems in various contexts. Nine chapters explore flood risk analysis and preliminary mapping, climate change vulnerability, comparing contingency plans in various scales and presenting experiences centred on adaptation planning. The last three chapters introduce some best practices of weather and climate change monitoring, of flood risk mapping and assessment.
The city of Vadodara, India is prone to frequent floods and the most severe floods were received in 1994, 1996, 2005 and 2014 in the recent past. The city has an area of 159 km² and a population of 1.6 million according to the 2010–11... more
The city of Vadodara, India is prone to frequent floods and the most severe floods were received in 1994, 1996, 2005 and 2014 in the recent past. The city has an area of 159 km² and a population of 1.6 million according to the 2010–11 census. Vadodara receives an average rainfall of 1020 mm. Vadodara sits on the banks of the River Vishwamitri, fed by the Ajwa Reservoir. The width of the river decreases as it flows through the city and is subjected to the drainage of the city's sewage and effluents from nearby industries. Alterations of its banks and human encroachment have reduced its width further. A large number of wetlands have been reclaimed and construction has been carried out over them. The number of slums has also increased by a great extent from 192 slums in 1972 to 397 in 2013. The stormwater drainage network in the city is also inadequate. The study aims at highlighting the role of change in land use pattern, unplanned development, depletion of water bodies and buildi...
In recent years, the acquisition of data from multiple sources, together with improvements in computational capabilities, has allowed to improve our understanding on natural hazard through new approaches based on machine learning and Big... more
In recent years, the acquisition of data from multiple sources, together with improvements in computational capabilities, has allowed to improve our understanding on natural hazard through new approaches based on machine learning and Big Data ana-lytics. This has given new potential to flood risk mapping, allowing the automatic extraction of flood prone areas using digital elevation model (DEM) based geomor-phic approaches. Most of the proposed geomorphic approaches are conceived mainly for the identification of flood extent. In this article, the DEM-based method based on a geomorphic descriptor-the geomorphic flood index (GFI)-has been further exploited to predict inundation depth, which is useful for quantifying flood induced damages. The new procedure is applied on a case study located in southern Italy, obtaining satisfactory performances. In particular, the inundation depths are very similar to the ones obtained by hydraulic simulations, with a root-mean-square error (RMSE) = 0.335 m, in the domain where 2D dynamics prevail. The reduced computational effort and the general availability of the required data make the method suitable for applications over large and data-sparse areas, opening new horizons for flood risk assessment at national/continental/global scale. K E Y W O R D S DEM-based methods, digital elevation models, flooding, geomorphic flood index, inundation depth, linear binary classification
Flood causes loss of life, damage to critical infrastructure, increase in waterborne diseases, and disruption of human means of livelihood. This calls for the importance of a flood hazard map that can help the government and populace to... more
Flood causes loss of life, damage to critical infrastructure, increase in waterborne diseases, and disruption of human means of livelihood. This calls for the importance of a flood hazard map that can help the government and populace to know where might be flooded in order to be prepared and to mitigate this constantly occurring hazard.This paper utilized geospatial techniques to generate and combine flood hazard components and in the process create a flood hazard map of Fufore Local Government Area, North-Eastern Nigeria. The datasets include the distance from rivers, elevation, slope, rainfall intensity, and land use/ landcover of the study area.
Four hazard zones were derived: very high, high, low, and very low. The analysis shows that Low flood hazard
zone has the highest coverage with 2112.5 km2 (49.9%), followed by a High flood hazard zone of 1784.6 km2
(42.2%) and Very High with 183.58 (4.3%). The Very Low areas have the least areal extent with 144.89 km2
(3.42%). The total coverage of Very Low and Low areas is 53.32% while High and Very High zones constitute
46.68%. Out of the 26 communities hosting major markets, 4 are found in the Very High zone, 10 in High, 12 in Low and none in Very Low Hazard zone. Markets such as Kasuwar Wurobokki, Kasuwar Bilachi Bwatye, Chigari, Chikito, Mayo Ine, Mayo Sadi, Shuwari Market, and Tike Market are highly susceptible to flooding.
Generally, about 91 settlements including Mayo Inne, Damboire Nadere, Tunga Agatu, Tudun WadaWuro
Fulbere and Gangare Gidan Audu are all located within the Very High flood hazard zone. Some of these impotant are located within the low-lying areas of Lagdo River and its tributaries. This indicates the fact that in the event of flooding, a high proportion of the population in the study area might be displaced, loose their means of livelihood, impede children's access to schools, and damage essential infrastructure and buildings. The paper has revealed the capabilities of hazard maps to communicate information that could enable policymakers, community members, and related stake holders to take to mitigate flood disaster in the study area.
Four hazard zones were derived: very high, high, low, and very low. The analysis shows that Low flood hazard
zone has the highest coverage with 2112.5 km2 (49.9%), followed by a High flood hazard zone of 1784.6 km2
(42.2%) and Very High with 183.58 (4.3%). The Very Low areas have the least areal extent with 144.89 km2
(3.42%). The total coverage of Very Low and Low areas is 53.32% while High and Very High zones constitute
46.68%. Out of the 26 communities hosting major markets, 4 are found in the Very High zone, 10 in High, 12 in Low and none in Very Low Hazard zone. Markets such as Kasuwar Wurobokki, Kasuwar Bilachi Bwatye, Chigari, Chikito, Mayo Ine, Mayo Sadi, Shuwari Market, and Tike Market are highly susceptible to flooding.
Generally, about 91 settlements including Mayo Inne, Damboire Nadere, Tunga Agatu, Tudun WadaWuro
Fulbere and Gangare Gidan Audu are all located within the Very High flood hazard zone. Some of these impotant are located within the low-lying areas of Lagdo River and its tributaries. This indicates the fact that in the event of flooding, a high proportion of the population in the study area might be displaced, loose their means of livelihood, impede children's access to schools, and damage essential infrastructure and buildings. The paper has revealed the capabilities of hazard maps to communicate information that could enable policymakers, community members, and related stake holders to take to mitigate flood disaster in the study area.
Flood risk in coastal megacities of developing nations is higher than those in developed nations due to inadequate fiscal resources, urbanization, and poor flood maintenance infrastructure, amongst other factors. Lagos is one of the... more
Flood risk in coastal megacities of developing nations is higher than those in developed nations due to inadequate fiscal resources, urbanization, and poor flood maintenance infrastructure, amongst other factors. Lagos is one of the coastal megacities of the developing nations characterized by increasing urbanization and population growth. This study presents geospatial mapping of flood risk areas in the coastal megacity of Nigeria. The flood prone areas were derived by overlaying seven flood factors in ArcGIS environment, which include: elevation, curvature, slope, flow accumulation, normalized difference water index (NDWI), land cover and drainage density. Results showed that of the 2507.2 km 2 land area covered by this study area, 0.006% (0.15km 2) falls in very high risk, 30.9% (774.7 km 2) falls in high risk, 68.8% (1725km 2) falls in moderate risk and only 0.31% (7.8km 2) falls in low risk areas. Furthermore, highly urbanized Local Governments in relatively low elevations with low slope angles such as Eti-Osa, Apapa, Lagos Island, Lagos Mainland and Ojo have high risk of getting flooded while most Local Governments with low level of urbanization and high elevations have moderate to low risk of getting flooded. These findings have implications on sustainable decision making and planning for flood risk prevention and management, prioritizing flood risk control mechanisms where necessary, and the development and implementation of potent flood control policies with appropriate infrastructure in areas that fall in both very high risk and high risk.
- by Adeniji Kayode and +1
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- Flood Risk Mapping using GIS
Accurate flood mapping is important for both planning activities during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic... more
Accurate flood mapping is important for both planning activities during emergencies and as a support for the successive assessment of damaged areas. A valuable information source for such a procedure can be remote sensing synthetic aperture radar (SAR) imagery. However, flood scenarios are typical examples of complex situations in which different factors have to be considered to provide accurate and robust interpretation of the situation on the ground. For this reason, a data fusion approach of remote sensing data with ancillary information can be particularly useful. In this paper, a Bayesian network is proposed to integrate remotely sensed data, such as multitemporal SAR intensity images and interferometric-SAR coherence data, with geomorphic and other ground information. The methodology is tested on a case study regarding a flood that occurred in the Basilicata region (Italy) on December 2013, monitored using a time series of COSMO-SkyMed data. It is shown that the synergetic use of different information layers can help to detect more precisely the areas affected by the flood, reducing false alarms and missed identifications which may affect algorithms based on data from a single source. The produced flood maps are compared to data obtained independently from the analysis of optical images; the comparison indicates that the proposed methodology is able to reliably follow the temporal evolution of the phenomenon, assigning high probability to areas most likely to be flooded, in spite of their heterogeneous temporal SAR/InSAR signatures, reaching accuracies of up to 89%. Index Terms—Bayesian networks (BNs), data fusion, flood mapping , synthetic aperture radar (SAR) change detection, synthetic aperture radar (SAR)/interferometric SAR (InSAR) time series analysis.
En Afrique tropicale la réduction du risque hydro-climatique peine à devenir une politique publique. La Région de Dosso au Niger (31 000 km2, deux millions d’habitants) a été inondée et frappée par la sécheresse à plusieurs reprises... more
En Afrique tropicale la réduction du risque hydro-climatique peine à devenir une politique publique.
La Région de Dosso au Niger (31 000 km2, deux millions d’habitants) a été inondée et frappée par la sécheresse à plusieurs reprises durant les dernières 10 années. Alors, pour mieux comprendre et maîtriser ces aléas les changements climatiques d’ici au 2030 sont caractérisées à l’échelle locale. La base de données sur les inondations est transférée dans une archive ouverte. La dynamique spatiale des localités rurale est observée durant les 20 dernières années, L’analyse-évaluation du risque d’inondation et de sécheresse est développée à l’échelle régionale, communale et de localité rurale. Des services climatologiques sont offerts aux petits producteurs ruraux. Les méthodes proposées utilisent des informations en libre accès et sont donc aisément reproductibles dans d’autres régions du Pays et d’Afrique francophone. Ce livre présente des outils pour connaître et gérer le risque hydro-climatique à l’échelle locale.
La Région de Dosso au Niger (31 000 km2, deux millions d’habitants) a été inondée et frappée par la sécheresse à plusieurs reprises durant les dernières 10 années. Alors, pour mieux comprendre et maîtriser ces aléas les changements climatiques d’ici au 2030 sont caractérisées à l’échelle locale. La base de données sur les inondations est transférée dans une archive ouverte. La dynamique spatiale des localités rurale est observée durant les 20 dernières années, L’analyse-évaluation du risque d’inondation et de sécheresse est développée à l’échelle régionale, communale et de localité rurale. Des services climatologiques sont offerts aux petits producteurs ruraux. Les méthodes proposées utilisent des informations en libre accès et sont donc aisément reproductibles dans d’autres régions du Pays et d’Afrique francophone. Ce livre présente des outils pour connaître et gérer le risque hydro-climatique à l’échelle locale.
Carte risque d'inondation (Tr 500)
The city of Vadodara is prone to frequent floods and the most severe floods were received in 1994, 1996, 2005 and 2014 in the recent past. The city has an area of 149 km² and a population of 4.1 million according to the 2010–11 census.... more
The city of Vadodara is prone to frequent floods and the most severe floods were received in 1994, 1996, 2005 and 2014 in the recent past. The city has an area of 149 km² and a population of 4.1 million according to the 2010–11 census. Vadodara receives an average rainfall of 970 mm. Vadodara sits on the banks of the River Vishwamitri, fed by the Ajwa Reservoir. The width of the river decreases as it flows through the city and is subjected to the drainage of the city's sewage and effluents from nearby industries. Alteration of its banks and human encroachment have reduced its width further. A large number of wetlands have been reclaimed and construction has been carried out over them. The construction in the city has increased by about 50 km2 from 1991 to 2005, but the area covered by water bodies has reduced by nearly half from 4.38 to 2.77 km2. The number of slums have also increased by a great extent from 192 slums in 1972 to 397 in 2013. The storm water drainage network in the city is also inadequate. The study aims at highlighting the role of change in land use pattern, unplanned development, depletion of water bodies and building of slums along the river banks in causing frequent and severe floods in the city using GIS. The annual rainfall data of the city was obtained and subjected to graphical and statistical operations which revealed that heavy rainfall is not the only factor causing floods in the city. The low lying zones were identified and the direction of the flow of rainwater was determined using an elevation map. This also gave the reasons for severe waterlogging in some areas of the city. The historic LANDSAT images of the city from 1991 to 2014 were obtained from the USGS Global Visualisation (GloVis) Viewer. The images were analysed under different band combinations using the Integrated Land and Water Information System (ILWIS 3.4). The results show the continuous increase in the urban sprawl, increase in construction throughout the city, especially in the western parts and increase in the density of buildings. It was also revealed that the number of water bodies has decreased, which used to act as sinks for the rainwater. The area of the existing water bodies is also decreasing due to dumping of wastes and construction along the banks. The presence of slums has increased by a great extent throughout the city, especially along the banks of Vishwamitri River reducing the width of the river and causing frequent floods. Unplanned construction has been carried out in the low lying zones, obstructing the flow of water into the sinks to cause waterlogging in these areas.
Key Words: Urban floods, Vadodara, Vishwamitri, Land use pattern, GIS, Water bodies, Rainwater, Unplanned development, Slums
Key Words: Urban floods, Vadodara, Vishwamitri, Land use pattern, GIS, Water bodies, Rainwater, Unplanned development, Slums
The objective of this study is to compare two new generation low-complexity tools, AutoRoute and Height Above the Nearest Drainage (HAND), with a two-dimensional hydrodynamic model (Hydrologic Engineering Center-River Analysis System,... more
The objective of this study is to compare two new generation low-complexity tools, AutoRoute and Height Above the Nearest Drainage (HAND), with a two-dimensional hydrodynamic model (Hydrologic Engineering Center-River Analysis System, HEC-RAS 2D). The assessment was conducted on two hydrologically different and geographically distant test-cases in the United States, including the 16,900 km2 Cedar River (CR) watershed in Iowa and a 62 km2 domain along the Black Warrior River (BWR) in Alabama. For BWR, twelve different configurations were set up for each of the models, including four different terrain setups (e.g. with and without channel bathymetry and a levee), and three flooding conditions representing moderate to extreme hazards at 10-, 100-, and 500-year return periods. For the CR watershed, models were compared with a simplistic terrain setup (without bathymetry and any form of hydraulic controls) and one flooding condition (100-year return period). Input streamflow forcing data representing these hypothetical events were constructed by applying a new fusion approach on National Water Model outputs. Simulated inundation extent and depth from AutoRoute, HAND, and HEC-RAS 2D were compared with one another and with the corresponding FEMA reference estimates. Irrespective of the configurations, the low-complexity models were able to produce inundation extents similar to HEC- RAS 2D, with AutoRoute showing slightly higher accuracy than the HAND model. Among four terrain setups, the one including both levee and channel bathymetry showed lowest fitness score on the spatial agreement of inundation extent, due to the weak physical representation of low-complexity models compared to a hydrodynamic model. For inundation depth, the low-complexity models showed an overestimating tendency, especially in the deeper segments of the channel. Based on such reasonably good prediction skills, low-complexity flood models can be considered as a suitable alternative for fast predictions in large-scale hyper-resolution operational frameworks, without completely overriding hydrodynamic models’ efficacy.
The Kedang Pahu river is one of the tributaries of the Mahakam river. The research plan is located in Damai District, West Kutai Regency, East Kalimantan province. Recently, the Damai Kota and Damai Seberang areas have flooded activities... more
The Kedang Pahu river is one of the tributaries of the Mahakam river. The research plan is located in Damai District, West Kutai Regency, East Kalimantan province. Recently, the Damai Kota and Damai Seberang areas have flooded activities that have caused the surrounding settlements to flood to residential areas and block existing road access. Planning analysis and knowing the annual flood elevation is very necessary. The analysis uses the method of calculating the mean annual flood (MAF) as the search for the average annual flood discharge data and the search for the average annual elevation. Data validation using simple linear regression method produces a correlation coefficient of 58.67% or R value = 0.5867. The analysis results in the value of Q1 or the 1st year period, the mean annual flood rate of the average annual flood discharge is 2576.0695 m³/second and the value associated with the magnifying factor (GF) is the average annual flood discharge rate of Q5=3014,00 m³/ sec, Q10 = 3529.22 m³/sec, Q20 = 4095.95 m/sec, Q50 = 5049.10 m³/sec, Q100 = 5847.68 m³/sec, Q200 = 6852.34 m³/sec, Q500 = 8423.75 m³/sec & Q1000 = 9917.87 m³/sec. The results of the analysis at HEC-RAS 5.07 based on manning analysis showed the elevation values were Q1=18.47m, Q5=18.85m, Q10=18.86m, Q20=19.18m, Q50=19.74m & Q100=19.99m. Researchers only show elevations up to Q100 or the 100th year because of limited data and the accuracy of the data reviewed.
A fundamental component of the European natural disaster management policy is the detection of potential flood-prone areas, which is directly connected to the European Directive (2007/60). This study presents a framework for mapping... more
A fundamental component of the European natural disaster management policy is the detection of potential flood-prone areas, which is directly connected to the European Directive (2007/60). This study presents a framework for mapping potential flooding areas incorporating geographic information systems (GIS), fuzzy logic and clustering techniques, and multi-criteria evaluation methods. Factors are divided in different groups which do not have the same level of trade off. These groups are related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin as well as to anthropogenic land use. GIS and numerical simulation are used for geographic data acquisition and processing. The selected factor maps are considered in order to estimate the spatial distribution of the potential flood prone areas. Using these maps, the study area is classified into five categories of flood vulnerable areas. The Multi-Criteria Analysis (MCA) techniques consist of the crisp and fuzzy analytical hierarchy processes (AHP) and are enhanced with different standardization methods. The classification is based on different clustering techniques and it is applied in two approaches. In the first approach, all criteria are normalized before the MCA process and then, the clustering techniques are applied to derive the final flood prone area maps. In the second approach, the criteria are clustered before and after the MCA process for the potential flood prone area mapping. The methodology is demonstrated in Xerias River watershed, Thessaly region, Greece. Xerias River floodplain was repeatedly flooded in the last few years. These floods had major impacts on agricultural areas, transportation networks and infrastructure. Historical flood inundation data has been used for the validation of the methodology. Results show that multiple MCA techniques should be taken into account in initial low-cost detection surveys of flood-prone areas and/or in preliminary analysis of flood hazard mapping.
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