Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

Frequent flood is a concern for most of the coastal regions of India. The importance of flood maps in governing strategies for flood risk management is of prime importance. Flood inundation maps are considered dependable output generated from simulation results from hydraulic models in evaluating flood risks. In the present work, a continuous hydrologic-hydraulic model has been implemented for mapping the flood, caused by the Baitarani River of Odisha, India. A rainfall time-series data were fed into the hydrologic model and the runoff generated from the model was given as an input into the hydraulic model. The study was performed using the HEC-HMS model and the FLO-2D model to map the extent of flooding in the area. Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Model (DEM) data, Land use/Land cover map (LULC), soil texture data of the basin area were used to compute the topographic and hydraulic parameters. Flood inundation was simulated using the FLO-2D model and based on the flow depth, hazard zones were specified using the MAPPER tool of the hydraulic model. Bhadrak District was found to be the most hazard-prone district affected by the flood of the Baitarani River. The result of the study exhibited the hydraulic model as a utile tool for generating inundation maps. An approach for assessing the risk of flooding and proper management could help in mitigating the flood. The automated procedure for mapping and the details of the study can be used for planning flood disaster preparedness in the worst affected area.

     

Delineating flood risk areas in Greater Dhaka of Bangladesh using geoinformatics

This paper illustrates the development of flood hazard and risk maps in Greater Dhaka of Bangladesh using geoinformatics. Multi-temporal RADARSAT SAR and GIS data were employed to delineate flood hazard and risk areas for the 1998 historical flood. Flood-affected frequency and flood depth were estimated from multi-date SAR data and considered as hydrologic parameters for the evaluation of flood hazard. Using land-cover, gemorphic units and elevation data as thematic components, flood hazard maps were created by considering the interactive effect of flood frequency and flood water depth concurrently. Analysis revealed that a major portion of Greater Dhaka was exposed to high to very high hazard zones while a smaller portion (2.72%) was free from the potential flood hazard. Flood risk map according to administrative division showed that 75.35% of Greater Dhaka was within medium to very high risk areas of which 53.39% of areas are believed to be fully urbanized by the year 2010.     

Characterizing flood hazard risk in data-scarce areas,using a remote sensing and GIS-based flood hazard index

The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.     

Geomorphological zoning for flood inundation using satellite data

The authors investigated geomorphological features on the central plain of Thailand utilizing satellite remote sensing data and made geomorphological land classification map showing flood-stricken area. Land classification maps showing flood-striken area tell us former flood inundation area, such as inundation depth, inundation width, flood flow course and flood direction, as well as estimating of the features of flooding. Thus map is useful for planning of flood control works.We classified land form units in the central plain of Thailand as following; delta, tidal flat, lagoon, mud spit, back marsh, natural levee, fan and former river course and so on. After that, the principal component analysis is applied to Landsat TM data and gives good results for photo interpretation of land form units and we transfer geomorphological land classification map to make zoning map of flood risk for the purpose of evaluating the flood damages.     

Flash flood inundation map preparation for wadis in arid regions

Flood inundation maps are dependent on the topographic and geomorphologic features of a wadi (drainage basin) in arid regions, which are most susceptible for potential flash flood occurrences, such as in the southwestern part of the Kingdom of Saudi Arabia. It is not possible to control the potential flood hazards by using only technological instruments that forewarn the occurrences or imminence. Additionally, it would be better to prepare flood risk maps so as to delineate the risky areas to educate the administrators and local settlers. The availability of these maps is the key requirement for any urban development that entails land use allocation, identification of dam, tunnel, highway, bridge sites, and infrastructure locations for sustainable future. This paper suggests the necessary steps in flood inundation map preparation after determining the possible flood discharge. For this purpose, a set of critical cross-sections along the possible flood plain are taken in the field with surveying methods and measurements. The calculation of the average flow velocity in each section is calculated according to the cross-section geometric, hydraulic, and material properties. Synthetic rating curves (SRC) are prepared for each cross section, which are very useful especially in arid and semi-arid regions where there are no perennial surface water flows for natural rating curve measurements. All the SRCs appear in the form of power function which relates the flow depth to discharge in a given cross section. It is then possible to calculate the flood depth in the cross section through its SRC. Depending on the cross-section shape, the flood width can be calculated. The connection of a series of widths on a scaled topographic map delineates the flood inundation area. If digital elevation map (DEM) is available, then the SRCs can be integrated with these maps and the flood inundation delineation can be achieved automatically. Since DEMs are not available, the topographic maps are used for this purpose in order to delineate flood inundation areas within wadis Hali and Yiba from the southwestern Kingdom of Saudi Arabia.     

Effect of uncertainty in land use, damage models and inundation depth on flood damage estimates

With the recent transition to a more risk-based approach in flood management, flood risk models—being a key component in flood risk management—are becoming increasingly important. Such models combine information from four components: (1) the flood hazard (mostly inundation depth), (2) the exposure (e.g. land use), (3) the value of elements at risk and (4) the susceptibility of the elements at risk to hydrologic conditions (e.g. depth–damage curves). All these components contain, however, a certain degree of uncertainty which propagates through the calculation and accumulates in the final damage estimate. In this study, an effort has been made to assess the influence of uncertainty in these four components on the final damage estimate. Different land-use data sets and damage models have been used to represent the uncertainties in the exposure, value and susceptibility components. For the flood hazard component, inundation depth has been varied systematically to estimate the sensitivity of flood damage estimations to this component. The results indicate that, assuming the uncertainty in inundation depth is about 25 cm (about 15% of the mean inundation depth), the total uncertainty surrounding the final damage estimate in the case study area can amount to a factor 5–6. The value of elements at risk and depth–damage curves are the most important sources of uncertainty in flood damage estimates and can both introduce about a factor 2 of uncertainty in the final damage estimates. Very large uncertainties in inundation depth would be necessary to have a similar effect on the uncertainty of the final damage estimate, which seem highly unrealistic. Hence, in order to reduce the uncertainties surrounding potential flood damage estimates, these components deserve prioritisation in future flood damage research. While absolute estimates of flood damage exhibit considerable uncertainty (the above-mentioned factor 5–6), estimates for proportional changes in flood damages (defined as the change in flood damages as a percentage of a base situation) are much more robust.     

Multi-scenario flash flood hazard assessment based on rainfall–runoff modeling and flood inundation modeling: a case study

Flash flooding is one of the most devastating natural disasters in China. A quantitative flash flood hazard assessment is important for saving human lives and reducing economic losses. In this study, integrated rainfall–runoff modeling (HEC-HMS) and hydraulic modeling (FLO-2D) schemes were used to assess flash flood inundation areas and depths under 5-year, 10-year, 25-year, 50-year, 100-year, 200-year, 500-year and 1000-year rainfall scenarios in a mountainous basin (Hadahe River Basin, HRB) in northern China. The overall flash flood hazard in HRB is high. Under the eight rainfall scenarios, the total flooded area ranged from 6 to 8.73 km²; the flash flood inundation areas with depths of 1–2 m, 2–3 m, and over 3 m was 1.53–2.69 km², 0.63–1.44 km² and 0.33–1.11 km², respectively; and these areas accounted for 25.5–30.8%, 10.5–16.5% and 5.5–12.7% of the whole flooded area. The total flooded area increases rapidly with the return period increasing from 5 to 200 years, and the increase gradient slows when the return period is greater than 200 years. In the downstream area of HRB, the flash flood area with inundation depths greater than 1 m accounted for 54–71% of the flooded area under the eight scenarios. In comparison to other areas in the HRB, the downstream area is at the highest risk given its extensive inundation and substantial property exposure. The quantitative hazard assessment framework presented in this study can be applied in other mountainous basins for flash flood defense and disaster management purposes.

     

Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach

An innovative approach in the investigation of complex landscapes for hydraulic modelling applications is the use of terrestrial laser scanner (TLS) that can lead to a high-resolution digital elevation model (DEM). Another notable factor in flood modelling is the selection of the hydrodynamic model (1D, 2D and 1D/2D), especially in complex riverine topographies, that can influence the accuracy of flood inundation area and mapping. This paper uses different types of hydraulic–hydrodynamic modelling approaches and several types of river and riparian area spatial resolution for the implementation of a sensitivity analysis for floodplain mapping and flood inundation modelling process at ungauged watersheds. Four data sets have been used for the construction of the river and riparian areas: processed and unprocessed TLS data, topographic land survey data and typical digitized contours from 1:5000-scale topographic maps. Modelling approaches combinations consist of: one-dimensional hydraulic models (HEC-RAS, MIKE 11), two-dimensional hydraulic models (MIKE 21, MIKE 21 FM) and combinations of coupled hydraulic models (MIKE 11/MIKE 21) within the MIKE FLOOD platform. Historical flood records and estimated flooded area derived from an observed extreme flash-flood event have been used in the validation process using 2 × 2 contingency tables. Flood inundation maps have been generated for each modelling approach and landscape configuration at the lower part of Xerias River reach at Volos, Greece, and compared for assessing the sensitivity of input data and model structure uncertainty. Results provided from contingency table analysis indicate the sensitivity of floodplain modelling on the DEM spatial resolution and the hydraulic modelling approach.     

Estimation of structural vulnerability for flooding using geospatial tools in the rural area of Orissa,India

Vulnerability assessment of natural disasters is a crucial input for risk assessment and management. In the light of increasing frequency of disasters, societies must become more disaster resilient. This research tries to contribute to this aim. For risk assessment, insight is needed into the hazard, the elements at risk and their vulnerabilities. This study focused on the estimation of structural vulnerability due to flood for a number of structural elements at risk in the rural area of Orissa, India (Kendrapara), using a community-based approach together with geospatial analysis tools. Sixty-three households were interviewed about the 2003 floods in 11 villages and 166 elements at risk (buildings) were identified. Two main structural types were identified in the study area, and their vulnerability curves were made by plotting the relationships between flood depth and vulnerability for each structural type. The vulnerability ranges from 0 (no damage) to 1 (collapse/total damage). Structural type-1 is characterized by mud wall/floor material and a roof of paddy straw, and structural type-2 is characterized by reinforced cement concrete (RCC) walls/floor and a RCC roof. The results indicate that structural type-1 is most vulnerable for flooding. Besides flood depth, flood duration is also of major importance. Houses from structural type-1 were totally collapsed after 3 days of inundation. Damage of the houses of structural type-2 began after 10 days of inundation.     

动态实时洪水风险分析及管理系统

当前洪水风险分析按照典型设计标准洪水进行计算的模式难以满足实际防洪管理需要,为了提高洪水风险分析的实时性以及适应洪水演进的动态性,设计了动态实时洪水风险分析框架。在本框架中,先采用一维和二维动态耦合水动力学数值方法耦合溃堤模型,然后在樵桑联围防洪保护区建立洪水演进模拟模型,通过灵活处理模型计算边界条件以及动态设置溃堤功能,计算不同设计标准洪水发生时,堤防出现单一溃口或者组合溃口后保护区内洪水演进过程。按照上述框架开发了樵桑联围动态实时洪水风险图编制与管理应用系统,并利用历史洪水资料开展模型验证,验证结果表明,2008-06洪水马口站、三水站、大熬站、甘竹（一）站的实测最高水位和模型计算最高水位的绝对误差分别为-0.10、0.10、0.09、0.04 m,均满足洪水模拟精度要求。利用模型计算了西江发生200年一遇的洪水情况下,江根堤防出现溃口后的洪水流量及溃口内外洪水水位变化过程,模拟溃口宽度168 m,最大溃口洪水流量达到5 190 m³,分析了堤防溃决后3、6和24 h洪水漫延导致村落淹没情况,结果表明其满足合理性分析。     

A DEM-based evaluation of potential flood risk to enhance decision support system for safe evacuation

A practical, DEM-based practical method is proposed to enhance flood risk management in fluvial areas by quantifying relative risk as a function of vulnerability to inland and evacuation difficulty. Both measures are based mainly on the topography of the region, so the method does not require detailed data on the physical characteristics of the land. First, we use the deterministic 8-node method on a digital elevation map (DEM) to trace storm waterways. Second, we repeat the process on a reversed DEM to trace evacuation routes that avoid the waterways and zones dangerously close to the rivers. Finally, on the basis of such two flow lines of evacuee and storm water, we proposed the protocol to evaluate the flood risk at every point on the map taking into account both the minimum time required for floodwater to arrive and duration of an evacuation from that location. The time that must be allocated for safe evacuation is defined as the potential flood risk of evacuation (PFRE). The method is demonstrated on a fluvial area of the Kaki River in Nagaoka city, Japan. In addition, we illustrated the application of the PFRE map to divide the region into areas of greater or lesser evacuation urgency.     

The extent of saltwater intrusion in southern Baldwin County,Alabama

Sea level rise (SLR) as a result of global warming has an impact on the increasing inundation on the coastal area. Nowadays, Semarang coastal area in Indonesia is already subject to coastal hazard due to tidal inundation and land subsidence. The impact of the inundation is predicted to be even more severe with the scenario of sea level rise. This paper concentrates on the risk assessment to the population, land use, and monetary losses as a result of coastal inundation under enhanced sea level rise. This paper uses the scenario of the depth of inundation to generate coastal inundation model using GIS-Technology. Anticipatory issues including methodology development for hazard assessment would be necessary for Semarang coastal area, and therefore, geo-information technology can be considered as a useful tool to rapidly assess the impact of the coastal hazard and evaluate the economic losses.     

Tsunami vulnerability assessment in urban areas using numerical model and GIS

Natural disasters can neither be predicted nor prevented. Urban areas with a high population density coupled with the construction of man-made structures are subjected to greater levels of risk to life and property in the event of natural hazards. One of the major and densely populated urban areas in the east coast of India is the city of Chennai (Madras), which was severely affected by the 2004 Tsunami, and mitigation efforts were severely dampened due to the non-availability of data on the vulnerability on the Chennai coast to tsunami hazard. Chennai is prone to coastal hazards and hence has hazard maps on its earth-quake prone areas, cyclone prone areas and flood prone areas but no information on areas vulnerable to tsunamis. Hence, mapping has to be done of the areas where the tsunami of December 2004 had directly hit and flooded the coastal areas in Chennai in order to develop tsunami vulnerability map for coastal Chennai. The objective of this study is to develop a GIS-based tsunami vulnerability map for Chennai by using a numerical model of tsunami propagation together with documented observations and field measurements of the evidence left behind by the tsunami in December 2004. World-renowned and the second-longest tourist beach in the world “Marina” present in this region witnessed maximum death toll due to its flat topography, resulting in an inundation of about 300 m landward with high flow velocity of the order of 2 m/s.     

GIS支持下的洪水淹没范围模拟

洪水淹没范围的确定是洪灾损失评估的核心环节。采用地理信息系统 (GIS)与水力演进模型,结合三维模拟技术和对象关系模型数据库,对浙江奉化江流域洪水淹没范围进行模拟。该方法能够准确地模拟洪水淹没范围,为快速评估洪灾损失和防洪决策服务提供了科学的依据。     

Waterlogging and flood hazards vulnerability and risk assessment in Indo Gangetic plain

The recurrent flooding during monsoon and subsequent waterlogging in the northern Bihar plains and the magnitude of losses due to these hazards indicate the continuing vulnerability of the region to flood and waterlogging. Management of floods and waterlogging hazards in highly flood-prone regions of India, including Bihar state has been largely response oriented with little or no attention to mitigation and preparedness. This paper presents a method for spatial, Geographic Information Systems-based assessment of flood and waterlogging vulnerability and risk in northern Bihar plains. Multitemporal satellite data was used to evaluate the area statistics and dynamics of waterlogging over the period from 1975 to 2008. The flood proneness is evaluated at district level with reference to flood inundation during a period from 1998 to 2008. Census data were used to examine the socio-economic characteristics of the region through computation of population density, cultivators, agricultural labourers, sex ratio, children in age group 0–6 years and literates. The geohazard map derived by combining area prone to waterlogging and flood inundation was multiplied with socio-economic vulnerability map to derive the flood-waterlogging risk map of the region. The result shows that flood and water-logging pose highest risk to the central districts in the northern Bihar plains with 50.95% of the total area under high and very high risk.     

Assessment of ground subsidence hazard near an abandoned underground coal mine using GIS

This study constructs a hazard map for ground subsidence around abandoned underground coal mines (AUCMs) at Samcheok City in Korea using a probability (frequency ratio) model, a statistical (logistic regression) model, and a Geographic Information System (GIS). To evaluate the factors related to ground subsidence, an image database was constructed from a topographical map, geological map, mining tunnel map, Global Positioning System (GPS) data, land use map, lineaments, digital elevation model (DEM) data, and borehole data. An attribute database was also constructed from field investigations and reports on the existing ground subsidence areas at the study site. Nine major factors causing ground subsidence were extracted from the probability analysis of the existing ground subsidence area: (1) depth of drift; (2) DEM and slope gradient; (3) groundwater level, permeability, and rock mass rating (RMR); (4) lineaments and geology; and (5) land use. The frequency ratio and logistic regression models were applied to determine each factor’s rating, and the ratings were overlain for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with existing subsidence areas. The verification results showed that the logistic regression model (accuracy of 95.01%) is better in prediction than the frequency ratio model (accuracy of 93.29%). The verification results showed sufficient agreement between the hazard map and the existing data on ground subsidence area. Analysis of ground subsidence with the frequency ratio and logistic regression models suggests that quantitative analysis of ground subsidence near AUCMs is possible.     

Flood risk analyses—how detailed do we need to be?

Applied flood risk analyses, especially in urban areas, very often pose the question how detailed the analysis needs to be in order to give a realistic figure of the expected risk. The methods used in research and practical applications range from very basic approaches with numerous simplifying assumptions up to very sophisticated, data and calculation time demanding applications both on the hazard and on the vulnerability part of the risk. In order to shed some light on the question of required model complexity in flood risk analyses and outputs sufficiently fulfilling the task at hand, a number of combinations of models of different complexity both on the hazard and on the vulnerability side were tested in a case study. The different models can be organized in a model matrix of different complexity levels: On the hazard side, the approaches/models selected were (A) linear interpolation of gauge water levels and intersection with a digital elevation model (DEM), (B) a mixed 1D/2D hydraulic model with simplifying assumptions (LISFLOOD-FP) and (C) a Saint-Venant 2D zero-inertia hyperbolic hydraulic model considering the built environment and infrastructure. On the vulnerability side, the models used for the estimation of direct damage to residential buildings are in order of increasing complexity: (I) meso-scale stage-damage functions applied to CORINE land cover data, (II) the rule-based meso-scale model FLEMOps+ using census data on the municipal building stock and CORINE land cover data and (III) a rule-based micro-scale model applied to a detailed building inventory. Besides the inundation depths, the latter two models consider different building types and qualities as well as the level of private precaution and contamination of the floodwater. The models were applied in a municipality in east Germany, Eilenburg. It suffered extraordinary damage during the flood of August 2002, which was well documented as were the inundation extent and depths. These data provide an almost unique data set for the validation of flood risk analyses. The analysis shows that the combination of the 1D/2D model and the meso-scale damage model FLEMOps+ performed best and provide the best compromise between data requirements, simulation effort, and an acceptable accuracy of the results. The more detailed approaches suffered from complex model set-up, high data requirements, and long computation times.     

Estimating potential direct runoff for ungauged urban watersheds based on RST and GIS

Estimating the potential direct runoff for urban watersheds is essential for flood risk mitigation and rainwater harvesting. Thus, this study aims to estimate the potential runoff depth based on the natural resources conservation service (NRCS) method and delineation of the watersheds in Riyadh, Saudi Arabia. To accomplish this objective, the geographic information systems (GIS) and remote sensing technique (RST) data were integrated to save time and improve analysis accuracy. The employed data include the digital elevation model (DEM), soil map, geology map, satellite images, and daily precipitation records. Accordingly, the hydrologic soil groups (HSG), the land use/land cover (LULC), and curve number (CN) were determined for each watershed in the study area. The results of this analysis show that the study area can be delineated into 40 watersheds with a total area of 8500 km². Furthermore, the dominant HSG is group D, which represents about 71% of the total area. The LULC maps indicate four major land types in the entire study area: urban, barren land, agricultural land, and roads. The CN of the study area ranges from 64 to 98, while the weighted CN is 92 for the city. The rainfall-runoff analysis shows that the area has a high and very high daily runoff (35–50 and >?50 mm, respectively). Therefore, in this case, the runoff leads to flooding, especially in the urban area and agricultural lands.     

Prediction of ground subsidence in Samcheok City,Korea using artificial neural networks and GIS

This study shows the construction of a hazard map for presumptive ground subsidence around abandoned underground coal mines (AUCMs) at Samcheok City in Korea using an artificial neural network, with a geographic information system (GIS). To evaluate the factors governing ground subsidence, an image database was constructed from a topographical map, geological map, mining tunnel map, global positioning system (GPS) data, land use map, digital elevation model (DEM) data, and borehole data. An attribute database was also constructed by employing field investigations and reinforcement working reports for the existing ground subsidence areas at the study site. Seven major factors controlling ground subsidence were determined from the probability analysis of the existing ground subsidence area. Depth of drift from the mining tunnel map, DEM and slope gradient obtained from the topographical map, groundwater level and permeability from borehole data, geology and land use. These factors were employed by with artificial neural networks to analyze ground subsidence hazard. Each factor’s weight was determined by the back-propagation training method. Then the ground subsidence hazard indices were calculated using the trained back-propagation weights, and the ground subsidence hazard map was created by GIS. Ground subsidence locations were used to verify results of the ground subsidence hazard map and the verification results showed 96.06% accuracy. The verification results exhibited sufficient agreement between the presumptive hazard map and the existing data on ground subsidence area. An erratum to this article can be found at