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1
Shrestha, Badri Bhakta. "Approach for Analysis of Land-Cover Changes and Their Impact on Flooding Regime." Quaternary 2, no. 3 (July 28, 2019): 27. http://dx.doi.org/10.3390/quat2030027.
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This study focused on the analysis of land-use/land-cover changes and their impact on flood runoff, flood hazards and inundation, focusing in the Pampanga River basin of the Philippines. The land-cover maps for the years 1996 and 2016 were generated using Landsat images, and the land cover changes were analyzed using TerrSet Geospatial Monitoring and Modeling System (TGMMS). Based on an empirical approach and considering variable factors, the land-cover maps for the future were predicted using Land Change Modeler (LCM). After preparation of land-cover maps for past and future years, flood characteristics were analyzed using a distributed hydrological model named the rainfall runoff inundation (RRI) model with a land-cover map for different years. The impacts of land cover changes on flood runoff, flood volume and flood inundation were analyzed for 50- and 100-year floods. The results show that flood runoff, flood inundation volume and flood extent areas may increase in the future due to land-cover change in the basin.
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Chang, Li-Chiu, Mohd Amin, Shun-Nien Yang, and Fi-John Chang. "Building ANN-Based Regional Multi-Step-Ahead Flood Inundation Forecast Models." Water 10, no. 9 (September 19, 2018): 1283. http://dx.doi.org/10.3390/w10091283.
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A regional inundation early warning system is crucial to alleviating flood risks and reducing loss of life and property. This study aims to provide real-time multi-step-ahead forecasting of flood inundation maps during storm events for flood early warnings in inundation-prone regions. For decades, the Kemaman River Basin, located on the east coast of the West Malaysia Peninsular, has suffered from monsoon floods that have caused serious damage. The downstream region with an area of approximately 100 km2 located on the east side of this basin is selected as the study area. We explore and implement a hybrid ANN-based regional flood inundation forecast system in the study area. The system combines two popular artificial neural networks—the self-organizing map (SOM) and the recurrent nonlinear autoregressive with exogenous inputs (RNARX)—to sequentially produce regional flood inundation maps during storm events. The results show that: (1) the 4 × 4 SOM network can effectively cluster regional inundation depths; (2) RNARX networks can accurately forecast the long-term (3–12 h) regional average inundation depths; and (3) the hybrid models can produce adequate real-time regional flood inundation maps. The proposed ANN-based model was shown to very quickly carry out multi-step-ahead forecasting of area-wide inundation depths with sufficient lead time (up to 12 h) and can visualize the forecasted results on Google Earth using user devices to help decision makers and residents take precautionary measures against flooding.
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Gusyev, M. A., Y. Kwak, M. I. Khairul, M. B. Arifuzzaman, J. Magome, H. Sawano, and K. Takeuchi. "Effectiveness of water infrastructure for river flood management – Part 1: Flood hazard assessment using hydrological models in Bangladesh." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 75–81. http://dx.doi.org/10.5194/piahs-370-75-2015.
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Abstract. This study introduces a flood hazard assessment part of the global flood risk assessment (Part 2) conducted with a distributed hydrological Block-wise TOP (BTOP) model and a GIS-based Flood Inundation Depth (FID) model. In this study, the 20 km grid BTOP model was developed with globally available data on and applied for the Ganges, Brahmaputra and Meghna (GBM) river basin. The BTOP model was calibrated with observed river discharges in Bangladesh and was applied for climate change impact assessment to produce flood discharges at each BTOP cell under present and future climates. For Bangladesh, the cumulative flood inundation maps were produced using the FID model with the BTOP simulated flood discharges and allowed us to consider levee effectiveness for reduction of flood inundation. For the climate change impacts, the flood hazard increased both in flood discharge and inundation area for the 50- and 100-year floods. From these preliminary results, the proposed methodology can partly overcome the limitation of the data unavailability and produces flood~maps that can be used for the nationwide flood risk assessment, which is presented in Part 2 of this study.
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Zarekarizi, Mahkameh, K. Joel Roop-Eckart, Sanjib Sharma, and Klaus Keller. "The FLOod Probability Interpolation Tool (FLOPIT): A Simple Tool to Improve Spatial Flood Probability Quantification and Communication." Water 13, no. 5 (March 1, 2021): 666. http://dx.doi.org/10.3390/w13050666.
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Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.
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Kim, Hyun Il, and Kun Yeun Han. "Inundation Map Prediction with Rainfall Return Period and Machine Learning." Water 12, no. 6 (May 29, 2020): 1552. http://dx.doi.org/10.3390/w12061552.
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To date, various methods of flood prediction using numerical analysis or machine learning have been studied. However, a methodology for simultaneously predicting the rainfall return period and an inundation map for observed rainfall has not been presented. Simultaneous prediction of the return period and inundation map would be a useful technique for responding to floods in real-time and could provide an expected inundation area by return period. In this study, return period estimation for observed rainfall was performed via PNN (probabilistic neural network). SVR (support vector regression) and a SOM (self-organizing map) were used to predict flood volume and inundation maps. The study area was the Gangnam area, which has experienced extensive urbanization. The database for training SVR and SOM was constructed by one- and two-dimensional flood analysis with consideration of 120 probable rainfall events. The probable rainfall events were composed with 2–100 year return periods and 1–3 hour durations. The SVR technique was used to predict flood volume according to the rainfall return period, and the SOM was used to cluster various expected flood patterns to be used for predicting inundation maps. The prediction results were compared with the simulation results of a two-dimensional flood analysis model. The highest fitness of the predicted flood maps in the study area was calculated at 85.94%. The proposed method was found to constitute a practical methodology that could be helpful in improving urban flood response capabilities.
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Ziana, Ziana, Azmeri Azmeri, Alfiansyah Yulianur, Ella Meilianda, and Mubarak Mubarak. "Mapping of Flood Inundation and Eco-hydraulic Analyses to Minimize Food Discharge in Tributaries." Aceh International Journal of Science and Technology 12, no. 1 (April 30, 2023): 126–38. http://dx.doi.org/10.13170/aijst.12.1.31120.
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Eco-hydraulic analyses begin with the arrangement of tributaries. This research aimed to minimize the discharge of flood run-off downstream and map the flood inundation by spatial analysis uses DEMNAS data and mapping of flood inundation areas using ArcGIS. Analysis of return period flood points using HEC-RAS version 5.0.7. The data needed is the cross section of the river, the distance between the sections, the Manning's roughness number, the return period flood discharge and the slope of the river. The integration between topographic maps, watersheds and flood water levels can display areas that are potentially affected by inundation floods, so that the flood inundation limits and flood inundation areas can be calculated. This research examined proper eco-hydraulics design so that it could reduce discharge, identify locations prone to flooding, and describe the magnitude of the flood impact quantitatively. The results eco-hydraulic method obtained the design border width of 100 m, the condition before the existing river border arrangement was carried out, the inundation height was 0.30 – 1.13 m and after the river border arrangement the discharge could be reduced to 113.09 – 209 m3/s and the inundation height is 0 – 0.31 m. Based on the research results, it is known that border arrangement can provide benefits for flood control measures.
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Bhola, Punit, Jorge Leandro, and Markus Disse. "Framework for Offline Flood Inundation Forecasts for Two-Dimensional Hydrodynamic Models." Geosciences 8, no. 9 (September 13, 2018): 346. http://dx.doi.org/10.3390/geosciences8090346.
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The paper presents a new methodology for hydrodynamic-based flood forecast that focuses on scenario generation and database queries to select appropriate flood inundation maps in real-time. In operational flood forecasting, only discharges are forecasted at specific gauges using hydrological models. Hydrodynamic models, which are required to produce inundation maps, are computationally expensive, hence not feasible for real-time inundation forecasting. In this study, we have used a substantial number of pre-calculated inundation maps that are stored in a database and a methodology to extract the most likely maps in real-time. The method uses real-time discharge forecast at upstream gauge as an input and compares it with the pre-recorded scenarios. The results show satisfactory agreements between offline inundation maps that are retrieved from a pre-recorded database and online maps, which are hindcasted using historical events. Furthermore, this allows an efficient early warning system, thanks to the fast run-time of the proposed offline selection of inundation maps. The framework is validated in the city of Kulmbach in Germany.
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Uddin, Matin, and Meyer. "Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh." Remote Sensing 11, no. 13 (July 3, 2019): 1581. http://dx.doi.org/10.3390/rs11131581.
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Bangladesh is one of the most flood-affected countries in the world. In the last few decades, flood frequency, intensity, duration, and devastation have increased in Bangladesh. Identifying flood-damaged areas is highly essential for an effective flood response. This study aimed at developing an operational methodology for rapid flood inundation and potential flood damaged area mapping to support a quick and effective event response. Sentinel-1 images from March, April, June, and August 2017 were used to generate inundation extents of the corresponding months. The 2017 pre-flood land cover maps were prepared using Landsat-8 images to identify major land cover on the ground before flooding. The overall accuracy of flood inundation mapping was 96.44% and the accuracy of the land cover map was 87.51%. The total flood inundated area corresponded to 2.01%, 4.53%, and 7.01% for the months April, June, and August 2017, respectively. Based on the Landsat-8 derived land cover information, the study determined that cropland damaged by floods was 1.51% in April, 3.46% in June, 5.30% in August, located mostly in the Sylhet and Rangpur divisions. Finally, flood inundation maps were distributed to the broader user community to aid in hazard response. The data and methodology of the study can be replicated for every year to map flooding in Bangladesh.
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Chang, Ming-Jui, Hsiang-Kuan Chang, Yun-Chun Chen, Gwo-Fong Lin, Peng-An Chen, Jihn-Sung Lai, and Yih-Chi Tan. "A Support Vector Machine Forecasting Model for Typhoon Flood Inundation Mapping and Early Flood Warning Systems." Water 10, no. 12 (November 26, 2018): 1734. http://dx.doi.org/10.3390/w10121734.
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Accurate real-time forecasts of inundation depth and extent during typhoon flooding are crucial to disaster emergency response. To manage disaster risk, the development of a flood inundation forecasting model has been recognized as essential. In this paper, a forecasting model by integrating a hydrodynamic model, k-means clustering algorithm and support vector machines (SVM) is proposed. The task of this study is divided into four parts. First, the SOBEK model is used in simulating inundation hydrodynamics. Second, the k-means clustering algorithm classifies flood inundation data and identifies the dominant clusters of flood gauging stations. Third, SVM yields water level forecasts with 1–3 h lead time. Finally, a spatial expansion module produces flood inundation maps, based on forecasted information from flood gauging stations and consideration of flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we present an application to the Yilan River basin, Taiwan. The forecasting results indicate that the simulated water level forecasts from the point forecasting module are in good agreement with the observed data, and the proposed model yields the accurate flood inundation maps for 1–3 h lead time. These results indicate that the proposed model accurately forecasts not only flood inundation depth but also inundation extent. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response.
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Mangukiya, Nikunj K., Darshan J. Mehta, and Raj Jariwala. "Flood frequency analysis and inundation mapping for lower Narmada basin, India." Water Practice and Technology 17, no. 2 (January 31, 2022): 612–22. http://dx.doi.org/10.2166/wpt.2022.009.
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Abstract Floods are one of the world's most destructive natural disasters, taking more lives and causing more infrastructural damage than any other natural phenomenon. Floods have a significant economic, social, and environmental impact in developing countries like India. As a result, it is essential to address this natural disaster to mitigate its effects. The lower Narmada basin has experienced numerous floods, including severe flooding in 1970, 1973, 1984, 1990, 1994, and 2013. The objective of the present study is to use flood frequency analysis to anticipate peak floods and prepare flood inundation maps for the lower Narmada River reach. The flood frequency analysis was carried out using Gumbel's and Log-Pearson Type III Distribution methods. The hydrodynamic simulation was performed using HEC-RAS v6.0 to prepare flood inundation maps for predicted flood peaks. The result shows that the Log-Pearson Type-III distribution method gives good results for the lower return period while Gumbel's method gives good results for the higher return period. The hydrodynamic model results indicate that as the return period increases, the area of the high-risk zone increases while the area of the low-risk zone remains almost constant. The present study concludes that the existing embankment system on the banks of the Narmada River is not sufficient for significant floods. The developed maps will be helpful to government authorities and individual stakeholders to decide the flood mitigation measures.
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Adane, Amare, and Brook Abate. "RIVER MODELING FOR FLOOD INUNDATION MAP PREDICTIONS USING 2D-HEC-RAS HYDRAULIC MODELING WITH INTEGRATION OF GIS." ASEAN Engineering Journal 12, no. 1 (February 28, 2022): 9–15. http://dx.doi.org/10.11113/aej.v12.16483.
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Floods are natural disasters which if occurred produce damage to property and human life. The study of floods is important for protection of properties and human life risk. This study focuses on flooding characteristics in the flood plain of Tikurwha river catchment using two-dimensional (2D) hydrodynamic modeling. The flood inundation map of the flood prone areas is carried out using HEC-RAS 2D models with incorporation of Arc-GIS tools. Hence, using the magnitude of the flood at 2, 10, 50- and 100-year return period with a respective value of 72, 98.69, 123 and 135 (m3/s). The output of flood hazard inundation maps are carried out in 2D HEC-RAS Mapper in which the flood area at a respective return period’s flood magnitude are 75 ha, 102 ha, 108 ha, and 122 ha respectively. Based on the obtained flood inundation area, the economic impact of the flood at the specified return periods are estimated as 1791.99, 2436.89, 2589.45, and 2914.861 quintals of crop production were damaged due to flooding at respective return periods of 2, 10, 50 and 100 years.
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Pappenberger, F., K. Frodsham, K. Beven, R. Romanowicz, and P. Matgen. "Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations." Hydrology and Earth System Sciences Discussions 3, no. 4 (August 15, 2006): 2243–77. http://dx.doi.org/10.5194/hessd-3-2243-2006.
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Abstract. The paper presents a methodology for the estimation of uncertainty of inundation extent, which takes account of the uncertainty in the observed spatially distributed information and implements a fuzzy evaluation methodology. The Generalised Likelihood Uncertainty Estimation (GLUE) technique and the 2-D LISFLOOD-FP model were applied to derive the set of uncertain inundation realisations and resulting flood inundation maps. Conditioning of the inundation maps on fuzzified Synthetic Aperture Radar (SAR) images results in much more realistic inundation risk maps which can better depict the variable pattern of inundation extent than previously used methods. It has been shown that the methodology compares well to traditional approaches and can produce flood hazard maps that reflect the uncertainties in model evaluation.
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Pappenberger, F., K. Frodsham, K. Beven, R. Romanowicz, and P. Matgen. "Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations." Hydrology and Earth System Sciences 11, no. 2 (January 17, 2007): 739–52. http://dx.doi.org/10.5194/hess-11-739-2007.
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Abstract. The paper presents a methodology for the estimation of uncertainty of inundation extent, which takes account of the uncertainty in the observed spatially distributed information and implements a fuzzy evaluation methodology. The Generalised Likelihood Uncertainty Estimation (GLUE) technique and the 2-D LISFLOOD-FP model were applied to derive the set of uncertain inundation realisations and resulting flood inundation maps. Conditioning of the inundation maps on fuzzified Synthetic Aperture Radar (SAR) images results in much more realistic inundation risk maps which can better depict the variable pattern of inundation extent than previously used methods. It has been shown that the evaluation methodology compares well to traditional approaches and can produce flood hazard maps that reflect the uncertainties in model evaluation.
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Sriariyawat, Anurak, Bounhome Kimmany, Mamoru Miyamoto, Daiki Kakinuma, Shakti P. C., and Supattra Visessri. "An Approach to Flood Hazard Mapping for the Chao Phraya River Basin Using Rainfall-Runoff-Inundation Model." Journal of Disaster Research 17, no. 6 (October 1, 2022): 864–76. http://dx.doi.org/10.20965/jdr.2022.p0864.
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Flooding is a major natural hazard that can cause significant damage to socioeconomic and ecological systems. This study presents an approach to producing the maximum flood inundation and flood duration maps over the Chao Phraya River Basin (CPRB), Thailand. An integrated numerical model and spatial analysis tool were utilized in this study. The Rainfall-Runoff-Inundation (RRI) model was first used to simulate both river discharge and inundation depth. Then, the maximum flood inundation and flood duration maps with different return periods were estimated using a Geographical Information System (GIS) tool. The results illustrate that the flood inundation areas were spread out, starting from Nakhon Sawan Province, which is located in the central part of the basin. The maximum flood inundation depth could reach up to approximately 7.71, 8.28, and 8.78 m for the flood return periods of 50, 100, and 200 years, respectively. The results also indicate that the inundation areas over the CPRB could cover approximately 21,837, 23,392, and 24,533 km2 for flood return periods of 50, 100, and 200 years, respectively. The longest flood durations for return periods of 50, 100, and 200 years were approximately 159, 177, and 198 days, respectively. The longest flood duration occurred in the vicinity of the Nakhon Sawan. This study suggests that flood inundation areas and duration mapping could provide supporting information regarding the impacts caused by varying degrees of flood hazards and can be used to enhance comprehensive disaster risk management planning.
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Bales, J. D., and C. R. Wagner. "Sources of uncertainty in flood inundation maps." Journal of Flood Risk Management 2, no. 2 (June 2009): 139–47. http://dx.doi.org/10.1111/j.1753-318x.2009.01029.x.
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Apel, H., O. M. Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung. "Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam." Natural Hazards and Earth System Sciences Discussions 3, no. 8 (August 26, 2015): 4967–5013. http://dx.doi.org/10.5194/nhessd-3-4967-2015.
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Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.
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Chang, Ming-Jui, I.-Hang Huang, Chih-Tsung Hsu, Shiang-Jen Wu, Jihn-Sung Lai, and Gwo-Fong Lin. "Long-Term Flooding Maps Forecasting System Using Series Machine Learning and Numerical Weather Prediction System." Water 14, no. 20 (October 21, 2022): 3346. http://dx.doi.org/10.3390/w14203346.
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Accurate real-time forecasts of inundation depth and area during typhoon flooding is crucial to disaster emergency response. The development of an inundation forecasting model has been recognized as essential to manage disaster risk. In the past, most researchers used multiple single-point forecasts to obtain surface flooding depth forecasts with spatial interpolation. In this study, a forecasting model (QPF-RIF) integrating a hydrodynamic model (SOBEK), support vector machine–multi-step forecast (SVM-MSF), and a self-organizing map (SOM) were proposed. The task of this model was divided into four parts: hydrodynamic simulation, point forecasting, inundation database clustering, and spatial expansion. First, the SOBEK model was used in simulating inundation hydrodynamics to construct the flooding maps database. Second, the SVM-MSF yields water level (inundation volume) forecasted with a 1 to 72 h lead time. Third, the SOM clustered the previous flooding maps database into several groups representing different flooding characteristics. Finally, a spatial expansion module produced inundation maps based on forecasting information from forecasting flood volume and flood causative factors. To demonstrate the effectiveness of the proposed forecasting model, we presented an application to the Yilan River basin in Taiwan. Our forecasting results indicated that the proposed model yields accurate flood inundation maps (less than 1 cm error) for a 1 h lead time. For long-term forecasting (46 h to 72 h ahead), the model controlled the error of the forecast results within 7 cm. In the testing events, the model forecasted an average of 83% of the flooding area in the long term. This flood inundation forecasting model is expected to be useful in providing early flood warning information for disaster emergency response.
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Burnama, Nabila Siti, Faizal Immaddudin Wira Rohmat, Mohammad Farid, Arno Adi Kuntoro, Hadi Kardhana, Fauzan Ikhlas Wira Rohmat, and Winda Wijayasari. "The Utilization of Satellite Data and Machine Learning for Predicting the Inundation Height in the Majalaya Watershed." Water 15, no. 17 (August 23, 2023): 3026. http://dx.doi.org/10.3390/w15173026.
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The Majalaya area is one of the most valuable economic districts in the south of Greater Bandung, West Java, Indonesia, and experiences at least six floods per year. The floods are characterized by a sudden rise in the water level approximately one to two hours after the rain occurs. With the aim of reducing flood risk, this study models a data-driven method for predicting the inundation height across the Majalaya Watershed. The flood inundation maps of selected events were modeled using the HEC-RAS 2D numerical model. Extracted data from the HEC-RAS model, GSMaP satellite rainfall data, elevation, and other spatial data were combined to build an artificial neural network (ANN) model. The trained model targets inundation height, while the spatiotemporal data serve as the explanatory variables. The results from the trained ANN model provided very good R2 (0.9537), NSE (0.9292), and RMSE (0.3701) validation performances. The ANN model was tested with a new dataset to demonstrate the capability of predicting flood inundation height with unseen data. Such a data-driven approach is a promising tool to be developed to reduce flood risks in the Majalaya Watershed and other flood-prone locations.
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Wise, MSCE, EIT, Richard, Andrew Darnell, MSCE, EIT, and John Quaranta, PhD, PE. "Critical review of Terrain Tile and Google Earth: Virtual image mapping methods for floodplain management." Journal of Emergency Management 10, no. 6 (March 21, 2018): 433. http://dx.doi.org/10.5055/jem.2012.0120.
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Inundation mapping is a major component of floodplain management, providing critical information as to the consequences of potential failures of flood control structures. Flood mitigation efforts rely on the creation of inundation maps to develop appropriate response measures for crisis situations, including dam failures. To develop inundation maps, a dam and river system is modeled with engineering computer programs, and a simulation of the dam failure is performed to generate data for the flood. This output data are input into other programs to develop inundation maps. Inundation maps have traditionally been produced in a paper format, but recent advances in computer modeling have provided the capability for virtual inundation maps. Virtual inundation maps offer new methods of presentation and analysis of flood impacts; thus, these mapping methods need to be investigated to determine the applications and relevance to floodplain management. The goal of this research is to advance the development and use of inundation maps by floodplain managers and emergency agencies. A simulation of a potential dam failure was performed using computer modeling for a candidate river system, and the inundation maps were created using two procedures: Terrain Tiles and Google Earth. An analysis of the strengths and weaknesses of each mapping procedure was conducted. The results indicated that the Terrain Tiles procedure has advantages in displaying critical information, such as arrival times and water depths. However, this mapping procedure is more labor intensive, and the online file sharing may not be accessible for all users. The strengths of the Google Earth procedure include two-dimensional and three-dimensional views for analysis, user-friendly file sharing, and the inclusion of built-in critical infrastructure and terrain data. Drawbacks of this procedure are that the inundation must still be generated in ArcGIS, the display of critical information is not as clear, and the online file sharing may pose security issues. Thus, the Terrain Tiles procedure should be used for the development of emergency response measures, and the Google Earth procedure should be used by emergency responders in the event of an actual emergency.
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P. C., Shakti, Kohin Hirano, and Koyuru Iwanami. "Developing Flood Risk Zones during an Extreme Rain Event from the Perspective of Social Insurance Management." Sustainability 15, no. 6 (March 9, 2023): 4909. http://dx.doi.org/10.3390/su15064909.
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Recently, Japan has been hit by more frequent and severe rainstorms and floods. Typhoon Hagibis caused heavy flooding in many river basins in central and eastern Japan from 12–13 October 2019, resulting in loss of life, substantial damage, and many flood insurance claims. Considering that obtaining accurate assessments of flood situations remains a significant challenge, this study used a geographic information system (GIS)-based analytical hierarchy process (AHP) approach to develop flood susceptibility maps for the Abukuma, Naka, and Natsui River Basins during the Typhoon Hagibis event. The maps were based on population density, building density, land-use profile, distance from the river, slope, and flood inundation. A novel approach was also employed to simulate the flood inundation profiles of the river basins. In addition, a crosscheck evaluated the relationship between flood insurance claims and the developed flood risk zones within the river basins. Over 70% of insurance claims were concentrated in high to very high risk zones identified by the flood susceptibility maps. These findings demonstrate the effectiveness of this type of assessment in identifying areas that are particularly vulnerable to flood damage, which can be a useful reference for flood disaster management and related stakeholder concerns for future extreme flood events.
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Prabowo, Prabowo, Gusfan Halik, Entin Hidayah, and Taqiudin Haq. "Reduce Flood Losses Of Kali Tanggul Using Spatial Based Technical Approaches." UKaRsT 5, no. 2 (December 20, 2021): 174. http://dx.doi.org/10.30737/ukarst.v5i2.1678.
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Flood disasters frequently occurred in Jember Regency, East Java. It is usually caused by the overflow of the Tanggul River in the rainy season, especially in the downstream area. Flood control could be done by building dams, embankments, shortcuts, and other technical flood protections. Meanwhile, mitigation efforts such as developing thematic maps of flood inundation need to be done to minimize losses caused by the flood. This study aims to design a flood mitigation strategy technically. The flood control structure was proposed by designing a shortcut in Kali Tanggul. Its performance was analyzed to reduce flood inundation in the Tanggul watershed. The flood inundation modeling was carried out using spatial analysis using ArcGIS 10.1 and hydraulic analysis using HECRAS 5.0.3. Flood inundation results were compared with the Tanggul watershed flood map developed by UPT PUSDA Lumajang. Based on modeling results, flood control using shortcuts is considered an effective strategy for flood mitigation. It was indicated by the reduction of flood inundation distributions, flood inundation height, and flood-affected areas. The results show that the flood height decrease 0.47 up to 0.56 m
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Sava, Elena, Guido Cervone, and Alfred Kalyanapu. "Multiscale Observation Product (MOP) for Temporal Flood Inundation Mapping of the 2015 Dallas Texas Flood." Remote Sensing 15, no. 6 (March 16, 2023): 1615. http://dx.doi.org/10.3390/rs15061615.
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This paper presents a new data fusion multiscale observation product (MOP) for flood emergencies. The MOP was created by integrating multiple sources of contributed open-source data with traditional spaceborne remote sensing imagery in order to provide a sequence of high spatial and temporal resolution flood inundation maps. The study focuses on the 2015 Memorial Day floods that caused up to USD 61 million dollars of damage. The Hydraulic Engineering Center River Analysis System (HEC-RAS) model was used to simulate water surfaces for the northern part of the Trinity River in Dallas, using reservoir surcharge releases and topographic data provided by the U.S. Army Corps of Engineers. A measure of fit assessment is performed on the MOP flood maps with the HEC-RAS simulated flood inundation output to quantify spatial differences. Estimating possible flood inundation using individual datasets that vary spatially and temporally allow to gain an understanding of how much each observational dataset contributes to the overall water estimation. Results show that water surfaces estimated by MOP are comparable with the simulated output for the duration of the flood event. Additionally, contributed data, such as Civil Air Patrol, although they may be geographically sparse, become an important data source when fused with other observation data.
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Natho, Stephanie. "How Flood Hazard Maps Improve the Understanding of Ecologically Active Floodplains." Water 13, no. 7 (March 30, 2021): 937. http://dx.doi.org/10.3390/w13070937.
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Floodplains are threatened ecosystems and are not only ecologically meaningful but also important for humans by creating multiple benefits. Many underlying functions, like nutrient retention, carbon sequestration or water regulation, strongly depend on regular inundation. So far, these are approached on the basis of what are called ‘active floodplains’. Active floodplains, defined as statistically inundated once every 100 years, represent less than 10% of a floodplain’s original size. Still, should this remaining area be considered as one homogenous surface in terms of floodplain function, or are there any alternative approaches to quantify ecologically active floodplains? With the European Flood Hazard Maps, the extent of not only medium floods (T-medium) but also frequent floods (T-frequent) needs to be modelled by all member states of the European Union. For large German rivers, both scenarios were compared to quantify the extent, as well as selected indicators for naturalness derived from inundation. It is assumed that the more naturalness there is, the more inundation and the better the functioning. Real inundation was quantified using measured discharges from relevant gauges over the past 20 years. As a result, land uses indicating strong human impacts changed significantly from T-frequent to T-medium floodplains. Furthermore, the extent, water depth and water volume stored in the T-frequent and T-medium floodplains is significantly different. Even T-frequent floodplains experienced inundation for only half of the considered gauges during the past 20 years. This study gives evidence for considering regulation functions on the basis of ecologically active floodplains, meaning in floodplains with more frequent inundation that T-medium floodplains delineate.
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Darnell, MSCE, EIT, Andrew, Richard Wise, MSCE, EIT, and John Quaranta, PhD, PE. "Comparison of ArcToolbox and Terrain Tiles processing procedures for inundation mapping in mountainous terrain." Journal of Emergency Management 11, no. 2 (February 16, 2017): 133. http://dx.doi.org/10.5055/jem.2013.0132.
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Floodplain management consists of efforts to reduce flood damage to critical infrastructure and to protect the life and health of individuals from flooding. A major component of this effort is the monitoring of flood control structures such as dams because the potential failure of these structures may have catastrophic consequences. To prepare for these threats, engineers use inundation maps that illustrate the flood resulting from high river stages. To create the maps, the structure and river systems are modeled using engineering software programs, and hydrologic events are used to simulate the conditions leading to the failure of the structure. The output data are then exported to other software programs for the creation of inundation maps. Although the computer programs for this process have been established, the processing procedures vary and yield inconsistent results. Thus, these processing methods need to be examined to determine the functionality of each in floodplain management practices. The main goal of this article is to present the development of a more integrated, accurate, and precise graphical interface tool for interpretation by emergency managers and floodplain engineers. To accomplish this purpose, a potential dam failure was simulated and analyzed for a candidate river system using two processing methods: ArcToolbox and Terrain Tiles. The research involved performing a comparison of the outputs, which revealed that both procedures yielded similar inundations for single river reaches. However, the results indicated key differences when examining outputs for large river systems. On the basis of criteria involving the hydrologic accuracy and effects on infrastructure, the Terrain Tiles inundation surpassed the ArcToolbox inundation in terms of following topography and depicting flow rates and flood extents at confluences, bends, and tributary streams. Thus, the Terrain Tiles procedure is a more accurate representation of flood extents for use by floodplain engineers, hydrologists, geographers, and emergency managers.
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Pranadiarso, Tedy, Entin Hidayah, and Gusfan Halik. "Pemetaan Cepat Genangan Banjir Menggunakan Teknologi Remote Sensing." Rekayasa Sipil 16, no. 2 (June 30, 2022): 132–41. http://dx.doi.org/10.21776/ub.rekayasasipil.2022.016.02.9.
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The existence of a flood inundation rapid map is needed in flood mitigation. This research is intended to map flood inundation quickly by utilizing satellite image technology. Sentinel 2 Level 1C technology uses before and after the flood. The extraction process uses the methods of NDWI (Normalized Difference Water Index) and MNDWI (Modified Normalized Difference Water Index). The result is treated with a threshold value by dividing the pixel value into flooded and unflooded areas. The performance model shows that the MNDWI method is more accurate than the NDWI method in producing flood inundation maps. Thus, the results of the MNDWI method are practical and able to map flood inundation quickly.
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Ridolfi, Elena, Silvia Di Francesco, Claudia Pandolfo, Nicola Berni, Chiara Biscarini, and Piergiorgio Manciola. "Coping with Extreme Events: Effect of Different Reservoir Operation Strategies on Flood Inundation Maps." Water 11, no. 5 (May 10, 2019): 982. http://dx.doi.org/10.3390/w11050982.
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The need of addressing “residual flood risk” associated with structural protection measures, such as levee systems and flood-control reservoirs, has fostered actions aimed at increasing flood risk awareness. Structural measures have lowered risk perception by inducing a false sense of safety. As a result, these structures contribute to an underestimation of the “residual risk”. We analyze the effect of different reservoir operations, such as coping with drought versus coping with flood events, on flood inundation patterns. First, a hydrological model simulates different scenarios, which represent the dam regulation strategies. Each regulation strategy is the combination of an opening of the outlet gate and of the initial water level in the reservoir. Second, the corresponding outputs of the dam in terms of maximum discharge values are estimated. Then, in turn, each output of the dam is used as an upstream boundary condition of a hydraulic model used to simulate the flood propagation and the inundation processes in the river reach. The hydraulic model is thus used to determine the effect, in terms of inundated areas, of each dam regulation scenario. Finally, the ensemble of all flood inundation maps is built to define the areas more prone to be flooded. The test site is the Casanuova dam (Umbria, central Italy) which aims at: (i) mitigating floods occurring at the Chiascio River, one of the main tributaries of Tiber River, while (ii) providing water supply for irrigation. Because of these two competitive interests, the understanding of different scenarios generated by the dam operations offers an unique support to flood mitigation strategies. Results can lead to draw interesting remarks for a wide number of case studies.
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Jayapadma, J. M. M. U., Kazuyoshi Souma, Hiroshi Ishidaira, Jun Magome, and T. N. Wickramaarachchi. "The Effect of Incorporation of Embankment Information for Flood Simulation of the Gin River, Sri Lanka." Journal of Disaster Research 17, no. 3 (April 1, 2022): 475–86. http://dx.doi.org/10.20965/jdr.2022.p0475.
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As flooding is inevitable and becoming increasingly frequent, efficient flood management strategies should be developed to manage floods, especially in developing countries. Rainfall-Runoff-Inundation (RRI) model, which is based on a diffusive wave model, was applied to Gin River Basin, Sri Lanka using daily rainfall data. The RRI model was calibrated and validated for three past flood events (2003, 2016, and 2017) based on observed discharge data and inundation maps developed from ground survey data and satellite images. The Nash–Sutcliffe efficiency (NSE) values for river discharge obtained at the downstream gauging station were greater than 0.7 during both the calibration and validation experiments. Simulated inundation data showed good agreement with the limited observational records. The Critical Success Index (CSI) value for inundated extent in large flood event (May 2017) within downstream was greater than 0.3. Incorporation of embankment information significantly improved the accuracy of the simulation of inundation extent during large flood events (May 2017). The CSI value without embankment information for large flood event (May 2017) within downstream decreased to around 0.1. On the other hand, the embankment information was less useful for smaller flood events caused by less extreme rainfall. Inclusion of embankment information for large flood events enhanced the model performance, thus ensuring the availability of accurate inundation information for efficient flood risk planning and management in the basin.
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Zanchetta, Andre D. L., and Paulin Coulibaly. "Probabilistic Forecasts of Flood Inundation Maps Using Surrogate Models." Geosciences 12, no. 11 (November 21, 2022): 426. http://dx.doi.org/10.3390/geosciences12110426.
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The use of data-driven surrogate models to produce deterministic flood inundation maps in a timely manner has been investigated and proposed as an additional component for flood early warning systems. This study explores the potential of such surrogate models to forecast multiple inundation maps in order to generate probabilistic outputs and assesses the impact of including quantitative precipitation forecasts (QPFs) in the set of predictors. The use of a k-fold approach for training an ensemble of flood inundation surrogate models that replicate the behavior of a physics-based hydraulic model is proposed. The models are used to forecast the inundation maps resulting from three out-of-the-dataset intense rainfall events both using and not using QPFs as a predictor, and the outputs are compared against the maps produced by a physics-based hydrodynamic model. The results show that the k-fold ensemble approach has the potential to capture the uncertainties related to the process of surrogating a hydrodynamic model. Results also indicate that the inclusion of the QPFs has the potential to increase the sharpness, with the tread-off also increasing the bias of the forecasts issued for lead times longer than 2 h.
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Kassem, Yousseuf, Hüseyin Gökçekuş, and Nour Alijl. "Flash flood risk assessment modelling and methods: Kyrenia Region, Northern Cyprus." World Journal of Environmental Research 11, no. 1 (May 16, 2022): 42–52. http://dx.doi.org/10.18844/wjer.v11i1.7190.
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Flash flooding risk impacts can be reduced through the implementation of mitigation strategies plan (MSP) for flood management. This study aims to develop a flash-floods risk mitigation plan, which appears to be beneficial for municipalities, provincial administrators, and authorities to reduce the impact of the flash flood in the Kyrenia region, Northern Cyprus. In this work, rainfall data were collected from the nearest stations for 22 years. The return periods of maximum daily rainfall are also determined by using six formulas. Furthermore, flood inundation and hazard maps were defined by utilizing SAGA, QGIS, ArcGIS, 2D HEC RAS, and HEC -HMS software then determining the degree of risk and identifying strategies based on quantitative risk analysis by developing a risk matrix. As a final result, catastrophic risk areas are distributed significantly downstream. In conclusion, the proposed flash flood mitigation plan includes strategies to reduce flood losses of human life and constructed structures across Kyrenia and proposed hazard and inundation risk maps to assess planners and decision-makers for the potential impact of floods to avoid. Keywords: DEM; Flash Flood; Hazard map; HEC-RA Mitigation plan; Risk matrix
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Kassem, Y., H. Gökçekuş, and N. Alijl. "Flash Flood Risk Assessment for Girne Region, Northern Cyprus." Engineering, Technology & Applied Science Research 12, no. 3 (June 6, 2022): 8728–37. http://dx.doi.org/10.48084/etasr.4939.
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Girne region is in the northern part of Northern Cyprus which is environmentally fragile and susceptible to natural disasters. Flash floods are a major problem in the region due to the heavy and torrential rainfalls in its urban environment. Therefore, this study aims to assess the flash flood risk for the Girne region, using the Geographic Information System (GIS). A mitigation flood risk plan is proposed and applied to the case study of the Girne region. The flood risk matrix is proposed based on the occurrence probability of the flood and the associated inundation depth. The risk matrix criterion was classified according to the degree of risks as high, moderate, and low. Five thematic maps affecting flood occurrences, including slope, elevation, land use, peak discharge, and flow accumulation, were classified to generate flood hazard maps. The results of the estimation of the magnitude of the inundation areas that can assess the degree of damage and its economic aspects are presented graphically. The developed flood risk matrix tool is a quantitative tool to assess damage and is essential for decision-makers.
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Apel, Heiko, Oriol Martínez Trepat, Nguyen Nghia Hung, Do Thi Chinh, Bruno Merz, and Nguyen Viet Dung. "Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam." Natural Hazards and Earth System Sciences 16, no. 4 (April 13, 2016): 941–61. http://dx.doi.org/10.5194/nhess-16-941-2016.
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Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either a fluvial or pluvial flood hazard, studies of a combined fluvial and pluvial flood hazard are hardly available. Thus this study aims to analyse a fluvial and a pluvial flood hazard individually, but also to develop a method for the analysis of a combined pluvial and fluvial flood hazard. This combined fluvial–pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as an example. In this tropical environment the annual monsoon triggered floods of the Mekong River, which can coincide with heavy local convective precipitation events, causing both fluvial and pluvial flooding at the same time. The fluvial flood hazard was estimated with a copula-based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. The pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data and a stochastic rainstorm generator. Inundation for all flood scenarios was simulated by a 2-dimensional hydrodynamic model implemented on a Graphics Processing Unit (GPU) for time-efficient flood propagation modelling. The combined fluvial–pluvial flood scenarios were derived by adding rainstorms to the fluvial flood events during the highest fluvial water levels. The probabilities of occurrence of the combined events were determined assuming independence of the two flood types and taking the seasonality and probability of coincidence into account. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation taking into account the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and their usage in flood risk management are outlined.
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Tadesse, Yohannis Birhanu, and Peter Fröhle. "Modelling of Flood Inundation due to Levee Breaches: Sensitivity of Flood Inundation against Breach Process Parameters." Water 12, no. 12 (December 18, 2020): 3566. http://dx.doi.org/10.3390/w12123566.
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This paper analyses the sensitivity of flood inundation due to river levee breach against breach process parameters using the 1996 Awash River levee breach case at Wonji, Ethiopia. A parametric levee breach model integrated into the 2D hydrodynamic numerical model Telemac-2D is used to simulate a levee breach flood event at Wonji, Ethiopia. Levee breach process parameters are systemically varied to find out their effect on the flood inundation. The analysis of the model results shows that the flood inundation is sensitive to the final breach dimensions and breach location. However, the parameters describing the levee breach development have negligible influence on the flood inundation. This implies that final breach dimension and breach location in an event of levee breach are the most important and decisive parameters affecting the resulting inundation of the flood plain, and as such should be given due consideration when creating flood inundation maps due to levee breach.
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Dogan, Emrah, Osman Sonmez, Emrah Yapan, Koray Othan, Sait Ozdemir, and Tarik Citgez. "Creating Flood Inundation Maps For Lower Sakarya River." SAÜ Fen Bilimleri Enstitüsü Dergisi 17, no. 3 (2013): 363–69. http://dx.doi.org/10.5505/saufbe.2013.98700.
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Kim, Hyun, Ho Keum, and Kun Han. "Real-Time Urban Inundation Prediction Combining Hydraulic and Probabilistic Methods." Water 11, no. 2 (February 8, 2019): 293. http://dx.doi.org/10.3390/w11020293.
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Damage caused by flash floods is increasing due to urbanization and climate change, thus it is important to recognize floods in advance. The current physical hydraulic runoff model has been used to predict inundation in urban areas. Even though the physical calculation process is astute and elaborate, it has several shortcomings in regard to real-time flood prediction. The physical model requires various data, such as rainfall, hydrological parameters, and one-/two-dimensional (1D/2D) urban flood simulations. In addition, it is difficult to secure lead time because of the considerable simulation time required. This study presents an immediate solution to these problems by combining hydraulic and probabilistic methods. The accumulative overflows from manholes and an inundation map were predicted within the study area. That is, the method for predicting manhole overflows and an inundation map from rainfall in an urban area is proposed based on results from hydraulic simulations and uncertainty analysis. The Second Verification Algorithm of Nonlinear Auto-Regressive with eXogenous inputs (SVNARX) model is used to learn the relationship between rainfall and overflow, which is calculated from the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM). In addition, a Self-Organizing Feature Map (SOFM) is used to suggest the proper inundation area by clustering inundation maps from a 2D flood simulation model based on manhole overflow from SWMM. The results from two artificial neural networks (SVNARX and SOFM) were estimated in parallel and interpolated to provide prediction in a short period of time. Real-time flood prediction with the hydraulic and probabilistic models suggested in this study improves the accuracy of the predicted flood inundation map and secures lead time. Through the presented method, the goodness of fit of the inundation area reached 80.4% compared with the verified 2D inundation model.
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Zhou, Xudong, Wenchao Ma, Wataru Echizenya, and Dai Yamazaki. "The uncertainty of flood frequency analyses in hydrodynamic model simulations." Natural Hazards and Earth System Sciences 21, no. 3 (March 23, 2021): 1071–85. http://dx.doi.org/10.5194/nhess-21-1071-2021.
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Abstract. Assessing the risk of a historical-level flood is essential for regional flood protection and resilience establishment. However, due to the limited spatiotemporal coverage of observations, the impact assessment relies on model simulations and is thus subject to uncertainties from cascade physical processes. This study assesses the flood hazard map with uncertainties subject to different combinations of runoff inputs, variables for flood frequency analysis and fitting distributions based on estimations by the CaMa-Flood global hydrodynamic model. Our results show that deviation in the runoff inputs is the most influential source of uncertainties in the estimated flooded water depth and inundation area, contributing more than 80 % of the total uncertainties investigated in this study. Global and regional inundation maps for floods with 1-in-100 year return periods show large uncertainty values but small uncertainty ratios for river channels and lakes, while the opposite results are found for dry zones and mountainous regions. This uncertainty is a result of increasing variation at tails among various fitting distributions. In addition, the uncertainty between selected variables is limited but increases from the regular period to the rarer floods, both for the water depth at points and for inundation area over regions. The uncertainties in inundation area also lead to uncertainties in estimating the population and economy exposure to the floods. In total, inundation accounts for 9.1 % [8.1 %–10.3 %] of the land area for a 1-in-100 year flood, leading to 13.4 % [12.1 %–15 %] of population exposure and 13.1 % [11.8 %–14.7 %] of economic exposure for the globe. The flood exposure and uncertainties vary by continent and the results in Africa have the largest uncertainty, probably due to the limited observations to constrain runoff simulations, indicating a necessity to improve the performance of different hydrological models especially for data-limited regions.
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Tran, Hoang, Phu Nguyen, Mohammed Ombadi, Kuolin Hsu, Soroosh Sorooshian, and Konstantinos Andreadis. "Improving Hydrologic Modeling Using Cloud-Free MODIS Flood Maps." Journal of Hydrometeorology 20, no. 11 (November 1, 2019): 2203–14. http://dx.doi.org/10.1175/jhm-d-19-0021.1.
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Abstract Flood mapping from satellites provides large-scale observations of flood events, but cloud obstruction in satellite optical sensors limits its practical usability. In this study, we implemented the Variational Interpolation (VI) algorithm to remove clouds from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area (SCA) products. The VI algorithm estimated states of cloud-hindered pixels by constructing three-dimensional space–time surfaces based on assumptions of snow persistence. The resulting cloud-free flood maps, while maintaining the temporal resolution of the original MODIS product, showed an improvement of nearly 70% in average probability of detection (POD) (from 0.29 to 0.49) when validated with flood maps derived from Landsat-8 imagery. The second part of this study utilized the cloud-free flood maps for calibration of a hydrologic model to improve simulation of flood inundation maps. The results demonstrated the utility of the cloud-free maps, as simulated inundation maps had average POD, false alarm ratio (FAR), and Hanssen–Kuipers (HK) skill score of 0.87, 0.49, and 0.84, respectively, compared to POD, FAR, and HK of 0.70, 0.61, and 0.67 when original maps were used for calibration.
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Pagneux, Emmanuel, and Árni Snorrason. "High-accuracy mapping of inundations induced by ice jams: a case study from Iceland." Hydrology Research 43, no. 4 (January 27, 2012): 412–21. http://dx.doi.org/10.2166/nh.2012.114.
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Hydraulic modelling is widely used for deriving flood hazard maps featuring depth of flooding and flow velocity from discharge scenarios. Due to uncertainties about flow conditions or inaccurate terrain models, flood hazards maps obtained from hydraulic modelling may be of limited relevance and accuracy. Hydraulic modelling is particularly challenging in Arctic regions, where ice jams lead to flooding in areas that would not be subjected to inundation under open-water conditions. As numerical models of ice jam processes require information that may be difficult and expensive to collect, an alternative approach based on the photo interpretation of documented historical events is presented here. Orthophotographs and a digital elevation model at high resolution are used to support the photo interpretation process. Tested in an Icelandic watershed prone to ice jam floods, reconstructions provide locally unprecedented and robust information on the extent and depth of flooding of inundations induced by ice jams.
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Griesbaum, Luisa, Sabrina Marx, and Bernhard Höfle. "Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images." Natural Hazards and Earth System Sciences 17, no. 7 (July 14, 2017): 1191–201. http://dx.doi.org/10.5194/nhess-17-1191-2017.
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Abstract. In recent years, the number of people affected by flooding caused by extreme weather events has increased considerably. In order to provide support in disaster recovery or to develop mitigation plans, accurate flood information is necessary. Particularly pluvial urban floods, characterized by high temporal and spatial variations, are not well documented. This study proposes a new, low-cost approach to determining local flood elevation and inundation depth of buildings based on user-generated flood images. It first applies close-range digital photogrammetry to generate a geo-referenced 3-D point cloud. Second, based on estimated camera orientation parameters, the flood level captured in a single flood image is mapped to the previously derived point cloud. The local flood elevation and the building inundation depth can then be derived automatically from the point cloud. The proposed method is carried out once for each of 66 different flood images showing the same building façade. An overall accuracy of 0.05 m with an uncertainty of ±0.13 m for the derived flood elevation within the area of interest as well as an accuracy of 0.13 m ± 0.10 m for the determined building inundation depth is achieved. Our results demonstrate that the proposed method can provide reliable flood information on a local scale using user-generated flood images as input. The approach can thus allow inundation depth maps to be derived even in complex urban environments with relatively high accuracies.
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Hu, Anson, and Ibrahim Demir. "Real-Time Flood Mapping on Client-Side Web Systems Using HAND Model." Hydrology 8, no. 2 (April 11, 2021): 65. http://dx.doi.org/10.3390/hydrology8020065.
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The height above nearest drainage (HAND) model is frequently used to calculate properties of the soil and predict flood inundation extents. HAND is extremely useful due to its lack of reliance on prior data, as only the digital elevation model (DEM) is needed. It is close to optimal, running in linear or linearithmic time in the number of cells depending on the values of the heights. It can predict watersheds and flood extent to a high degree of accuracy. We applied a client-side HAND model on the web to determine extent of flood inundation in several flood prone areas in Iowa, including the city of Cedar Rapids and Ames. We demonstrated that the HAND model was able to achieve inundation maps comparable to advanced hydrodynamic models (i.e., Federal Emergency Management Agency approved flood insurance rate maps) in Iowa, and would be helpful in the absence of detailed hydrological data. The HAND model is applicable in situations where a combination of accuracy and short runtime are needed, for example, in interactive flood mapping and supporting mitigation decisions, where users can add features to the landscape and see the predicted inundation.
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Hasibuan, M. A. S., Widiatmaka, S. D. Tarigan, and W. Ambarwulan. "Flood Inundation Distribution Modelling for River Boundary Management in Cisadane Sub-Watershed." IOP Conference Series: Earth and Environmental Science 1109, no. 1 (November 1, 2022): 012087. http://dx.doi.org/10.1088/1755-1315/1109/1/012087.
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Abstract Cisadane watershed is one of the priority watersheds to be restored immediately. The Cisadane River has the potency to cause floods in the river’s border region due to a reduction in river width, river depth, and land-use changes. This study aims to analyze the distribution of flood inundation by employing the HEC-RAS. Flood distribution modeling using components the flood distribution in the steady flow of water level profile component. The permanent flow use is 19 January 2022 discharge. Scenarios discharge was reported with a return period of 5, 10, 25, 50 and 100 years. Digital Elevation Model (DEM), discharge, watershed boundary, and land use maps are included in the data used. The results indicated that 30 districts were affected by the flood. The extent of the annual flood inundation is predicted to expand by 24.41 hectares per year throughout each discharge period. Teluk Naga, Sepatan Timur, Paku Haji, and Neglasari Districts have the broadest and deepest probablility inundation in Tangerang Regency, with a total inundation area 644,7 hectares (permanent flow). The depth will increase from 0.40 to 1.33 m as the return period discharge rises. Tangerang Regency, located in the Lower Cisadane watershed, is the most affected area.
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Awadallah, Mahmoud Omer Mahmoud, Ana Juárez, and Knut Alfredsen. "Comparison between Topographic and Bathymetric LiDAR Terrain Models in Flood Inundation Estimations." Remote Sensing 14, no. 1 (January 5, 2022): 227. http://dx.doi.org/10.3390/rs14010227.
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Remotely sensed LiDAR data has allowed for more accurate flood map generation through hydraulic simulations. Topographic and bathymetric LiDARs are the two types of LiDAR used, of which the former cannot penetrate water bodies while the latter can. Usually, the topographic LiDAR is more available than bathymetric LiDAR, and it is, therefore, a very interesting data source for flood mapping. In this study, we made comparisons between flood inundation maps from several flood scenarios generated by the HEC-RAS 2D model for 11 sites in Norway using both bathymetric and topographic terrain models. The main objective is to investigate the accuracy of the flood inundations generated from the plain topographic LiDAR, the links of the inaccuracies with geomorphic features, and the potential of using corrections for missing underwater geometry in the topographic LiDAR data to improve accuracy. The results show that the difference in inundation between topographic and bathymetric LiDAR models decreases with increasing the flood size, and this trend was found to be correlated with the amount of protection embankments in the reach. In reaches where considerable embankments are constructed, the difference between the inundations increases until the embankments are overtopped and then returns to the general trend. In addition, the magnitude of the inundation error was found to correlate positively with the sinuosity and embankment coverage and negatively with the angle of the bank. Corrections were conducted by modifying the flood discharge based on the flight discharge of the topographic LiDAR or by correcting the topographic LiDAR terrain based on the volume of the flight discharge, where the latter method generally gave better improvements.
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Hearn Jr, PhD, Paul P., Herbert E. "Gene" Longenecker III, MS, and Ami N. Rahav. "Delivering integrated HAZUS-MH flood loss analyses and flood inundation maps over the Web." Journal of Emergency Management 11, no. 4 (February 16, 2017): 293. http://dx.doi.org/10.5055/jem.2013.0145.
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Catastrophic flooding is responsible for more loss of life and damages to property than any other natural hazard. Recently developed flood inundation mapping technologies make it possible to view the extent and depth of flooding on the land surface over the Internet; however, by themselves these technologies are unable to provide estimates of losses to property and infrastructure.The Federal Emergency Management Agency’s (FEMA's) HAZUS-MH software is extensively used to conduct flood loss analyses in the United States, providing a nationwide database of population and infrastructure at risk. Unfortunately, HAZUS-MH requires a dedicated Geographic Information System (GIS) workstation and a trained operator, and analyses are not adapted for convenient delivery over the Web. This article describes a cooperative effort by the US Geological Survey (USGS) and FEMA to make HAZUS-MH output GIS and Web compatible and to integrate these data with digital flood inundation maps in USGS’s newly developed Inundation Mapping Web Portal. By running the computationally intensive HAZUS-MH flood analyses offline and converting the output to a Web-GIS compatible format, detailed estimates of flood losses can now be delivered to anyone with Internet access, thus dramatically increasing the availability of these forecasts to local emergency planners and first responders.
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Tsitroulis, I., K. Voudouris, A. Vasileiou, C. Mattas, Μ. Sapountzis, and F. Maris. "FLOOD HAZARD ASSESSMENT AND DELIMITATION OF THE LIKELY FLOOD HAZARD ZONES OF THE UPPER PART IN GALLIKOS RIVER BASIN." Bulletin of the Geological Society of Greece 50, no. 2 (July 27, 2017): 995. http://dx.doi.org/10.12681/bgsg.11804.
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Floods are one of the most common natural hazards in global range and could threat the human life, health, environment and infrastructure. The aim of this paper is the estimation and the delimitation of the likely flood hazard zones, for different rainfall intensities in the upper part of Gallikos river basin (central Macedonia) according to the European directive 2007/60. For the analysis of the meteorological data and the construction of flood zone maps, HYDROGNOMON, HEC-HMS, HEC-RAS free software packages were used. The thematic maps were constructed with ESRI GIS. The results are depicted in flood inundation maps, delimitating and visualizing the scale of the flood hazard effect in the area. The construction of flood prediction models is a very useful tool towards the direction of the design of an efficient flood management framework.
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Wang, Zixiong, Ya Sun, Chunhui Li, Ling Jin, Xinguo Sun, Xiaoli Liu, and Tianxiang Wang. "Analysis of Small and Medium–Scale River Flood Risk in Case of Exceeding Control Standard Floods Using Hydraulic Model." Water 14, no. 1 (December 28, 2021): 57. http://dx.doi.org/10.3390/w14010057.
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Exceeding control standard floods pose threats to the management of small and medium–scale rivers. Taking Fuzhouhe river as an example, this paper analyzes the submerged depth, submerged area and arrival time of river flood risk in the case of exceeding control standard floods (with return period of 20, 50, 100 and 200 years) through a coupled one– and two–dimensional hydrodynamic model, draws the flood risk maps and proposes emergency plans. The simulation results of the one–dimensional model reveal that the dikes would be at risk of overflowing for different frequencies of floods, with a higher level of risk on the left bank. The results of the coupled model demonstrate that under all scenarios, the inundation area gradually increases with time until the flood peak subsides, and the larger the flood peak, the faster the inundation area increases. The maximum submerged areas are 42.73 km2, 65.95 km2, 74.86 km2 and 82.71 km2 for four frequencies of flood, respectively. The change of submerged depth under different frequency floods shows a downward–upward–downward trend and the average submerged depth of each frequency floods is about 1.4 m. The flood risk maps of different flood frequencies are created by GIS to analyze flood arrival time, submerged area and submerged depth to plan escape routes and resettlement units. The migration distances are limited within 4 km, the average migration distance is about 2 km, the vehicle evacuation time is less than 20 min, and the walking evacuation time is set to about 70 min. It is concluded that the flood risk of small and medium–scale rivers is a dynamic change process, and dynamic flood assessment, flood warning and embankment modification scheme should be further explored.
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Brandt, S. Anders, and Nancy J. Lim. "Visualising DEM-related flood-map uncertainties using a disparity-distance equation algorithm." Proceedings of the International Association of Hydrological Sciences 373 (May 12, 2016): 153–59. http://dx.doi.org/10.5194/piahs-373-153-2016.
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Abstract. The apparent absoluteness of information presented by crisp-delineated flood boundaries can lead to misconceptions among planners about the inherent uncertainties associated in generated flood maps. Even maps based on hydraulic modelling using the highest-resolution digital elevation models (DEMs), and calibrated with the most optimal Manning's roughness (n) coefficients, are susceptible to errors when compared to actual flood boundaries, specifically in flat areas. Therefore, the inaccuracies in inundation extents, brought about by the characteristics of the slope perpendicular to the flow direction of the river, have to be accounted for. Instead of using the typical Monte Carlo simulation and probabilistic methods for uncertainty quantification, an empirical-based disparity-distance equation that considers the effects of both the DEM resolution and slope was used to create prediction-uncertainty zones around the resulting inundation extents of a one-dimensional (1-D) hydraulic model. The equation was originally derived for the Eskilstuna River where flood maps, based on DEM data of different resolutions, were evaluated for the slope-disparity relationship. To assess whether the equation is applicable to another river with different characteristics, modelled inundation extents from the Testebo River were utilised and tested with the equation. By using the cross-sectional locations, water surface elevations, and DEM, uncertainty zones around the original inundation boundary line can be produced for different confidences. The results show that (1) the proposed method is useful both for estimating and directly visualising model inaccuracies caused by the combined effects of slope and DEM resolution, and (2) the DEM-related uncertainties alone do not account for the total inaccuracy of the derived flood map. Decision-makers can apply it to already existing flood maps, thereby recapitulating and re-analysing the inundation boundaries and the areas that are uncertain. Hence, more comprehensive flood information can be provided when determining locations where extra precautions are needed. Yet, when applied, users must also be aware that there are other factors that can influence the extent of the delineated flood boundary.
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Chang, Li-Chiu, Fi-John Chang, Shun-Nien Yang, I.-Feng Kao, Ying-Yu Ku, Chun-Ling Kuo, and Ir Amin. "Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems." Water 11, no. 1 (December 21, 2018): 9. http://dx.doi.org/10.3390/w11010009.
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Flood disasters have had a great impact on city development. Early flood warning systems (EFWS) are promising countermeasures against flood hazards and losses. Machine learning (ML) is the kernel for building a satisfactory EFWS. This paper first summarizes the ML methods proposed in this special issue for flood forecasts and their significant advantages. Then, it develops an intelligent hydroinformatics integration platform (IHIP) to derive a user-friendly web interface system through the state-of-the-art machine learning, visualization and system developing techniques for improving online forecast capability and flood risk management. The holistic framework of the IHIP includes five layers (data access, data integration, servicer, functional subsystem, and end-user application) and one database for effectively dealing with flood disasters. The IHIP provides real-time flood-related data, such as rainfall and multi-step-ahead regional flood inundation maps. The interface of Google Maps fused into the IHIP significantly removes the obstacles for users to access this system, helps communities in making better-informed decisions about the occurrence of floods, and alerts communities in advance. The IHIP has been implemented in the Tainan City of Taiwan as the study case. The modular design and adaptive structure of the IHIP could be applied with similar efforts to other cities of interest for assisting the authorities in flood risk management.
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Ouyang, Mao, Yuka Ito, and Tomochika Tokunaga. "Local land subsidence exacerbates inundation hazard to the Kujukuri Plain, Japan." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 657–61. http://dx.doi.org/10.5194/piahs-382-657-2020.
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Abstract. Flood-inundation hazard maps are generally made based on the anticipated flood patterns under the configurations such as current topography and land use/land cover situations. These maps have not taken into account the possible significance of land subsidence and surface environmental changes. The Kujukuri Plain, Japan, the site of this research, has experienced severe land subsidence due to 2011 Tohoku earthquake. This paper aims to quantify the effects of local land subsidence on flood hazards under heavy rainfalls in the Kujukuri Plain. The high-resolution LiDAR data at two different periods (before and after the Tohoku earthquake) were obtained and used as the input data for the physically-based hydrological model. Through the comparison of simulated inundation areas of the scenarios with the same precipitation pattern but different topographies, the effect of land subsidence was discussed. The maps estimating the inundation areas by only considering rainfalls, i.e., without taking into account the effect of land subsidence, underestimated the inundation areas by around 10 % compared with the ones that accounted for the local land subsidence. The results of this study highlight the importance of taking into account the temporal changes of elevations and other parameters in flood hazard assessments.
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Diehl, Rebecca M., Jesse D. Gourevitch, Stephanie Drago, and Beverley C. Wemple. "Improving flood hazard datasets using a low-complexity, probabilistic floodplain mapping approach." PLOS ONE 16, no. 3 (March 29, 2021): e0248683. http://dx.doi.org/10.1371/journal.pone.0248683.
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As runoff patterns shift with a changing climate, it is critical to effectively communicate current and future flood risks, yet existing flood hazard maps are insufficient. Modifying, extending, or updating flood inundation extents is difficult, especially over large scales, because traditional floodplain mapping approaches are data and resource intensive. Low-complexity floodplain mapping techniques are promising alternatives, but their simplistic representation of process falls short of capturing inundation patterns in all situations or settings. To address these needs and deficiencies, we formalize and extend the functionality of the Height Above Nearest Drainage (i.e., HAND) floodplain mapping approach into the probHAND model by incorporating an uncertainty analysis. With publicly available datasets, the probHAND model can produce probabilistic floodplain maps for large areas relatively rapidly. We describe the modeling approach and then provide an example application in the Lake Champlain Basin, Vermont, USA. Uncertainties translate to on-the-ground changes to inundated areas, or floodplain widths, in the study area by an average of 40%. We found that the spatial extent of probable inundation captured the distribution of observed and modeled flood extents well, suggesting that low-complexity models may be sufficient for representing inundation extents in support of flood risk and conservation mapping applications, especially when uncertainties in parameter inputs and process simplifications are accounted for. To improve the accuracy of flood hazard datasets, we recommend investing limited resources in accurate topographic datasets and improved flood frequency analyses. Such investments will have the greatest impact on decreasing model output variability, therefore increasing the certainty of flood inundation extents.
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Shakti P. C., Kohin Hirano, and Satoshi Iizuka. "Flood Inundation Mapping of the Hitachi Region in the Kuji River Basin, Japan, During the October 11–13, 2019 Extreme Rain Event." Journal of Disaster Research 15, no. 6 (October 1, 2020): 712–25. http://dx.doi.org/10.20965/jdr.2020.p0712.
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The frequency of severe flood events has been increasing recently in Japan. One of the latest events occurred in October 2019 and caused extensive damage in several river basins, especially in the central and northern regions of the country. In this study, we selected the Hitachi region (Hitachi-Omiya and Hitachi-Ota) within the Kuji River Basin which underwent considerable flooding due to the failure of embankments at two locations in the region. Maximum-possible flood inundation maps were generated using survey-based data and hydrological modeling for the Hitachi region. These maps incorporated the flood scenarios (embankment failures). All the generated products were compared with the reference flood mapping, i.e., Sentinel-1 data and Geospatial Information Authority of Japan (GSI) data for that region. It was observed that generated flood inundation mapping product based on the survey-data yielded results similar to those obtained with GSI data for the Hitachi region. Although each flood mapping product has advantages and disadvantages, they can be a good reference for the proper management and mitigation of flood disaster in the future. The rapid development of flood inundation mapping products that consider varying flood scenarios is an important part of flood mitigation strategies.
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Zanchetta, Andre D. L., and Paulin Coulibaly. "Hybrid Surrogate Model for Timely Prediction of Flash Flood Inundation Maps Caused by Rapid River Overflow." Forecasting 4, no. 1 (January 23, 2022): 126–48. http://dx.doi.org/10.3390/forecast4010007.
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Timely generation of accurate and reliable forecasts of flash flood events is of paramount importance for flood early warning systems in urban areas. Although physically based models are able to provide realistic reproductions of fast-developing inundation maps in high resolutions, the high computational demand of such hydraulic models makes them difficult to be implemented as part of real-time forecasting systems. This paper evaluates the use of a hybrid machine learning approach as a surrogate of a quasi-2D urban flood inundation model developed in PCSWMM for an urban catchment located in Toronto (Ontario, Canada). The capability to replicate the behavior of the hydraulic model was evaluated through multiple performance metrics considering error, bias, correlation, and contingency table analysis. Results indicate that the surrogate system can provide useful forecasts for decision makers by rapidly generating future flood inundation maps comparable to the simulations of physically based models. The experimental tool developed can issue reliable alerts of upcoming inundation depths on traffic locations within one to two hours of lead time, which is sufficient for the adoption of important preventive actions. These promising outcomes were achieved in a deterministic setup and use only past records of precipitation and discharge as input during runtime.