Using Steady‐State Backwater Analysis to Predict Inundated Area from National Water Model Streamflow Simulations

National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts for 2.7 million reaches in the National Hydrography Dataset for continental United States (U.S.). NWM uses Muskingum–Cunge channel routing, which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain more accurate estimates of streamflow and stage in rivers, especially for applications such as flood‐inundation mapping. Here, we used a steady‐state backwater version of Simulation Program for River NeTworks (SPRNT) model. We evaluated SPRNT’s and NWM’s abilities to predict inundated area for the record flood of Hurricane Matthew in October 2016. The Neuse River experienced record‐breaking floods and was well‐documented by U.S. Geological Survey. Streamflow simulations from NWM retrospective analysis were used as input for the SPRNT simulation. Retrospective NWM discharge predictions were converted to stage. The stages (from both SPRNT and NWM) were utilized to produce flood‐inundation maps using the Height Above Nearest Drainage method which uses the local relative heights to find out the local draining potentials and provide spatial representation of inundated area. The inundated‐area accuracies for NWM and SPRNT (based on comparison to a remotely sensed dataset) were 65.1% and 67.6%, respectively. These results show using steady‐state SPRNT results in a modest improvement of inundation‐forecast accuracy compared to NWM.     

A Faster and Economical Approach to Floodplain Mapping Using Soil Information

Flood inundation maps play a key role in assessment and mitigation of potential flood hazards. However, owing to high costs associated with the conventional flood mapping methods, many communities in the United States lack flood inundation maps. The objective of this study is to develop and examine an economical alternative approach to floodplain mapping using widely available soil survey geographic (SSURGO) database. In this study, floodplain maps are developed for the entire state of Indiana, and some counties in Minnesota, Wisconsin, and Washington states by identifying flood‐prone soil map units based on their attributes. For validation, the flood extents obtained from SSURGO database are compared with the extents from other floodplain maps such as the Federal Emergency Management Agency issued flood insurance rate maps (FIRMs), flood extents observed during past floods, and flood maps derived using digital elevation models. In general, SSURGO‐based floodplain maps (SFMs) are largely in agreement with other flood inundation maps. Specifically, the floodplain extents from SFMs cover 78‐95% area compared to FIRMs and observed flood extents. Thus, albeit with a slight loss in accuracy, the SSURGO approach offers an economical and fast alternative for floodplain mapping. In particular, it has potentially high utility in areas where no detailed flood studies have been conducted.     

AutoRAPID: A Model for Prompt Streamflow Estimation and Flood Inundation Mapping over Regional to Continental Extents

This article couples two existing models to quickly generate flow and flood‐inundation estimates at high resolutions over large spatial extents for use in emergency response situations. Input data are gridded runoff values from a climate model, which are used by the Routing Application for Parallel computatIon of Discharge (RAPID) model to simulate flow rates within a vector river network. Peak flows in each river reach are then supplied to the AutoRoute model, which produces raster flood inundation maps. The coupled tool (AutoRAPID) is tested for the June 2008 floods in the Midwest and the April‐June 2011 floods in the Mississippi Delta. RAPID was implemented from 2005 to 2014 for the entire Mississippi River Basin (1.2 million river reaches) in approximately 45 min. Discretizing a 230,000‐km² area in the Midwest and a 109,500‐km² area in the Mississippi Delta into thirty‐nine 1° by 1° tiles, AutoRoute simulated a high‐resolution (~10 m) flood inundation map in 20 min for each tile. The hydrographs simulated by RAPID are found to perform better in reaches without influences from unrepresented dams and without backwater effects. Flood inundation maps using the RAPID peak flows vary in accuracy with F‐statistic values between 38.1 and 90.9%. Better performance is observed in regions with more accurate peak flows from RAPID and moderate to high topographic relief.     

Estimating Floodwater Depths from Flood Inundation Maps and Topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS‐based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large‐scale event for which we use medium resolution input layer (10 m) and a small‐scale event for which we use a high‐resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.     

A Hydraulic MultiModel Ensemble Framework for Visualizing Flood Inundation Uncertainty

While deterministic forecasts provide a single realization of potential inundation, the inherent uncertainty associated with forecasts also needs to be conveyed for improved decision support. The objective of this study was to develop an ensemble framework for the quantification and visualization of uncertainty associated with flood inundation forecast maps. An 11‐member ensemble streamflow forecast at lead times from 0 to 48 hr was used to force two hydraulic models to produce a multimodel ensemble. The hydraulic models used are (1) the International River Interface Cooperative along with Flow and Sediment Transport with Morphological Evolution of Channels solver and (2) the two‐dimensional Hydrologic Engineering Center‐River Analysis System. Uncertainty was quantified and augmented onto flood inundation maps by calculating statistical spread among the ensemble members. For visualization, a series of probability flood maps conveying the uncertainty in forecasted water extent, water depth, and flow velocity was disseminated through a web‐based decision support tool. The results from this study offer a framework for quantifying and visualizing model uncertainty in forecasted flood inundation maps.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Comparative Analysis of Inundation Mapping Approaches for the 2016 Flood in the Brazos River,Texas

Accurate and timely flood inundation maps serve as crucial information for hydrologists, first‐responders, and decision makers of natural disaster management agencies. In this study, two modeling approaches are applied to estimate the inundation area for a large flooding event that occurred in May 2016 in the Brazos River: (1) Height Above the Nearest Drainage combined with National Hydrograph Dataset Plus (NHDPlus‐HAND) and (2) International River Interface Cooperative — Flow and Sediment Transport with Morphological Evolution of Channels (iRIC‐FaSTMECH). The inundation extents simulated from these two modeling approaches are then compared against the observed inundation extents derived from a Landsat 8 satellite image. The simulated results from NHDPlus‐HAND and iRIC‐FaSTMECH show 56% and 70% of overlaps with the observed flood extents, respectively. A modified version of the NHDPlus‐HAND model, considering networked catchment behaviors, is also tested with an improved fitness of 67%. This study suggests that NHDPlus‐HAND has the potential for real‐time continental inundation forecast due to its low computational cost and ease to couple with the National Water Model. Better performance of NHDPlus‐HAND can be achieved by considering the inter‐catchment flows during extreme riverine flood events. Overall, this study presents a comprehensive examination made of remote sensing compared with HAND‐based inundation mapping in a region of complex topography.     

A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping

We present a Digital Elevation Model‐based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc‐second (10 m) height above nearest drainage (HAND) raster data for the conterminous United States (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc‐second CONUS HAND raster dataset was computed in 1.5 days on the cyberGIS Resourcing Open Geospatial Education and Research supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model forecast data to enable near real‐time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process were profiled to gain insights into the computational characteristics in high‐performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies.     

Conceptual Framework for the National Flood Interoperability Experiment

The National Flood Interoperability Experiment is a research collaboration among academia, National Oceanic and Atmospheric Administration National Weather Service, and government and commercial partners to advance the application of the National Water Model for flood forecasting. In preparation for a Summer Institute at the National Water Center in June‐July 2015, a demonstration version of a near real‐time, high spatial resolution flood forecasting model was developed for the continental United States. The river and stream network was divided into 2.7 million reaches using the National Hydrography Dataset Plus geospatial dataset and it was demonstrated that the runoff into these stream reaches and the discharge within them could be computed in 10 min at the Texas Advanced Computing Center. This study presents a conceptual framework to connect information from high‐resolution flood forecasting with real‐time observations and flood inundation mapping and planning for local flood emergency response.     

A Framework to Develop Nationwide Flooding Extents Using Climate Models and Assess Forecast Potential for Flood Resilience

The methods used to simulate flood inundation extents can be significantly improved by high‐resolution spatial data captured over a large area. This paper presents a hydraulic analysis methodology and framework to estimate national‐level floodplain changes likely to be generated by climate change. The hydraulic analysis was performed using existing published Federal Emergency Management Agency 100‐year floodplains and estimated 100‐ and 10‐year return period peak flow discharges. The discharges were estimated using climate variables from global climate models for two future growth scenarios: Representative Concentration Pathways 2.6 and 8.5. River channel dimensions were developed based on existing regional United States Geological Survey publications relating bankfull discharges with channel characteristics. Mathematic relationships for channel bankfull topwidth, depth, and side slope to contributing drainage area measured at model cross sections were developed. The proposed framework can be utilized at a national level to identify critical areas for flood risk assessment. Existing hydraulic models at these “hot spots” could be repurposed for near–real‐time flood forecasting operations. Revitalizing these models for use in simulating flood scenarios in near–real time through the use of meteorological forecasts could provide useful information for first responders of flood emergencies.     

FLOODPLAIN ANALYSIS,SIMPLIFIED VS. COMPLEX METHODS: A CASE STUDY1

ABSTRACT: The accurate and reliable determination of floodplains, floodway boundaries, and flood water elevations are integral requirements of Flood Insurance Studies. These studies are intended to be used for determining the flood insurance rates. Therefore, the accuracy of the water surface profiles are important. To ensure the high degree of accuracy, the HUD Flood Insurance Administration has developed standards which must be met in the analysis of water surface profiles. A somewhat less accurate study is required for the preparation of Flood Emergency Plans. As part of the flood insurance studies of eight locations in the State of North Dakota, various flood hazard and floodplain information reports were reviewed. The hydrologic and hydraulic analyses, especially the computation of the 100-year water surface profiles, were completed using both simplified and complex hydraulic computation methods. Significant differences were found (1 to 3 feet) between the profiles computed by the SCS simplified method and those computed by HEC-2 computer program. However, the floodplain boundaries determined by both methods were found to be similar. Approximate methods are recommended for rapid determination of the floodplain, floodway boundaries, and inundation area mapping, while sophisticated computer programs (HEC-2) are recommended to be used for developing areas where the 100-year flood elevation has a significant impact on the cost of land development.     

The use of Landsat multispectral scanner data for the analysis and management of flooding on the river Severn,England

Remote sensing has emerged as one of the major techniques for the analysis and delineation of large floods. This analysis can provide data invaluable for the hydrological management of large river systems. A need for information on the extent of floodplain inundation for the lower reaches of the largest river in the UK was met by a search through Landsat images of floods and the analysis of the best example recorded. Automated classification of the Landsat imagery of this flood on the river Severn in 1977 was used to provide estimates of the extent and spatial distribution of inundation. Flood images were generated using the Plessey IDP 3000 image processor, and the maps derived accorded well with aerial photography and qualitative flood information. Three distinct floodplain environments were delineated and flood images produced by different spectral bands compared. Specific questions prompted by flood hazard management and concerning the processes and extent of flooding were answered by the Landsat data analysis. Management of the flood risk of large rivers is expensive and remote sensing data is a relatively cheap and effective way of monitoring control works and providing data for the prediction of the effects of future hydrological works. Remote sensing is a practical way in which spatial information concerning the behavior of large dynamic systems can be obtained both quickly and relatively cheaply.     

ANALYSIS OF UNCERTAINTY IN FLOOD PLAIN MAPPING1

ABSTRACT: Components contributing to uncertainty in the location of the flood plain fringe of a mapped flood plain are identified and examined to determine their relative importance. First-order uncertainty analysis is used to provide a procedure for quantifying the magnitude of uncertainty in the location of the flood plain fringe. Application of the procedure indicated that one standard deviation of uncertainty in flood plain inundation width was about one third of the mean computed inundation width for several flood population-flood geometry combinations. Suggested mapping criteria, which directly incorporate uncertainty estimates, are given. While these criteria are more suitable for use in developing areas than in flood plains that have had extensive development, the analysis procedure can be used to accommodate property owners who challenge the validity of estimated flood fringe boundaries. Use of uncertainty analysis in flood plain mapping should enhance the credibility of the final plan.     

FLOOD HAZARD STUDIES IN THE MISSISSIPPI RIVER BASIN USING REMOTE SENSING1

ABSTRACT. The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicate that ERTS-I is extremely useful as a regional tool for flood management. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. The flood prone areas delineated on these maps correspond to areas that would be inundated by significant flooding (approximately the 100 year flood). The flood prone area boundaries were generally in agreement with flood hazard maps produced by the U. S. Army Corps of Engineers and U. S. Geological Survey although the latter are somewhat more detailed because of their larger scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.     

River Channel Geometry and Rating Curve Estimation Using Height above the Nearest Drainage

River channel geometry is an important input to hydraulic and hydrologic models. Traditional approaches to quantify river geometry have involved surveyed river cross sections, which cannot be extended to ungaged basins. In this paper, we describe a method for developing a synthetic rating curve to relate flow to water level in a stream reach based on reach‐averaged channel geometry properties developed using the Height above Nearest Drainage (HAND) method. HAND uses a digital elevation model (DEM) of the terrain and computes the elevation difference between each land surface cell and the stream bed cell to which it drains. Taking increments in water level in the stream, HAND defines the inundation zone and a water depth grid within this zone, and the channel characteristics are defined from this water depth grid. We apply our method to the Blanco River (Texas) and the Tar River (North Carolina) using 10‐m terrain data from the United States Geological Survey (USGS) 3D Elevation Program (3DEP) dataset. We evaluate the method's performance by comparing the reach‐average stage‐river geometry relationships and rating curves to those from calibrated Hydrologic Engineering Center's River Analysis System (HEC‐RAS) models and USGS gage observations. The results demonstrate that after some adjustment, the river geometry information and rating curves derived from HAND using national‐coverage datasets are comparable to those obtained from hydraulic models or gage measurements. We evaluate the inundation extent and show our approach is able to capture the majority of the Federal Emergency Management Agency (FEMA) 100‐year floodplain.     

Characterizing the Extent of Spatially Integrated Floodplain and Wetland Systems in the White River,Indiana, USA

Floodplain delineation may inform protection of wetland systems under local, state, or federal laws. Nationally available Federal Emergency Management Agency Flood Insurance Rate Maps (FIRMs, “100‐year floodplain” maps) focus on urban areas and higher‐order river systems, limiting utility at large scales. Few other national‐scale floodplain data are available. We acquired FIRMs for a large watershed and compared FIRMs to floodplain and integrated wetland area mapping methods based on (1) geospatial distance, (2) geomorphic setting, and (3) soil characteristics. We used observed flooding events (OFEs) with recurrence intervals of 25‐50 to >100 years to assess floodplain estimate accuracy. FIRMs accurately reflected floodplain areas based on OFEs and covered 32% of river length, whereas soil‐based mapping was not as accurate as FIRMs but characterized floodplain areas over approximately 65% of stream length. Geomorphic approaches included more areas than indicated by OFE, whereas geospatial approaches tended to cover less area. Overall, soil‐based methods have the highest utility in determining floodplains and their integrated wetland areas at large scales due to the use of nationally available data and flexibility for regional application. These findings will improve floodplain and integrated wetland system extent assessment for better management at local, state, and national scales.     

Intercomparison of Satellite Remote Sensing‐Based Flood Inundation Mapping Techniques

The objective of this study was to determine the accuracy of five different digital image processing techniques to map flood inundation extent with Landsat 8–Operational Land Imager satellite imagery. The May 2016 flooding event in the Hempstead region of the Brazos River, Texas is used as a case study for this first comprehensive comparison of classification techniques of its kind. Five flood water classification techniques (i.e., supervised classification, unsupervised classification, delta‐cue change detection, Normalized Difference Water Index [NDWI], modified NDWI [MNDWI]) were implemented to characterize flooded regions. To identify flood water obscured by cloud cover, a digital elevation model (DEM)–based approach was employed. Classified floods were compared using an Advanced Fitness Index to a “reference flood map” created based on manual digitization, as well as other data sources, using the same satellite image. Supervised classification yielded the highest accuracy of 86.4%, while unsupervised, MNDWI, and NDWI closely followed at 79.6%, 77.3%, and 77.1%, respectively. Delta‐cue change detection yielded the lowest accuracy with 70.1%. Thus, supervised classification is recommended for flood water classification and inundation map generation under these settings. The DEM‐based approach used to identify cloud‐obscured flood water pixels was found reliable and easy to apply. It is therefore recommended for regions with relatively flat topography.     

Climate Change and Floodplain Delineation in Two Southern Quebec River Basins1

Laforce, Serge, Marie‐Claude Simard, Robert Leconte, and François Brissette, 2011. Climate Change and Floodplain Delineation in Two Southern Quebec River Basins. Journal of the American Water Resources Association (JAWRA) 47(4):785‐799. DOI: 10.1111/j.1752‐1688.2011.00560.x Abstract: A methodology is presented for mapping the flooded extent of rivers under projected climate change. The methodology follows a top‐down modeling approach, where future climate projections generated by global climate models (GCMs) are downscaled to the watershed scale and used as input to hydrological and hydrodynamic models for predicting future river flows and associated open water levels. A range of possible future climate responses are taken into account, allowing quantification of flood‐mapping uncertainties resulting from GCM structure and greenhouse gas emission scenarios (GHGES). Probabilistic projections of future flood zones are developed by assuming that all GCMs and GHGES be equally weighted. The proposed methodology was applied to two river basins located in southern Quebec, Canada, for the time horizons 2020 and 2080. Twenty‐ and hundred‐year floods were computed and corresponding flood maps have been produced. Results indicate that there is a general trend toward an increased spring peak discharge for the Châteauguay River Basin and a decrease for the du Nord River Basin at the 2020 horizon. A less obvious trend was observed for the 2080 horizon, some GCM‐GHGES producing an increase in spring peak flows, whereas others would result in a less severe spring flood. These uncertainties in flood flows have cascaded into uncertainties in the corresponding flooded extent and represented as probabilistic flood maps.     

Coastal Flood Inundation Monitoring with Satellite C‐band and L‐band Synthetic Aperture Radar Data

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm‐ and tidal‐related flooding of spatially extensive coastal marshes within the north‐central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L‐Band SAR (PALSAR) (L‐band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C‐band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006‐2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR‐ and ASAR‐based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference‐scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR‐based inundation accuracies averaged 84% (n = 160), while ASAR‐based mapping accuracies averaged 62% (n = 245).     

Demonstrating Floodplain Uncertainty Using Flood Probability Maps1

Abstract: The U.S. Federal Emergency Management Agency (FEMA) flood maps depict the 100‐year recurrence interval floodplain boundary as a single line. However, because of natural variability and model uncertainty, no floodplain extents can be accurately defined by a single line. This article presents a new approach to floodplain mapping that takes advantage of accepted methodologies in hydrologic and hydraulic analysis while including the effects of uncertainty. In this approach, the extents of computed floodplain boundaries are defined as a continuous map of flood probabilities, rather than as a single line. Engineers and planners can use these flood probability maps for viewing the uncertainty of a floodplain boundary at any recurrence interval. Such a flood probability map is a useful tool for visualizing the uncertainty of a floodplain boundary and represents greater honesty in engineering technologies that are used for flood mapping. While institutional barriers may prevent adoption of such definitions for use in graduated flood insurance rates (as most other insurance industries use to account for relative risks), the methods open the door technically to such a reality.