Maximum Inundation Extent Research Articles

Long-term surface water changes and driving cause in Xiong’an, China: from dense Landsat time series images and synthetic analysis

China’s government statement recently reported the plan of constructing Xiong’an New Area, which aims to phase out some extra capital functions from Beijing and to explore an innovative urban development mode with the priority in eco-environmental protection. The New Area is located in the semi-arid North China Plain (NCP) and is home to NCP’s largest natural freshwater wetland, Baiyangdian Lake. A comprehensive realization of surface water dynamics would be crucial for policy-makers to outline a sustainable environment development strategy for New Area. In this study, we used a total of 245 time slices of cloud-free Landsat images to document the continuous changes of water bodies within Xiong’an City during 1984–2016 and to provide detailed evidence of water presence and persistency states and changes under the influences of climate change and human actions. Our results reveal that the New Area water body areas varied dramatically during the past 33 years, ranging from 0.44 km2 in April 1988 to 317.85 km2 in February 1989. The change of surface water area was not characterized by a monotonically decreasing tendency. The evolution processes can be divided into four sub-stages: the first extreme desiccation in mid-1980s, the wet stage with the most extensive inundation areas and strong inter-annual fluctuations from late-1988 to late 1999, another desiccation stage in early 2000s, and the overall recovering stage between 2007 and 2016. We also mapped the maximum water inundation extents and frequencies of all-season, pre-wet season (February-May) and post-wet season (September-December) for the 33 years and different sub-periods. Although there is good agreement between time series of surface water area evolution in the New Area and station-based precipitation and evaporation variations, multiple lines of evidences reviewed in previous research indicate that the degraded Baiyangdian Lake was also tightly associated with human activities from various aspects, including dam construction, groundwater extraction, agricultural irrigation, etc. We highlighted the current status of exploring the driving mechanism of surface water changes and existing problems, and then offer recommendations.

Effects of large wood on floodplain connectivity in a headwater Mid-Atlantic stream

Large wood (LW) plays an essential role in aquatic ecosystem health and function. Traditionally, LW has been removed from streams to minimize localized flooding and increase conveyance efficiency. More recently, LW is often added to streams as a component of stream and river restoration activities. While much research has focused on the role of LW in habitat provisioning, geomorphic stability, and hydraulics at low to medium flows, we know little about the role of LW during storm events. To address this question, we investigated the role of LW on floodplain connectivity along a headwater stream in the Mid-Atlantic region of the United States. Specifically, we conducted two artificial floods, one with and one without LW, and then utilized field measurements in conjunction with hydrodynamic modeling to quantify floodplain connectivity during the experimental floods and to characterize potential management variables for optimized restoration activities. Experimental observations show that the addition of LW increased maximum floodplain inundation extent by 34%, increased floodplain inundation depth by 33%, and decreased maximum thalweg velocity by 10%. Model results demonstrated that different placement of LW along the reach has the potential to increase floodplain flow by up to 40%, with highest flooding potential at cross sections with high longitudinal velocity and shallow depth. Additionally, model simulations show that the effects of LW on floodplain discharge decrease as storm recurrence interval increases, with no measurable impact at a recurrence interval of more than 25 years.

Increasing Methane Emissions From Natural Land Ecosystems due to Sea‐Level Rise

AbstractAtmospheric methane (CH4) is one of the most important greenhouse gases. However, there is still a large uncertainty in simulating CH4 emissions from terrestrial ecosystems. Different from modeling studies focusing on response of CH4 emissions to various environmental changes in land ecosystems, this study analyzed the response of CH4 emissions to sea‐level rise (SLR). To do so, a large‐scale surface water routing module was incorporated into an existing CH4 model. This allowed the model to simulate the effect of SLR on river flows and inland water levels. This study focused on these freshwater systems and did not address saltwater intrusion or coastal wetland impacts. Both the annual maximum inundation extent and CH4 emissions at the global level showed a steadily growing trend, with an increase of 1.21 × 105 km2 in extent and an increase of 3.13 Tg CH4/year in CH4 emissions, in a 22‐year SLR experiment from 1993 to 2014. Most of new inundation and methane source areas were located near rivers' deltas and along downstream reaches of rivers. The increase in the inundation extent is primarily influenced by precipitation, channel geomorphic characteristics, and topography of riverside area. The increase of CH4 emissions due to the SLR is largely determined by the inundation extent, but other factors such as air temperature and carbon storage also play roles. Although the current SLR‐induced increases in the inundation extent and CH4 emissions only accounted for 1.0% and 1.3% of their global totals, these increases contributed 7.0% and 17.3% of the mean annual variability in both, respectively, during the study period. Considering that SLR has a long‐term increasing trend, future SLR under a changing climate could play a more important role in global CH4 emissions.

Are inundation limit and maximum extent of sand useful for differentiating tsunamis and storms? An example from sediment transport simulations on the Sendai Plain, Japan

We examined the quantitative difference in the distribution of tsunami and storm deposits based on numerical simulations of inundation and sediment transport due to tsunami and storm events on the Sendai Plain, Japan. The calculated distance from the shoreline inundated by the 2011 Tohoku-oki tsunami was smaller than that inundated by storm surges from hypothetical typhoon events. Previous studies have assumed that deposits observed farther inland than the possible inundation limit of storm waves and storm surge were tsunami deposits. However, confirming only the extent of inundation is insufficient to distinguish tsunami and storm deposits, because the inundation limit of storm surges may be farther inland than that of tsunamis in the case of gently sloping coastal topography such as on the Sendai Plain. In other locations, where coastal topography is steep, the maximum inland inundation extent of storm surges may be only several hundred meters, so marine-sourced deposits that are distributed several km inland can be identified as tsunami deposits by default. Over both gentle and steep slopes, another difference between tsunami and storm deposits is the total volume deposited, as flow speed over land during a tsunami is faster than during a storm surge. Therefore, the total deposit volume could also be a useful proxy to differentiate tsunami and storm deposits.

Sensitivity considerations and the impact of spatial scaling for storm surge modeling in wetlands of the Mid-Atlantic region

Among the many activities in the recent efforts to evaluate coastal resiliency is the study of the capacity of wetlands and coastal marshes to attenuate storm surge. The development of an acceptable index or attenuation rate for coastal flooding is complicated by the many factors that contribute to maximum surge elevation, inundation extent and duration, including storm characteristics (e.g. track, size, forward speed, duration, central low pressure) and local features including topo-bathymetry, land-cover, barrier islands, channels, lagoons and inlets. For this study, we investigated the impact of spatial scaling, mesh resolution, storm characteristics and bottom friction on storm surge in wetland areas in the barrier island system of the Delmarva Peninsula using the coupled hydrodynamic-wave model (ADCIRC + SWAN). Synthetic storms derived from hindcasts of historical storms affecting this region were used for model forcing through multi resolution meshes recreating the complex wetland areas exposed to varying degrees of ocean surge through natural breaks in the barrier islands. Sensitivity to mesh resolution and bottom friction were evaluated for regional attributes and storm characteristics, confirming the results of previous studies. Results suggest inlet configuration and exposure to ocean surge are dominant factors for surge propagation through small scale wetlands and barrier island systems for weak to moderate storms. Attenuation rates observed for weaker storms, were influenced secondarily by the complex geometry of channels, lagoons and the presence and continuity of marshes. Results evaluating greater surge produced by stronger storms, even of less than a meter of storm surge increase, indicate that the mitigating impacts of local features are greatly diminished. Our results indicate that although the back bays systems in the Delmarva Peninsula and similar ecosystems in the US East Coast could provide storm surge attenuation for annual storm events, its use in coastal engineering protection may require a case by case analysis due to the high dependence on local characteristics.

Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard

Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies.

Mapping inundation extent, frequency and duration in the Okavango Delta from 2001 to 2012

The frequency and duration of inundation in river systems are important for a variety of applications, such as water resource management, floodplain mapping and habitat restoration. The Okavango Delta, the fifth largest Ramsar site in the world, has experienced a series of large floods since 2007, following the much lower flooding of the 1990s and early 2000s. This study aimed to establish inundation frequency and duration maps of the Okavango Delta for 2001 to 2012 using MOD09Q1 and MOD11A1. An earlier methods paper testing MODIS for flood mapping in the delta showed 99.4% overall accuracy for inundation mapping of the delta, with a kappa coefficient of 80%. A method based on a time-varying threshold derived from bimodal single-band histograms was used to classify the images into inundated and non-inundated areas. The method relies on the difference in reflectance between waterbodies and dry or vegetated soil, with the former having low reflectance and the latter displaying higher reflectance values. The method takes into account seasonal changes in reflectance. Inundation maps showed a gradual decrease in the delta's maximum annual inundation extent from 2001 to 2003, followed by a gradual increase from 2004 to 2012, with maximum inundation extent during 2010–2012.

A large‐scale methane model by incorporating the surface water transport

AbstractThe effect of surface water movement on methane emissions is not explicitly considered in most of the current methane models. In this study, a surface water routing was coupled into our previously developed large‐scale methane model. The revised methane model was then used to simulate global methane emissions during 2006–2010. From our simulations, the global mean annual maximum inundation extent is 10.6 ± 1.9 km2 and the methane emission is 297 ± 11 Tg C/yr in the study period. In comparison to the currently used TOPMODEL‐based approach, we found that the incorporation of surface water routing leads to 24.7% increase in the annual maximum inundation extent and 30.8% increase in the methane emissions at the global scale for the study period, respectively. The effect of surface water transport on methane emissions varies in different regions: (1) the largest difference occurs in flat and moist regions, such as Eastern China; (2) high‐latitude regions, hot spots in methane emissions, show a small increase in both inundation extent and methane emissions with the consideration of surface water movement; and (3) in arid regions, the new model yields significantly larger maximum flooded areas and a relatively small increase in the methane emissions. Although surface water is a small component in the terrestrial water balance, it plays an important role in determining inundation extent and methane emissions, especially in flat regions. This study indicates that future quantification of methane emissions shall consider the effects of surface water transport.

Projections of climate change effects on discharge and inundation in the Amazon basin

Climate change and its effects on the hydrologic regime of the Amazon basin can impact biogeochemical processes, transportation, flood vulnerability, fisheries and hydropower generation. We examined projections of climate change on discharge and inundation extent in the Amazon basin using the regional hydrological model MGB-IPH with 1-dimensional river hydraulic and water storage simulation in floodplains. Future projections (2070–2099) were obtained from five GCMs from IPCC’s Fifth Assessment Report CMIP5. Climate projections have uncertainty and results from different climate models did not agree in total Amazon flooded area or discharge anomalies along the main stem river. Overall, model runs agree better with wetter (drier) conditions over western (eastern) Amazon. Results indicate that increased mean and maximum river discharge for large rivers draining the Andes in the northwest contributes to increased mean and maximum discharge and inundation extent over Peruvian floodplains and Solimoes River (annual mean-max: +9 % - +18.3 %) in western Amazonia. Decreased river discharges (mostly dry season) are projected for eastern basins, and decreased inundation extent at low water (annual min) in the central (−15.9 %) and lower Amazon (−4.4 %).

Severity and exposure associated with tsunami actions in urban waterfronts: the case of Lisbon, Portugal

The Tagus estuary is bordered by the largest metropolitan area in Portugal, the Lisbon capital city council. It has suffered the impact of several major tsunamis in the past, as shown by a recent revision of the catalogue of tsunamis that struck the Portuguese coast over the past two millennia. Hence, the exposure of populations and infrastructure established along the riverfront comprises a critical concern for the civil protection services. The main objectives of this work are to determine critical inundation areas in Lisbon and to quantify the associated severity through a simple index derived from the local maximum of momentum flux per unit mass and width. The employed methodology is based on the mathematical modelling of a tsunami propagating along the estuary, resembling the one occurred on the 1 November of 1755 that followed the 8.5 Mw Great Lisbon Earthquake. The employed simulation tool was STAV-2D, a shallow-flow solver coupled with conservation equations for fine solid phases, and now featuring the novelty of discrete Lagrangian tracking of large debris. Different sets of initial conditions were studied, combining distinct tidal, atmospheric and fluvial scenarios, so that the civil protection services were provided with comprehensive information to devise public warning and alert systems and post-event mitigation intervention. For the most severe scenario, the obtained results have shown a maximum inundation extent of 1.29 km at the Alcântara valley and water depths reaching nearly 10 m across Lisbon’s riverfront.

A spatial assessment framework for evaluating flood risk under extreme climates

Australian coal mines have been facing a major challenge of increasing risk of flooding caused by intensive rainfall events in recent years. In light of growing climate change concerns and the predicted escalation of flooding, estimating flood inundation risk becomes essential for understanding sustainable mine water management in the Australian mining sector. This research develops a spatial multi-criteria decision making prototype for the evaluation of flooding risk at a regional scale using the Bowen Basin and its surroundings in Queensland as a case study. Spatial gridded data, including climate, hydrology, topography, vegetation and soils, were collected and processed in ArcGIS. Several indices were derived based on time series of observations and spatial modeling taking account of extreme rainfall, evapotranspiration, stream flow, potential soil water retention, elevation and slope generated from a digital elevation model (DEM), as well as drainage density and proximity extracted from a river network. These spatial indices were weighted using the analytical hierarchy process (AHP) and integrated in an AHP-based suitability assessment (AHP-SA) model under the spatial risk evaluation framework. A regional flooding risk map was delineated to represent likely impacts of criterion indices at different risk levels, which was verified using the maximum inundation extent detectable by a time series of remote sensing imagery. The result provides baseline information to help Bowen Basin coal mines identify and assess flooding risk when making adaptation strategies and implementing mitigation measures in future. The framework and methodology developed in this research offers the Australian mining industry, and social and environmental studies around the world, an effective way to produce reliable assessment on flood risk for managing uncertainty in water availability under climate change.

Modeling Storm Surge and Inundation in Washington, DC, during Hurricane Isabel and the 1936 Potomac River Great Flood

Washington, DC, the capital of the U.S., is located along the Upper Tidal Potomac River, where a reliable operational model is needed for making predictions of storm surge and river-induced flooding. We set up a finite volume model using a semi-implicit, Eulerian-Lagrangian scheme on a base grid (200 m) and a special feature of sub-grids (10 m), sourced with high-resolution LiDAR data and bathymetry surveys. The model domain starts at the fall line and extends 120 km downstream to Colonial Beach, VA. The model was used to simulate storm tides during the 2003 Hurricane Isabel. The water level measuring 3.1 m reached the upper tidal river in the vicinity of Washington during the peak of the storm, followed by second and third flood peaks two and four days later, resulting from river flooding coming downstream after heavy precipitation in the watershed. The modeled water level and timing were accurate in matching with the verified peak observations within 9 cm and 3 cm, and with R2 equal to 0.93 and 0.98 at the Wisconsin Avenue and Washington gauges, respectively. A simulation was also conducted for reconstructing the historical 1936 Potomac River Great Flood that inundated downtown. It was identified that the flood water, with a velocity exceeding 2.7 m/s in the downstream of Roosevelt Island, pinched through the bank northwest of East Potomac Park near DC. The modeled maximum inundation extents revealed a crescent-shaped flooding area, which was consistent with the historical surveyed flood map of the event.

Maximising the usefulness of flood risk assessment for the River Vistula in Warsaw

Abstract. The derivation of the flood risk maps requires an estimation of maximum inundation extent for a flood with a given return period, e.g. 100 or 500 yr. The results of numerical simulations of flood wave propagation are used to overcome the lack of relevant observations. In practice, deterministic 1-D models are used for that purpose. The solution of a 1-D model depends on the initial and boundary conditions and estimates of model parameters based on the available noisy observations. Therefore, there is a large uncertainty involved in the derivation of flood risk maps using a single realisation of a flow model. Bayesian conditioning based on multiple model simulations can be used to quantify this uncertainty; however, it is too computer-time demanding to be applied in flood risk assessment in practice, without further flow routing model simplifications. We propose robust and feasible methodology for estimating flood risk. In order to decrease the computation times the assumption of a gradually varied flow and the application of a steady state flow routing model is introduced. The aim of this work is an analysis of the influence of those simplifying assumptions and uncertainty of observations and modelling errors on flood inundation mapping and a quantitative comparison with deterministic flood extent maps. Apart from the uncertainty related to the model structure and its parameters, the uncertainty of the estimated flood wave with a specified probability of return period (so-called 1-in-10 yr, or 1-in-100 yr flood) is also taken into account. In order to derive the uncertainty of inundation extent conditioned on the design flood, the probabilities related to the design wave and flow model uncertainties are integrated. In the present paper that integration is done whilst taking into account the dependence of roughness coefficients on discharge. The roughness is parameterised based on maximum annual discharges. This approach allows for the relationship between flood extent and flow values to be derived, thus giving a cumulative assessment of flood risk. The methods are illustrated using the Warsaw reach of the River Vistula as a case study. The results indicate that deterministic and stochastic flood inundation maps cannot be quantitatively compared. We show that the proposed simplified approach to flood risk assessment can be applied even when breaching of the embankment occurs, with the condition that the flooded area is small enough to be filled rapidly.

On sediment extent and runup of tsunami waves

Tsunami sediments play an important role in tsunami hazard assessments. Recent tsunami events and their associated tsunami deposits have produced a wealth of sediment data. Surveys of recent tsunami events observed that maximum inland tsunami inundation exceeds the maximum inland extent of sand deposition. A driving question of tsunami sedimentology is whether the difference between maximum tsunami inundation and inland extent of sand can be employed as a measure of inundation for past events for which only the extent of the sand is known. Attempts to infer the causative flow characteristics from these sediments often suffer from uncertainties in the data and from restrictive assumptions made in inversion models. The latter demonstrates that the interaction between the tsunami flow and the movable bed is not fully understood. In our contribution, we employ numerical simulations of tsunami propagation and inundation with MOST and a simple model for deposition. In our simulations, we vary the onshore slope, the initial amplitude, which can be interpreted as offshore wave amplitude, and the grain size. While the initial amplitude and onshore slope influence the difference between maximum inundation and sand extent, the grain size has little effect. The link between the onshore slope, initial amplitude and the difference between the maximum tsunami inundation and inland sediment extent can be employed as a first-order quantitative tool to estimate tsunami flow characteristics and maximum inundation from tsunami deposits. We anticipate these results will improve tsunami hazard assessments and narrow the gap between field observations and numerical simulations.

Tsunami hazard assessment in the coastal area of Rabat and Salé, Morocco

Abstract. In the framework of the three-year SCHEMA European project (www.schemaproject.org), we present a generic methodology developed to produce tsunami building vulnerability and impact maps. We apply this methodology to the Moroccan coast. This study focuses on the Bouregreg Valley which is at the junction between Rabat (administrative capital), and Salé. Both present large populations and new infrastructure development. Using a combination of numerical modelling, field surveys, Earth Observation and GIS data, the risk has been evaluated for this vulnerable area. Two tsunami scenarios were studied to estimate a realistic range of hazards on this coast: a worst-case scenario based on the historical Lisbon earthquake of 1755 and a moderate scenario based on the Horseshoe earthquake of 28 February 1969. For each scenario, numerical models allowed the production of tsunami hazard maps (maximum inundation extent and maximum inundation depths). Moreover, the modelling results of these two scenarios were compared with the historical data available. A companion paper to this article (Atillah et al., 2011) presents the following steps of the methodology, namely the elaboration of building damage maps by crossing layers of building vulnerability and the so-inferred inundation depths.

Tsunami–tide interaction in 1964 Prince William Sound tsunami

We conduct a comprehensive modeling study of the impact of the 1964 Prince William Sound tsunami on the US Pacific Northwest coast. A 3D unstructured grid model, SELFE, is applied in its 2D spherical coordinate configuration. Simulations are conducted with and without dynamic tides to elucidate their influence. We compare numerical results with tide gauge records, maximum wave heights, runups, and inundation extents at several locations in the region. Detailed inundation patterns at Coos Bay and Cannon Beach, Oregon are compared to field estimates. The model results are shown to be in very good agreement with field observations. The results demonstrate that while negligible at the open coast, the tide–tsunami interaction is solely responsible for inundation around some estuaries and rivers.

Flood inundation modeling using MIKE FLOOD and remote sensing data

A coupled 1D-2D hydrodynamic model, MIKE FLOOD was used to simulate the flood inundation extent and flooding depth in the delta region of Mahanadi River basin in India. Initially, the 1D model MIKE 11 was calibrated using river water level and discharge data of various gauging sites for the monsoon period (June to October) of the year 2002. Subsequently, the calibrated set up was validated using both discharge and water level data for the same period of the year 2001. The performance of calibration and validation results of MIKE 11 were evaluated using different performance indices. A bathymetry of the study area with a spatial resolution of 90m was prepared from SRTM DEM and provided as an input to the 2D model, MIKE 21. MIKE 11 and MIKE 21 models were then coupled using lateral links to form the MIKE FLOOD model set up for simulating the two dimensional flood inundations in the study area. Flood inundation is simulated for the year 2001 and the maximum flood inundation extent simulated by the model was compared with the corresponding actual inundated area obtained from IRS-1D WiFS image.

Use of parameter optimization to estimate a flood wave: Potential applications to remote sensing of rivers

In this paper, the potential for identifying discharge and/or flood hydrograph from remotely sensed data is explored. The parameter identification process is based on the minimization of the difference between the solution of the model equations and the observed system response which consists in maximum inundation extent. The river geometry is supposed to be known, effect of the accuracy of these data on the estimation has been tested. Sensitivity of the model to individual parameters is then assessed using an extension of the generalized sensitivity analysis. Synthetic data have been used to test the methodology. Results show that the Nash criterion of the estimated flood hydrograph is higher than 0.9 for all the tested cases.