US fluvial, pluvial and coastal flood hazard under current and future climates

2021 ◽  
Author(s):  
Paul Bates ◽  
Niall Quinn ◽  
Christopher Sampson ◽  
Andrew Smith ◽  
Oliver Wing ◽  
...  
Keyword(s):  
Flood Hazard ◽  
Model Performance ◽  
Flood Hazards ◽  
Coastal Zones ◽  
Land Area ◽  
Future Time ◽  
Coastal Flood ◽  
Critical Success ◽  
Annual Probability ◽  
Near Future

<p>This talk reports a new and significantly enhanced analysis of US flood hazard at 30m spatial resolution.  For the first time we consider pluvial, fluvial and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centred on 2035 and 2050 under the RCP4.5 emissions pathway.  Validation against high quality local models and the entire catalogue of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69-0.82.  Significant improvements over a previous pluvial/fluvial model version are shown for high frequency events and coastal zones, along with minor improvements in areas where model performance was already good.  The result is the first comprehensive and consistent national scale analysis of flood hazard for the conterminous US for both current and future conditions.  Even though we consider a stabilization emissions scenario and a near future time horizon we project clear patterns of changing flood hazard (3σ changes in 100yr inundated area of -3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defence protection may become compromised by this time.</p>

scholarly journals Flood hazard and change impact assessments may profit from rethinking model calibration strategies

2020 ◽  
Author(s):  
Manuela I. Brunner ◽  
Lieke A. Melsen ◽  
Andrew W. Wood ◽  
Oldrich Rakovec ◽  
Naoki Mizukami ◽  
...  
Keyword(s):  
Model Calibration ◽  
Flood Hazard ◽  
Model Performance ◽  
Hydrologic Model ◽  
Flood Hazards ◽  
Hydrologic Models ◽  
Change Impact ◽  
Hazard Assessments ◽  
Flood Characteristics ◽  
Flood Flow

Abstract. Floods cause large damages, especially if they affect large regions. Assessments of current, local and regional flood hazards and their future changes often involve the use of hydrologic models. However, uncertainties in simulated floods can be considerable and yield unreliable hazard and climate change impact assessments. A reliable hydrologic model ideally reproduces both local flood characteristics and spatial aspects of flooding, which is, however, not guaranteed especially when using standard model calibration metrics. In this paper we investigate how flood timing, magnitude and spatial variability are represented by an ensemble of hydrological models when calibrated on streamflow using the Kling–Gupta efficiency metric, an increasingly common metric of hydrologic model performance. We compare how four well-known models (SAC, HBV, VIC, and mHM) represent (1) flood characteristics and their spatial patterns; and (2) how they translate changes in meteorologic variables that trigger floods into changes in flood magnitudes. Our results show that both the modeling of local and spatial flood characteristics is challenging. They further show that changes in precipitation and temperature are not necessarily well translated to changes in flood flow, which makes local and regional flood hazard assessments even more difficult for future conditions. We conclude that models calibrated on integrated metrics such as the Kling–Gupta efficiency alone have limited reliability in flood hazard assessments, in particular in regional and future assessments, and suggest the development of alternative process-based and spatial evaluation metrics.

Social Vulnerability to Coastal and Inland Flood Hazards

2013 ◽  
Vol 4 (3) ◽  
pp. 58-79 ◽  
Author(s):  
Marilyn C. Montgomery ◽  
Jayajit Chakraborty
Keyword(s):  
Social Vulnerability ◽  
Spatial Interpolation ◽  
Interpolation Method ◽  
Flood Hazard ◽  
Tampa Bay ◽  
Flood Hazards ◽  
Demographic Groups ◽  
Coastal Flood ◽  
Exposure Patterns ◽  
Spatial Interpolation Method

Previous research on exposure to flood hazards suggests that individuals characterized by low social vulnerability are more likely to reside in coastal flood hazard zones than individuals of higher social vulnerability, but few studies have examined if similar exposure patterns can be observed in inland flood hazard zones. This paper examines differences in environmental justice implications between coastal and inland flood hazard zones in Tampa Bay, Florida, based on implementation and comparison of five different GIS-based interpolation methods. The results of the authors’ study indicate that individuals with traits of low social vulnerability are more likely to reside within either coastal or inland flood hazard zones than areas outside flood zones, and socially vulnerable individuals are more likely to reside within inland flood zones than coastal. They also observe that choice of spatial interpolation method does not significantly affect which socio-demographic groups are most exposed to coastal and inland flood hazards.

scholarly journals Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models

2021 ◽  
Vol 25 (1) ◽  
pp. 105-119
Author(s):  
Manuela I. Brunner ◽  
Lieke A. Melsen ◽  
Andrew W. Wood ◽  
Oldrich Rakovec ◽  
Naoki Mizukami ◽  
...  
Keyword(s):  
Flood Hazard ◽  
Spatial Coherence ◽  
Model Performance ◽  
Hydrologic Model ◽  
Flood Hazards ◽  
Infiltration Capacity ◽  
Climate Conditions ◽  
Large Sample ◽  
Hazard Assessments ◽  
Flood Characteristics

Abstract. Floods cause extensive damage, especially if they affect large regions. Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable hydrologic model ideally reproduces both local flood characteristics and spatial aspects of flooding under current and future climate conditions. However, uncertainties in simulated floods can be considerable and yield unreliable hazard and climate change impact assessments. This study evaluates the extent to which models calibrated according to standard model calibration metrics such as the widely used Kling–Gupta efficiency are able to capture flood spatial coherence and triggering mechanisms. To highlight challenges related to flood simulations, we investigate how flood timing, magnitude, and spatial variability are represented by an ensemble of hydrological models when calibrated on streamflow using the Kling–Gupta efficiency metric, an increasingly common metric of hydrologic model performance also in flood-related studies. Specifically, we compare how four well-known models (the Sacramento Soil Moisture Accounting model, SAC; the Hydrologiska Byråns Vattenbalansavdelning model, HBV; the variable infiltration capacity model, VIC; and the mesoscale hydrologic model, mHM) represent (1) flood characteristics and their spatial patterns and (2) how they translate changes in meteorologic variables that trigger floods into changes in flood magnitudes. Our results show that both the modeling of local and spatial flood characteristics are challenging as models underestimate flood magnitude, and flood timing is not necessarily well captured. They further show that changes in precipitation and temperature are not always well translated to changes in flood flow, which makes local and regional flood hazard assessments even more difficult for future conditions. From a large sample of catchments and with multiple models, we conclude that calibration on the integrated Kling–Gupta metric alone is likely to yield models that have limited reliability in flood hazard assessments, undermining their utility for regional and future change assessments. We underscore that such assessments can be improved by developing flood-focused, multi-objective, and spatial calibration metrics, by improving flood generating process representation through model structure comparisons and by considering uncertainty in precipitation input.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

scholarly journals Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
A. Hooijer ◽  
R. Vernimmen
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Flood Risk ◽  
Land Area ◽  
Area At Risk ◽  
Population Number ◽  
Coastal Flood ◽  
Elevation Data ◽  
Coastal Flood Risk ◽  
The Tropics

AbstractCoastal flood risk assessments require accurate land elevation data. Those to date existed only for limited parts of the world, which has resulted in high uncertainty in projections of land area at risk of sea-level rise (SLR). Here we have applied the first global elevation model derived from satellite LiDAR data. We find that of the worldwide land area less than 2 m above mean sea level, that is most vulnerable to SLR, 649,000 km2 or 62% is in the tropics. Even assuming a low-end relative SLR of 1 m by 2100 and a stable lowland population number and distribution, the 2020 population of 267 million on such land would increase to at least 410 million of which 72% in the tropics and 59% in tropical Asia alone. We conclude that the burden of current coastal flood risk and future SLR falls disproportionally on tropical regions, especially in Asia.

scholarly journals Compounding effects of sea level rise and fluvial flooding

2017 ◽  
Vol 114 (37) ◽  
pp. 9785-9790 ◽  
Author(s):  
Hamed R. Moftakhari ◽  
Gianfausto Salvadori ◽  
Amir AghaKouchak ◽  
Brett F. Sanders ◽  
Richard A. Matthew
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Hazard Assessment ◽  
Failure Probability ◽  
River Flow ◽  
Flood Hazard ◽  
High Tide ◽  
Probability Method ◽  
Flood Hazards ◽  
Flood Hazard Assessment

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

Coastal Flood Hazard: A Quick Mapping Methodology. Case Study: Gioia Tauro (Italy)

2020 ◽  
pp. 1608-1617
Author(s):  
Giuseppina Chiara Barillà ◽  
Giandomenico Foti ◽  
Giuseppe Barbaro ◽  
Fabrizio Currò
Keyword(s):  
Flood Hazard ◽  
Coastal Flood

scholarly journals Distribution of Flood Risk Area in Bodri Watershed of Kendal Regency

2021 ◽  
Vol 6 (2) ◽  
pp. 59-69
Author(s):  
Husna Fauzia ◽  
◽  
Eka Cahyaningsih ◽  
Hery Hariyanto ◽  
Satya Nugraha ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Modeling ◽  
Flood Risk ◽  
Flood Hazard ◽  
Risk Level ◽  
Flood Hazards ◽  
Risk Area ◽  
Flood Peak ◽  
Risk Levels ◽  
Central Java

Flooding is a catastrophic phenomenon that can occur due to various factors, such as uncontrolled landuse changes, climate change, and weather anomalies, and drainage infrastructure damage. The Bodri watershed in Kendal Regency is one of the watersheds in Central Java, which is categorized as critical based on Decree No.328/Menhut-II/2009. Some of the problems in the Bodri watershed include land use that is not suitable for its designation, flooding, erosion, and landslides. This study aims to conduct spatial modeling to create flood hazard maps and flood risk level maps in the Bodri watershed. The method used is hydrograph analysis, flood modeling, potential flood hazards, and flood risk levels. Analysis of the potential for flood hazards from the spatial modeling inundation map with the input of the flood peak return period of 2 years (Q2), 5 years (Q5), and 50 years (Q50). Vulnerability analysis based on land use maps of flood hazard areas. The distribution of flood-prone areas in the Bodri watershed is in Pidodo Kulon Village, Pidodo Wetan Village, and Bangunsari Village.

scholarly journals GIS based Flood Vulnerability Studies for Ife Central Local Government Area, Osun State, Nigeria

2020 ◽  
Vol 4 (1) ◽  
pp. 160-171
Author(s):  
V.A. Ijaware
Keyword(s):  
Local Government ◽  
Flood Hazard ◽  
Pairwise Comparison ◽  
Tropical Rainfall Measuring Mission ◽  
Satellite System ◽  
Comparison Method ◽  
Local Government Area ◽  
Landsat 8 ◽  
Flood Hazards ◽  
Flood Vulnerability

Flood has negatively affected Ife Central Local Government Area of Osun State, Nigeria. This work is aimed at mapping the vulnerability of the area to flood. Its objectives addressed the ranking of various natural and artificial factors causing flood, the determination and delineation of vulnerability to flood in the study area. Using remote sensing and GIS techniques, coordinates of flooded sites were acquired with Global Navigation Satellite System receiver; Landsat 8 data were acquired from the USGS website. To map land use, elevation data were acquired from the Shuttle Radar Topographic Mission Digital Elevation Models, soil data was obtained from the Nigerian Geological Survey website, and rainfall data was acquired from Tropical Rainfall Measuring Mission satellit. Using Pairwise Comparison, the various weights of factors constituting flood in the area were acquired. Weighted Linear Combination and Analytical Hierarchical Process was used in producing the flood hazard and flood vulnerability maps. ArcGIS 10.2 Software was used in spatial and attribute data acquisition, processing, and information presentation. The Pairwise Comparison method adopted was validated and observed to have a consistency ration of 0.003. Results obtained show that 9.2% of the study area is highly prone to flood hazards 20.4% is prone to flood hazard and 44.3% is moderately prone to flood hazard. The method adopted correctly identifies all existing flood incidence areas within the flood- prone areas in the hazard map. The maps produced will serve as an effective tool to aid the prevention and mitigation of flood disaster in the flood-prone area.

scholarly journals Climate change impact on flood hazard

2014 ◽  
Vol 364 ◽  
pp. 164-170 ◽  
Author(s):  
M. Brilly ◽  
K. Kavčič ◽  
M. Šraj ◽  
S. Rusjan ◽  
A. Vidmar
Keyword(s):  
Climate Changes ◽  
Flood Hazard ◽  
High Impact ◽  
Precipitation Data ◽  
Simple Correlation ◽  
Future Time ◽  
Special Situation ◽  
Change Impact ◽  
Time Periods ◽  
Hbv Model

Abstract. Climate changes have a high impact on river discharges and therefore on floods. There are a few different methods we can use to predict discharge changes in the future. In this paper we used the complex HBV model for the Vipava River and simple correlation between discharge and precipitation data for the Soča River. The discharge prediction is based on the E-OBS precipitation data for three future time periods (2011–2040, 2041–2070 and 2071–2100). Estimated discharges for those three future periods are presented for both rivers. But a special situation occurs at the confluence where the two rivers with rather different catchments unite, and this requires an additional probability analysis.

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