scholarly journals Unraveling Long-Term Flood Risk Dynamics Across the Murray-Darling Basin Using a Large-Scale Hydraulic Model and Satellite Data

2022 ◽  
Vol 3 ◽  
Author(s):  
Serena Ceola ◽  
Alessio Domeneghetti ◽  
Guy J. P. Schumann
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Spatial Scales ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Human Society ◽  
Murray Darling Basin ◽  
Flooded Areas

River floods are one of the most devastating extreme hydrological events, with oftentimes remarkably negative effects for human society and the environment. Economic losses and social consequences, in terms of affected people and human fatalities, are increasing worldwide due to climate change and urbanization processes. Long-term dynamics of flood risk are intimately driven by the temporal evolution of hazard, exposure and vulnerability. Although needed for effective flood risk management, a comprehensive long-term analysis of all these components is not straightforward, mostly due to a lack of hydrological data, exposure information, and large computational resources required for 2-D flood model simulations at adequately high resolution over large spatial scales. This study tries to overcome these limitations and attempts to investigate the dynamics of different flood risk components in the Murray-Darling basin (MDB, Australia) in the period 1973–2014. To this aim, the LISFLOOD-FP model, i.e., a large-scale 2-D hydrodynamic model, and satellite-derived built-up data are employed. Results show that the maximum extension of flooded areas decreases in time, without revealing any significant geographical transfer of inundated areas across the study period. Despite this, a remarkable increment of built-up areas characterizes MDB, with larger annual increments across not-flooded locations compared to flooded areas. When combining flood hazard and exposure, we find that the overall extension of areas exposed to high flood risk more than doubled within the study period, thus highlighting the need for improving flood risk awareness and flood mitigation strategies in the near future.

Ignoring spatial dependence misestimates flood risk at the European scale

2020 ◽  
Author(s):  
Viet Dung Nguyen ◽  
Ayse Duha Metin ◽  
Lorenzo Alfieri ◽  
Sergiy Vorogushyn ◽  
Bruno Merz
Keyword(s):  
Return Period ◽  
Flood Risk ◽  
Spatial Dependence ◽  
Large Scale ◽  
Spatial Scales ◽  
Tail Dependence ◽  
Flood Protection ◽  
Economic Losses ◽  
Dependence Structure ◽  
Spatial Homogeneity

<p>Flooding is a major problem worldwide causing many fatalities and economic losses. The quantification of flood risk can be difficult for large spatial scales due to its spatial variability. The traditional risk assessment approaches assuming unrealistic spatial homogeneity of flood return period for the entire catchment are often used and hence in many cases lead to misleading results especially for large-scale applications. In this study, we aim at investigating the influences of spatial dependence in flood risk estimation over national and continental scales by comparing the assessments under three spatial dependence assumptions: modelled dependence (MD), complete dependence (CD) and complete independence (CI) of flow return periods. In order to achieve the aim, we develop a copula-based model representing the dependence structure of annual maximum stream flow (AMS) at 507 stations (with basin area > 500km2) across Europe and use it to generate long-term (10000 years) spatially coherent AMS at these locations. The generated series at multiple sites are then used for estimating associated flood loss considering two levels (with and without) of flood protection. The flood risk is estimated and aggregated for the representative 3 regions (England, Germany and Europe) and for the three dependence assumptions considering also the role of tail dependence of the used copulas. The results highlight that ignoring spatial dependence misestimates flood risk. The deviation from the modelled risk (under-/over-estimation) depends differently on the assumptions of spatial dependence, tail dependence, flood protection level and spatial scales. For example, under CD assumption for 200-year return period and considering flood protection, approximately 2.5-, 3- and 3.5-fold overestimation of flood risk in England, Germany and Europe, respectively, is found.</p>

scholarly journals Towards risk-based flood management in highly productive paddy rice cultivation – concept development and application to the Mekong Delta

2018 ◽  
Vol 18 (11) ◽  
pp. 2859-2876 ◽  
Author(s):  
Nguyen Van Khanh Triet ◽  
Nguyen Viet Dung ◽  
Bruno Merz ◽  
Heiko Apel
Keyword(s):  
Land Use ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Mekong Delta ◽  
Flood Management ◽  
Paddy Rice ◽  
Rice Cultivation ◽  
Spatially Explicit ◽  
Risk Maps

Abstract. Flooding is an imminent natural hazard threatening most river deltas, e.g. the Mekong Delta. An appropriate flood management is thus required for a sustainable development of the often densely populated regions. Recently, the traditional event-based hazard control shifted towards a risk management approach in many regions, driven by intensive research leading to new legal regulation on flood management. However, a large-scale flood risk assessment does not exist for the Mekong Delta. Particularly, flood risk to paddy rice cultivation, the most important economic activity in the delta, has not been performed yet. Therefore, the present study was developed to provide the very first insight into delta-scale flood damages and risks to rice cultivation. The flood hazard was quantified by probabilistic flood hazard maps of the whole delta using a bivariate extreme value statistics, synthetic flood hydrographs, and a large-scale hydraulic model. The flood risk to paddy rice was then quantified considering cropping calendars, rice phenology, and harvest times based on a time series of enhanced vegetation index (EVI) derived from MODIS satellite data, and a published rice flood damage function. The proposed concept provided flood risk maps to paddy rice for the Mekong Delta in terms of expected annual damage. The presented concept can be used as a blueprint for regions facing similar problems due to its generic approach. Furthermore, the changes in flood risk to paddy rice caused by changes in land use currently under discussion in the Mekong Delta were estimated. Two land-use scenarios either intensifying or reducing rice cropping were considered, and the changes in risk were presented in spatially explicit flood risk maps. The basic risk maps could serve as guidance for the authorities to develop spatially explicit flood management and mitigation plans for the delta. The land-use change risk maps could further be used for adaptive risk management plans and as a basis for a cost–benefit of the discussed land-use change scenarios. Additionally, the damage and risks maps may support the recently initiated agricultural insurance programme in Vietnam.

scholarly journals Variability of Cloudiness over Mountain Terrain in the Western United States

2017 ◽  
Vol 18 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Edwin Sumargo ◽  
Daniel R. Cayan
Keyword(s):  
United States ◽  
Large Scale ◽  
Spatial Scales ◽  
High Elevation ◽  
Empirical Orthogonal Functions ◽  
Western United States ◽  
Spatial And Temporal Variability ◽  
Regional Patterns ◽  
Cloud Albedo

Abstract This study investigates the spatial and temporal variability of cloudiness across mountain zones in the western United States. Daily average cloud albedo is derived from a 19-yr series (1996–2014) of half-hourly Geostationary Operational Environmental Satellite (GOES) images. During springtime when incident radiation is active in driving snowmelt–runoff processes, the magnitude of daily cloud variations can exceed 50% of long-term averages. Even when aggregated over 3-month periods, cloud albedo varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) of daily cloud albedo anomalies over high-elevation regions of the western conterminous United States identify distinct regional patterns, wherein the first five REOFs account for ~67% of the total variance. REOF1 is centered over Northern California and Oregon and is pronounced between November and March. REOF2 is centered over the interior northwest and is accentuated between March and July. Each of the REOF/rotated principal components (RPC) modes associates with anomalous large-scale atmospheric circulation patterns and one or more large-scale teleconnection indices (Arctic Oscillation, Niño-3.4, and Pacific–North American), which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.

scholarly journals Flood Risk Assessment and Quantification at the Community and Property Level in the State of Iowa

2021 ◽  
Author(s):  
Enes Yildirim ◽  
Ibrahim Demir
Keyword(s):  
Risk Assessment ◽  
High Resolution ◽  
Flood Risk ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Flood Risk Assessment ◽  
Study Region ◽  
Study Results ◽  
Flood Maps

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

scholarly journals Flood-Prone Area Assessment Using GIS-Based Multi-Criteria Analysis: A Case Study in Davao Oriental, Philippines

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2203 ◽  
Author(s):  
Cabrera ◽  
Lee
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Drainage Density ◽  
Mitigation Strategies ◽  
Risk Area ◽  
Analytic Hierarchy ◽  
Comparison Results ◽  
Prone Area ◽  
Ground Truthing ◽  
Very High

Flooding is one of the major destructive natural disasters in Davao Oriental, Philippines, and results primarily from a high incidence of typhoons and heavy rainfalls. The main objective of this study was to identify flood-prone risk areas by mapping them based on the integration of multiple indicators, including rainfall, slope, elevation, drainage density, soil type, distance to the main channel and population density. For this purpose, a GIS-based flood risk spatial assessment was conducted by using analytic hierarchy process (AHP), weights by rank (WR) and ratio weighting (RW) frameworks to determine the relative importance of each indicator against another in the province of Davao Oriental. The resulting flood-prone areas by the three methods are validated by comparing with the estimated flood map based on ground truthing points from a field survey. The comparison results show that AHP is the most appropriate method among them to assess flood hazard. The result of the AHP flood risk map shows that 95.99% (5451.27 km2) of Davao Oriental is under low and moderate flood risk. The high and very high flood risk area covers approximately 3.39% (192.52 km2) of the province, primarily in the coastal areas. Thirty-one out of the one hundred eighty-three (31/183) barangays (towns) are at a high to very high risk of flooding at current climate, calling for the immediate attention of decision-makers to develop mitigation strategies for the future occurrence of flooding in Davao Oriental.

Analysis of potential flood damage on crops at global scale

2020 ◽  
Author(s):  
Antonio Annis ◽  
Davide Danilo Chiarelli ◽  
Fernando Nardi ◽  
Maria Cristina Rulli
Keyword(s):  
Food Security ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Strong Support ◽  
Flood Damage ◽  
Natural Ecosystems ◽  
Remotely Sensed Data ◽  
Regulated Rivers ◽  
Cropland Area

<p>Most of the food production connected to crops is located in fluvial corridors because of their suitable morphology and fertile soils. The knowledge and large scale quantification of the agricultural resources at flood risk has a crucial importance for improving urban and regional planning. Recent advances in satellite derived products related to land use, digital terrain and hydrologic variables can give a strong support on extensive analyses on cropland areas in floodplains and their interactions with natural ecosystems and human activities. In this work, we present a global assessment of cropland at flood risk in terms of extension, productivity and the related calories adopting the Global Cropland Area Database (GCAD), the Global Floodplain Dataset (GFPLAIN250m), the Global flood hazard maps (GFHM) in conjunction with continental remotely-sensed data representing free flowing (versus artificially regulated) rivers and urban density maps. Spatially distributed and aggregated results of the research allow to identify the most critical areas in terms of food security and floods, thus allowing to support intervention strategies for food security management at large scale and for different socio-economic contexts.</p>

Rapid Global Exposure Assessment for Extreme River Flood Risk Under Climate Change

2016 ◽  
Vol 11 (6) ◽  
pp. 1128-1136 ◽  
Author(s):  
Youngjoo Kwak ◽  
◽  
Yoichi Iwami ◽  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Data Availability ◽  
Flood Risk Assessment ◽  
Daily Data ◽  
Extreme Flood ◽  
River Flood

Globally, large-scale floods are one of the most serious disasters, considering increased frequency and intensity of heavy rainfall. This is not only a domestic problem but also an international water issue related to transboundary rivers in terms of global river flood risk assessment. The purpose of this study is to propose a rapid flood hazard model as a methodological possibility to be used on a global scale, which uses flood inundation depth and works reasonably despite low data availability. The method is designed to effectively simplify complexities involving hydrological and topographical variables in a flood risk-prone area when applied in an integrated global flood risk assessment framework. The model was used to evaluate flood hazard and exposure through pixel-based comparison in the case of extreme flood events caused by an annual maximum daily river discharge of 1/50 probability of occurrence under the condition of climate change between two periods, Present (daily data from 1980 to 2004) and Future (daily data from 2075 to 2099). As preliminary results, the maximum potential extent of inundation area and the maximum number of affected people show an upward trend in Present and Future.

Generation of Low-Frequency Spiciness Variability in the Thermocline*

2011 ◽  
Vol 41 (2) ◽  
pp. 365-377 ◽  
Author(s):  
Thomas Kilpatrick ◽  
Niklas Schneider ◽  
Emanuele Di Lorenzo
Keyword(s):  
Markov Model ◽  
Large Scale ◽  
Spatial Scales ◽  
Low Frequency ◽  
Passive Tracer ◽  
Wind Stress Curl ◽  
Frequency Spectra ◽  
Low Frequencies ◽  
Geostrophic Advection

Abstract The generation of variance by anomalous advection of a passive tracer in the thermocline is investigated using the example of density-compensated temperature and salinity anomalies, or spiciness. A coupled Markov model is developed in which wind stress curl forces the large-scale baroclinic ocean pressure that in turn controls the anomalous geostrophic advection of spiciness. The “double integration” of white noise atmospheric forcing by this Markov model results in a frequency (ω) spectrum of large-scale spiciness proportional to ω−4, so that spiciness variability is concentrated at low frequencies. An eddy-permitting regional model hindcast of the northeast Pacific (1950–2007) confirms that time series of large-scale spiciness variability are exceptionally smooth, with frequency spectra ∝ ω−4 for frequencies greater than 0.2 cpy. At shorter spatial scales (wavelengths less than ∼500 km), the spiciness frequency spectrum is whitened by mesoscale eddies, but this eddy-forced variability can be filtered out by spatially averaging. Large-scale and long-term measurements are needed to observe the variance of spiciness or any other passive tracer subject to anomalous advection in the thermocline.

scholarly journals Use of HAND terrain descriptor for estimating flood-prone areas in river basins

2021 ◽  
Vol 56 (3) ◽  
pp. 501-516
Author(s):  
Ana Alice Rodrigues Dantas ◽  
Adriano Rolim Paz
Keyword(s):  
River Basin ◽  
Flood Hazard ◽  
Mitigation Strategies ◽  
Drainage Area ◽  
Hazard Mapping ◽  
Morphological Pattern ◽  
River Drainage ◽  
Variable Approach ◽  
The Impact ◽  
Flooded Areas

The flood hazard mapping in a river basin is crucial for flooding risk management, mitigation strategies, and flood forecasting and warning systems, among other benefits. One approach for this mapping is based on the HAND (Height Above Nearest Drainage) terrain descriptor, directly derived from the Digital Elevation Model (DEM), in which each pixel represents the elevation difference of this point in relation to the river drainage network to which it is connected. Considering the Mamanguape river basin (3,522.7 km²; state of Paraíba, Brazil) as the study location, the present research applied this method and verified it as for five aspects: consideration of a spatially variable minimum drainage area for denoting the river drainage initiation; the impact of considering a depressionless DEM; evaluation of hydrostatic condition; effect of incorporating an existing river vector network; and comparative analysis of basin morphology regarding longitudinal river profiles. According to the results, adopting a uniform minimum drainage area for the river network initiation is a simplification that should be avoided, using a spatially variable approach, which influences the amount and spatial distribution of flooded areas. Additionally, considering the depressionless DEM leads to higher values of HAND and to a smaller flooded area (difference ranging between 3% and 99%), when compared with the use of DEM with depression, despite 3.1% of the pixels representing depressions. The use of the depressionless DEM is recommended, whereas the DEM pre-processing by incorporating a vector network (stream burning) generates dubious results regarding the relation between HAND and the morphological pattern presented in the DEM. Moreover, the estimation of flooded areas based on HAND does not guarantee the hydrostatic condition, but this disagreement comprises a negligible area for practical purposes.

scholarly journals Projected Seasonal Changes in Large-Scale Global Precipitation and Temperature Extremes Based on the CMIP5 Ensemble

2020 ◽  
Vol 33 (13) ◽  
pp. 5651-5671 ◽  
Author(s):  
Wang Zhan ◽  
Xiaogang He ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Extreme Events ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Extreme Temperature ◽  
Economic Losses ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Future ◽  
Precipitation Events

AbstractOver the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future.

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