Deriving global flood hazard maps of fluvial floods through a physical model cascade

Abstract. Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25 × 25 km grid, which is then reprojected onto a 1 × 1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25 × 25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

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Deriving global flood hazard maps of fluvial floods through a physical model cascade

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-9-6615-2012 ◽

2012 ◽

Vol 9 (5) ◽

pp. 6615-6647 ◽

Cited By ~ 13

Author(s):

F. Pappenberger ◽

E. Dutra ◽

F. Wetterhall ◽

H. Cloke

Keyword(s):

Land Surface ◽

Large Scale ◽

Flood Hazard ◽

Regional Scale ◽

Surface Model ◽

Return Periods ◽

Hazard Maps ◽

Data Set ◽

Flood Hazard Maps ◽

River Routing

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Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

Geoscientific Model Development ◽

10.5194/gmd-10-2031-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 2031-2055 ◽

Cited By ~ 14

Author(s):

Thomas Schwitalla ◽

Hans-Stefan Bauer ◽

Volker Wulfmeyer ◽

Kirsten Warrach-Sagi

Keyword(s):

High Resolution ◽

Land Surface ◽

Large Scale ◽

Temperature Fields ◽

Surface Model ◽

Limited Area ◽

Data Set ◽

Latitude Belt ◽

Simulated Precipitation ◽

The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

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Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

Biogeosciences Discussions ◽

10.5194/bgd-5-4161-2008 ◽

2008 ◽

Vol 5 (5) ◽

pp. 4161-4207 ◽

Cited By ~ 5

Author(s):

H. W. Ter Maat ◽

R. W. A. Hutjes

Keyword(s):

Carbon Dioxide ◽

Land Surface ◽

Large Scale ◽

Regional Scale ◽

Atmospheric Model ◽

Surface Fluxes ◽

Heat Fluxes ◽

Surface Model ◽

Carbon Exchange ◽

Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

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Revealing the spatial pattern of subsurface soil salinity over the Argentinean Dry Chaco

10.5194/egusphere-egu21-10157 ◽

2021 ◽

Author(s):

Michiel Maertens ◽

Veerle Vanacker ◽

Gabriëlle De Lannoy ◽

Frederike Vincent ◽

Raul Giménez ◽

...

Keyword(s):

Soil Salinity ◽

Land Surface ◽

Large Scale ◽

Hydrological Cycle ◽

Regional Scale ◽

Shallow Groundwater ◽

Soil Salinization ◽

Dry Forest ◽

Surface Model ◽

Subsurface Soil

The South-American Dry Chaco is a unique ecoregion as it is one of the largest sedimentary plains in the world hosting the planet&#8217;s largest dry forest. The 787.000 km&#178; region covers parts of Argentina, Paraguay, and Bolivia and is characterized by a negative climatic water balance as a consequence of limited rainfall inputs (800 mm/year) and high temperatures (21&#176;C). In combination with the region&#8217;s extreme flat topography (slopes < 0.1%) and shallow groundwater tables, saline soils are expected in substantial parts of the region. In addition, it is expected that large-scale deforestation processes disrupt the hydrological cycle resulting in rising groundwater tables and further increase the risk for soil salinization.In this study, we identified the regional-scale patterns of subsurface soil salinity in the Dry Chaco. &#160;Field data were obtained during a two-month field campaign in the dry season of 2019. A total of 492 surface- and 142 subsurface-samples were collected along East-West transects to determine soil electric conductivity, pH, bulk density and humidity. Spatial regression techniques were used to reveal the topographic and ecohydrological variables that are associated with subsurface soil salinity over the Dry Chaco. The hydrological information was obtained from a state-of-the-art land surface model with an improved set of satellite-derived vegetation and land cover parameters.In the presentation, we will present a subsurface soil salinity map for a part of the Argentinean Dry Chaco and provide relevant insights into the driving mechanisms behind it.

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Global flood hazard map and exposed GDP comparison: a China case study

10.5194/nhess-2020-1 ◽

2020 ◽

Author(s):

Jerom P. M. Aerts ◽

Steffi Uhlemann-Elmer ◽

Dirk Eilander ◽

Philip J. Ward

Keyword(s):

Return Period ◽

Flood Hazard ◽

Regional Scale ◽

Flood Protection ◽

Economic Losses ◽

Return Periods ◽

Hazard Maps ◽

High Exposure ◽

Pluvial Flooding

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse 8 global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

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Using 1D HEC-RAS Modeling and LiDAR Data to Improve Flood Hazard Maps Accuracy: A Case Study from Jijia Floodplain (NE Romania)

Water ◽

10.3390/w12061624 ◽

2020 ◽

Vol 12 (6) ◽

pp. 1624 ◽

Cited By ~ 1

Author(s):

Elena Huţanu ◽

Alin Mihu-Pintilie ◽

Andrei Urzica ◽

Larisa Elena Paveluc ◽

Cristian Constantin Stoleriu ◽

...

Keyword(s):

Geographical Information Systems ◽

Large Scale ◽

Flood Hazard ◽

Hydraulic Modeling ◽

Geographical Information ◽

Computer Algorithms ◽

Hazard Maps ◽

Modeling Software ◽

Recurrence Intervals ◽

Flood Hazard Maps

The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

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Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe

Biogeosciences ◽

10.5194/bg-14-1969-2017 ◽

2017 ◽

Vol 14 (7) ◽

pp. 1969-1987 ◽

Cited By ~ 23

Author(s):

Tea Thum ◽

Sönke Zaehle ◽

Philipp Köhler ◽

Tuula Aalto ◽

Mika Aurela ◽

...

Keyword(s):

Chlorophyll Fluorescence ◽

Land Surface ◽

Large Scale ◽

Model Simulation ◽

Gross Primary Production ◽

Regional Scale ◽

Coniferous Forest ◽

Flux Measurement ◽

Surface Model ◽

Fluorescence Measurements

Abstract. Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

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Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

Geoscientific Model Development ◽

10.5194/gmd-8-3033-2015 ◽

2015 ◽

Vol 8 (10) ◽

pp. 3033-3053 ◽

Cited By ~ 7

Author(s):

S. Garrigues ◽

A. Olioso ◽

D. Carrer ◽

B. Decharme ◽

J.-C. Calvet ◽

...

Keyword(s):

Spatial Resolution ◽

Land Surface ◽

Large Scale ◽

Surface Model ◽

Data Sets ◽

Data Set ◽

Area Index ◽

Hydrodynamic Parameters ◽

Land Surface Parameter ◽

Crop Succession

Abstract. Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m−2) compared to the negative biases found for SAFRAN (−10 W m−2) and the MSG satellite (−12 W m−2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by −12 and −16 W m−2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

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Using High-Density LiDAR Data and 2D Streamflow Hydraulic Modeling to Improve Urban Flood Hazard Maps: A HEC-RAS Multi-Scenario Approach

Water ◽

10.3390/w11091832 ◽

2019 ◽

Vol 11 (9) ◽

pp. 1832 ◽

Cited By ~ 13

Author(s):

Alin Mihu-Pintilie ◽

Cătălin Ioan Cîmpianu ◽

Cristian Constantin Stoleriu ◽

Martín Núñez Pérez ◽

Larisa Elena Paveluc

Keyword(s):

Urban Areas ◽

Large Scale ◽

Flood Hazard ◽

Hydraulic Modeling ◽

Flood Mitigation ◽

Small Scale ◽

Lidar Data ◽

Hazard Maps ◽

Urban Flood ◽

Flood Hazard Maps

The ability to extract streamflow hydraulic settings using geoinformatic techniques, especially in high populated territories like urban and peri-urban areas, is an important aspect of any disaster management plan and flood mitigation effort. 1D and 2D hydraulic models, generated based on DEMs with high accuracy (e.g., Light Detection and Ranging (LiDAR)) and processed in geographic information systems (GIS) modeling software (e.g., HEC-RAS), can improve urban flood hazard maps. In this study, we present a small-scale conceptual approach using HEC-RAS multi-scenario methodology based on remote sensing (RS), LiDAR data, and 2D hydraulic modeling for the urban and peri-urban area of Bacău City (Bistriţa River, NE Romania). In order to test the flood mitigation capacity of Bacău 1 reservoir (rB1) and Bacău 2 reservoir (rB2), four 2D streamflow hydraulic scenarios (s1–s4) based on average discharge and calculated discharge (s1–s4) data for rB1 spillway gate (Sw1) and for its hydro-power plant (H-pp) were computed. Compared with the large-scale flood hazard data provided by regional authorities, the 2D HEC-RAS multi-scenario provided a more realistic perspective about the possible flood threats in the study area and has shown to be a valuable asset in the improvement process of the official flood hazard maps.

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Generating Flood Hazard Maps Based on an Innovative Spatial Interpolation Methodology for Precipitation

Atmosphere ◽

10.3390/atmos12101336 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1336

Author(s):

Mohammad Zare ◽

Guy J.-P. Schumann ◽

Felix Norman Teferle ◽

Ruja Mansorian

Keyword(s):

Time Scale ◽

Spatial Interpolation ◽

Interpolation Method ◽

Flood Hazard ◽

Daily Rainfall ◽

Return Periods ◽

Hazard Maps ◽

Rain Gauges ◽

Fcm Clustering ◽

Flood Hazard Maps

In this study, a new approach for rainfall spatial interpolation in the Luxembourgian case study is introduced. The method used here is based on a Fuzzy C-Means (FCM) clustering method. In a typical FCM procedure, there are a lot of available data and each data point belongs to a cluster, with a membership degree [0 1]. On the other hand, in our methodology, the center of clusters is determined first and then random data are generated around cluster centers. Therefore, this approach is called inverse FCM (i-FCM). In order to calibrate and validate the new spatial interpolation method, seven rain gauges in Luxembourg, Germany and France (three for calibration and four for validation) with more than 10 years of measured data were used and consequently, the rainfall for ungauged locations was estimated. The results show that the i-FCM method can be applied with acceptable accuracy in validation rain gauges with values for R2 and RMSE of (0.94–0.98) and (9–14 mm), respectively, on a monthly time scale and (0.86–0.89) and (1.67–2 mm) on a daily time scale. In the following, the maximum daily rainfall return periods (10, 25, 50 and 100 years) were calculated using a two-parameter Weibull distribution. Finally, the LISFLOOD FP flood model was used to generate flood hazard maps in Dudelange, Luxembourg with the aim to demonstrate a practical application of the estimated local rainfall return periods in an urban area.

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