Data and Scripts for Advancing a High-Resolution Impact-based Early Warning System for Riverine Flooding (Najafi et al., 2024) 0 14607

Projekt
hydrometeorological data
Beschreibung
- Numerical wether prediction (ICON-D2 EPS) from DWD

The ensemble precipitation forecast utilized in this study is sourced from archived data produced by the numerical weather prediction models employed at the DWD (Pamore), accessible to registered users through https://www.dwd.de/EN/ourservices/pamore/pamore.html. The regional ensemble forecast model, ICON-D2 EPS, is employed with 20 ensemble members serving as forcing. Forecasts are generated at +48-hour intervals, commencing at 00, 06, 09, 12, 15, 18, and 21 UTC, and are updated every 3 hours. The model, with a horizontal resolution of 2.2 km, can be accessed at https://www.dwd.de/EN/ourservices/nwp_forecast_data/nwp_forecast_data.html. The raw data from ICON-D2-EPS is initially in GRIB format. Following post-processing, the data undergoes conversion to netCDF format, facilitating its integration as input for mHM in streamflow ensemble forecasting.


- Hydrological Modeling and forecasting  

Streamflow and water level forecasts are generated based on mHM at a resolution of
1.1 km. The mHM uses multiscale parameter regionalisation for
estimating distributed parameter fields (Samaniego et al., 2010)
and is forced with real-time forecasts from DWD-ICON-D2 EPS for
hindcast evaluation and hydrological predictability of the Ahr flood.
The mHM setup used in this study has been described earlier by Boeing et
al. (2022), except that model was now forced directly
with hourly meteorological inputs. A detail description of the procedure for calibrate mHM can
be found in Rakovec et al. (2019). In the present case,
we considered a 10-year simulation period (1.1.2011--31.12.2020) with
five years of warm-up; thus the July 2021 flood peak was excluded from
the calibration exercise. Hourly RADOLAN grids of
precipitation (Bartels et al., 2004; Winterrath et al., 2012)
adjusted to 24-h total precipitation REGNIE (Rauthe et al., 2013) and used
for model calibration.


Hydrodynamic forecasting

The RIM2D hydrodynamic model was
set-up and validation are described in a recent flood inundation
simulation of the 2021 flood event for the Ahr
valley (Apel et al., 2022 ). The locations of buildings,
roads and railways were extracted from the OpenStreetMap (OSM) layers.
Hydrodynamic forecasts are triggered only upon reaching or
exceeding pre-established warning thresholds customised for selected
percentiles based on the user's specific interest. This automated
trigger mechanism enhances the responsiveness and adaptability of the
system accommodating real-time services easier. The RIM2D simulations
are executed on the Graphical Processor Units (GPUs) to achieve high
computational performance. Each ensemble run is allocated to a single
GPU device allowing for parallel processing. While 20 ensemble members
are available, our real-time forecasting focuses on selected
percentiles with respect to peak discharge at the upstream boundary. This approach ensures
timely forecasts every 3 hours and is able to accommodate larger
ensembles if needed.

Flood hazard maps are based on (https://geoportal.bafg.de/karten/HWRM_Aktuell/#). We used the flood hazard maps from Rhineland-Palatinate used show the updated hazard maps (https://hochwassermanagement.rlp-umwelt.de/servlet/is/200041/) accessed on 23.06.2022. The flood hazard map could have been updated after the 2021 flood event.


Quantitative impact forecasting

Several criteria can be provided for impact forecasting including the object-based forecasting
(e.g., buildings footprint), the length of roads
and railways. This information are calculated based on the synthesis of
data extracted from open geographic database such as
OpenStreetMap (OSM), and hydrodynamic forecasting outputs.


Copernicus EMS Mapping products

The Copernicus
Emergency Management Service (CEMS) employs satellite imagery and
additional geospatial data to respond to natural disasters, including
floods. CEMS offers a variety of products that provide insights into
the impact and reach of the event, including overall flood extent and
detailed assessments of damage severity (CEMS_mapping). It
provides information on affected buildings and infrastructures based
on several detection methods such as semi-automatic and automatic
extractions. We utilised the standard spatial datasets (vector data)
from CEMS, which are publicly available free of
charge (CEMS_mapping).


The scientific results have been computed at the High-Performance Computing (HPC) Cluster EVE, a joint effort of both the Helmholtz Centre for Environmental Research - UFZ (http://www.ufz.de/) and a server at GFZ.


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References:

Kumar, R., Samaniego, L. and Attinger, S., 2013. Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resources Research, 49(1), pp.360-379.

Samaniego, L., Kumar, R. and Attinger, S., 2010. Multiscale parameter regionalization of a grid‐based hydrologic model at the mesoscale. Water Resources Research, 46(5).

LfU. Hochwasser im Juli 2021. Tech. Rep., Landesamt für Umwelt (LfU) Rheinland-595
Pfalz (2022). URL https://lfu.rlp.de/fileadmin/lfu/Wasserwirtschaf596
t/Ahr-Katastrophe/Hochwasser_im_Juli2021.pdf.597

Reinert, D. et al. DWD database reference for the global and regional ICON and653
ICON-EPS forecasting system. Technical report Version 2.1. 8, Deutscher Wetterdi-654
enst (2020).655

Bundesamt für Kartographie und Geodäsie. https://www.bkg.bund.de/, last access:669
January 2022 (2022).

OpenStreetMap. OpenStreetMap contributors (2017)

Apel, H., Vorogushyn, S. & Merz, B. Brief communication: Impact forecasting could682
substantially improve the emergency management of deadly floods: case study July683
2021 floods in Germany. Natural Hazards and Earth System Sciences 22, 3005–684
3014 (2022).

Copernicus EMS Mapping products, EMSR517. Available at: [EMSR517]: Bad709
Neuenahr-Ahrweiler: Grading Product, Monitoring 1, version 3, release 1, RTP Map710
01 (2023). Accessed on: 4 October 2023

WINTERRATH, T., ROSENOW, W. & WEIGL, E. On the dwd quantitative precipi-724
tation analysis and nowcasting system for real-time application in german flood risk725
management. IAHS-AISH publication 323–329 (2012).

Rauthe, M. et al. A central european precipitation climatology–part i: Generation727
and validation of a high-resolution gridded daily data set (hyras). Meteorologische728
Zeitschrift 22, 235–256 (2013).729









DOI
https://doi.org/10.48758/ufz.14607
Zitiervorschlag (APA)
Najafi, H., Shrestha, P. K., Rakovec, O., Thober, S., Kumar, R., & Samaniego-Eguiguren, L. (2024). Data and Scripts for Advancing a High-Resolution Impact-based Early Warning System for Riverine Flooding (Najafi et al., 2024). Helmholtz-Centre for Environmental Research. https://doi.org/10.48758/UFZ.14607
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Metadaten Kataloge
Dublin Core
URI
https://www.ufz.de/record/dmp/archive/14607
Thema
Advancing a High-Resolution Impact-based Early Warning System for Riverine Flooding (Najafi et al., 2024)
Veröffenlichungsdatum
18.01.2024
Geltungsbereich
Ahr River basin
Datenart
Model
Datenqualität
qualitätsgesicherte Daten
Datenstatus
bearbeitete Daten
Datenformat
netcdf
txt
Urheber
Najafi, Husain
Shrestha, Pallav Kumar
Rakovec, Oldrich
Thober, Stephan
Kumar, Rohini
Samaniego-Eguiguren, Luis
Beitragende
GFZ, Dr. Heiko Apel (heiko.apel@gfz-potsdam.de), Dr. Sergiy Vorogushyn (sergiy.vorogushyn@gfz-potsdam.de), Prof . Bruno Merz (bmerz@gfz-potsdam.de)
Herausgeber
Helmholtz-Centre for Environmental Research
Rechteinhaber
Helmholtz-Centre for Environmental Research
Hinweis zur Zitation
The data corresponding to paper (Najafi et al., in review)
Kontakt
husain.najafi@ufz.de
luis.samaniego@ufz.de
Zeitpunkt oder -bereich der Erzeugung der Daten
01.01.1950 - 31.12.2021 24:00
Sprache des Inhalts
Englisch
Zugriffsrechte
freier Zugriff
 
Geo Core
Räumliches Bezugssystem
WGS84 (EPSG: 4326)
Datenart
Raster
Datentyp
Float
Auflösung
Auflösung in m: 10
Auflösung in Grad: -
Anzahl Zeilen: -
Anzahl Reihen: -