Integration into JRODOS the models of radionuclide

Integration into JRODOS the models of radionuclide transport in rivers, reservoirs
and coastal waters to support the emergency response in early accidental stages
M. Zheleznyak1,2, R.Bezhenar1,2, A.Boyko 1,2, I. Ievdin1,2 , P.Kolomiets, V.Koshebutsky 1,2, I.Kovalets 1,2, V.Maderich 1,2,
W. Raskob3 , D. Trybushnyi3
1Ukrainian
Center of Environmental and Water Projects (UCEWP), [email protected]
2 Institute of Mathematical Machines & Systems, National Academy of Sciences, Kiev, Ukraine
3Karlsruhe Institute of Technology, Institut für Kern- und Energietechnik, Eggenstein-Leopoldshafen, Germany
Decision Support System RODOS The decision support
system for offsite nuclear emergency management RODOS (Realtime on-line decision support), developed under several EC RTD
Framework Programs [1]. contains many models related to support
decision making in case of a nuclear or radiological emergency.
Based on the request of the end users, it was re-engineered based
on the JAVA technology and further named JRODOS. As part of
the RODOS system re-engineering a new version of the
Hydrological Dispersion Module (JHDM) has been introduced. First
implementation of JHDM within the EuropeAid project of JRODOS
installation in Ukraine is overviewed.
Fig.3 Instant fallout density in JRODOS interface at ZNPP and
the integrated deposition density generated in the meteo
situation of the significant turns of the wind during the release
Hydrological Dispersion Module (HDM)
The simulation models are directed onto an estimation of water
contamination (solute, particulated phase) and doses from aquatic
pathway, knowing a deposition from Atmospheric Dispersion Module.
There are several models depending on their complexity:
Hydrological Dispersion Models (HDM) of EC Decision Support
System for Nuclear Emergency- JRODOS
Models of
radionuclide
washoff from
watersheds
1-D river flow,
sediments and
radionuclide
transport models
2-D reservoirs,
floodplains and
coastal areas
model
(unstructured
grid)
3D model for
deep river
reservoirs, lakes
and marine
environment
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RETRACERUNTOX
RIVTOX
ADM
HDM
Athm Dispers
Module
FDMA
1
4
d
2
7
5
6
3
Freshwater Food
Chain and Dose
model
Fig.4 Transport of Cs-137 in Kakhovka Reservoir due to the
deposition after the simulated atmospheric release from ZNPP
Rivno NPP (RNPP) HDM implementation
For the RNPP, located at the bank of the Sozh River which
is a tributary of the Pripyat River, the modeling chain
includes “atmospheric fallout to watershed” – “radionuclide
inflow to river net using the RETRACE -R model” –
“ radionuclide wash off from the river floodplain at the NPP
using 2D COASTOX model “radionuclide transport in river
using the 1D model RIVTOX” – “doses via aquatic
pathways using the FDMA model,”
COASTOX
180
160
140
120
100
Ml_cal
80
Mlyn 2005
60
40
20
0
1
THREETOX
POSEIDON
Marine food
chain and dose
model
Zaporizzhya NPP (ZNPP) HDM implementation
51
101
151
201
251
301
351
120
100
80
Ml_cal
60
Mlyn 2 003
40
20
0
1
51
101
151
201
251
301
351
Fig.5 Computational grid of NWP model WRF around ZNPP,
windows of 1D RIVTOX model for Sozh River , the predicted water
discharge vs the measured data
The ZNPP, located close to the large (18 cub.km) Kakhovka Reservoir,
the modeling chain consists of “atmospheric fallout to reservoirs water
surface ” – “radionuclide transport in the reservoir applying the 3D
model THREETOX" – " radionuclide transport in the Dnieper river
downstream of the Kakhovka Reservoir applying the 1D model
RIVTOX“- "doses via aquatic pathways applying the FDMA model".
Fig. 2D COASTOX for Sozh River floodplain at RNPP:
computational grid, flooded area during two highest floods, the
fluxes of Cs-137 at the downflow crossections in solute and with
suspended sediments for two scenarios of atmospheric releases
References
Fig.2 Computational grid of WRF numerical weather prediction model
3*3 km around ZNPP, the example of near surface wind field and
predicted wind speed versus measurements
KIT – University of the State of Baden-Wuerttemberg and
National Research Center of the Helmholtz Association
Landman, C., Päsler-Sauer, J., & Raskob, W. (2014). The Decision Support System
RODOS. In The Risks of Nuclear Energy Technology (pp. 337-348). Springer Berlin
Heidelberg.
Heling R., Zheleznyak M., Raskob W., et al. Overview of modelling of hydrological pathways
in RODOS. Radiat. Protect. Dosim., 73, 67-70 (1997).

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