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DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model
Dataset
Update Frequency: Not Planned
Status: Completed
Online Status: ONLINE
Publication State: Citable
Publication Date: 2018-06-28
Download Stats: last 12 months
 
Abstract

This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1).

COSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the "topHSPF" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model.

CSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model

Citable as:  García-Pintado, J. (2018): DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model . Centre for Environmental Data Analysis, date of citation. doi:10.5285/b43ce022c8f94f79b5c3b3ede7aad975. http://dx.doi.org/10.5285/b43ce022c8f94f79b5c3b3ede7aad975
Keywords:  DEMON, Synthetic Aperture Radar, Flood forecast, Assimilation, Ensemble Kalman Filter
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Abbreviation:
Not defined
Data lineage:

Data were delivered by the project team to be archived at the Centre for Environmental Data Analysis (CEDA)

Data Quality:
Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)
File Format:
Data are R binary formatted
Process overview
This dataset was generated by the computation detailed below.

Title
Lisflood-FP v5.9, subgrid compset
Abstract
LISFLOOD-FP is a two-dimensional hydrodynamic model specifically designed to simulate floodplain inundation in a computationally efficient manner over complex topography. It is capable of simulating grids up to 106 cells for dynamic flood events and can take advantage of new sources of terrain information from remote sensing techniques such as airborne laser altimetry and satellite interferometric radar. The model predicts water depths in each grid cell at each time step, and hence can simulate the dynamic propagation of flood waves over fluvial, coastal and estuarine floodplains. It is a non-commercial, research code developed as part of an effort to improve our fundamental understanding of flood hydraulics, flood inundation prediction and flood risk assessment. In this project the COSMO-Skymed Synthetic Aperture Radar (CSK-SAR) were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Environment Agency (EA) rain gauges were used to estimate precipitation and MORECS as potential evapotranspiration to generate the forcings into a catchment-scale rainfall-runoff hydrologic model (topHSPF) to generate simulated runoff forecast, to be used as forcing for the coupled Lisflood-FP v5.9 inundation model. EA water level gauges were used for validation. CSK-SAR based WLO were assimilated into ensemble simulations with Lisflood-FP v5.9 generated with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the above mentioned hydrologic model.
Input Description
None
Output Description
None
Software Reference
None
No variables found
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Temporal Range
2012-11-01T00:00:00
2012-12-31T23:59:59
Geographic Extent

  52.3969°  
-2.3912°     -1.9421°
  51.9491°  
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