1          Introduction

Wiki MarkupThis document ([^HFPTforNFFSHFPTforNFFS.pdf] ) describes the Historic Forecast Performance Tool (HFPT) adapter which was first developed under Environment Agency R&D project SC080030 'risk ‘risk based probabilistic flood forecasting' \[flood forecasting’ [1]\]. The original scientific name of the method is 'Quantile Regression' which was subsequently renamed to HFPT. This report includes a description of the Historic Forecast Performance Tool adapter that can be used within NFFS, the file formats for reading and writing of the quantiles, the configuration of the Historic Forecast Performance Tool adapter in NFFS. In addition, a limited background on the method is described. In Appendix A the off-line calibration module of the Historic Forecast Performance Tool is described. \\is ‘Quantile Regression’ which was subsequently renamed to HFPT. This report includes a description of the Historic Forecast Performance Tool adapter that can be used within NFFS, the file formats for reading and writing of the quantiles, the configuration of the Historic Forecast Performance Tool adapter in NFFS. In addition, a limited background on the method is described. In Appendix A the off-line calibration module of the Historic Forecast Performance Tool is described.

The migration of the prototype R&D to the current version of the NFFS adaptor consists of several steps:

• Increase robustness module for operational purpose. This includes adding error handling and creation of log files, adding flags to module output/result files, module under subversion (SVN), simplified configuration (removing unnecessary items).
• Updating test configurations SC080030 for case studies developed under the R&D project.
• Documentation of configuration of the adapter in NFFS.

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\[[1] \] [http://evidence.environment-agency.gov.uk/FCERM/en/Default/HomeAndLeisure/Floods/WhatWereDoing/IntoTheFuture/ScienceProgramme/ResearchAndDevelopment/FCRM.aspx]

2          Role in NFFS

The role of the Historic Forecast Performance Tool is to provide a probability distribution of the water level forecasts (or flow) conditioned on the deterministic water level forecast (or flow forecast). This can one, a few or many or percentiles or quantiles (including median or any other percentile/quantile like 0.05, 0.10, 0.25, 0.50, 0.75, 0.95).

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The following folder structure is necessary and contained in the ModuleDataSet file

config

QR_models

•           locationId\[1\]

•           locationId\[2\]

•           locationId\[3\]

•           locationId[1]

•           locationId[2]

•           locationId[3]

•           locationId[n Wiki Markup•           locationId\[n\]

Work

4.2.4         Location and file naming convention

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Several flags can be added to the timeseries in output.xml:

Flag="0" ”0”           value is equal to original value (t < t0)

Flag="1" ”1”           value is corrected and reliable

Flag="2" ”2”           value is corrected, reliable but interpolated in between lead times

Flag="5" ”5”           value is unreliable, extrapolated beyond the domain Quantile Regression relationships calibration

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Koenker, R.: Quantile Regression, Cambridge University Press., 2005.

Wiki MarkupKoenker, R.: Quantile regression in R: A vignette, \ [online\] Available from: [http://cran.r-project.org/web/packages/quantreg/vignettes/rq.pdf], 2010.

Koenker, R. and Basset, G.: Regression Quantiles, Econometrica, 46(1), 33-50, 1978.

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