EAM6 - Understanding Hydrological Uncertainties

Project overview

In flood risk management, hydrological data and analysis, including modelling, typically takes place within a “chain” of models and analytical processes. Hydrology is often the biggest source of uncertainty in flood modelling but frequently gets overlooked with more attention paid to other parts of the modelling chain including the hydraulic model.

Understanding uncertainty and identifying where in the modelling chain it occurs is extremely important because it has a direct influence upon real world flooding issues ranging from flood defence design and cost benefit analysis to mapping, real time forecasting, warning and resilience to climate change. Crucially, uncertainty may make a difference to the decision that is made by a flood management authority.

This project will assess the major sources of uncertainty at different points in the modelling chain and identify those that we can reduce. Outputs from this project will provide the evidence to show where to focus efforts in operational modelling studies and also to direct methodological improvements.

Our project will:

  • Illustrate the importance of accurate hydrology in flood modelling and identify where efforts should be best focused to reduce hydrological uncertainty in the future
  • Provide evidence to demonstrate how improvements in flood hydrology could result in better investment or operational decisions being made to increase our resilience in the future
  • Help hydrologists, both within the Environment Agency and the wider hydrological community, to understand and communicate the potential scale of uncertainty in their estimates and forecasts.
  • Use example case studies to illustrate how hydrological uncertainty varies between catchments, flood sources and study types
  • Inform the next generation of flood hydrology models and methods delivered by Flood Hydrology Improvements Programme and the UK Flood Hydrology Roadmap

How our project is improving flood hydrology

This project provided evidence of the scale of uncertainty that can exist across a range of flood hydrology applications and catchment types and the impacts it can have on both operational and investment decision making. This will help support the Full Business Case for Flood Hydrology Improvements Programme and inform scopes for later projects also addressing uncertainty.

The following recommendations were made:

  • Ensure high quality observational data is widely available and any uncertainties are acknowledged and shared.
  • Ensure our methods make the most use of data possible e.g. FEH Local.
  • Improve flood estimation methods, particularly for surface water and groundwater driven flooding. Consider the inclusion of continuous simulation and probabilistic outputs.
  • Accounting for non-stationarity within our flow and rainfall record.
  • Expand upon and improve applied methods for quantifying uncertainty.
  • Explore better ways of communicating uncertainty and ensuring they are considered throughout the whole modelling chain.


How our project is contributing to the UK Flood Hydrology Roadmap

The UK Flood Hydrology Roadmap will be realised through 31 actions grouped into 4 thematic work areas of ways of working, data, methods and scientific understanding. Eight actions have been identified to improve methods in UK flood hydrology related to improving flood hydrology methods, models and systems.

This project has contributed to the methods strand actions:

  • M5 - Review management of uncertainty in flood hydrology the project has reviewed the management of uncertainty in flood hydrology and has made recommendations for improvement. This will help answer the following key questions identified in the Roadmap:
  • Why is uncertainty management important?
  • Who is uncertainty management important for?
  • What are the sources of uncertainty in flood hydrology?
  • Which types of uncertainty are important?
  • What are the greatest sources of uncertainty in modelling for flood risk management?
  • What is the relative importance of different assumptions/data sets that contribute to uncertainty?
  • How much is the assumption of data stationarity important compared to other assumptions involved in estimating design floods?
  • M6 and M7 - Develop options to improve flood hydrology knowledge, methods, models and systems.

Project overview

In flood risk management, hydrological data and analysis, including modelling, typically takes place within a “chain” of models and analytical processes. Hydrology is often the biggest source of uncertainty in flood modelling but frequently gets overlooked with more attention paid to other parts of the modelling chain including the hydraulic model.

Understanding uncertainty and identifying where in the modelling chain it occurs is extremely important because it has a direct influence upon real world flooding issues ranging from flood defence design and cost benefit analysis to mapping, real time forecasting, warning and resilience to climate change. Crucially, uncertainty may make a difference to the decision that is made by a flood management authority.

This project will assess the major sources of uncertainty at different points in the modelling chain and identify those that we can reduce. Outputs from this project will provide the evidence to show where to focus efforts in operational modelling studies and also to direct methodological improvements.

Our project will:

  • Illustrate the importance of accurate hydrology in flood modelling and identify where efforts should be best focused to reduce hydrological uncertainty in the future
  • Provide evidence to demonstrate how improvements in flood hydrology could result in better investment or operational decisions being made to increase our resilience in the future
  • Help hydrologists, both within the Environment Agency and the wider hydrological community, to understand and communicate the potential scale of uncertainty in their estimates and forecasts.
  • Use example case studies to illustrate how hydrological uncertainty varies between catchments, flood sources and study types
  • Inform the next generation of flood hydrology models and methods delivered by Flood Hydrology Improvements Programme and the UK Flood Hydrology Roadmap

How our project is improving flood hydrology

This project provided evidence of the scale of uncertainty that can exist across a range of flood hydrology applications and catchment types and the impacts it can have on both operational and investment decision making. This will help support the Full Business Case for Flood Hydrology Improvements Programme and inform scopes for later projects also addressing uncertainty.

The following recommendations were made:

  • Ensure high quality observational data is widely available and any uncertainties are acknowledged and shared.
  • Ensure our methods make the most use of data possible e.g. FEH Local.
  • Improve flood estimation methods, particularly for surface water and groundwater driven flooding. Consider the inclusion of continuous simulation and probabilistic outputs.
  • Accounting for non-stationarity within our flow and rainfall record.
  • Expand upon and improve applied methods for quantifying uncertainty.
  • Explore better ways of communicating uncertainty and ensuring they are considered throughout the whole modelling chain.


How our project is contributing to the UK Flood Hydrology Roadmap

The UK Flood Hydrology Roadmap will be realised through 31 actions grouped into 4 thematic work areas of ways of working, data, methods and scientific understanding. Eight actions have been identified to improve methods in UK flood hydrology related to improving flood hydrology methods, models and systems.

This project has contributed to the methods strand actions:

  • M5 - Review management of uncertainty in flood hydrology the project has reviewed the management of uncertainty in flood hydrology and has made recommendations for improvement. This will help answer the following key questions identified in the Roadmap:
  • Why is uncertainty management important?
  • Who is uncertainty management important for?
  • What are the sources of uncertainty in flood hydrology?
  • Which types of uncertainty are important?
  • What are the greatest sources of uncertainty in modelling for flood risk management?
  • What is the relative importance of different assumptions/data sets that contribute to uncertainty?
  • How much is the assumption of data stationarity important compared to other assumptions involved in estimating design floods?
  • M6 and M7 - Develop options to improve flood hydrology knowledge, methods, models and systems.

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Page last updated: 25 Mar 2024, 03:06 PM