SHSG 2005 Catchment Modelling – Huband and Sene
INTEGRATED CATCHMENT MODELLING ISSUES FOR FLOW FORECASTING APPLICATIONS Marc Huband – Atkins Water1 Kevin Sene – Atkins Water2 Abstract Hydraulic models are increasingly used for real time forecasting applications, such as flood forecasting, water resource management and pollution control. This paper discusses some of the key initial modelling decisions to take in developing new models for real time use (or converting existing models). The topics discussed include the overall model design, model configuration options, real time updating issues, and model run time and accuracy considerations. These issues are illustrated using the example of a complex real time model which was recently developed for the Welland and Glen catchment in Lincolnshire, which incorporates more than 400km of real time hydraulic model reaches, and almost 500 structures of various types. 1.
Introduction
Integrated catchment forecasting models can provide real time estimates of future levels and flows in a catchment, and can be applied to a range of applications, including flood forecasting, water resource monitoring and management, and pollution control. Their offline counterparts, which often form the basis for the real time version, can also be used for other applications, such as developing Catchment Flood Management Plans. With modern computing power, it is increasingly practicable to develop complex real time hydraulic models for all significant river reaches and structures in a catchment, which are capable of assimilating data from raingauges, river gauges, structures and other sources (e.g. weather radar) in real time, and running within the typical telemetry polling interval of 15 minutes (in UK practice). However, some modelling simplifications may be required, and modelling effort tends to be focussed on key locations where forecasts are required (so-called Forecasting Points), with a more approximate approach for other parts of the catchment. In designing models of this type, a number of key decisions need to be made, including whether the model is to be optimised for only part of the flow regime (e.g. for high flows, in flood forecasting applications), and whether the model should be developed as a single integrated model, or as a series of individual models to represent the catchment. Each choice has implications for the accuracy, reliability and timeliness of the resulting model, and of course on the overall cost and time of implementation. This paper discusses some of these design decisions, using the Welland and Glen catchment in Lincolnshire as an example. This model includes 55 conceptual rainfall runoff models feeding over 400 km of hydrodynamic network, and simulates flows and levels across the full range of flows at 52 locations in the catchment. The final build of the model required just under 500 structures to effect a satisfactory calibration, including: 1 2
Atkins Water, Orton Southgate, Peterborough, PE2 6YS (
[email protected]) Atkins Water, Chadwick House, Birchwood, Warrington, WA3 6AE (
[email protected])
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SHSG 2005 Catchment Modelling – Huband and Sene
• • • • • •
Flood storage reservoirs Siphons Pumps and complex gates Bridges Weirs Culverts
The model runs ‘around the clock’ on a modern internet-based flow forecasting system, and will shortly be migrated to the Environment Agency’s National Flood Forecasting System (NFFS). 2.
The Welland and Glen Example
The Welland and Glen catchment extends from its headwaters near Market Harborough in Leicestershire to the Wash Estuary (Figure 1).
Figure 1 – Schematic of the major subcatchments in the Welland and Glen catchment Major towns within the catchment include Oakham, Stamford, Spalding, Market Harborough and the northern fringes of Peterborough. In general terms, the catchment can be divided into three segments • Rapidly responding clay upland catchments • Broad floodplains in the middle section • High level carriers (embanked reaches) in the lower section There are numerous complicating influences on flows, particularly in the lower reaches, including pumped and gravity fed discharges and abstractions, off-line storage reservoirs (e.g. ‘washlands’), tidal influences, and manual and automatic flow control structures. An early decision was made in the project to develop a full flow forecasting model, rather than
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SHSG 2005 Catchment Modelling – Huband and Sene
one aimed specifically at flood forecasting, so some possible additional applications of the model include: • • • • •
Management of raw water transfers Management of river support Management of drought and license control Management of pollution incidents Management of navigation and of strong stream warnings
3.
Key Modelling Decisions
3.1
The Parent Model Approach
The Welland and Glen was a pilot for a major forecasting model development programme in East Anglia. This programme has adopted a general modelling approach of so-called ‘Parent Models’. In this approach, an overall model is constructed which can either be used unchanged for a range of applications, or simplified/optimised for other applications (such as flood forecasting) as required. The advantage of this approach is that, at any one time, there is only one ‘best attempt’ model for the catchment, which can form the basis for all ‘Child Models’ used for specific applications. This simplifies the process of maintaining and improving the model, and makes it easier to document and audit the history of model development. Of course, the initial development time and costs can be higher than in the more classical approach of developing a range of models for different applications (although may be lower overall in the long term). In particular, for forecasting low flows, all key inflows and outflows need to be represented, including surface and groundwater abstractions and discharges for water supply, agricultural demands, land drainage and other requirements. For example, Figure 2 shows an example of a decision tree for selection of the most appropriate modelling approach for key discharges in the catchment. To maximise forecast lead times, and to represent the year-round influences of catchment antecedent conditions, the model also includes 55 conceptual rainfall runoff models. These include automated accounting for catchment state, and can be updated in real time at telemetry sites (where these are available). The models also represent lateral inflows to the hydraulic model reaches, thereby allowing for spatial variations in rainfall and catchment conditions during events of interest.
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SHSG 2005 Catchment Modelling – Huband and Sene
Split Significant and Non Significant discharges. Significant Discharges
Split time variant discharges from those that show a similar profile year on year. Constant Profile
Time Variant
Split discharges: those with and those without historic data. Historic Data
Prepare annual profile on a monthly timestep, based on average historic discharge in each month.
Identify location of abstraction in model and create boundary condition file.
Use historic data
Use historic data
Use boundary condition file.
User enters abstraction rate (or model falls back on default boundary condition file).
Prepare annual profile on a monthly timestep, based on licence details.
Agregate the profiles by type and in interforecast point reach and define the typical annual profiles to create boundary condition file.
Use boundary condition file. Adjust to correct bias error during low flows attributable to abstraction.
Use calibrated boundary condition file.
Calibration Design Runs
Identify location of discharge in model and create boundary condition file.
No Historic Data
Model Build
Prepare annual profile on a monthly timestep, based on average historic discharge in each month.
Non Significant Discharges
Inter-forecast point reach - reach between points of interest on the river system.
Figure 2 – Example of a model selection decision tree for key discharges 3.2
Model Configuration Options
For the hydrodynamic and routing components of a real time model, modern flow forecasting systems can allow a range of model configuration options including: • Single Models – one model for the whole catchment • Multiple Models – two or more models running in sequence or in parallel for all or part of the catchment • Nested Models – single or multiple models with more complex models nested within them for specific forecasting issues These methods have a range of strengths and limitations as indicated in the following table:
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SHSG 2005 Catchment Modelling – Huband and Sene
Table 1 – Some strengths and limitations of various model configuration options for hydraulic and routing reaches Method Single Model
Multiple Models
Nested Models
Strengths - Simple to manage future development of the model - No complex decisions to make about which forecast to use - No discrepancies between forecasts for the same location - No boundaries between models to define - Models can be run independently (not requiring the full model run) - Parallel processing of model runs is possible giving faster overall run times - A staged delivery of models is possible - The splits between models allow independent updating algorithms to be used
Limitations - Possible node limitations for hydraulic models - Run times can be long - Model must be built and tested in one operation - Updating must be internal to the model
- Boundary conditions must be defined explicitly at model joins - Downstream information may not be correctly transferred to models upstream e.g. backwater influences, tidal effects - An overall catchment water balance may not be preserved - Greater complexity for Duty Officers during an event (if the model run sequence is not automated) - More detailed model outputs can - More difficult to maintain and be provided in areas of interest update models - Nested components can be used - Greater complexity for Duty ‘on demand’ so do not normally Officers during an event impact upon overall model run - Conflicting forecasts possible at times the same location - An alternative simpler model will - The physical representation of the be available as a fall back in case catchment may no longer apply (e.g. of model failure model reaches may need to overlap) - Parallel processing is possible giving faster run times
The issue of updating is an important consideration for forecasting models, since the facility to update forecasts based on real time (telemetered) data can provide major improvements in forecast accuracy, provided that the real time data is of acceptable accuracy. For hydraulic models, the main approaches to updating at present include: • Error prediction (e.g. statistical models to adjust model outputs) • State updating (e.g. adjustments to inflows to distribute ‘errors’) • Parameter updating (e.g, adjustments to roughness or other parameters) It is worth noting that, for some ‘brands’ of hydraulic model, updating can only be performed by external algorithms (e.g. error prediction routines), so the model must be split at all required updating points, whereas other types allow either state or error
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SHSG 2005 Catchment Modelling – Huband and Sene
prediction updating to be performed internally, with state updating maintaining an internal water balance, although at the expensive of some computational overhead. For the Welland and Glen model development, the model ‘brand’ which was used allowed either error prediction or state updating and, for accuracy and operational simplicity, the decision was made to build a single model, using internal state updating in the hydraulic reaches. 3.3
Run Time and Accuracy Considerations
The hydraulic components of the model were constructed by converting sections from previous scheme and flood risk mapping models, and building new model reaches where required from survey data. The model was calibrated to observed 15 minute data over a full two year period and validated using data for the subsequent year. For conversion of an existing model to real time use, there are a number of other factors to consider in addition to run time, including: • The model must be stable for all likely flow conditions and at all locations • The model accuracy requirements may vary around the catchment, with higher accuracy required at Forecasting Points and updating locations • The calibration criteria for an off-line model may focus on one aspect of performance (e.g. peak levels) rather than accuracy year-round under all flow conditions As noted earlier, 52 key forecasting locations (or ‘Forecasting Points’) were identified in the catchment, and the model was optimised around these points and the telemetry network. Some approaches to adapting the available models to real time use included: • Rationalisation of models – removal of cross sections and structures between Forecasting Points which did not significantly influence levels in the neighbourhood of Forecasting Points (to produce a so-called sparse hydrodynamic model) • Simplification of models – simpler representation of structures and other features where this did not significantly influence levels in the neighbourhood of Forecasting Points • Reconfiguration of models – alternative representations for structures etc which were to be retained, but which caused stability or convergence problems Particular care was required in the representation of reservoirs and floodplains, and of manual and automatic control structures.
4.
Conclusions
The construction of complex hydraulic models for real time use is becoming increasingly practicable, although considerable care is required in some aspects of the model build or conversion. Some key considerations in the initial model design include the configuration of the model (into single, multiple or nested models), and the likely run time and stability for real time use. A decision is also required on whether to focus the model on one particular aspect of catchment response (e.g. for flood forecasting), or whether to adopt the
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SHSG 2005 Catchment Modelling – Huband and Sene
‘parent model’ approach, of building the best possible model for a range of applications. Each decision has implications for the likely cost and development time of the model, and the accuracy and run time when used operationally. For real time applications, a number of other factors also affect model run times and accuracy, of course, although are not discussed here (these can include data redundancy scenarios, representation of tidal boundaries, feedback influences at control structures, and other effects). Acknowledgements The ideas presented in this paper have arisen out of a range of previous and ongoing real time flood forecasting model implementation projects for the Environment Agency. The Welland and Glen model development was performed as a pilot study for implementation of the Anglian Flow Forecasting and Modelling System (AFFMS) in Anglian Region of the Environment Agency. References Van Kalken, T., Huband, M., Cadman, D., Butts, 2001. Development of a Flood Forecasting Model for the Welland and Glen Rivers in East Anglia, UK. 4th DHI Software Conference, Helsingør, Denmark. Tilford, K.A., Sene, K.J., 2003. Flood Forecasting Model Selection – A New Approach: An Example Case Study, Kilmarnock. Flooding in Scotland Conference, Perth, 25 April 2003. Tilford, K.A., Sene, K.J., Khatibi, R., 2004. Towards Best Practice Application of Flood Forecasting Models. The 39th Defra Flood and Coastal Defence Conference, York University, England, pp 9.5.1-9.5.3. Sene, K.J., Tilford, K.A., Khatibi, R., 2004. Rainfall Runoff Flood Forecasting Models for Fast Response Catchments. Proc. IMA/FloodRiskNet Conference on Flood Risk Assessment, Bath, September 2004. Chen, Y.C., Sene, K.J., Hearn, K., 2005. Converting Hydrodynamic Models for Real Time Flood Forecasting. Paper accepted for the 40th Defra Flood and Coastal Management Conference, York. Tilford, K.A., Sene, K.J., Khatibi, R., 2005. Flood Forecasting Model Selection - A New Approach. Accepted for publication in 'Flooding in Europe: Challenges and Developments in Flood Risk Management', Eds: Begum, S., Hall, J.W., Stive, M.J.F. Advances in Natural and Technological Hazards Research, Kluwer.
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