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Modelling, Management and Prediction of Extreme Urban Pluvial Floods

edo Maksimovi1, Nuno Simes2, Lipen Wang3

1Prof, PhD/Department of Civil and Environmental Engineering/Imperial College London, LONDON, UK.

c.maksimovic author@imperial.ac.uk

2PhD student/ Imperial College London, LONDON, UK. nuno.simoes08@imperial.ac.uk

3 PhD student/ Imperial College London, LONDON, UK. li-pen.wang08@imperial.ac.uk

ABSTRACT: Urban surface water flooding is affected by local topography, the drainage infrastructure, the built urban

environment and that events are characterised by rapid onset, high intensity precipitation. Owing to rapid development of LIDAR

technology for generating high resolution DEM/DTM (Digital Elevation/Terrain models) improvement in fine resolution of urban

surface runoff modelling is enabled. High resolution One dimensional (1D) and two dimensional (2D) models have recently been

developed and tested for applications in urban (built) environment. However for reduction of natural disaster caused by this type

(usually called flash) floods in urban areas a new approach for urban surface (pluvial) flood prediction (and warning) is

required.

Keywords: Urban pluvial flooding, rainfall prediction, flood prediction, research needs.

1. INTRODUCTION

Flooding in urban areas is causing repeated damage that calls for improved management of floods from all sources. According to the UK Governments Independent Review into the summer 2007 flood event (Pitt Review) about two thirds of flood damage in urban areas was caused by surface water (pluvial) flooding. While fluvial and coastal floods are well documented with extensive fluvial flood mapping and fluvial flood warning systems in place, this is not the case for surface water. Furthermore the time

scales of fluvial and coastal flooding allows for timely flood warning response. Surface water (pluvial) flooding caused by intense local storms during which the capacity of the sewer network and of the surface drainage system is often exceeded has, until now, not been given appropriate attention within Northwest Europe. Because urban surface water flooding is affected by local topography, the drainage infrastructure, the built urban environment and that events are characterised by rapid onset, high intensity precipitation, a new approach for urban surface water flood prediction (and warning) is required. Although significant breakthroughs in advanced modelling of pluvial flooding process have recently been made (UWRG have developed an advanced pluvial modelling tool), there is a big need to further enhance

predictive capabilities by addressing both short term rainfall prediction and surface flood prediction in highly developed urban environments. This paper presents the state-of-the-art in fine scale (street and property level) urban pluvial flood modelling, management and initial activities in research of urban pluvial flood prediction.

2. MODELLING AND MANAGEMENT OF URBAN PLUVIAL FLOODING PROCESS

As opposed the concepts used in the past, mainly based on conceptual simplications and high level of empirical assumptions, Modelling of rainfall runoff process implemented here is based on mass and momentum conservation principles and spatially distributed catchment and drainage system characteristics as well as on spatially distributed rainfall as input for modelling. Implementation of this concept has been enabled by the availability of high resolution LIDAR (LIght Detection And Ranging) data. Current technology enables vertical resolution (Z coordinate) of 5- 10cm to be obtained. Following the advancement in data availability, reliability and affordability, advanced models have been developed over past few years enabling reliable analysis for planning design and systems rehabilitation to be carried out . Finally after several decades in which conceptual models have been dominant, advanced physically based models are gradually becoming a norm. Field surveys for model calibrations have reached level of maturity, thus the conventional models are gradually being replaced with the advanced ones.

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2.1 Modelling concept

In Fig 1 the concept of dual drainage applied throughout the modeling process is presented. It uses physically based concept of dynamic simulation of rainfall-runoff process.

Subcatchment

Depression

Flooded area

Total rain

Flow in the sewer

Overflow from depression

Surface runoff

Effective rain

Outflow to the surface

Legend:

0

0

12

3

4

5

6

7

8

1

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Dual drainage concept

Fig 1 Dual drainage concept applied in AOFD for urban pluvial flood modelling

Modelling of detailed surface runoff is run concurrently with flow in storm drainage (separate or combined) network. During flooding period drainage network is usually surcharged and water can flow in as well as out of the network.

2.2. Results of models testing in the UK

The models developed within FRMRC1 include 1D/1D model (AOFD) of UWRG (Imperial College London) presented in Maksimovi et al (2009) and 1D/2D developed by Centre for Water Systems (Exeter University) and presented by Djodjevi (2009). The models have been tested thoroughly by independent modelers through UKWIR (UK Water Industry Research) and the results are presented in Allitt et al. (2009). The results of the modeling have shown the advantages of the two approaches

3. URBAN PLUVIAL FLOOD PREDICTION AT ITS ONSET

3.1 Beyond the conventional wisdom

Conventionally flood prediction and flood warning systems are based on experiences gained in fluvial flood modelling and prediction which last longer and have longer lead time. However the requirement for predicted rainfall information for urban

pluvial (surface) flood management is for spatial detail at the street scale (~100m) up to several hours ahead, so as to enable: (a) real-time operation of storm drainage assets and routing of water through the storm drain system to avoid surcharging (b) prediction of floodwater collection in local depressions to permit pre-emptive mitigation actions by local emergency responders and the public.

Although the locations of potential flood vulnerable areas (trouble spots) might be known, whether or they will be activated during the forthcoming storm can only be determined by a combination of short term rainfall and surface flood prediction. Measurement of the rain rate distribution at street scale every 5-minutes is possible using low-cost high-resolution X-band radars up to a range of about ten to twenty kilometres. Deterministic prediction at this scale using NWP technology is prevented by the

chaotic nature of the atmosphere beyond a few minutes ahead but probabilistic prediction may be possible provided the stochastic nature of the small scales can be deduced and modelled sufficiently accurately. However, it must be recognised that the resulting probability of exceeding flood-producing thresholds will be small on most occasions when flooding occurs, implying that action must be taken on a much higher frequency of occasions. Nevertheless, there may be sufficient predictability up to an hour ahead to enable cost-effective application to real-time control, and the addition of observations from local radar may enhance this.

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The concept of the short term rainfall prediction based on combination of several techniques such as (i) NWP (Numerical Weather Prediction) combined with real time communication of point measured rainfall rata used in combination of fine resolution radar signals obtained by either X-Band radars or super resolution C-Band ones is presented in Fig 2. The proposed system is based on combination several technologies, which in the past have been applied separately. Based on general concept presented in Fig 2 short term rainfall prediction is being developed for input to short term urban pluvial fold prediction presented

in what follows.

Numerical Weather Prediction: UM/MM510 km

1 km

C-Band

Meteorological Radar

X-Band1 km

100 m

Ground Raingauge Network

CALIBRATION

T = Future

T = Currenti

t

1 kmDOWNSCALING ISSUES

i i

tTemporal

Spatial

NOWCASTING

Fig 2 The concept for development of short term urban pluvial flood prediction

3.2. Short Term Rainfall Prediction

For reliable prediction of urban pluvial flooding it is essential to have reliable spatial and temporal rainfall prediction. Possible improvements that can be carried out to upgrade the state-of-the-art techniques of short term rainfall prediction are three-fold (shown as Fig 3). First, the nowcasting technique, which was conventionally undertaken by extrapolating radar observations, can be improved by calibrating with certain NWP outputs (e.g., rainfall, pressure, and advection) to increase the forecast lead time (to 2-3 hours) and accuracy as well as to reflect the weather variation over lager scales. Second, the current range of radar data resolution can be enhanced by adopting X-band radar observations or advanced image reconstruction techniques (e.g., super-

resolution techniques). This enhancement (Wang et al (2009) is expected to obtain ~500m radar observations, which is somewhat closer to the ideal spatial scale for the urban surface flood modelling. Third, advanced statistically-based space-time downscaling methods are needed to circumvent the stochastic nature of finer-scale rainfall data and to provide feasible high-resolution rainfall details for local uses.

Spatially distributed rainfall has to be predicted in this way rather quickly so that the time between the first indication of the possible problematic event and full scale prediction (ready to issue flood warning if needed) is shortened to no more than 10 15

minutes.

Fig 2 Possible improvements in the state-of-the-art scheme of short term rainfall prediction

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3.3 Short term flood prediction issues

Short term fine resolution rainfall prediction is used as an input to short term runoff and pluvial flood prediction.

In flood forecast situations, one of the critical aspects is the period of time available between the acquisition of data, such as rainfall, and the results obtained by hydraulic simulations. Therefore, data transmission, correction of anomalies and hydraulic simulation of the drainage system need to be fast, reliable and as accurate as possible in order to get the best possible estimation of flood magnitude and extension. Besides the increase of computational power, there are several techniques to decrease the

simulation time like conceptual simplifications and empirical assumptions. However it is also possible to use physical based models based in dual drainage concept: it is possible to reduce the simulation time by simplifying the network model topology (Simes et al, 2010) and by using a better coverage of flood vulnerable areas using different spatial resolutions (nesting) models. Both techniques allow to have very detailed networks in vulnerable areas and less detailed in other parts. The 1D/1D is much faster than 1D/2D models and the physical based models have the advantage of being adjustable to future changes in the area.

3.4 The way forward and research needs

Based on the above presentation future research and development needs are: (i) further development of reliable short term rainfall prediction for increased time period (beyond 2-3 hours), (ii) enhancement of runoff and pluvial flood prediction and (iii) testing

and approval of the methodology in several full scale case studies in different environmental and climate conditions.

4. CONCLUSIONS

The state-of-the-art in urban pluvial flood modelling enables rapid development of pluvial flood prediction.

Initial results in this direction obtained by the UER research is encouraging, but significant efforts are still needed in order to

bring the initial research results to full scale application products, their testing and approval. Since urban pluvial flooding is local issue it has to be dealt with at local level. Development of local institutions capacity to take-up the technology and to carry out full scale deployment is a serious challenge which is yet to be addressed.

5. REFERENCES

Allitt, Richard; Blanksby, John; Djordjevi, Slobodan; Maksimovi, edo; and Stewart, David (2009), Investigations into 1D-1D and 1D-2D Urban Flood Modelling Proc of the WaPUG Autumn Conference, Blackpool

Djordjevi, Slobodan (2009) 1D, 2D and 3D modelling of urban flooding, Morning Lecture, UDM09 Conference, Tokyo

Leito, Joo; Boonya-aroonnet, Surajate; Prodanovi, Duan; and Maksimovi, edo; (2009) The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding, Water Science & TechnologyWST, 60.12 Maksimovi, edo; Prodanovi, Duan; Boonya-aroonnet, Surajate; Leito, Joo;. Djordjevi, Slobodan and Allitt, Richard (2009). Overland flow and pathway analysis for modelling of urban pluvial flooding. Journal of Hydraulic Research, 47(4):512-523. Simes, Nuno E.; Leito, Joo P,; Maksimovi, edo; S Marques, Alfeu; and Pina, Rui (2010) Sensitivity Analysis of Surface Runoff Generation in Urban Floods Forecasting, Water Science & Technology, (in press)

Wang, Li-Pen; Maksimovi, edo and Onof, Christian (2009). A determinitsic multiplicative cascade method for sub-daily rainfall forecast, 8th International workshop on precipitation in urban area, St. Moritz, Switzerland, 83-87.