METEOROLOGICAL INPUTS

METEOROLOGICAL INPUTS

Unit 2.1 of I-Learning module on Flood Modelling for Management

Prof. Dr. Roland K. Price UNESCO-IHE Institute for Water Education

Flood Modelling for Management 1

Flood Process (Unit 2.1) Roland K Price

Meteorological inputs

1 Introduction1 Most floods that we are considering are generated from very intense short duration rainfall, such as thunderstorms, or heavy prolonged precipitation of a frontal type, though possibly with embedded cells. The physics of rainfall generation is very complex and depends on a number of thermodynamic and conservation processes taking place in the atmosphere. Generally, global circulation models (GCMs) tend to forecast the weather, and the rainfall at least qualitatively, for a matter of a few days ahead with reasonable accuracy. However, they then tend to become quite inaccurate in a way that is intimately dependent on small perturbations in the initial conditions. This tendency toward chaos means that ensembles of forecasts have to be made, taking into account the possible variations in the boundary conditions. There are obviously limits to the forecasting horizon for rainfall forecasts deduced from models, whether GCMs or even local area models (LAMs). The value of such models is that they enable more effective rainfall forecasts to be made when there is very little lead-time between the peak rainfall and the peak runoff, such as in flash flood events. The modelling may help to gain sufficient lead-time to enable warning to be given to the local population and evacuation to take place. This means that traditionally, where there is sufficient lead-time between peak rainfall and runoff, forecasting methods for rainfall have been based more directly on data measurements. Normally there are two principle ways of carrying out rainfall monitoring: point rainfall measurements through networked autographic gauges and direct area measurements of rainfall through weather radar. Generally, as weather radar becomes more wide spread, this method tends do become the dominant technology. The basic assumption about the use of radar images for rainfall forecasting is that there is some degree of resilience in the patterns of rainfall made by a storm event, and that the pattern is dynamically evolving. From these assumptions storm-tracking methods have evolved. Their implementation has three stages: • Estimation of storm parameters • Storm forecasting • Data quality control In the first instance the latest observed radar images are used to describe the storm characteristics through certain key parameters. The basic parameters of interest are the direction of the global storm movement and its speed. More complex parameters include the cell areas, speeds and directions of movements of the individual cells, growth and decay of cells and cell splitting and merging. Particular pattern recognition techniques such as cross correlation are used to define these parameters. The storm forecast is based on the assumption that these key parameters remain constant for the duration of the forecast period, and that the evolution of the storm can

1 The text in this lecture owes much to Cluckie and Austin (2003).



be described by a linear extrapolation of the velocity vectors from the latest radar image. Finally, because unrealistic values can be generated in the forecast images, quality control constraining the results has to be imposed. One of the first cross correlation forecasting techniques was developed at McGill University Montreal under the SHARP (Short Term Precipitation Forecasting Procedure) programme (see Austin and Bellon (1974)). A similar approach has been developed to augment the 5km resolution for forecasts produced by the FRONTIERS system. Precipitation type Validity of linear

extrapolation Non-linear predictive capability

Downburst/Microburst 1 – a few minutes Very limited Individual thunderstorm/Heavy shower

5 – 20 minutes Very limited

Severe thunderstorm 10 – 60 minutes Very limited Mesoscale organised thunderstorm

60 – 120 minutes Some

Flash flood rainfall 1 – a few hours Very limited Onographically triggered showers

60 minutes Very limited

Frontal passage Many hours Fair - good

2 Use of radar A meteorological radar system emits a short pulse of duration the order of a microsecond of microwave energy. This is reflected from the target, in our case a drop of rain. A very small part of the reflected signal returns to the aerial system where it is amplified to a reasonable voltage. The signal is then digitised as a function of time after the trigger impulse. Digital values are then averaged in order to reduce pulse-to-pulse variability and then converted into data suitable for display. In this way, provided we know the drop size spectrum of the rainfall, the relationship between the radar reflectivity, Z, and the rainfall rate, R, can be determined. The problem is that a great variety of Z-R relationships are found. This can be addressed through calibration against point rainfall gauges. However, other problems can also arise. Beam blocking occurs, particularly in mountainous areas, though even in flat terrain, trees and buildings can affect the signal. The radar resolution cell (~ 1 km2) is considerably bigger than the small area (100 m2) covered by the point rainfall gauge. Higher rainfall rates are therefore to be expected at the point gauge compared with the radar cell. Thus, continuous agreement between the radar and rainfall gauge should not be expected. Then again, there is the phenomenon of the bright band, which is the level at which snow converts to rainfall. The band affects the reflexivity of the radar signal and needs to be accounted for if the signals are to be interpreted accurately. Finally, the drop size spectrum can change causing the calibration to become less valid. Care is obviously needed in order to interpret the radar signals correctly. If this is done however, radar can then provide an excellent means of tracking rainfall movement and provide a substantial basis on which to forecast rainfall.



2.1. Use of remote sensing Another method of assessing rainfall, especially in giving advance warning of the occurrence of rainfall is through the use of geostationary satellite images (Milford and Dugdale (1989)). The use of such images offers considerable scope in providing insight into cloud movement in remote areas. Grijsen et al (1992) report that it has been successfully used for the development of the Nile Flood Early Warning System.

3 Rainfall data2 The original means of measuring precipitation is through the use of some storage device that accumulates precipitation near the ground. The most straightforward device is to measure the amount collecting in a graded bottle in the period of 24 hours, making any necessary adjustment for evaporation. Many mechanical devices have been invented to automate the measurement, including siphons and tipping buckets coupled with a chart recorder. The latest recorders are solid state and/or linked to telemetry systems. The selection of a site for a rainfall gauge is not necessarily easy. The objective is to ensure that the rainfall collected is representative of the precipitation over the surrounding area. What is actually caught is the amount that falls over approximately 150 cm2. This is effectively a ‘point’ measurement and has to be converted into a measurement of precipitation for a much larger area. Obviously there are limitations on the accuracy of such an interpretation. Such limitations can be reduced through the use of an appropriate network of rainfall gauges. The optimal positioning of a rainfall gauge network is an important subject. Where there are a number of rainfall gauges in a catchment the areal rainfall can be calculated through the division of the catchment into sub areas through the Thiessen polygon or isohyetal methods. With knowledge of the areal rainfall it is then possible to consider a depth-area-duration analysis to determine the maximum falls for different durations over a range of areas. One of the most sophisticated studies of rainfall data done in Europe was for the Flood Studies Report (1975). A particular relationship was derived linking point rainfall measurements and areal rainfall for a range of areas and durations. For example, the application of an Areal Reduction Factor to the mean of the point rainfall observations over a given duration, leads to the areal rainfall over a catchment area; see Fig 1.

2 For a very readable summary see Shaw (1994)



Fig 1 Average Annual Rainfall 1916-1950 The next important analysis is for rainfall frequency. This depends fundamentally on the duration of the rainfall for which the frequency is required. This type of analysis depends critically on having a sufficient length of data in the time series. Typically in countries in temperate climates the distributions of rainfall frequencies are as shown in Fig 2.



Fig 2 Areal reduction factor (ARF) as a percentage, related to area A and duration D for the UK (NERC, 1975) This leads us on to an intensity-duration-frequency analysis of continuous rainfall events. Typically, the average rainfall intensity is given by

btaI+

=

where t is the duration and a and b are functions of the return period. Sophisticated versions of this equation have been derived to estimate the (design) intensity of rainfall for any duration and frequency throughout the UK making extensive use of a number of maps; see, for example, the average annual rainfall for the UK in Fig 3.



Fig 3a Map of rainfall amount falling in 2 days with return period 5 years (M5-2 day) (cf Jackson, 1977)



Fig 3b Map of rainfall amount falling in 60 mins with return period 5 years (M5-60 min) (cf Jackson, 1977) Catastrophic flooding is generally caused by extreme rainfall (possibly with snowmelt) events. One of the highest recorded events in the UK was 155 mm in 105 mins at Hewenden Reservoir. This was generated by severe convective thunderstorms. Analysis of similar storms worldwide (the largest daily rainfall appears to have been 1870 mm on 15 March 1952 at Cilaos, Le Reunion) indicates that there may be a physical upper limit to rainfall. The concept has been called the



probable maximum precipitation (PMP). This becomes an important value for the design of dams.

4 Rainfall-runoff Apart from recording and/or forecasting rainfall itself, the next most important problem is understanding and forecasting the runoff generated by the rainfall. This difficult problem has attracted enormous amounts of attention and effort around the world. There are possibly as many models for calculating rainfall-runoff, as there are people who have a direct interest in the subject. This shows that firstly, it is a very complex and varied physical process to understand, and secondly it depends on a large number of details such that the 80-20 rule applies: although 20% of the effort can produce 80% of the answer another 80% of effort is needed to refine the process. Runoff generation from rainfall over a catchment can be assumed to depend on factors such as

• Atmospheric conditions over the catchment (wind speed, direction, temperature, humidity etc)

• The surface cover (type, distribution, interception, take up, evapotranspiration etc)

• Surface soil (type, permeability, porosity, etc) • Terrain (slope, surface texture, etc) • Geology (structure distribution, permeability, porosity, groundwater levels,

etc) Generally the following processes are usually identified as taking place:

• Evapotranspiration at the surface • Surface infiltration • Overland flow • Unsaturated zone flow • Saturated zone flow (groundwater)

Each process is mode more complicated by other more detailed sub-processes. For simplicity it is assumed that the key processes during the generation of a rainfall runoff during a flood are the last three. Precipitation falls on the catchment surface, which is covered largely by vegetation in the case of a natural catchment. Urban catchments will of course have a sizeable proportion of the surface paved in the form of roads or buildings. Infiltration takes place dependent on the nature of the surface cover and the wetness of the surface (soil) layer in so far as it limits the capacity of the ground to absorb the rainfall. Rainfall that cannot infiltrate locally due to the intense nature of the rainfall, say, runs away from the immediate area over the surface. Such water could well infiltrate elsewhere, pond up or join a surface stream. Water that does infiltrate seeps through the soil, which will generally be unsaturated near the ground surface. Flow through this unsaturated zone is very complex, and highly dependent on surface tension of the water and the nature and structure of the soil. Modelling this part of the overall process has proved to be very difficult. At a certain level (depth) locally the infiltrating water can reach the saturated zone where the flow may be defined by the local (upper) aquifer. Flows here take place horizontally as well as vertically, and there can be (slow) interactions with neighbouring surface streams. Again, the geological structure can generate significant variations in the flow below ground, though in general the time scales associated with such flows will be considerably longer than the surface runoff flows generated during intense rainfall.



The overall generation of flood flows in a natural catchment largely takes place through surface runoff into the dendritic network of small (surface) streams that are formed out of the variations in the natural topography. The smaller streams feed larger streams that have generally been formed over thousands of years through erosion by repeated storm events of different magnitude. The distribution and dimensions of the streams are related to the variations in surface topography of the catchment and the geological structure. Generally, it can be assumed that a natural catchment is in fact pear-shaped. It is the shape of the catchment that tends to concentrate flows lower down in the stream network. This implies that for rainfall falling uniformly over the whole catchment the bulk of the runoff at the given outfall comes from higher up the catchment, and not from the adjacent parts. When the spatial variation of the rainfall is taken into account then intense rainfall in the upper parts of a catchment can lead to flood discharges in the lower reaches of the stream network, even though there may be no rainfall there. In this way we can discretise the catchment and stream network such that we can talk about flood generation over a catchment (or part of it) and flood propagation in the lower stream network. Flood generation (from rainfall) is largely a matter of rainfall-runoff and therefore a hydrological problem, whereas flood propagation in a stream/river network is the concern of hydraulics. Rainfall-runoff from an urban catchment is similar, but in many respects simpler than runoff from a natural catchment. In an urban catchment rainfall over a significant proportion of the surface is prevented from infiltrating freely due to the artificial paving due to roads and buildings. This means that the surface runoff from such surfaces can be considerably greater than from a natural surface. Therefore, the water running off the paved surfaces quickly ponds up or flows in sizeable volumes, causing a serious nuisance and damage. Consequently, artificial conduits augmenting any natural channels are constructed to convey excess rainfall away from critical areas quickly and efficiently. Such water can of course be stored effectively in detention areas depending on the capacity of the (downstream) conduits and natural channels. Infiltration of rainfall in an urban area is by definition limited, though engineers now recognise that there is considerable value in artificially maximising the infiltration of rainwater in order to limit the cumulative surface runoff, while ensuring that consequent groundwater levels do not adversely affect the foundations of urban structures.

References Austin and Bellon (1974)). Cluckie, I D and Austin, G L (2003) Hydrometeorological aspects. In River Basin Modelling for Flood Mitigation, Ed Knight and Samuels, Course at University of Birmingham, Oct 2002 Milford, J R and Dugdale, G (1989) Estimation of rainfall using geostationary satellite data. Applications of remote sensing in Agricultural Sciences, University of Nottingham, Butterworth, London Natural Environment research Council (1975) Flood Studies Report in 5 volumes, NERC :London



Grijsen, J G, Snoeker, X C, Vermeulen, C J M, Mohammed El Amin Moh. Nur, and Yasir Abbas Mohamed (1992) An information system for flood early warning, In Saul A J (Ed) Floods and Flood Management, Kluwer Academic Publishers, pp263-289 Shaw, E M (1994) Hydrology in practice. 3rd edition, Chapman and Hall, London

Documents

METEOROLOGICAL INPUTS