Operational snow mapping by satellites

Transcription

1 Hydrological Aspects of Alpine and High Mountain Areas (Proceedings of the Exeter Symposium, Juiy 1982). IAHS Publ. no Operational snow mapping by satellites INTRODUCTION TOM ANDERSEN Norwegian Water Resources and Electricity Board, Division of Hydrology, P.O.Box 5091, Majorstua, Oslo 3, Norway ABSTRACT A method of deriving snow information from weather and ocean satellites is described. The method is developed in order to improve operational forecasting of inflow to reservoirs for hydroelectric power production in the snow-melting period. Due to the topography typical for Norwegian mountain basins, the snowline concept is not useful. A better description of the snow distribution is achieved by using the satellite data to determine the area of snow cover within each picture element by using reference areas with known snow coverage. The method is well suited for drainage basins larger than 200 km, located above the tree limit. Advanced equipment is required for handling the data and extracting the information. Cloud cover is the limiting factor for the use of the method. If the method is used in an operational routine, the snow maps should be ready one or two days after the data are obtained. Such snow maps can improve the discharge forecasts and thus the power production, especially if at least limited data on the water equivalent of snow are available. In Norway the present production system for electricity is entirely based on hydro-electric power. A great number of existing power plants have reservoirs at about 1000 m a.m.s.l. accumulating inflow from high-mountain areas. In these areas the snow accumulation starts in September and October and the runoff from melting snow amounts to about 50% of the annual runoff. Consequently snow storage is a very important factor in the planning of the power production. In most of the power-plant basins, snow surveys are undertaken once or twice during the accumulation period. The last survey is carried out at the end of the winter before the snow starts melting. Normally the surveys are based on direct measurements, but in some important basins surveys based on the gamma-ray method are also carried out. When snowmelt has started the snow conditions change and the high-mountain basins are not accessible for regular snow surveys. Besides, the representativeness of point measurements is not of the best in the melting period. However, information about the snow storage remaining is of great interest to water-power engineers for prediction of inflow into reservoirs and planning the optimal management of power plants. Areas above the tree line are suitable for studies by satellites, 149

2 150 Tom Andersen and data from satellites have proved to yield valuable information on the areal extent of snow in periods when no information had earlier been available (Rango, 1975). AVAILABLE SATELLITE DATA In operational routines data on the total snow storage in a basin and on the distribution of the storage within the basin are most important. At present it is not possible to detect the water equivalent of snow from satellites. The areal extent of the snow cover can be detected and is used as a measure of the snow storage. There are, however, strong limitations in the interpretation of snow-cover data (Martinec, 1980), and additional information on the water equivalent of the snow should be available. The first Norwegian studies on the application of satellite data in hydrology were based on data from Landsat (0degaard, 1974}. The ground resolution proved to be better than needed for operational purposes, but the 18 day and 9 day repetition rate of Landsat did not fulfil the operational requirements. The next experiments were made with NOAA images, but the analogue presentation made it difficult to reach a satisfactory resolution. The limitations experienced with both Landsat data and analogue NOAA data, made it necessary to develop routines for computer-based processing of digital data from TIROS-N and NOAA. The large pixel size for NOAA-images, about 1 km, proved to be no real problem because most water power basins have an area of several hundred square kilometres which is large enough for this resolution. An important factor in operational use is the availability of the data. Data from the satellites TIROS-N and NOAA are received regularly at the Norwegian satellite receiving station in Troms(zS, northern Norway. If desirable a magnetic tape containing the digital data can be received in the processing centre the day after the satellite has passed. This arrangement makes it possible to do the data processing and make maps of snow cover only one or two davs after the data were recorded. THE SNOW DISTRIBUTION In the mountain areas of Norway the ground is entirely covered by snow every winter. There is no snowline between snow-covered areas and snow-free areas. In this period it is not possible to use present satellite data to estimate the amount of water in the snow cover. The method can only be used when the snow cover has started to melt and parts of the ground are uncovered. Due to the typical topography in most Norwegian high-mountain basins, the snow distribution in spring will be characterized by zones of almost snow-free ground in the lowest part of the basin, then an increasing amount of snow patches and, finally, almost continuous snow cover in the highest parts. Thus it is impossible to talk about a definite "snowline", a term which is commonly used in areas of more Alpine mountain characteristics. Because of the uneven snow distribution it is not satisfactory to

3 Operational snow mapping by satellites 151 classify each pixel(picture element)as either snow-free or snowcovered. More information on the snow cover is available in the data and some of this information is extracted by using the method presented here. THE PRINCIPLES OF THE METHOD To solve the problem of the uneven snow distribution, the snowcovered area is calculated for each of the pixels. Consider a square on the ground 900 m x 900 m in size. The square is covered by dark soil and some low vegetation which is normal for the high mountain basins. If the area is gradually covered by 1/10, 2/10, 3/10 etc, of snow, the reflectance from the area will also increase up to a value which, finally, corresponds to complete snow cover. The reflectance of the area will therefore change from that of soil to that of snow, depending on the snow/soil ratio. In order to establish a relationship between snow cover and reflectance, reference areas with known snow coverage have been selected. Two types of field are used, areas with full snow cover and snow-free areas (two to four of each kind). Each field contains 20 to 40 pixels. Based on the satellite brightness values of each pixel, the mean response for the two types of fields are computed. Each picture element has a digital value in the range of which indicates the amount of reflected light. Typical value of the brightness in snow-free areas is 20 while the grey-scale level HO could represent a completely snow-covered reference field. This means that about 90 of the available 256 grey levels are used in the snow-mapping routines. As an approximation a linear relationship is assumed between the pixel brightness value and the snow coverage, see Fig.l. For each image under study the mean grey levels for the reference fields are decided and then the grey levels for 20%, 40%, 60% and 80% snow coverage are computed. DATA PROCESSING Prior to the melting season the basins included in the study are digitized and connected to the UTM coordinate system. The digitized basin outlines are stored in the computer memory. An example is shown in Fig.2. The processing is based on an interactive system called ERMAN II, and the programs are run on an IBM-3 70 computer with a two-screen display system. Black and white output is available via a Tectronix hard-copy unit connected to the computer. When a scene with satisfactory cloud conditions is received on a magnetic tape, a subset is made of the area of interest. Geometric correction and registration to UTM projection is performed using we11-distributed ground-control points with known coordinates. The reference areas are identified on the image and the relationship between snow coverage and brightness values is established. The actual satellite data are mixed with the digitized basin

4 152 T 0m Andersen FIG. 1 A linear relation is established between the snow coverage and the brightness level for each image. The curve is based upon the intensity levels of numerous pixels within the selected reference fields, where ground truth is available. FIG.2 The Tokke basin in a binary digitized presentation. Scale 1:850 OOO. The white surface has value O (lakes) and the black value 1. When this image is multiplied with the satellite data, all information of the lakes and the area outside the basin is eliminated.

5 Operational snow mapping by satellites 153 outlines and information outside the basins is omitted. The classification of the snow coverage in each picture element is made for each of the basins using the recorded data and the established relation. The result is monitored on a computer screen and can be presented in several ways depending on the needs of the users. A map of the snow coverage in the Tysso basin in the western part of Norway is shown in Fig.3. The image or map on the screen can be copied onto paper at any level of processing. This paper can then be used for presentation to the user or for further analysis. FIG.3 Map of the areal extent of the snow cover in the Tysso basin on 3 June The map was made on 4 June, based on NOAA-6 digital data. Scale 1: The results can also be presented as tables with information on the total snow-covered area in the basin, the snow coverage in different elevation zones, etc. (Andersen & 0degaard, 1980). CONCLUSIONS The method has been tested in three consecutive years. The results indicate that the extent of the snow cover in the mountains can be mapped from NOAA-type digital data in satisfactory detail for hydrological planning and for management of water-power plants. The method is only suitable for basins larger than 200 km when digital processing is performed. When the snow distribution in the basins is included as a parameter in hydrological models for prediction of runoff, the method will give fast and relevant data for updating the snow-cover parameters in the models (Rango & Martinec, 1979). The results can be available within one or two days after the data have been obtained. This is satisfactory for operational use of snowcovered areas in runoff forecasts. The main problem is cloud cover. Clouds appear in the images

6 154 Tom Andersen with the same grey tones as the snow cover. Automatic differentiation is not possible today, but hopefully new sensors will make this problem easier to solve. During the last three years images with satisfactory cloud conditions have been available in the melting period. Without an automatic procedure for checking the cloud cover, strong requirements must apply for images to be processed. Still as few as one or two snow-cover maps during the melting period can give valuable information to hydrologists and water-power engineers. REFERENCES Andersen, T. & 0degaard, H. (1980) Application of satellite data for snow mapping. Norwegian National Committee for Hydrology, Report no. 3. Martinec, J. (19 80) Limitations in hydrological interpretations of the snow coverage. Nordic Hydrol. 11(5), degaard, H. (1974) The application of ERTS imagery to mapping snow cover in Norway. ERTS-1 Contract NASA F-418. Rango, A. (1975) An overview of the applications systems verification test on snowcover mapping. NASA SP-391. Rango, A. & Martinec, J. (1979) Application of a snowmelt-runoff model using Landsat data. Nordic Hydrol. 10(4),