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Water Resources
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Estimation of basin Snow water equivalent (SWE) using accumulation and depletion patterns of Snowcover from optical satellite Data
P. Reuben Paul1, Ch. L. V. Ramana roa1, E. Siva Sankar 1
1 Engineers, Water Resources Group,
National Remote Sensing Agency
Dept. of Space, Hyderabad 500037
Abstract
Basin Snow Water Equivalent (SWE) which is an indicator of the amount of water stored in the snowpack, is one of the most important variables in forecasting snowmelt runoffs. However , no direct measurements of snow water equivalent are made in most of the Himalayan basins due to various reasons. Very often only snowfall measurements at a few unrepresentative snow gauges located in valleys are the only data available. Indices for SWE can still be derived from the snowfall and temperature data dnd used in snowmelt runoff modelling as in the case of Sutlej basin. However, this grund measured snowfall and temperature data are not available at the time of forecasting snowmelt rumoffs due to inaccessibility of the terrain.
A method to estimate basin SWE Index has been developed using Accumulation and Depletion Paterns data. These estimates are being use in operational forecasting of 3 month (Apr-May_Jun) snomelt runoffs at Bhakra dam on Sutlej river. This method is based on the fact that a thick snowpack starts depleting late and depletes slower compared to a thin snowpack which starts depletin early and also depletes faster. The accumulation and depletion curves which are constructed by using areal extent of snowcover on different dates spread over the entire snowmelt season reveal this information on the SWE. The set of curves for the past many years are analysed and the SCA as on 1st April, rate of depletion (slope of the curve) and an index of the onset of the depletion (indicating early, normal or late setting-in of the depletion) is related to snow water Equivalent Index computed from ground measured snowfall at 20 stations in the Sutlej basin.
In any forecast year, by monitoring snow cover during late accumulation and early depletion period and by using the above relationship, the basin SWE Index can be estimated and used for forecasting snowmelt runoff. The results of the simulations are presented and discussed.
Engineers, Water Resources Group, National Remote Sensing Agency, Dept. of Space, Hyderabad 5000 037.
1.0 Introduction:
Snowmelt runoff modelling and forecasting in mountainous basins requires a lot of information of the snowpack, meteorology, hydrology, and terrain Very often, such information is not available in the large data sparse basin of the Himalayas. Remote sensing remains the most important means of obtaining some information on the snowpack. One of the most easily obtainable information which is used in runoff modelling is the Snow Covered Area, and can be very efficiently mapped and monitored using various spatial, spectral and temporal rssolution satellite data depending on the size of the basin and the availability of such data.
In the model developed for Sutlej basin to forecast long-term (3 month) summer inflows into the Bahakra reservoir, Snow Covered Area (SCA), an Index of the volume of water stored in the snowpack (Snow water Equivalent Index) and an Index of the Energy input to the Snowpack (Accumulated Degree Days Index) have been used.
A new method of estimating the Index of the volume of water stored in the snowwpack (SWE Index) using accumulation and depletion patterns of snow cover derived from optical remote sensing data has been developed and is being used in operational long-term snowmelt runoff forecasts in the Sutlej basin.
2.0 Description of The Basin:
The Sutlej river which originates near the Manasarovar lake in Tibet, cuts across the Himalayas and flows into India. The basin upto the Bhakra Dam is about 50,000sq. Kms in extent and is highly heterogenous in terms of climatology, terrain, snow acumulation and land cover The Tibetian portion of the basin is arid with less amount of precipitation, Whereas, the Spiti and other portions of the basin receive considerable amount of precipitation. It is interesting to note that above a certain contour there is absolutely no rainfall even during the south West monsoon. In addition, the Tibetian portion of the basin to a large extent, is relatively very flat, thereby draatically affecting the snow covered areas even with small amounts of snow percipitation.
3.0 Snow Water Equivalent and Its Significance:
Snow water Equivalent (SWE) at any point in the basin is expressed as standing column of water resulting from the melting of a snow sample of a unit cross section and height equal to the depth of the snowpack at the point of measurement. Conventionally, SWE measurements. At a number of points in the basin are made in order to get an overall idea of the water contained in the snowpack in the basin on any particular day. Usually these measurements are made by snowpit method or using instruments like Snow pillows etc. In the case of Sutlej basin -as is the case in most of the Himalayan basins - no regular snow surveys are conducted for in - situ measurements of SWE, However, the Bhakra Beas Management Board (BBMB) has established about 21 snow gauges in the Indian portion of the basin to measure daily snowfall (1)
Therefore, this valuable ground data on daily snowfall in Sutlej basin, is being used to compute an Index of the Water Equivalent of the entire basin (SWE Iindex) by cumulating the Snowfall at all the 21 snow guages over the ntire accumulation season after certain corrections are made (2,3) Even though these stations are distributed only in the Indian portion of the basin and are also located at relatively low elevations. The SWE Index computed from these measurements still explains considerable amount of yearly variability of snow accumulation as is seen in the relationshi with the Apre -May-Jun discharges (fig. 1)
Figure 1 SWE index computed from daily snowfall data Vs. 3-month (April-May-June) discharges showing a significant correlation.
This Index computed from ground data is used for snowmelt runoff model simulations and validation. However, the ground measured snowfall is not received from the field till about the middle of May, due to inaccesssibility of terrain, Therefore , computing the bdex of SWE from ground data in not possible when the initial Forecast of snowmelt runoffs is given in the 1st week of April every Year.
The new method accummulation and depletion period using remote sensing is based on the premises that a thin snowpack ( low SWE ) starts depleting early and also depleting faster compared toa thick snowpack ( high SWE ) which starts depleting late and also depletes slower ( Fig. 2)
Figure 2 The hypothetical relationship between SWE Index and the depletion of snow cover.
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