Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/1077
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBagchi, A.K-
dc.date.accessioned2014-09-22T05:55:17Z-
dc.date.available2014-09-22T05:55:17Z-
dc.date.issued1981-
dc.identifierPh.Den_US
dc.identifier.urihttp://hdl.handle.net/123456789/1077-
dc.guideTiwari, R.S-
dc.description.abstractThe snow that accumulates in the Himalayas is a major hydrologic reservoir and the runoff therefrom is one of the principal sources of water in the Indo-Gangetic plains. In so far as snow hydrology is concerned the following may be said to be typical Himalayan features: (i) extreme elevation range (ii ) general lack of hydrometeorolocfical data (iii) almost total absence of this data at higher altitudes. r The present research was undertaken with the aim of developing a streamflow model which would function in the Himalayan snowfed rivers with limited available data. Beas basin above Manali, covering an area of 344.5 sq km was chosen as the study area. The basin is situated in the western Himalayas and has an extensive snow cover. In winter almost the entire basin is snow covered while by the end of summer about 95% of the basin becomes bare. The elevation range is considerable - from 1900 m to 5932 m. Meteorological and discharge data are recorded at Manali. Landsat imageries were obtained from EROS data centre/ U.S.A.. Due to limited number of usable imageries a method of estimating the snowline altitude in the basin from the altitudes of a neighbouring basin, obtained from the imagery/ has been developed. The streamflow on any day may be expressed as the ordinate of the normal recession curve together with additional discharge due to snowmelt or rain in the basin on that day. Thus the discharge on the (n + 1) day is given by Qn+1 * VS,+ (<Vn + (I >.} Where 0 • discharge K = recession coefficient I = snowmelt input L_ = rain water input n = no. of days The recession coefficient k has been related to the discharge and is given by the equation: Kn - 1.00 - .0008 Qn • (2) For the determination of snowmelt input I the temperature 9 index method has been adopted which gives z_ (Vi = a L L <w±j-*Aj ----<») i = 1 i = 1 j = j' where a = degree-day factor (Trnax)i = maximum temperature on the i day in the j zone A A. = area of j zone (the basin area having been J devided into 20C melevation zones, j = 1 to 2o). In the above equation j• refers to the lowest zone in the snow covered area, the extent of which is obtainable from Landsat imageries and j" the highest zone for which T is max above o-C. The value of (Tniax)±. was determined using the temp erature data at the base station and by assuming a suitable lapse rate. The snowmelt input I during the summer months has been 5 calculated by subtracting recession flow and rain water contri bution from the total runoff. To determine the component of runoff due to rain, two factors need consideration: (i) change of the form of precipitation with altitude (ii) orographic variation of precipitation. The percentage of snow in the total precipitation, x, has been found to be related to the minimum daily temperature by the equation: x =9(3.5 -Tm±n) ----- j -(4) where Tm±n ** ro^i™11"1 daily temperature in °C. For a situation when rainfall is small/ the basin input from rain (I ) is given by. n n 20 d ) * fit ^— -^— Ri loo Z Pil / (ioo-x.)Aa. i = 1 A J J - 1 ----- (5) where P^ = precipitation at Manali (j = 1) on the ith day. A = a factor (averaged over the basin) accounting for orogTraphic increase in precipitation «and evapotranspiration. p has been found by correlation of annual runoff to annual precipitation at Manali. p.- is measured and Z.\ A. is planimetered from nap. i is then calculated from Equation 5. Thereafter value of 'a' has been calculated from Equation 3 and has been found to be 2.1 mm per degree-day. From sequential Landsat imageries it is possible to find out the number of days during which a particular zone j remained under snow. By equating the accumulated snow during the period and the total snowmelt it is possible to find out p . the orographic increase (or decrease) factor relevent to the zone. I- can now be calculated from the following equation: ** •- T^o- 1 fj (10° -V AAJ --•"•(6) j = 1 Having found i_ and I_ the streamflow can be generated s k using Equation 1. From the methodologies decribed above it is possible to calculate depth of standing snow at any altitude and also snow altitude on any day. Snow altitude figures generated from meteorological data can be used to fill the gap between Landsat derived snow altitude data. The streamflows generated with and without the help of Landsat imageries have been compared with the observed discharges; the comparison is satisfactory in both the cases. The estimate of standing snow in the basin at the end of the snow accumulation season has been used to fore cast future snowmelt streamflow with satisfactory result. The study breaks new ground for generation a nd forecasting of snowmelt streamflow with limited data.en_US
dc.language.isoenen_US
dc.subjectCIVIL ENGINEERINGen_US
dc.subjectSNOWMELT RUNOFFen_US
dc.subjectSATELLITE IMAGERIESen_US
dc.subjectHYDROLOGIC RESERVOIRen_US
dc.titleSNOWMELT RUNOFF IN BEAS BASIN USING SATELLITE IMAGERIESen_US
dc.typeDoctoral Thesisen_US
dc.accession.number177787en_US
Appears in Collections:DOCTORAL THESES (Civil Engg)

Files in This Item:
File Description SizeFormat 
SNOWMELT RUNOFF IN BEAS BASIN USING SATELLITE IMAGERIES.pdf18.71 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.