Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/15770
Title: STUDY OF SURFACE TEMPERATURE LAPSE RATE IN HIMALAYAN REGION
Authors: Dube, Supriya
Keywords: Temperature Lapse Rate (TLR);Indus-Ganga-Brahmaputra (IGB);Moderate Resolution Imaging Spectrometer (MODIS);Sutlej-Beas
Issue Date: May-2019
Publisher: I I T ROORKEE
Abstract: Study of temperature lapse rate (TLR) is of vital importance for understanding the hydrological process and its relation with climate change. TLR on the account of land surface temperature (LST) and air temperature was determined for Indus-Ganga-Brahmaputra (IGB) river basin. To assess the LST lapse rate, Moderate Resolution Imaging Spectrometer (MODIS) datasets provided LST over the IGB basin. The LST values were plotted for their corresponding elevation for each of the basin and TLR was calculated using linear regression analysis. The LST lapse rate differed from 6.5-7.2º C/Km for the entire basin area. Monthly air temperature was obtained from the IMD and MOSDAC meteorological stations from September 2011 to December 2018 and was correlated with elevation to obtain near-surface air TLRs for selected sub-basin of each of the 3 major basins. The average monthly TLR ranges between 4.6 ºC Km-1 and 8.39 ºC Km-1 from January 2011 to December 2016 for the Alkananda and Bhagirathi sub-basin in Ganga, whereas 4.1 – 8.1ºC Km-1 for the Sutlej-Beas sub-basin in Indus and 4.9 – 6.5 ºC Km-1 for the Teesta river sub-basin in Brahmaputra respectively. This study also includes the air temperature modeling using land surface temperature obtained from Landsat 8 data to analyze the air temperature in the Upper reaches of the Himalaya basin, where the field observations are limited. Multivariate linear regression method is used for the air temperature retrieval through remote sensing. This method is based on the empirical correlation between the air temperature and other variables. The estimated modeled air temperature is validated with the field observation obtained from the AWS data. It was observed that the modeled air temperature shows ± 0.5 º C error with the observation data and the obtained result was well correlated with the station data. The modeled method-based air temperature depends upon the accuracy, size of the study area and the remote sensing image resolution. It is important to determine the change in temperature with elevation to map the climate change and sustainable water resource management.
URI: http://localhost:8081/xmlui/handle/123456789/15770
metadata.dc.type: Other
Appears in Collections:MASTERS' THESES (Earth Sci.)

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