Assessment of Temperature Lapse Rate and Its Integration with Hydrological Modeling using AWS and MODIS data over the Uttarakhand Region

Abstract ID: 3.11775 | Accepted as Poster | Poster | TBA | TBA

Priyanka Negi (0)
Goswami, Ajanta (1), Joshi, Girish Chandra (2)
Priyanka Negi (1)
Goswami, Ajanta (1), Joshi, Girish Chandra (2)

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(1) Indian Institute of Technology Roorkee, Department of Earth Sciences
(2) Vice President, BLLT, A Brand of Retrota Technology (P) Ltd.,, Dehradun, Uttarakhand

(1) Indian Institute of Technology Roorkee, Department of Earth Sciences
(2) Vice President, BLLT, A Brand of Retrota Technology (P) Ltd.,, Dehradun, Uttarakhand

Categories: Cryo- & Hydrosphere, Remote Sensing
Keywords: Rainfall-Runoff, TLR, SPHY, Hydrological model

Categories: Cryo- & Hydrosphere, Remote Sensing
Keywords: Rainfall-Runoff, TLR, SPHY, Hydrological model

Temperature lapse Rate (TLR) is regarded as the most critical parameter in the hydrological and climatological models. The lapse rate influences whether precipitation falls as rain or snow, which has important implications for water storage and runoff. To show the variation in total runoff components over the Uttarakhand major basins due to the increasing surface temperature, we perform an approach by utilizing the MODIS-LST data and the observed station data. To understand the percentage of Rainfall Runoff and Glacier Runoff, a grid-based, fully distributed hydrologic model, Spatial Process in Hydrology (SPHY), is employed to analyze runoff partitioning in the Alaknanda and Mandakini Basins. SPHY integrates air temperature, precipitation indices, soil properties, and land use/land cover data to quantify runoff components-rainfall, snowmelt, glacier melt, and base flow. Two outlet locations within the basins are marked to assess spatial variations in runoff contributions. This study provides insights into the hydrological response of high-altitude basins to rising temperatures, aiding in water resource management and climate adaptation strategies.

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