Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/17217
Title: Geomorphological-Empirical Soil Thickness Mapping in the Joshimath Region, India
Authors: Gupta, Kunal
Satyam, Neelima D.
Keywords: Empirical;Modeling;Soil thickness
Issue Date: 2025
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Gupta, K., Satyam, N. D., & Segoni, S. (2025). Geomorphological-Empirical Soil Thickness Mapping in the Joshimath Region, India. In Lecture Notes in Civil Engineering: Vol. 703 LNCE. https://doi.org/10.1007/978-981-96-7787-0_31
Abstract: This study focuses on soil thickness modeling of the Joshimath-Badrinath road section in the Joshimath region of Chamoli district, Uttarakhand, India, a crucial area for local transportation, pilgrimage, and military logistics. The study area, located between longitudes 79.46°E-79.62°E and latitudes 30.53°N-30.82°N, covers 213.43 km2. The terrain is rugged, with slopes ranging from 20 to over 60°, and features diverse vegetation and moderate climatic conditions. The methodology employed integrates soil thickness data from boreholes, a geological map, and a digital elevation model (DEM). Using the GIST model, which incorporates geomorphological and geological factors, soil thickness was modeled. Key factors include hillslope position, surface curvature, and slope gradient, with adjustments made to fit the study area's specific characteristics. Results reveal that the GIST model predicts soil thickness ranging from 0 to 30 m, with a tendency to underestimate mean and maximum values. The model's performance was evaluated against observed data, showing a moderate correlation (R2 = 0.7172), with a root mean square error (RMSE) of 3.4733 m and a mean absolute error (MAE) of 2.6260 m. The model tends to underestimate soil thickness, particularly in extreme values, as indicated by a positive residual skewness (0.6778). While the GIST model offers a reasonable estimate of soil thickness, it tends to fall short in its predictions and sometimes provides unrealistic values. Recognizing these limitations is crucial for refining the model and improving soil thickness assessments in related geotechnical and environmental scenarios. © 2025 Elsevier B.V., All rights reserved.
URI: https://dx.doi.org/10.1007/978-981-96-7787-0_31
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/17217
ISBN: 9789819620951
9789819674879
9789819688333
9789819616053
9783031988929
9783031927539
9783031920431
9789819652051
9789819620333
9789811613029
ISSN: 2366-2565
2366-2557
Type of Material: Conference Paper
Appears in Collections:Department of Civil Engineering

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