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Chaitanya B. Pande
Researcher at Sant Gadge Baba Amravati University
Publications - 74
Citations - 1450
Chaitanya B. Pande is an academic researcher from Sant Gadge Baba Amravati University. The author has contributed to research in topics: Environmental science & Groundwater. The author has an hindex of 14, co-authored 45 publications receiving 569 citations. Previous affiliations of Chaitanya B. Pande include Shivaji College, Karwar & Dr. Panjabrao Deshmukh Krishi Vidyapeeth.
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GIS based quantitative morphometric analysis and its consequences: a case study from Shanur River Basin, Maharashtra India
TL;DR: In this paper, a morphometric analysis of Shanur basin has been carried out using geoprocessing techniques in GIS and it revealed that the terrain exhibits dendritic to sub-dendritic drainage pattern.
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Ground water flow modeling for calibrating steady state using MODFLOW software: a case study of Mahesh River basin, India
TL;DR: In this paper, the authors presented the results of a mathematical groundwater model developed for the Mahesh River basin in the Akola and Buldhana districts, employing conceptual groundwater modelling approach.
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Assessment of groundwater potential zonation of Mahesh River basin Akola and Buldhana districts, Maharashtra, India using remote sensing and GIS techniques
TL;DR: In this article, the identification of suitable groundwater potential zonation was prepared using remote sensing and GIS techniques using satellite images using Arc GIS software, which can be used for soil and water conservation project, watershed development programs and groundwater resources management in basaltic hard rock terrain.
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An integrated approach to delineate the groundwater potential zones in Devdari watershed area of Akola district, Maharashtra, Central India
TL;DR: In this article, the authors accentuated the hydrogeological evaluation for Devdari watershed of Maharashtra, Central India, using remote sensing, GIS, and multi influencing factor (MIF).
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Study of land use classification in an arid region using multispectral satellite images
TL;DR: In this paper, the authors investigated land use variations in the arid region with the help of multi-temporal images and employed image classification tools in ArcGIS software to create land cover variation maps and land use forecast maps.