Drainage morphometric analysis using open access earth observation datasets in a drought-affected part of Bundelkhand, India

In this study, a part of Yamuna and Ken basin was selected for quantitative estimation of morphometric parameters through open access earth observation datasets. Further, spectral indices, namely Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Normalized Differe...

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Bibliographic Details
Published in:Applied geomatics 2018-09, Vol.10 (3), p.173-189
Main Authors: Kumar, Nirmal, Singh, Sudhir Kumar, Pandey, H. K.
Format: Article
Language:English
Subjects:
Area
Boreholes
Datasets
Drainage density
Drought
Droughts
Earth
Earth and Environmental Science
Geographical Information Systems/Cartography
Geography
Geophysics/Geodesy
Groundwater
Groundwater management
India
Lithology
Management
Measurement Science and Instrumentation
Morphometry
Open access
Original Paper
Parameters
Remote Sensing/Photogrammetry
Rivers
Soil
Soil moisture
Stream order
Surveying
Vegetation
Water
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Summary:In this study, a part of Yamuna and Ken basin was selected for quantitative estimation of morphometric parameters through open access earth observation datasets. Further, spectral indices, namely Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI), and Soil Brightness Index (SBI), have been calculated to know the relationship with the morphometric parameters. The area has sub-dendritic to dendritic drainage pattern and designated as fifth order stream and drainage density (0.564 km/km 2 ). The stream order is mainly controlled by physiographic and lithological conditions of the area. Spectral indices have been employed to understand the vegetation, wetness, and soil moisture and soil characteristics in the area. The water retention curves of the area have been developed. The spectral indices and morphometric parameters (Dd) shows highly positive correlation. The result has been validated with the aid of borehole/lithology datasets. These quantitative estimates will help in achieving and developing long-term strategies for combating hydrological drought, meteorological drought, climate-related drought, agricultural drought, water mismanagement-related drought, and affected region for preparation of suitable groundwater management plans.
ISSN:1866-9298
1866-928X
DOI:10.1007/s12518-018-0218-2