• Suresh Kumar

      Articles written in Journal of Earth System Science

    • Geochemical characteristics of Mesoproterozoic metabasite dykes from the Chhotanagpur Gneissic Terrain, eastern India: Implications for their emplacement in a plate margin tectonic environment

      Rajesh K Srivastava Anup K Sinha Suresh Kumar

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      A number of mafic intrusive bodies (mostly dykes) are exposed in the Chhotanagpur Gneissic Terrain (CGT). Most dykes trend in ENE–WSW to E–W following major structural trends of the region. These metabasite dykes show granoblastic to grano-nematoblastic textures and contain hornblende, plagioclase, chlorite, quartz and epidote which suggest their metamorphism under amphibolite grade P–T conditions. Although no radiometric age is available for the metabasite dykes, field relationships with host rock and available geochronology on granitoids suggest their emplacement during Mesoproterozoic. Geochemical characteristics of these dykes classify them as low-K tholeiite to medium-K calcalkaline type. At least two types of metabasite dykes are recognized on the basis of their HFSE contents; one group shows entirely calc-alkaline nature, whereas the other group has rocks of tholeiite-calc-alkaline series. High Mg#observed in a number of samples indicates their derivation from primary melt. Multielement spidergrams and rare-earth element patterns observed in these samples also corroborate their derivation from different magma batches. Trace element patterns observed for Nb–Ta, Hf–Zr, Sr and Y suggesting involvement of subduction related processes in the genesis of CGT metabasite dykes. Perceived geochemical characteristics suggest that metamorphism did not affect much on the chemistry of metabasites but source region, responsible for the generation of CGT metabasites, was possibly modified during subduction process. This study suggests that magma generated in a destructive plate setting fed the Mesoproterozoic mafic dykes of the CGT.

    • Modelling soil erosion risk based on RUSLE-3D using GIS in a Shivalik sub-watershed

      Suresh Kumar S P S Kushwaha

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      The RUSLE-3D (Revised Universal Soil Loss Equation-3D) model was implemented in geographic information system (GIS) for predicting the soil loss and the spatial patterns of soil erosion risk required for soil conservation planning. High resolution remote sensing data (IKONOS and IRS LISS-IV) were used to prepare land use/land cover and soil maps to derive the vegetation cover and the soil erodibility factor whereas Digital Elevation Model (DEM) was used to generate spatial topographic factor. Soil erodibility (K) factor in the sub-watershed ranged from 0.30 to 0.48. The sub-watershed is dominated by natural forest in the hilly landform and agricultural land in the piedmont and alluvial plains. Average soil loss was predicted to be lowest in very dense forest and highest in the open forest in the hilly landform. Agricultural land-1 and agriculture land-2 to have moderately high and low soil erosion risk, respectively. The study predicted that 15% area has ‘moderate’ to ‘moderately high’ and 26% area has high to very high risk of soil erosion in the sub-watershed.

    • Geospatial approach in mapping soil erodibility using CartoDEM – A case study in hilly watershed of Lower Himalayan Range

      Suresh Kumar Surya Gupta

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      Soil erodibility is one of the most important factors used in spatial soil erosion risk assessment. Soil information derived from soil map is used to generate soil erodibility factor map. Soil maps are not available at appropriate scale. In general, soil maps at small scale are used in deriving soil erodibility map that largely generalized spatial variability and it largely ignores the spatial variability since soilmap units are discrete polygons. The present study was attempted to generate soil erodibilty map using terrain indices derived from DTM and surface soil sample data. Soil variability in the hilly landscape is largely controlled by topography represented by DTM. The CartoDEM (30 m) was used to derive terrainindices such as terrain wetness index (TWI), stream power index (SPI), sediment transport index (STI) and slope parameters. A total of 95 surface soil samples were collected to compute soil erodibility factor (K) values. The K values ranged from 0.23 to 0.81 t ha$^{−1}$R$^{−1}$ in the watershed. Correlation analysis among K-factor and terrain parameters showed highest correlation of soil erodibilty with TWI (r$^2 $=0.561) followed by slope (r$^2$ = 0.33). A multiple linear regression model was developed to derive soil erodibilty using terrain parameters. A set of 20 soil sample points were used to assess the accuracy of the model. The coefficient of determination (r2) and RMSE were computed to be 0.76 and 0.07 t ha$^{−1}$R$^{−1}$ respectively. The proposed methodology is quite useful in generating soil erodibilty factor map using digital elevation model (DEM) for any hilly terrain areas. The equation/model need to be established for the particular hilly terrain under the study. The developed model was used to generate spatial soilerodibility factor (K) map of the watershed in the lower Himalayan range.

    • Simulating climate change impact on soil erosion using RUSLE model − A case study in a watershed of mid-Himalayan landscape

      Surya Gupta Suresh Kumar

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      Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011–2040, 2041–2070, and 2071–2099, at large scale. Rainfall erosivity (R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data – IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility (K) factor map of the watershed. Topographic factors, slope length (L) and steepness (S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985–2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.

    • Interaction of dissolution, sorption and biodegradation on transport of BTEX in a saturated groundwater system: Numerical modeling and spatial moment analysis

      Renu Valsala Suresh Kumar Govindarajan

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      Interaction of various physical, chemical and biological transport processes plays an important role in deciding the fate and migration of contaminants in groundwater systems. In this study, a numerical investigation on the interaction of various transport processes of BTEX in a saturated groundwater system is carried out. In addition, the multi-component dissolution from a residual BTEX source under unsteady flow conditions is incorporated in the modeling framework. The model considers Benzene, Toluene, Ethyl Benzene and Xylene dissolving from the residual BTEX source zone to undergo sorption and aerobic biodegradation within the groundwater aquifer. Spatial concentration profiles of dissolved BTEX components under the interaction of various sorption and biodegradation conditions have been studied. Subsequently, a spatial moment analysis is carried out to analyze the effect of interaction of various transport processes on the total dissolved mass and the mobility of dissolved BTEX components. Results from the present numerical study suggest that the interaction of dissolution, sorption andbiodegradation significantly influence the spatial distribution of dissolved BTEX components within the saturated groundwater system. Mobility of dissolved BTEX components is also found to be affected by the interaction of these transport processes.

    • C-equivalent correction factor for soil organic carbon inventory by wet oxidation, dry combustion and loss on ignition methods in Himalayan region

      Suresh Kumar Yogesh Sopan Ghotekar Vinay K Dadhwal

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      Soil organic carbon (SOC) is an important parameter to study the carbon cycle as soil carbon stock inventory as well as to serve as prime indicator in assessing soil health and soil quality. The present study was attempted to investigate C-equivalent correction factor for SOC by Walkley–Black (wet oxidation) and loss on ignition (LOI) methods in relation to TOC analyzer (dry combustion) method. TOC analyzer method supposed to be the best method of total soil organic carbon estimation. Soil sample from 77 sites representing dominant land use/land cover types of crop land, forest and scrub cover were collected in Himalayan region of Uttarakhand state, India. Surface (0–15 cm) and sub-surface (15–30 cm) soil samples were used for estimation of SOC by these three methods. C-equivalent correction factor ranged from 1.10 to 1.17 for SOC determination by Walkley and Black method to TOC analyzer method, whereas it varied from 0.257 to 0.417 for soil organic matter (SOM) by LOI method to TOC analyzer for soils under various land use/land cover types in the Himalayan region. The recovery of SOC by Walkley–Black method varied from 86.84 to 91.04% in the soils of various land use/land cover in the Himalayan landscape. Thus, there is need to develop specific correction factor for soils under various land use/land cover types for improved estimation of soil carbon stock. The regression models developed in the study can be directly used to obtain TOC analyzer equivalent total carbon contents in the soils (surface and sub-surface) for computation of soil carbon stock in Himalayan region.

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