RAJIV SINHA

Prof. RAJIV SINHA

Department of Earth Sciences,Indian Institute of Technology Kanpur,Kanpur, 208016 (UP). INDIA
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Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2008 in Journal of the Indian Society of Remote Sensing
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Journal Article
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RSRAJIV SINHA
RAJIV SINHA
GBG. V. Bapalu
G. V. Bapalu
LSL. K. Singh
L. K. Singh
BRB. Rath
B. Rath

1 April 2018 in Journal of Hydrology
Verified
Journal Article
Open access
SJSuneel Kumar Joshi
Suneel Kumar Joshi
SRShive Prakash Rai
Shive Prakash Rai
RSRAJIV SINHA
RAJIV SINHA
SGSanjeev Gupta
Sanjeev Gupta
ADAlexander Logan Densmore
Alexander Logan Densmore
SSShashank Shekhar
Shashank Shekhar

9 June 2011 in Natural Hazards
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Journal Article
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KGKumar Gaurav
Kumar Gaurav
RSRAJIV SINHA
RAJIV SINHA
PPP. K. Panda
P. K. Panda

1 March 2019 in Journal of Hydrology
Verified
Journal Article
Open access
RSRAJIV SINHA
RAJIV SINHA
AGAlok Gupta
Alok Gupta
KMKanchan Mishra
Kanchan Mishra
STShivam Tripathi
Shivam Tripathi
SNSantosh Nepal
Santosh Nepal
SSSomil Swarnkar
Somil Swarnkar

24 April 2018 in Hydrology and Earth System Sciences
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Journal Article
Open access
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SSSomil Swarnkar
Somil Swarnkar
AMAnshu Malini
Anshu Malini
STShivam Tripathi
Shivam Tripathi
RSRAJIV SINHA
RAJIV SINHA
High soil erosion and excessive sediment load are serious problems in several Himalayan river basins. To apply mitigation procedures, precise estimation of soil erosion and sediment yield with associated uncertainties are needed. Here, the revised universal soil loss equation (RUSLE) and the sediment delivery ratio (SDR) equations are used to estimate the spatial pattern of soil erosion (SE) and sediment yield (SY) in the Garra River basin, a small Himalayan tributary of the River Ganga. A methodology is proposed for quantifying and propagating uncertainties in SE, SDR and SY estimates. Expressions for uncertainty propagation are derived by first-order uncertainty analysis, making the method viable even for large river basins. The methodology is applied to investigate the relative importance of different RUSLE factors in estimating the magnitude and uncertainties in SE over two distinct morphoclimatic regimes of the Garra River basin, namely the upper mountainous region and the lower alluvial plains. Our results suggest that average SE in the basin is very high (23 ± 4.7 t ha−1 yr−1) with higher values in the upper mountainous region (92 ± 15.2 t ha−1 yr−1) compared to the lower alluvial plains (19.3 ± 4 t ha−1 yr−1). Furthermore, the topographic steepness (LS) and crop practice (CP) factors exhibit higher uncertainties than other RUSLE factors. The annual average SY is estimated at two locations in the basin – Nanak Sagar Dam (NSD) for the period 1962–2008 and Husepur gauging station (HGS) for 1987–2002. The SY at NSD and HGS are estimated to be 6.9 ± 1.2 × 105 t yr−1 and 6.7 ± 1.4 × 106 t yr−1, respectively, and the estimated 90 % interval contains the observed values of 6.4 × 105 t yr−1 and 7.2 × 106 t yr−1, respectively. The study demonstrated the usefulness of the proposed methodology for quantifying uncertainty in SE and SY estimates at ungauged basins.