Prioritization of sub-watersheds for soil erosion based on morphometric attributes using fuzzy AHP and compound factor in Jainti River basin, Jharkhand, Eastern India

2018 ◽  
Vol 22 (2) ◽  
pp. 1241-1268 ◽  
Author(s):  
Tusar Kanti Hembram ◽  
Sunil Saha
1995 ◽  
Vol 22 (1) ◽  
pp. 20-30 ◽  
Author(s):  
Nandini Chatterjee

Social Forestry (SF) schemes have been implemented in India since the 1980s to combat deforestation, increase the supply of fuel-wood and fodder, and provide minor forest products for the rural populaton. The relevance of such Schemes in the Mayurakshi River Basin is basically due to its environmentally degraded state. Latterly the Basin has been brought under the Mayurakshi River Valley Project, but unless measures are undertaken to mitigate problems of soil erosion, the efficiency of the Project will be hampered.


2021 ◽  
Vol 14 (6) ◽  
Author(s):  
Raj Kumar Bhattacharya ◽  
Nilanjana Das Chatterjee ◽  
Prasenjit Acharya ◽  
Kousik Das

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 39 ◽  
Author(s):  
Lifeng Yuan ◽  
Kenneth J. Forshay

Soil erosion and lake sediment loading are primary concerns of watershed managers around the world. In the Xinjiang River Basin of China, severe soil erosion occurs primarily during monsoon periods, resulting in sediment flow into Poyang Lake and subsequently causing lake water quality deterioration. Here, we identified high-risk soil erosion areas and conditions that drive sediment yield in a watershed system with limited available data to guide localized soil erosion control measures intended to support reduced sediment load into Poyang Lake. We used the Soil and Water Assessment Tool (SWAT) model to simulate monthly and annual sediment yield based on a calibrated SWAT streamflow model, identified where sediment originated, and determined what geographic factors drove the loading within the watershed. We applied monthly and daily streamflow discharge (1985–2009) and monthly suspended sediment load data (1985–2001) to Meigang station to conduct parameter sensitivity analysis, calibration, validation, and uncertainty analysis of the model. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and RMSE -observation’s standard deviation ratio (RSR) values of the monthly sediment load were 0.63, 0.62, 3.8%, and 0.61 during calibration, respectively. Spatially, the annual sediment yield rate ranged from 3 ton ha−1year−1 on riparian lowlands of the Xinjiang main channel to 33 ton ha−1year−1 on mountain highlands, with a basin-wide mean of 19 ton ha−1year−1. The study showed that 99.9% of the total land area suffered soil loss (greater than 5 ton ha−1year−1). More sediment originated from the southern mountain highlands than from the northern mountain highlands of the Xinjiang river channel. These results suggest that specific land use types and geographic conditions can be identified as hotspots of sediment source with relatively scarce data; in this case, orchards, barren lands, and mountain highlands with slopes greater than 25° were the primary sediment source areas. This study developed a reliable, physically-based streamflow model and illustrates critical source areas and conditions that influence sediment yield.


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