Towards settled cultivation from traditional jhum-A case study in Arunachal Pradesh, India

2016 ◽  
Author(s):  
S. K. Pattanaaik ◽  
B. N. Hazarika ◽  
A. K. Pandey ◽  
P. Debnath
Keyword(s):  
Soil Erosion ◽  
Finger Millet ◽  
Upland Rice ◽  
Arunachal Pradesh ◽  
Traditional Practice ◽  
Fallow Period ◽  
Fallow Lands ◽  
Current Scenario ◽  
Second Year

The shifting cultivation in Arunachal Pradesh is dynamic in nature and is known as ‘Jhum’. Upland rice is the main crop grown in mixture with maize, foxtail, finger millet, beans, cassava, yam, banana, sweet potato, ginger, chillies, vegetables, etc. in such system. The single crop of rice is preferred in the second year and this continues for 2-3 years and then it is left for fertility build up through regeneration of vegetation. The period is known as ‘fallow period’. But this leads to considerable soil erosion due to heavy intense rainfall instead of increasing its fertility. The fallow period has been reduced from 10-20 years to 5-7 years. Fortunately the mindset of the jhumias of East Siang district of Arunachal Pradesh, India has been changed. They cultivate citrus, bamboo and tache (wallichia) trees in these fallow lands, which not only prevent the land from soil erosion, but also give income even from a short fallow period. This is a little shift from the traditional practice towards a sustainable practice adopted by the jhumias. The paper presents the current scenario of settled cultivation from traditional jhum in reference to East Siang district of Arunachal Pradesh.

Social Forestry in Environmentally Degraded Regions of India: Case-study of the Mayurakshi Basin

1995 ◽  
Vol 22 (1) ◽  
pp. 20-30 ◽  
Author(s):  
Nandini Chatterjee
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Forest Products ◽  
River Valley ◽  
Social Forestry ◽  
Fuel Wood

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.

scholarly journals Soil Erosion Caused by Snow Avalanches: a Case Study in the Aosta Valley (NW Italy)

2010 ◽  
Vol 42 (4) ◽  
pp. 412-421 ◽  
Author(s):  
Michele Freppaz ◽  
Danilo Godone ◽  
Gianluca Filippa ◽  
Margherita Maggioni ◽  
Stefano Lunardi ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Snow Avalanches ◽  
Nw Italy

scholarly journals A comparison between soil loss evaluation index and the C-factor of RUSLE: a case study in the Loess Plateau of China

2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Drainage Network ◽  
Land Use Patterns ◽  
Low Area ◽  
Use Patterns ◽  
High Area ◽  
Land Use Types

Abstract. Land use and land cover are most important in quantifying soil erosion. Based on the C-factor of the popular soil erosion model, Revised Universal Soil Loss Equation (RUSLE) and a scale-pattern-process theory in landscape ecology, we proposed a multi-scale soil loss evaluation index (SL) to evaluate the effects of land use patterns on soil erosion. We examined the advantages and shortcomings of SL for small watershed (SLsw) by comparing to the C-factor used in RUSLE. We used the Yanhe watershed located on China's Loess Plateau as a case study to demonstrate the utilities of SLsw. The SLsw calculation involves the delineations of the drainage network and sub-watershed boundaries, the calculations of soil loss horizontal distance index, the soil loss vertical distance index, slope steepness, rainfall-runoff erosivity, soil erodibility, and cover and management practice. We used several extensions within the geographic information system (GIS), and AVSWAT2000 hydrological model to derive all the required GIS layers. We compared the SLsw with the C-factor to identify spatial patterns to understand the causes for the differences. The SLsw values for the Yanhe watershed are in the range of 0.15 to 0.45, and there are 593 sub-watersheds with SLsw values that are lower than the C-factor values (LOW) and 227 sub-watersheds with SLsw values higher than the C-factor values (HIGH). The HIGH area have greater rainfall-runoff erosivity than LOW area for all land use types. The cultivated land is located on the steeper slope or is closer to the drainage network in the horizontal direction in HIGH area in comparison to LOW area. The results imply that SLsw can be used to identify the effect of land use distribution on soil loss, whereas the C-factor has less power to do it. Both HIGH and LOW areas have similar soil erodibility values for all land use types. The average vertical distances of forest land and sparse forest land to the drainage network are shorter in LOW area than that in HIGH area. Other land use types have shorter average vertical distances in HIGH area than that LOW area. SLsw has advantages over C-factor in its ability to specify the subwatersheds that require the land use patterns optimization by adjusting the locations of land uses to minimize soil loss.

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