scholarly journals Studying soil erosion by evaluating changes in physico-chemical properties of soils under different land-use types

2021 ◽  
Vol 20 (3) ◽  
pp. 190-197
Author(s):  
Emre Babur ◽  
Ömer Süha Uslu ◽  
Martín Leonardo Battaglia ◽  
Andre Diatta ◽  
Shah Fahad ◽  
...  
Author(s):  
Chahat Verma ◽  
Abhinav Lal ◽  
Alec D. M. David ◽  
P. Smriti Rao

Physico-chemical properties of soils from different land use systems viz. agriculture, olericulture, horticulture etc in Prayagraj (Allahabad) Uttar Pradesh were analyzed in 2018-19. Samples were collected from 4 different sites of Allahabad district viz., ECC gaughat, Jhunsi, Karchhana & Subedarganj having distance between them of at least 4 kms. Some soils samples had higher water holding capacity & value of organic carbon. They have average value of pH and EC as compared to the cultivated soils. Potassium was found to be of low content in soil samples. Physical properties and parameters for all soils were average or medium whereas as variation in chemical properties were observed.


Author(s):  
Debarshi Dasgupta ◽  
G. P. Brahmaprakash

Soil consists of very complex, inter-related community of microorganisms which interact with one another and with plants and animals, forming a complex web of biological activity. The microbes determine health and potential of soil to perform a multitude of ecosystem processes, which depend on the community composition and functioning. The microbial community structure and functions in soil are influenced by physico-chemical properties of soils. Abiotic controls like surrounding climate, environment, land use, nutrients, pH and rhizosphere control the composition of microbes in soil, which in turn modify soil properties. In this review, we investigate the existing body of research exploring studies which have explored how microbes are shaped by soil properties.


2012 ◽  
Vol 16 (8) ◽  
pp. 2739-2748 ◽  
Author(s):  
W. W. Zhao ◽  
B. J. Fu ◽  
L. D. Chen

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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