scholarly journals Evaluation of Karst Soil Erosion and Nutrient Loss Based on RUSLE Model in Guizhou Province

2018 ◽  
Vol 108 ◽  
pp. 032014 ◽  
Author(s):  
Cheng Zeng ◽  
Yangbing Li ◽  
Xiaoyong Bai ◽  
Guangjie Luo
Keyword(s):  
Soil Erosion ◽  
Nutrient Loss ◽  
Guizhou Province ◽  
Rusle Model ◽  
Karst Soil

scholarly journals Effect of Forest Management Operations on Aggregate-Associated SOC Dynamics Using a 137Cs Tracing Method

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 859
Author(s):  
Geng Guo ◽  
Xiao Li ◽  
Xi Zhu ◽  
Yanyin Xu ◽  
Qiao Dai ◽  
...  
Keyword(s):  
Forest Management ◽  
Soil Erosion ◽  
Management Practices ◽  
Negative Impact ◽  
Dynamic Change ◽  
Aggregate Size ◽  
Nutrient Loss ◽  
Vegetation Coverage ◽  
Forest Conversion ◽  
Mountain Areas

Although forest conversions have long been a focus in carbon (C) research, the relationship between soil erosion and the dynamic change of soil organic carbon (SOC) has not been well-quantified. The objective of this study was to investigate the effects of converting CBF (coniferous and broad-leaved mixed forests) to economic forests, including CF (chestnut forest), HF (hawthorn forest), and AF (apple forest), on the soil structure and nutrient loss in the Huaibei Rocky Mountain Areas, China. A 137Cs tracer method was used to provide soil erosion data in order to quantify the loss of aggregate-associated SOC. The results showed that forest management operations caused macro-aggregates to decrease by 1.69% in CF, 4.52% in AF, and 3.87% in HF. Therefore, the stability of aggregates was reduced. The SOC contents in each aggregate size decreased significantly after forest conversion, with the largest decreases occurring in AF. We quantified the loss of 0.15, 0.38, and 0.31 Mg hm−2 of aggregate-associated SOC after conversion from CBF to CF, AF, and HF, respectively. These results suggest that forest management operations have a negative impact on soil quality and fertility. CF has better vegetation coverage and less human interference, making it more prominent among the three economic forests species. Therefore, when developing forest management operations, judicious selection of tree varieties and appropriate management practices are extremely critical. In addition, measures should be taken to increase surface cover to reduce soil erosion and achieve sustainable development of economic forests.

scholarly journals Explicitly Analyze the Soil Erosion in the Karst and Non-Karst Area of Different Morphological Types in Guizhou of China

2021 ◽  
Author(s):  
Anjun Lan ◽  
Zemeng Fan ◽  
Qingsong Zhao ◽  
Xuyang Bai
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Dynamic Change ◽  
Guizhou Province ◽  
Karst Area ◽  
Intensity Change ◽  
Good Effect ◽  
Analysis Model ◽  
Change Intensity ◽  
Erosion Intensity

Abstract How to explicitly understanding the soil erosion intensity change in different geomorphological types is one of key issues in the field of soil and water conservation. According to classification criterion of soil erosion intensity of China, the spatial soil erosion data with the resolution of 10 m×10m in Guizhou Province were obtained by combing with the multi-resolution remote sensing data of ALOS, ZY-3, GF-1, Landsat and GDEMV2, and 2762 field sampling data in 2010 and 2015, respectively. a spatial analysis model of soil erosion was improved to analyze the spatiotemporal change of soil erosion intensity in karst and non karst area of Guizhou province, which involved the spatial soil erosion data and different geomorphological type data of Guizhou province. The results show that the soil erosion intensity decreased by 6468.13km 2 in Guizhou Province from 2010 to 2015. The dynamic change intensity in the high-altitude area is larger than in the low-altitude area. The soil change intensity in karst area is higher than in non karst area, especially in the high and middle elevation area in Guizhou province. Moreover, the decreasing ratio of soil erosion intensity in karst area is generally larger than in non karst area, which can be used to explain that the ecological restoration projects and water soil conservation polices carried out in karst area has a good effect, especially in western of Guizhou province from 2010 to 2015, one the other hand, the soil erosion in non karst area should also be focused by local government in the future.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

RUSLE Model based Assessment of Soil Erosion in Parbati River Basin, Central India using Google Earth Engine and GIS

2021 ◽  
Author(s):  
Rohit Kumar ◽  
Benidhar Deshmukh ◽  
Kiran Sathunuri
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Pattern ◽  
River Basin ◽  
Soil Loss ◽  
Google Earth ◽  
Rusle Model ◽  
High Soil ◽  
Basin Scale ◽  
Google Earth Engine

<p>Land degradation is a global concern posing significant threat to sustainable development. One of its major aspects is soil erosion, which is recognised as one of the critical geomorphic processes controlling sediment budget and landscape evolution. Natural rate of soil erosion is exacerbated due to anthropogenic activities that may lead to soil infertility. Therefore, assessment of soil erosion at basin scale is needed to understand its spatial pattern so as to effectively plan for soil conservation. This study focuses on Parbati river basin, a major north flowing cratonic river and a tributary of river Chambal to identify erosion prone areas using RUSLE model. Soil erodibility (K), Rainfall erosivity (R), and Topographic (LS) factors were derived from National Bureau of Soil Survey and Land Use Planning, Nagpur (NBSS-LUP) soil maps, India Meteorological Department (IMD) datasets, and SRTM30m DEM, respectively in GIS environment. The crop management (C) and support practice (P) factors were calculated by assigning appropriate values to Land use /land cover (LULC) classes derived by random forest based supervised classification of Sentinel-2 level-1C satellite remote sensing data in Google Earth Engine platform. High and very high soil erosion were observed in NE and NW parts of the basin, respectively, which may be attributed to the presence of barren land, fallow areas and rugged topography. The result reveals that annual rate of soil loss for the Parbati river basin is ~319 tons/ha/yr (with the mean of 1.2 tons/ha/yr). Lowest rate of soil loss (i.e. ~36 tons/ha/yr with mean of 0.22 tons/ha/yr) has been observed in the open forest class whereas highest rate of soil loss (i.e. ~316 tons/ha/yr with mean of 32.08 tons/ha/yr) have been observed in gullied area class. The study indicates that gullied areas are contributing most to the high soil erosion rate in the basin. Further, the rate of soil loss in the gullied areas is much higher than the permissible value of 4.5–11 tons/ha/yr recognized for India. The study helps in understanding spatial pattern of soil loss in the study area and is therefore useful in identifying and prioritising erosion prone areas so as to plan for their conservation.</p>

Prevention of Soil Erosion and Torrential Floods

2022 ◽  
pp. 92-111
Author(s):  
Bhavya Kavitha Dwarapureddi ◽  
Swathi Dash ◽  
Aman Raj ◽  
Nihanth Soury Garika ◽  
Ankit Kumar ◽  
...  
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Soil Erosion ◽  
Erosion Rate ◽  
Land Use Changes ◽  
Climatic Conditions ◽  
Nutrient Loss ◽  
Erosion Processes ◽  
Over Exploitation ◽  
Flood Waves

Climatic conditions, precise relief features, variations of soil, flora cover, socio-economic conditions together lead to torrential flood waves as a result of current soil erosion processes. Erosion and torrential floods are aggravated due to over exploitation of agricultural and forest land along with urbanization. Effects of soil erosion include nutrient loss, land use changes, reduced productivity, siltation of water bodies, among other effects like affecting livelihood of marginal communities dependent on agriculture globally and public health. Nearly 11 million km2 of soil is impacted by erosion precisely by water. Other factors like intensified agriculture and climate change contribute to and aggravate the erosion rate. Contemporary torrential floods are characterized by their increased destruction and frequency unlike the pre-development periods when their occurrence was rare. The focus of this review is to compile and aid as a data base for understanding methods of preventing erosion of soil and torrential floods as put forth by various researchers.

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