Spatial and temporal characteristics of soil erosion in a typical karst basin in southwest China and its response to the landscape pattern of rock desertification

Abstract Soil erosion is a process of migration and redistribution of soil substances in the landscape, which is regulated by topography, vegetation, human activities and their spatial pattern. At the watershed scale, changes in landscape pattern are important factors in determining the degree of soil erosion. Taking Dabang River Basin as the study area, based on the three phases of land use data, remote sensing image data and daily rainfall data from eight stations in the basin in 2010, 2015 and 2020, the rocky desertification factor (D) was introduced into the general soil loss equation RUSLE to calculate the soil erosion in Karst and non-Karst Areas in 2010, 2015 and 2020 respectively. The relationship between landscape pattern and soil erosion was analyzed from two aspects: type level index and landscape level index. The results showed that: 1) From 2010 to 2020, the average soil erosion modulus in The Dabang River Basin decreased first and then increased. The average soil erosion modulus in the non-karst region was about twice that in the karst region, and the average soil erosion modulus in the karst region decreased first and then increased. The mean soil erosion modulus in the non-karst area showed an increasing trend; 2) Under different slope grades, the erosion was mainly slight and mild, and the area of slight erosion was the largest, and the area of very strong and severe erosion increased as the slope increased. the area of strong, very strong and severe erosion increased in the slope zone below 15°, the area of light and moderate erosion decreased, and the area of slight, strong and very strong erosion increased in the slope zone from 15 to 25°, and the area of slight erosion increased in the slope zone above 25° area increased and light, moderate and strong erosion area decreased in the slope zone above 25°; 3) The landscape pattern of the Dadang River Basin changed significantly from 2010 to 2020. At the landscape level, the number of patches increased and the average patch area decreased. At the type level, the area of paddy field, woodland and shrubland decreases and the area of dry land, grassland, construction land and water body increased, and the dominant land type in the watershed changed from woodland to grassland; 4) The amount of soil erosion was positively correlated with patch type area, landscape percentage, maximum patch index and aggregation index, and positively correlated with edge density; 5) There was a linear relationship between soil erosion and Shannon diversity index (SHDI) and Shannon mean index (SHEI) at landscape level. The results can provide reference for land use planning and soil and water conservation measures.

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A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽

10.3390/land10090990 ◽

2021 ◽

Vol 10 (9) ◽

pp. 990

Author(s):

Yongfen Zhang ◽

Nong Wang ◽

Chongjun Tang ◽

Shiqiang Zhang ◽

Yuejun Song ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Landscape Metrics ◽

Landscape Pattern ◽

Sediment Yield ◽

River Basins ◽

Landscape Patterns ◽

Soil Erodibility ◽

Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

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Landscape Pattern Analysis of Land Use in Low Mount Hilly Land of Harbin Eastern Suburb

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.641-642.514 ◽

2014 ◽

Vol 641-642 ◽

pp. 514-518

Author(s):

Hai Hong Song ◽

Yun Feng Tan

Keyword(s):

Land Use ◽

Landscape Pattern ◽

Human Activities ◽

Pattern Analysis ◽

Landscape Index ◽

Patch Type ◽

Landscape Pattern Analysis ◽

Patch Shape ◽

Patch Connectivity ◽

Landscape Patch

This article analyzes the general characteristics and its causes of the landscape pattern of land use, taking the Tuanjie town of DaoWai district in Harbin as an example. Using GIS and Fragstats software to calculate a series of landscape index, the data show that Tuanjie town is given priority to with agriculture landscape, and the landscape patch connectivity is stronger; the overall landscape patch shape is complex, showing the human activities interfere significantly; and each patch type concentration and fragmentation is quite different. Therefore, based on the use of their own advantages, put forward reasonable suggestions to the landscape optimization of Tuanjie town land use.

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Modeling Soil Erosion and Sediment Load for Red River Basin (Vietnam): Impact of Land Use Change and Reservoirs Operation

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) ◽

10.1109/eeeic.2018.8494392 ◽

2018 ◽

Author(s):

Thinh Le Van ◽

Roberto Ranzi ◽

Maria Cristina Rulli

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Use Change ◽

River Basin ◽

Sediment Load ◽

Red River ◽

Red River Basin

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Spatial Estimation of Soil Erosion Using RUSLE Modeling: A case study of Dolakha District, Nepal

10.21203/rs.3.rs-25478/v4 ◽

2020 ◽

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Agricultural Land ◽

Decision Makers ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

The North ◽

Soil Erosion Rate ◽

Severe Erosion

Abstract Background: Soil erosion causes topsoil loss, which decreases fertility in agricultural land. Spatial estimation of soil erosion essential for an agriculture-dependent country like Nepal for developing its control plans. This study evaluated impacts on Dolakha using the Revised Universal Soil Loss Equation (RUSLE) model; analyses the effect of Land Use and Land Cover (LULC) on soil erosion. Results: The soil erosion rate categorized into six classes based on the erosion severity, and 5.01% of the areas found under extreme severe erosion risk (> 80 Mg ha-1yr-1) addressed by decision-makers for reducing its rate and consequences. Followed by 10 % classified between high and severe range from 10 to 80 Mg ha-1yr-1. While 15% and 70% of areas remained in a moderate and low-risk zone, respectively. Result suggests the area of the north-eastern part suffers from a high soil erosion risk due to steep slope. Conclusions: The result produces a spatial distribution of soil erosion over Dolakha, which applied for conservation and management planning processes, at the policy level, by land-use planners and decision-makers.

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Modeling the Impacts of Land Use Changes on Soil Erosion at the River Basin Scale

Journal of the Faculty of Agriculture, Kyushu University ◽

10.5109/27370 ◽

2013 ◽

Vol 58 (2) ◽

pp. 377-387

Author(s):

Yanna Xiong ◽

Guoqiang Wang ◽

Yanguo Teng ◽

Kyoichi Otsuki

Keyword(s):

Land Use ◽

Soil Erosion ◽

River Basin ◽

Land Use Changes ◽

River Basin Scale ◽

Basin Scale

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

10.5194/egusphere-egu21-1524 ◽

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&#8211;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>

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Impact of landscape pattern change on runoff processes in catchment area of the Ulungur River Basin

Water Science & Technology Water Supply ◽

10.2166/ws.2020.027 ◽

2020 ◽

Vol 20 (3) ◽

pp. 1046-1058

Author(s):

Fan Gao ◽

Bing He ◽

Songsong Xue ◽

Yizhen Li

Keyword(s):

Land Use ◽

River Basin ◽

Landscape Pattern ◽

Water Conservation ◽

Catchment Area ◽

Positive Impact ◽

Swat Model ◽

Land Use Types ◽

Monthly Runoff ◽

Better Than

Abstract Based on the Soil and Water Assessment Tool (SWAT) model, the monthly runoff processes of two land-use types in 2000 and 2015 were simulated in this paper. The relationship between runoff and landscape pattern was analyzed, and the spatial correlation between runoff and landscape pattern analyzed using the geographic weighted regression model combined with the change of landscape pattern in the study area from 2000 to 2015. The results show the following. (1) The SWAT model can simulate the monthly runoff processes in the catchment area of the Ulungur River Basin (URB) under different land-use types for 2000 and 2015, but the simulation effect in 2000 was found to be better than that in 2015. (2) From 2000 to 2015, the area of woodland and grassland decreased. Runoff was positively correlated with woodland, grassland, largest patch index, mean patch area (AREA_MN), and contagion index, and negatively correlated with others. This indicates that the landscape fragmentation of URB was aggravated in 2000–2015, the landscape balance was destroyed, and the ability of rainfall interception and water conservation was weakened. (3) Landscape pattern indicators of grassland had a negative spatial impact on URB runoff, and the northern region of URB was more severely affected in 2015 than in 2000. AREA_MN landscape pattern index had a positive impact on runoff in the northern part of URB, and the positive impact in northern URB in 2000 was better than that in 2015.

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Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

Applied and Environmental Soil Science ◽

10.1155/2019/4037379 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 5

Author(s):

D. L. D. Panditharathne ◽

N. S. Abeysingha ◽

K. G. S. Nirmanee ◽

Ananda Mallawatantri

Keyword(s):

Land Use ◽

Sri Lanka ◽

Soil Erosion ◽

River Basin ◽

Soil Loss ◽

Management Practices ◽

Agricultural Land ◽

Universal Soil Loss Equation ◽

Rusle Model ◽

Soil Loss Equation

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

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