A new RUSLE slope length factor and its application to soil erosion assessment in a Loess Plateau watershed

2018 ◽  
Vol 182 ◽  
pp. 10-24 ◽  
Author(s):  
Wei Qin ◽  
Qiankun Guo ◽  
Wenhong Cao ◽  
Zhe Yin ◽  
Qinghong Yan ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Loess Plateau ◽  
Slope Length ◽  
Slope Length Factor ◽  
Soil Erosion Assessment

scholarly journals Assessment of Soil Erosion by RUSLE Model using Remote Sensing and GIS of Indla-Ghatkhed, District-Amravati, Maharashtra

2021 ◽  
pp. 247-253
Author(s):  
N. W. Ingole ◽  
S. S. Vinchurkar
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Crop Cover ◽  
Conservation Practice ◽  
Slope Length Factor ◽  
Pixel Value ◽  
Factor C ◽  
Soil Erosion Assessment

The catchment boundary of Indla Ghatkhed watershed covers an area about 14..62 sq km. The erosion is a natural geomorphic process occurring continually over the earth’s surface and it largely depends on topography, vegetation, soil and climatic variables and, therefore, exhibits pronounced spatial variability due to catchments heterogeneity and climatic variation. This problem can be circumvented by discrediting the catchments into approximately homogeneous sub-areas using Geographic Information System (GIS). Soil erosion assessment modeling was carried out based on the Revised Universal Soil Loss Equation (RUSLE). A set of factors are involved in RUSLE equation are A = Average annual soil loss (mt/ha/year), R = Rainfall erosivity factor (mt/ha/year), k = Soil erodibility factor, LS = Slope length factor, C = Crop cover management factor, P = Supporting conservation practice factor. These factors extracted from different surface features by analysis and brought in to raster format. The output depicts the amount of sediment rate from a particular grid in spatial domain and the pixel value of the outlet grid indicates the sediment yield at the outlet of the watershed.

MODELS TO PREDICT SLOPE LENGTH FROM OTHER WATERSHED ATTRIBUTES

2020 ◽  
Vol 51 (4) ◽  
pp. 1025-1037
Author(s):  
Mohammed & Karim
Keyword(s):  
Soil Erosion ◽  
Drainage Density ◽  
Slope Gradient ◽  
Bifurcation Ratio ◽  
Slope Length ◽  
Objective Standard ◽  
Slope Length Factor ◽  
Watershed Slope ◽  
Soil Erosion By Water ◽  
Least Squares Techniques

Soil erosion by water is an extensive and increasing problem worldwide. Albeit, this problem has been recognized as a significant hazard in Iraq, yet the number of studies on this topic is very limited. Most of the models used for estimating soil erosion contain parameters for slope length factor (LS). A major constraint is the difficulty in extracting the LS factor. Accordingly, the current study was initiated with the main objective of deriving models to predict the slope length from relatively easy to measure basin characteristics with a reasonable accuracy. To achieve the above objective, standard methodologies were employed to describe 30 main basins with the upper part of Iraq in terms linear, areal and relief morphometric parameters. The majority of the delineated watersheds were characterized by having high slope lengths indicating lower drainage density and higher erosion rate. Linear and non-linear least squares techniques were applied to predict the slope length from other basin characteristics. Different indicators were used to test the performance of the proposed models and the approach was validated using K-fold procedure at independent basins. The results indicated that the 4-parameter regression model outperformed the remaining models of watershed slope length. The regressors of this model are bifurcation ratio, perimeter, and basin length and slope gradient.

scholarly journals Soil Erosion and Controls in the Slope-Gully System of the Loess Plateau of China: A Review

2021 ◽  
Vol 9 ◽  
Author(s):  
Bingbing Zhu ◽  
Zhengchao Zhou ◽  
Zhanbin Li
Keyword(s):  
Soil Erosion ◽  
Loess Plateau ◽  
Overland Flow ◽  
Vegetation Pattern ◽  
Sediment Source ◽  
The Loess Plateau ◽  
Erosion Process ◽  
Slope Length ◽  
Base Level ◽  
Erosion Processes

The Loess Plateau has long been suffering from serious soil erosion of which erosion from the slope-gully system is now dominant. The slope-gully system is characterized with distinctive erosion distribution zones consisting of inner and inter gully areas wherein erosion patterns spatially vary, acting as both sediment source and the dominant sediment and water transport mechanism. In this paper, a substantial body of research is reviewed concentrating on the soil erosion processes and control practices in the slope-gully system. The inner gully area is identified as the main sediment source while runoff and sediment from the inter-gully upland is found to significantly affect down slope erosion processes. Correspondingly, the protective vegetation pattern and coverage should be strategically designed for different erosion zones with an emphasis on the critical vegetation cover and pattern to reduce sediment yield of the whole slope-gully system. Check-dam could change the base level of erosion and reduce the slope length of the gully side, which will further decrease the possibility and magnitude of gravity erosion. We concluded that understanding the erosion processes and implementing erosion practices for the slope-gully system are of importance and require more research efforts that emphasize: 1) the influence of upland runoff on erosion processes at downslope; 2) the relationship between hydraulic characteristics of overland flow and erosion process at a slope-gully system scale; 3) physical mechanisms of different vegetation patterns on the slope-gully erosion process.

Predicting Soil erosion based on the machine learning in Loess Plateau of China 

2021 ◽  
Author(s):  
Chenlu Huang ◽  
Qinke Yang
Keyword(s):  
Machine Learning ◽  
Soil Erosion ◽  
Loess Plateau ◽  
Evaluation Method ◽  
Interpolation Method ◽  
Dynamic Change ◽  
Control Factor ◽  
Change Analysis ◽  
Slope Length ◽  
Entire Study

<p>Soil erosion is one of the global ecological and environmental problems, which is an important factor leading to land degradation. To scientifically and effectively control soil erosion, it’s necessary to improve soil erosion evaluation methods that can obtain the actual rates of soil erosion, rather than potential erosion. For this, about 300 sampling units deployed in the Loess Plateau used as the basic data in our study, combining the seven soil erosion factors (rainfall-runoff erosivity factor, soil erodibility factor, slope length and steepness factor, biological-control factor, engineering-control factor, tillage practices factor) involved in the CSLE model and 50 soil erosion covariates related to climate, soil, topography, vegetation, human activities, etc. Using machine learning methods to establish an optimal model, and spatially predict the soil erosion rate and make a soil erosion mapof the entire study area. The prediction results show that the explanation degree of the random forest spatial prediction model is 73%. Among the selected optimal characteristic parameters, terrain and vegetation-related variables are the most important factors affecting soil erosion, from high to low, the order is LS > B > NDVI (May to September). Compared to previous studies with USLE/RUSLE/CSLE and GIS integrated mapping methods, or sampling survey based interpolation method, improvements in this paper can be concluded to : (1) the use of machine learning instead of simple multiply by soil erosion factors (linear regression), (2) higher resolution interpretation results supported by the project of “Pan-Third Pole Project”, which provide soil erosion that closed to the actual rates of soil erosion. (3) considerate additional related covariates such as population density, precipitation, soil conservation measures and so on. Further development of soil erosion prediction could provide a more accurate soil erosion evaluation method. This method can not only monitor and evaluate soil erosion in real time, and provide the possibility for the dynamic change analysis? of soil erosion in the future, but also help decision makers take effective measures in the process of mitigating soil erosion risk.</p>

scholarly journals Computing slope length (USLE): return to original definitions.

2021 ◽  
Author(s):  
Antonio Saa-Requejo ◽  
Pablo Sevilla ◽  
Ana María Tarquis ◽  
Anne Gobin
Keyword(s):  
Soil Erosion ◽  
Horizontal Resolution ◽  
Department Of Agriculture ◽  
Slope Length ◽  
Erosion Risk ◽  
Slope Length Factor ◽  
Erosion Models ◽  
Original Field ◽  
Field Perspective ◽  
Soil Erosion By Water

<p>Soil erosion is an important process of consideration in different erosion risk models and in planning soil conservation. Common erosion models, such as the USLE and its derivatives are widely used. In this context, the slope length is the variable with the most difficulties due to the different scales and procedures available that lead to very different results. Furthermore, many of the calculation procedures are based on a hydrological network definition that poses many problems in areas with a complex topography.</p><p>We propose an algorithm implemented in GIS, returning to the original field perspective form defined by the USLE and RUSLE, which is detached from the hydrological network definition. The calculation procedure is based on 5 m DEM and defines overland water flow at the field scale.</p><p>This method has been applied in three areas with different climate and geomorphology. The results are similar to those derived from aerial photograph observation.</p><p><strong>References</strong></p><p>Honghu Liu, Jens Kiesel, Georg Hörmann, Nicola Fohrer. (2011). Effects of DEM horizontal resolution and methods on calculating the slope length factor in gently rolling landscapes. Catena, 87, 368–375</p><p>Renard, K.G., Foster, G.R., Weesies, G.A., Mc. Cool, D.K y Yoder, D.C. (1997). Predicting Soil Erosion by Water: A Guide To Conservation Planning With The Revised Universal Soil Los Equation. Agricultural Handbook 703. USA: US Department of Agriculture.</p><p><strong>Acknowledgements</strong></p><p>Authors are grateful to Authors are grateful to Agroseguro funding this research.</p>

scholarly journals Regional soil erosion assessment based on a sample survey and geostatistics

2018 ◽  
Vol 22 (3) ◽  
pp. 1695-1712 ◽  
Author(s):  
Shuiqing Yin ◽  
Zhengyuan Zhu ◽  
Li Wang ◽  
Baoyuan Liu ◽  
Yun Xie ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Sample Survey ◽  
Shaanxi Province ◽  
Rainfall Erosivity ◽  
Soil Erodibility ◽  
Slope Length ◽  
Slope Steepness ◽  
Soil Erosion Assessment

Abstract. Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data worsened the estimation when used as the covariates for the interpolation of soil loss. Due to the unavailability of a 1 : 10 000 topography map for the entire area in this study, the model assisted by the land use, R, and K factors, with a resolution of 250 m, was used to generate the regional assessment of the soil erosion for Shaanxi Province. It demonstrated that 54.3 % of total land in Shaanxi Province had annual soil loss equal to or greater than 5 t ha−1 yr−1. High (20–40 t ha−1 yr−1), severe (40–80 t ha−1 yr−1), and extreme (> 80 t ha−1 yr−1) erosion occupied 14.0 % of the total land. The dry land and irrigated land, forest, shrubland, and grassland in Shaanxi Province had mean soil loss rates of 21.77, 3.51, 10.00, and 7.27 t ha−1 yr−1, respectively. Annual soil loss was about 207.3 Mt in Shaanxi Province, with 68.9 % of soil loss originating from the farmlands and grasslands in Yan'an and Yulin districts in the northern Loess Plateau region and Ankang and Hanzhong districts in the southern Qingba mountainous region. This methodology provides a more accurate regional soil erosion assessment and can help policymakers to take effective measures to mediate soil erosion risks.

scholarly journals Effects of Vegetation Restoration on Soil Erosion on the Loess Plateau: A Case Study in the Ansai Watershed

2021 ◽  
Vol 18 (12) ◽  
pp. 6266
Author(s):  
Hui Wei ◽  
Wenwu Zhao ◽  
Han Wang
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Loess Plateau ◽  
Water Conservation ◽  
Large Scale ◽  
Land Use Changes ◽  
Vegetation Restoration ◽  
The Loess Plateau ◽  
Local Soil ◽  
Erosion Environment

Large-scale vegetation restoration greatly changed the soil erosion environment in the Loess Plateau since the implementation of the “Grain for Green Project” (GGP) in 1999. Evaluating the effects of vegetation restoration on soil erosion is significant to local soil and water conservation and vegetation construction. Taking the Ansai Watershed as the case area, this study calculated the soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration, using the Chinese Soil Loess Equation (CSLE), based on rainfall and soil data, remote sensing images and socio-economic data. The effect of vegetation restoration on soil erosion was evaluated by comparing the average annual soil erosion modulus under two scenarios among 16 years. The results showed: (1) vegetation restoration significantly changed the local land use, characterized by the conversion of farmland to grassland, arboreal land, and shrub land. From 2000 to 2015, the area of arboreal land, shrub land, and grassland increased from 19.46 km2, 19.43 km2, and 719.49 km2 to 99.26 km2, 75.97 km2, and 1084.24 km2; while the farmland area decreased from 547.90 km2 to 34.35 km2; (2) the average annual soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration was 114.44 t/(hm²·a) and 78.42 t/(hm²·a), respectively, with an average annual reduction of 4.81 × 106 t of soil erosion amount thanks to the vegetation restoration; (3) the dominant soil erosion intensity changed from “severe and light erosion” to “moderate and light erosion”, vegetation restoration greatly improved the soil erosion environment in the study area; (4) areas with increased erosion and decreased erosion were alternately distributed, accounting for 48% and 52% of the total land area, and mainly distributed in the northwest and southeast of the watershed, respectively. Irrational land use changes in local areas (such as the conversion of farmland and grassland into construction land, etc.) and the ineffective implementation of vegetation restoration are the main reasons leading to the existence of areas with increased erosion.

scholarly journals Comparing High Accuracy t-LiDAR and UAV-SfM Derived Point Clouds for Geomorphological Change Detection

2021 ◽  
Vol 10 (6) ◽  
pp. 367
Author(s):  
Simoni Alexiou ◽  
Georgios Deligiannakis ◽  
Aggelos Pallikarakis ◽  
Ioannis Papanikolaou ◽  
Emmanouil Psomiadis ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Change Detection ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Mean Value ◽  
Detection Methods ◽  
Mountainous Catchments ◽  
Aerial Vehicle ◽  
Soil Erosion Assessment

Analysis of two small semi-mountainous catchments in central Evia island, Greece, highlights the advantages of Unmanned Aerial Vehicle (UAV) and Terrestrial Laser Scanning (TLS) based change detection methods. We use point clouds derived by both methods in two sites (S1 & S2), to analyse the effects of a recent wildfire on soil erosion. Results indicate that topsoil’s movements in the order of a few centimetres, occurring within a few months, can be estimated. Erosion at S2 is precisely delineated by both methods, yielding a mean value of 1.5 cm within four months. At S1, UAV-derived point clouds’ comparison quantifies annual soil erosion more accurately, showing a maximum annual erosion rate of 48 cm. UAV-derived point clouds appear to be more accurate for channel erosion display and measurement, while the slope wash is more precisely estimated using TLS. Analysis of Point Cloud time series is a reliable and fast process for soil erosion assessment, especially in rapidly changing environments with difficult access for direct measurement methods. This study will contribute to proper georesource management by defining the best-suited methodology for soil erosion assessment after a wildfire in Mediterranean environments.

scholarly journals The application of137Cs and210Pbexmethods in soil erosion research of Titel loess plateau, Vojvodina, Northern Serbia

2020 ◽  
Vol 12 (1) ◽  
pp. 11-24
Author(s):  
Kristina S. Kalkan ◽  
Sofija Forkapić ◽  
Slobodan B. Marković ◽  
Kristina Bikit ◽  
Milivoj B. Gavrilov ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Loess Plateau ◽  
Alternative Methods ◽  
Delivery Ratio ◽  
Undisturbed Soil ◽  
Migration Model ◽  
Erosion Rates ◽  
Soil Erosion Rates ◽  
Profile Distribution ◽  
And Migration

AbstractSoil erosion is one of the largest global problems of environmental protection and sustainable development, causing serious land degradation and environmental deterioration. The need for fast and accurate soil rate assessment of erosion and deposition favors the application of alternative methods based on the radionuclide measurement technique contrary to long-term conventional methods. In this paper, we used gamma spectrometry measurements of 137Cs and unsupported 210Pbex in order to quantify the erosion on the Titel Loess Plateau near the Tisa (Tisza) River in the Vojvodina province of Serbia. Along the slope of the study area and in the immediate vicinity eight representative soil depth profiles were taken and the radioactivity content in 1 cm thick soil layers was analyzed. Soil erosion rates were estimated according to the profile distribution model and the diffusion and migration model for undisturbed soil. The net soil erosion rates, estimated by 137Cs method range from −2.3 t ha−1 yr−1 to −2.7 t ha−1 yr−1, related to the used conversion model which is comparable to published results of similar studies of soil erosion in the region. Vertical distribution of natural radionuclides in soil profiles was also discussed and compared with the profile distribution of unsupported 210Pbex measurements. The use of diffusion and migration model to convert the results of 210Pbex activities to soil redistribution rates indicates a slightly higher net erosion of −3.7 t ha−1 yr−1 with 98% of the sediment delivery ratio.

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