Digital modeling of erosion soil cover patterns development over the last 300 years (Moscow region, Russia)

2020 ◽  
Author(s):  
Daria Fomicheva ◽  
Andrey Zhidkin
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Crop Rotation ◽  
Soil Loss ◽  
Soil Cover ◽  
Field Survey ◽  
Arable Land ◽  
Digital Modeling ◽  
History Of ◽  
Last 300 Years

<p>Digital modeling of soil erosion has been actively developed in recent decades, including for solving practical problems of agriculture. This paper presents a new approach to mapping the degree of erosion of the soil cover based on a detailed retrospective analysis of the history of land use over the last 300 years.</p><p>The study site is located in the Moscow region, characterized by a stage history of plowing. The analysis of the boundaries of arable land was carried out using the digitization of maps for 1797, 1860, 1871, 1931, 1954, 1985, 2000 and 2018 years.</p><p>Erosion processes were simulated using the WATEM / SEDEM. LS factor was calculated based on a digital elevation model based on the digitized detail topographic map. Soil erodibility factor was calculated according to the formula [1] based on our own analytical data on soil properties (K=0.065–0.090 kg*h*MJ<sup>-1</sup>mm<sup>-1</sup>). The rain erosivity factor was taken from the [2]. The crop erosivity factor was taken from regional data, taking into account a detailed analysis of the history of crop rotation.</p><p>Soil erosion was calculated for each of 8 periods. Estimated rates were multiplied by the duration of the periods. The soil loss volumes were summarized using the raster calculator. The authors have database of soil surveys at 1567 points. The obtained estimated long-term volumes of soil loss were correlated with the data of a field survey of soils. Based on the obtained dependencies between the calculated soil loss volumes and the field survey data, a map of the erosion soil cover structures was constructed.</p><p>In the territory, the volume of soil loss varied from 0.02 tons to 1170 tons. The average volume of soil loss over 300 years was about 63.33 tons. It was revealed that the volume of soil loss is determined not only by the area of ​​arable land, but also by the location and topography of the plowed plots and the composition of crop rotation. The most intense erosion was observed in the first decades after the abolition of serfdom law (after 1860).</p><p>Despite the long period of land use, the soil cover of the study area is not very eroded, primarily due to the low erosion potential of the relief. However, the territory is divided into sections, to a different degree, transformed by soil erosion due to plowing of different duration and the composition of crop rotation.</p><p>This work was supported by the Russian Foundation for Basic Research (project for young scientists no. 18-35-20011)</p><p>[1] Renard K., Foster G., Weesies G., McCool D., Yoder D. (1997) Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). USDA Agriculture Handbook â„–703, 384 p.</p><p>[2] Panagos P, Borrelli P, Meusburger K, et al. Global rainfall erosivity assessment based on high-temporal resolution rainfall records. Sci Rep. 2017;7(1):4175.</p>

scholarly journals Modeling the Impact of Climate Change and Land Use Change Scenarios on Soil Erosion at the Minab Dam Watershed

2019 ◽  
Vol 11 (12) ◽  
pp. 3353 ◽  
Author(s):  
Mohammad Reza Azimi Sardari ◽  
Ommolbanin Bazrafshan ◽  
Thomas Panagopoulos ◽  
Elham Rafiei Sardooi
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Land Use Change ◽  
Soil Loss ◽  
Soil Cover ◽  
Future Climate Change ◽  
Future Period ◽  
The Future ◽  
The Impact

Climate and land use change can influence susceptibility to erosion and consequently land degradation. The aim of this study was to investigate in the baseline and a future period, the land use and climate change effects on soil erosion at an important dam watershed occupying a strategic position on the narrow Strait of Hormuz. The future climate change at the study area was inferred using statistical downscaling and validated by the Canadian earth system model (CanESM2). The future land use change was also simulated using the Markov chain and artificial neural network, and the Revised Universal Soil Loss Equation was adopted to estimate soil loss under climate and land use change scenarios. Results show that rainfall erosivity (R factor) will increase under all Representative Concentration Pathway (RCP) scenarios. The highest amount of R was 40.6 MJ mm ha−1 h−1y−1 in 2030 under RPC 2.6. Future land use/land cover showed rangelands turning into agricultural lands, vegetation cover degradation and an increased soil cover among others. The change of C and R factors represented most of the increase of soil erosion and sediment production in the study area during the future period. The highest erosion during the future period was predicted to reach 14.5 t ha−1 y−1, which will generate 5.52 t ha−1 y−1 sediment. The difference between estimated and observed sediment was 1.42 t ha−1 year−1 at the baseline period. Among the soil erosion factors, soil cover (C factor) is the one that watershed managers could influence most in order to reduce soil loss and alleviate the negative effects of climate change.

The joint application of digital modeling and field soil survey data for improvement of the accuracy in soil erosion mapping

2020 ◽  
Author(s):  
Andrey Zhidkin ◽  
Mikhail Komissarov ◽  
Evgeny Zazdravnykh
Keyword(s):  
Soil Erosion ◽  
Agricultural Land ◽  
Soil Cover ◽  
Land Development ◽  
Erosion Rates ◽  
Digital Modeling ◽  
Republic Of Bashkortostan ◽  
Digital Elevation ◽  
History Of ◽  
The Republic

<p>We used the data from field surveys with more than 2500 soil sampling points at 4 research sites in various regions of Russia. The study sites are located in the European part of Russia in the most contrasting physical-geographical and socio-historical conditions of soil erosion: in the Moscow, Kursk, Belgorod regions and in the Republic of Bashkortostan. The digital modeling was carried out with using of the WATEM / SEDEM model based on digital elevation models of detailed scale (1:10 000) on a total area more than 2000 km<sup>2</sup>. An analysis of the sediment balance in small catchments showed, that the digital modeling of soil erosion (in case of a certain quality level of input parameters) at an acceptable level reflects on the average long-term erosion rates in the valley-beam relief. The authors developed an original method in soil erosion mapping. It consists in revealing statistical relationships between the calculated erosion rates by WATEM / SEDEM model and the actual data of soils humus horizons thicknesses. Based on these dependencies, the probability of participation of soils with varying degrees on erosion in each pixel is calculated.</p> <p>The specific in formation of soil erosion at the Moscow region is largely due to the complex stage history of agricultural land development. For this key site, a detailed study of historical maps was carried out (with digitization in the GIS of the sites boundaries with a different land use history) for 8 periods, starting from 1797 to the present. Also, the history of crop rotation was studied in detail. Based on the analysis of maps and digital modeling of erosion-accumulation processes in this territory, a very high dynamics of arable land and soil erosion over the past few centuries was revealed, which significantly influenced on the formation of soil cover. At research sites in the Belgorod and Kursk regions, the features in formation of erosion-accumulative soil cover structures are due to the large area of agricultural land development. The comparison of soil cover erosion maps produced in accordance to the traditional method and the author’s approach is revealed a high convergence of results and the perspective of digital modeling using. The indisputable advantage of the digital method is the ability to formalize the procedure for assessing soil erosion, minimizing the contribution of subjective factors. Detailed studies in the Republic of Bashkortostan revealed the features in the formation of soil erosion  due to the developed denudation processes and karst microrelief. A detailed mapping of the soil cover and topographic mapping of the relief in key areas was carried out. It was revealed, that the using of a digital elevation model with very high accuracy (scale 1: 1000 and higher) allows to qualitatively simulate and estimate the rates of erosion and accumulation even in conditions of pronounced karst microrelief.</p> <p><strong>Acknowledgement<br /></strong>This research was supported by the Russian Foundation for Basic Research (RFBR) within the scientific project No. 18–35–20011.</p> <p> </p>

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980-2017 in the Black Soil Region, (NE) China

2020 ◽  
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Rainfall Erosivity ◽  
Erosion Rates ◽  
Soil Erosion Rate

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

scholarly journals Different land-use intensities and their susceptibility to soil erosion

2019 ◽  
Vol 68 (Supplement) ◽  
pp. 14-23 ◽  
Author(s):  
Boglárka Keller ◽  
Judit Szabó ◽  
Csaba Centeri ◽  
Gergely Jakab ◽  
Zoltán Szalai
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Arable Land ◽  
Simulation Method ◽  
Rainfall Simulation ◽  
Moderate Increase ◽  
Infiltration Capacity ◽  
Good Tool ◽  
Climate Resilience

Summary Adaptation is the most important strategy to reduce the effect of climate change and soil erosion. During this process adequate, rational land use is necessary to ensure climate resilience. Therefore, the main objective in this study was to evaluate the susceptibility of different land use intensities (arable land and grassland) to soil erosion. The rainfall simulation method is a good tool to measure and estimate soil erosion in situ. The comparative measurements were carried out in the field with a Shower Power-02 simulator on 6 m2 plots in Gerézdpuszta, where the slope angles were ~8% and the simulated rainfall events had high intensities (~70-96 mm h−1). The runoff and soil loss were significantly higher from arable land. The runoff-infiltration ratio and runoff coefficient showed lower infiltration capacity in the case of arable land. On average, the suspended sediment loads were tenfold higher under intensive land use. In the case of grassland a moderate increase in infiltration was observed due to higher rainfall intensity, as also reported in the literature. The rainfall simulation method provides good data for soil loss estimations.

scholarly journals Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

2014 ◽  
Vol 18 (9) ◽  
pp. 3763-3775 ◽  
Author(s):  
K. Meusburger ◽  
G. Leitinger ◽  
L. Mabit ◽  
M. H. Mueller ◽  
A. Walter ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Sediment Yield ◽  
Soil Loss ◽  
Water Erosion ◽  
Erosion Rates ◽  
The Difference ◽  
Snow Gliding

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

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.

scholarly journals Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Land Development ◽  
Developed Countries ◽  
Surface Erosion ◽  
Agricultural Field ◽  
Land Cover Data

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.

scholarly journals Modeling Soil Erosion and Landscape Metric Analysis of River Catchments in Pulau Pinang, Malaysia

2020 ◽  
Vol 55 (3) ◽  
Author(s):  
Sumayyah Aimi Mohd Najib
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Diversity Index ◽  
Land Use Changes ◽  
Shannon Diversity Index ◽  
Universal Soil Loss Equation ◽  
Data Sampling ◽  
Shannon Diversity ◽  
Soil Loss Equation

To determine the soil erosion in ungauged catchments, the author used 2 methods: Universal Soil Loss Equation model and sampling data. Sampling data were used to verify and validate data from model. Changing land use due to human activities will affect soil erosion. Land use has changed significantly during the last century in Pulau Pinang. The main rapid changes are related to agriculture, settlement, and urbanization. Because soil erosion depends on surface runoff, which is regulated by the structure of land use and brought about through changes in slope length, land-use changes are one of many factors influencing land degradation caused by erosion. The Universal Soil Loss Equation was used to estimate past soil erosion based on land uses from 1974 to 2012. Results indicated a significant increase in three land-use categories: forestry, built-up areas, and agriculture. Another method to evaluate land use changes in this study was by using landscape metrics analysis. The mean patch size of built-up area and forest increased, while agriculture land use decreased from 48.82 patches in 1974 to 22.46 patches in 2012. Soil erosion increased from an estimated 110.18 ton/km2/year in 1974 to an estimated 122.44 ton/km2/year in 2012. Soil erosion is highly related (R2 = 0.97) to the Shannon Diversity Index, which describes the diversity in land-use composition in river basins. The Shannon Diversity Index also increased between 1974 and 2012. The findings from this study can be used for future reference and for ungauged catchment research studies.

scholarly journals Assessment of the soil loss caused by riverbank erosion in Serbia

2021 ◽  
Vol 101 (1) ◽  
pp. 31-47
Author(s):  
Marko Langovic ◽  
Slavoljub Dragicevic ◽  
Ivan Novkovic ◽  
Nenad Zivkovic ◽  
Radislav Tosic ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Loss ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Land Use Changes ◽  
Arable Land ◽  
Aerial Photographs ◽  
Lateral Migration ◽  
Channel Migration ◽  
Riverbank Erosion

Riverbank erosion and lateral channel migration are important geomorphological processes which cause various landscape, socio-economic, and environmental consequences. Although those processes are present on the territory of Serbia, there is no available data about the soil loss caused by riverbank erosion for the entire country. In this study, the spatial and temporal dynamics of the riverbank erosion for the largest internal rivers in Serbia (Velika Morava, Zapadna Morava, Juzna Morava, Pek, Mlava, Veliki Timok, Kolubara) was assessed using remote sensing and GIS. The aim of this paper is to determine the total and average soil loss over large-scale periods (1923-2020), comparing data from the available sources (aerial photographs, satellite images, and different scale paper maps). Results indicated that lateral migration caused significant problems through land loss (approximately 2,561 ha), especially arable land, and land use changes in river basins, but also economic loss due to the reduction of agricultural production. Total and average soil loss was calculated for five most representative meanders on all studied rivers, and on the basis of the obtained values, certain regularities about further development and dynamics of riverbank movement are presented. A better understanding of river channel migration in this area will be of a great importance for practical issues such as predicting channel migration rates for river engineering and planning purposes, soil and water management and land use changes, environment protection.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

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