Soil Erosion and its Effects on Maize Field as Modified by Amendments in Southwestern Coastal Bangladesh

The coastal soils of Bangladesh are preferentially dominated by silt content and stressed by salinity (Na+) as well as low humus content . Hence, these soils are moderately to extremely vulnerable to water erosion, which is a major form of land degradation. The aim of this study was to estimate the soil erosion rate from maize fields in the southwestern coastal region. A field experiment was conducted on maize grown field, which is nearly level, moderately saline, and silt dominated coastal land. The plots were amended with inorganic fertilizer, sieved sand, and decomposed cow dung. Each runoff plot was connected to separate reservoirs and was exposed to rainfall. From the erosive rainstorms, representative critical rainfall intensity was determined. The entrapped eroded material in the reservoirs was collected to estimate the loss of soil. The efficacy of the applied amendments was studied in terms of lowering seasonal (maize growth period) soil loss and erosion associated deterioration of relevant soil parameters. This study revealed that CRI was ≥15 mm h-1. The soil loss during the maize growth period from inorganic fertilizer, cow dung, and sand amended runoff plots were 64(±7) t ha-1 y-1, 51(±5) t ha-1 y-1, and 23(±2) t ha-1 y-1, respectively. The changes in soil properties indicated that after initial erosion, vulnerability to further erosion increased.

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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

ENVIRONMENTAL SYSTEMS RESEARCH ◽

10.1186/s40068-020-00203-3 ◽

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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Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

Environmental Sciences Proceedings ◽

10.3390/ecas2021-10348 ◽

2021 ◽

Vol 8 (1) ◽

pp. 26

Author(s):

Manti Patil ◽

Radheshyam Patel ◽

Arnab Saha

Keyword(s):

Spatial Distribution ◽

Soil Erosion ◽

Soil Loss ◽

Crop Production ◽

Erosion Rate ◽

Agricultural Land ◽

Reservoir Sedimentation ◽

Reservoir Water ◽

Slope Length ◽

Soil Erosion Rate

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

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Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria

Water ◽

10.3390/w12102786 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2786 ◽

Cited By ~ 2

Author(s):

Safwan Mohammed ◽

Hazem G. Abdo ◽

Szilard Szabo ◽

Quoc Bao Pham ◽

Imre J. Holb ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

Soil Loss ◽

Agricultural Land ◽

Human Impacts ◽

Coastal Region ◽

Water Erosion ◽

Land Uses ◽

Erosion Processes

Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ± 0.07 and 0.74 ± 0.33 kg/m2; in the BF plots, mean soil erosion ranged between 0.03 ± 0.01 and 0.24 ± 0.10 kg/m2. The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ± 0.001 and 0.07 ± 0.03 kg/m2. Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes.

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Remote sensing and GIS based assessment of soil erosion and soil loss risk around hill top surface mines situated in Saranda Forest, Jharkhand

Journal of Water and Climate Change ◽

10.2166/wcc.2015.100 ◽

2015 ◽

Vol 7 (1) ◽

pp. 68-82 ◽

Cited By ~ 1

Author(s):

Mali Vijay Kisan ◽

Pathak Khanindra ◽

Tiwari Kamlesh Narayan ◽

Tripathy Swarup Kumar

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Anthropogenic Activities ◽

Careful Consideration ◽

Imaging Data ◽

Mining Operations ◽

Erosion Rates ◽

Surface Mines ◽

Soil Erosion Rate ◽

Coefficients Of Variation

The quantitative analysis of soil erosion changes over 7 years due to mining operations in two neighboring hilltops in West-Singhbhum District, Jharkhand, are reported. CartoSat-1, ETM+ and LISS-IV satellites' data provided spatial inputs in Universal Soil Loss Equation (USLE) and Morgan, Morgan and Finney method (MMF) models, which were used to predict the average annual soil erosion during the period of 2001–2008 in a geographic information system (GIS), in six distinct classes. In the comparative analysis of the 7-year period, the MMF model revealed a lower coefficient of variation 0.71 (2001) and 0.84 (2008) in predicted average annual soil loss, which increased by 16% (81.3–94.2 t ha−1yr−1), whereas in the case of USLE, the coefficients of variation were 3.88 (2001) and 1.94 (2008), with an increase of 61% (48.56–78.38 t ha−1yr−1). The correlation coefficient of these models was 0.1 (2001) and 0.36 (2008), which shows that both models predicted significantly differently as a result of the different factors considered. Overall, the MMF model predicted a higher soil erosion rate but less variation than USLE. Both models showed soil erosion rates were drastically increased by anthropogenic activities in the area, hence careful consideration is needed. The same sensor and imaging data could not be maintained. Correction of errors may reduce erosion, but it will still remain significant for future planning.

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Investigation of the effect of anthropogenic land use on the Pănăzii Lake (Romania) catchment area using Cs-137 and Pb-210 radionuclides

PLoS ONE ◽

10.1371/journal.pone.0251603 ◽

2021 ◽

Vol 16 (6) ◽

pp. e0251603

Author(s):

Robert-Csaba Begy ◽

Codrin F. Savin ◽

Szabolcs Kelemen ◽

Daniel Veres ◽

Octavian-Liviu Muntean ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Sedimentation Rate ◽

Catchment Area ◽

Gamma Spectroscopy ◽

Soil Parameters ◽

Erosion Rates ◽

Soil Erosion Rate ◽

Soil Erosion Rates ◽

Lake Catchment

The problem of soil degradation has accentuated over recent decades. Aspects related to soil erosion and its relation to changes in land use as well as anthropogenic influence constitute a topic of great interest. The current study is focused on a soil erosion assessment in relation to land use activities in the Pănăzii Lake catchment area. Fallout radionuclides were used to provide information on soil erosion as well as redistribution rates and patterns. Variations in the sedimentation rate of the lake were also investigated as these reflect periods in which massive erosion events occurred in the lake catchment area. The novelty of this study is the construction of a timescale with regard to the soil erosion events to better understand the relationship between soil erosion and land use activities. In this study, 10 soil profiles and one sediment core from the lake were taken. Soil parameters were determined for each sample. The activities of 210Pb, 137Cs and 226Ra were measured by gamma spectroscopy. For low 210Pb activities, measurements via 210Po using an alpha spectrometer were performed. Soil erosion rates were determined by the 137Cs method and the sedimentation rate calculated by the Constant Rate of Supply (CRS) model. A soil erosion rate of 13.5 t·ha-1·yr-1 was obtained. Three distinct periods could be observed in the evolution of the sedimentation rate. For the first period, between 1880 and 1958, the average deposition rate was 9.2 tons/year, followed by a high deposition period (1960–1991) of 29.6 tons/year and a third period, consisting of the last 30 years, during which the sedimentation rate was 15.7 tons/year. These sedimentation rates fluctuated depending on the main land use activity, which can also be seen in the soil erosion rates that had almost doubled by the time agricultural activities were performed in the area.

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Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern Ethiopia

Air Soil and Water Research ◽

10.1177/1178622120985814 ◽

2021 ◽

Vol 14 ◽

pp. 117862212098581

Author(s):

Ajanaw Negese ◽

Endalkachew Fekadu ◽

Haile Getnet

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Conservation Planning ◽

Water Conservation ◽

Soil Loss ◽

Rainfall Erosivity ◽

Gis And Remote Sensing ◽

Soil Erosion Rate ◽

Conservation Measures ◽

Prone Area

Soil erosion by water is the major form of land degradation in Chereti watershed, Northeastern Ethiopia. This problem is exacerbated by high rainfall after a long period of dry seasons, undulating topography, intensive cultivation, and lack of proper soil and water conservation measures. Hence, this study aimed to estimate the 23 years (1995-2018) average soil erosion rate of the watershed and to identify and prioritize erosion-vulnerable subwatersheds for conservation planning. The integration of the revised universal soil loss equation (RUSLE), geographic information system, and remote sensing was applied to estimate the long-term soil loss of the watershed. The RUSLE factors such as rainfall erosivity ( R), soil erodibility ( K), topography ( LS), cover and management ( C), and support and conservation practices ( P) factors were computed and overlayed to estimate the soil loss. The result showed that the annual soil loss rate of the watershed ranged up to 187.47 t ha−1 year−1 in steep slope areas with a mean annual soil loss of 38.7 t ha−1 year−1, and the entire watershed lost a total of about 487 057.7 tons of soil annually. About 57.9% of the annual watershed soil loss was generated from 5 subwatersheds which need prior intervention for the planning and implementation of soil conservation measures. The integrated use of RUSLE with GIS and remote sensing was found to be indispensable, less costly, and effective for the estimation of soil erosion, and prioritization of vulnerable subwatersheds for conservation planning.

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Assessment of Soil Erosion by the RUSLE Model Using Remote Sensing and GIS: A Case Study of Jilin Province of China

10.20944/preprints202011.0435.v1 ◽

2020 ◽

Author(s):

Ping ZHOU ◽

Yajin GE ◽

Yue JIANG ◽

Yanan XIE ◽

Zhiwen SI ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Conservation ◽

Soil Loss ◽

Food Production ◽

Erosion Rate ◽

Slope Angle ◽

Jilin Province ◽

Rusle Model ◽

Soil Erosion Rate

The accurate assessment and monitoring of soil erosion is of great significance for guiding food production and ensuring ecological security, and it is a current research hotspot. In this paper, remote sensing and geographic information systems (GISs) are combined with the Revised Universal Soil Loss Equation (RUSLE model) to carry out research on soil erosion monitoring and make a quantitative evaluation. According to five factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, crop management and water and soil conservation measures, the distribution of the soil erosion rate in Jilin Province in 2019 was mapped, and the soil erosion rate was divided into 5 levels according to the degree of erosion, including very slight, slight, moderate, severe and extremely severe erosion. Based on the segmented S-slope factor model and the unique topographical features of the study area, the relationships among the soil erosion rate, erosion risk level, erosion area, erosion amount and slope angle (θ) were systematically analysed, and a slope angle of 15° was identified as the threshold for soil erosion on sloped farmland in Jilin Province. The total soil erosion in Jilin Province was 402.14×106 t in 2019, the average soil erosion rate was 21.6 t·ha-1·a-1, and the average soil loss thickness was 1.6 mm·a-1; these values were far greater than the soil erosion rate risk threshold of 10 t ·Ha-1·a-1. Thus, the province has a strong level of soil erosion. We conclude that soil degradation is accelerating, and food production and the ecological environment will face severe challenges. It is suggested that soil erosion control should be carried out according to different types and slopes of land, with an emphasis on the management of forestland and farmland because forestland and farmland are currently the first types of land to be managed in Jilin Province. This paper aims to explore a timely, fast, efficient and convenient soil erosion monitoring and evaluation method and provide effective monitoring tools for agricultural water and soil conservation, ecological safety management and stable food production in Jilin Province and similar black soil areas.

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The overshadow of the human evolvement process in the dynamics of soil drift of an agricultural watershed in Nilgiri Hills, India

Soil and Water Research ◽

10.17221/105/2020-swr ◽

2021 ◽

Author(s):

Sangeetha Ramakrishnan ◽

Ambujam Neelakanda Pillai Kanniperumal

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Agricultural Watershed ◽

Rainfall Erosivity ◽

Landsat Images ◽

Slope Length ◽

Data Format ◽

Conservation Practice ◽

Soil Erosion Rate ◽

Agricultural Planning

The Nilgiri Biosphere, being one of the critical catchments, a small agricultural watershed of Udhagamandalam has been analysed to show the need to improve the agriculture by reducing the soil erosion. For this study, the land use and land cover classification was undertaken using Landsat images to highlight the changes that have occurred between 1981 and 2019. The Revised Universal Soil Loss Equation (RUSLE) method and the Geographic Information System (GIS) was used in this study to determine the soil erosion vulnerability of Sillahalla watershed in the Nilgiri Hills in Tamilnadu. This study will help to promote the economic development of the watershed with proper agricultural planning and erosion management. This study focuses on the estimation of the average annual soil loss and to classify the spatial distribution of the soil loss as a map with the RUSLE method and GIS. To estimate the average annual soil loss of the study area, GIS layers of the RUSLE factors like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) were computed in a raster data format. The total soil loss and average annual soil loss of the study area for 1981–1990,1991–2000, 2001–2010, 2011–2019 were found to be 0.2, 0.254, 0.3, 0.35 million t/year and 31.33, 37.78, 46.7, 51.89 t/ha/year, respectively. The soil erosion rate is classified into different classes as per the FAO guidelines and this severity classification map was prepared to identify the vulnerable areas.

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

10.20944/preprints202009.0082.v1 ◽

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.

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Impact of Land Cover Change Due to Armed Conflicts on Soil Erosion in the Basin of the Northern Al-Kabeer River in Syria Using the RUSLE Model

Water ◽

10.3390/w12123323 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3323

Author(s):

Hussein Almohamad

Keyword(s):

Soil Erosion ◽

Land Cover ◽

Land Cover Change ◽

Forest Fires ◽

Armed Conflict ◽

Soil Loss ◽

Erosion Rate ◽

Armed Conflicts ◽

Rusle Model ◽

Soil Erosion Rate

Due to armed conflicts, the sudden changes in land cover are among the most drastic and recurring shocks on an international scale, and thus, have become a major source of threat to soil and water conservation. Throughout this analysis, the impact of land cover change on spatio-temporal variations of soil erosion from 2009/2010 to 2018/2019 was investigated using the Revised Universal Soil Loss Equation (RUSLE) model. The goal was to identify the characteristics and variations of soil erosion under armed conflicts in the basin of the Northern Al-Kabeer river in Syria. The soil erosion rate is 4 t ha−1 year−1 with a standard deviation of 6.4 t ha−1 year−1. In addition, the spatial distribution of erosion classes was estimated. Only about 10.1% of the basin is subject to a tolerable soil erosion rate and 79.9% of the study area experienced erosion at different levels. The soil erosion area of regions with no changes was 10%. The results revealed an increase in soil erosion until 2013/2014 and a decrease during the period from 20013/2014 to 2018/2019. This increase is a result of forest fires under armed conflict, particularly toward the steeper slopes. Coniferous forest as well as transitional woodland and scrub are the dominant land cover types in the upper part of the basin, for which the average post-fire soil loss rates (caused by factor C) were 200% to 800% higher than in the pre-fire situation. In the period from 2013/2014 to 2019/2020, soil erosion was mitigated due to a ceasefire that was agreed upon after 2016, resulting in decreased human pressures on soils in contested areas. By comparing 2009/2010 (before war) with 2018/2019 (at the end of the war stage), it can be concluded that the change in C factors slowed down the deterioration trend of soil erosion and reduced the average soil erosion rate in more than half of the basin by about 10–75%. The area concerned is located in the western part of the basin and is relatively far from the centers of armed conflicts. In contrast, the areas with increased soil erosion by about 60–400% are situated in the northeast and east, with shorter distances to armed conflict centers. These findings can be explained by forest fires, after which the burned forests were turned into agricultural land or refugee camps and road areas. Understanding the complex biophysical and socio-economic interactions of exposure to land loss is a key to guarantee regional environmental protection and to conserve the ecological quality of soil and forest systems.

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