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

2015 ◽  
Vol 7 (1) ◽  
pp. 68-82 ◽  
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.

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.

scholarly journals Linking Soil Erosion Modeling to Landscape Patterns and Geomorphometry: An Application in Crete, Greece

2021 ◽  
Vol 11 (12) ◽  
pp. 5684
Author(s):  
Imen Brini ◽  
Dimitrios D. Alexakis ◽  
Chariton Kalaitzidis
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Anthropogenic Activities ◽  
Landscape Patterns ◽  
Parameter Analysis ◽  
Morphometric Parameter ◽  
Erosion Modeling ◽  
Soil Erosion Modeling ◽  
Erosion Rates ◽  
Soil Erosion Rates

Soil erosion is a severe and continuous environmental problem caused mainly by natural factors, which can be enhanced by anthropogenic activities. The morphological relief with relatively steep slopes, the dense drainage network, and the Mediterranean climate are some of the factors that render the Paleochora region (South Chania, Crete, Greece) particularly prone to soil erosion in cases of intense rainfall events. In this study, we aimed to assess the correlation between soil erosion rates estimated from the Revised Universal Soil Loss Equation (RUSLE) and the landscape patterns and to detect the most erosion-prone sub-basins based on an analysis of morphometric parameters, using geographic information system (GIS) and remote sensing technologies. The assessment of soil erosion rates was conducted using the RUSLE model. The landscape metrics analysis was carried out to correlate soil erosion and landscape patterns. The morphometric analysis helped us to prioritize erosion-prone areas at the sub-basin level. The estimated soil erosion rates were mapped, showing the spatial distribution of the soil loss for the study area in 2020. For instance, the landscape patterns seemed to highly impact the soil erosion rates. The morphometric parameter analysis is considered as a useful tool for delineating areas that are highly vulnerable to soil erosion. The integration of three approaches showed that there is are robust relationships between soil erosion modeling, landscape patterns, and morphometry.

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 Quantitative Assessment of Soil Erosion Based on CSLE and the 2010 National Soil Erosion Survey at Regional Scale in Yunnan Province of China

2019 ◽  
Vol 11 (12) ◽  
pp. 3252 ◽  
Author(s):  
Guokun Chen ◽  
Zengxiang Zhang ◽  
Qiankun Guo ◽  
Xiao Wang ◽  
Qingke Wen
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Erosion Rate ◽  
Mountainous Areas ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Total Soil ◽  
Conservation Measures ◽  
Soil Conservation Measures

Regional soil loss assessment is the critical method of incorporating soil erosion into decision-making associated with land resources management and soil conservation planning. However, data availability has limited its application for mountainous areas. To obtain a clear understanding of soil erosion in Yunnan, a pixel-based estimation was employed to quantify soil erosion rate and the benefits of soil conservation measures based on Chinese Soil Loss Equation (CSLE) and data collected in the national soil erosion survey. Results showed that 38.77% of the land was being eroded at an erosion rate higher than the soil loss tolerance, the average soil erosion rate was found to be 12.46 t∙ha−1∙yr−1, resulting in a total soil loss of 0.47 Gt annually. Higher erosion rates mostly occurred in the downstream areas of the major rivers as compared to upstream areas, especially for the southwest agricultural regions. Rain-fed cropland suffered the most severe soil erosion, with a mean erosion rate of 47.69 t∙ha−1∙yr−1 and an erosion ratio of 64.24%. Lands with a permanent cover (forest, shrub, and grassland) were mostly characterized by erosion rates an order of magnitude lower than those from rain-fed cropland, except for erosion from sparse woods, which was noticeable and should not be underestimated. Soil loss from arable land, woodland and grassland accounted for 52.24%, 35.65% and 11.71% of the total soil loss, respectively. We also found significant regional differences in erosion rates and a close relationship between erosion and soil conservation measures adopted. The CSLE estimates did not compare well with qualitative estimates from the National Soil Erosion Database of China (NSED-C) and only 47.77% of the territory fell within the same erosion intensity for the two approaches. However, the CSLE estimates were consistent with the results from a national survey and local assessments under experimental plots. By advocating of soil conservation measures and converting slope cropland into grass/forest and terraced field, policy interventions during 2006–2010 have reduced soil erosion on rain-fed cropland by 20% in soil erosion rate and 32% in total soil loss compared to the local assessments. The quantitative CSLE method provides a reliable estimation, due to the consideration of erosion control measures and is potentially transferable to other mountainous areas as a robust approach for rapid assessment of sheet and rill erosion.

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 Assessment of Soil Erosion Vulnerability in the Heavily Populated and Ecologically Fragile Communities in Motozintla De Mendoza, Chiapas, Mexico

2017 ◽  
Author(s):  
Selene B. González-Morales ◽  
Alex Mayer ◽  
Neptalí Ramírez-Marcial
Keyword(s):  
Soil Erosion ◽  
Erosion Rate ◽  
Negative Response ◽  
Attitudes And Practices ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Kap Survey ◽  
Level Of Knowledge ◽  
Steep Slopes ◽  
Knowledge Attitudes And Practices

Abstract. The physical aspects and knowledge of soil erosion in six communities in rural Chiapas, Mexico were assessed. Average erosion rates estimated with the RUSLE model ranged from 200 to 1,200 ha−1 yr−1. Most erosion rates are relatively high due to steep slopes, sandy soils and bare land cover. The lowest rates occur where corn is cultivated for much of the year and slopes are relatively low. The results of a knowledge, attitudes and practices (KAP) survey showed that two-thirds of respondents believed that the major cause of soil erosion was hurricanes or rainfall and only 14 % of respondents identified human activities as causes of erosion. Forty-two percent of respondents indicated that the responsibility for solving soil erosion problems lies with government, as opposed to 26 % indicating that the community is responsible. More than half of respondents believed that reforestation is a viable option for reducing soil erosion, but only a third of respondents were currently applying reforestation practices and another one-third indicated that they were not following any conservation practices. The KAP results were used to assess the overall level of knowledge and interest in soil erosion problems and their solutions by compiling negative responses. The community of Barrio Vicente Guerrero may be most vulnerable to soil erosion, since it had the highest average negative response and the second highest soil erosion rate. However, Poblado Cambil had the highest estimated soil erosion rate and a relatively low average negative response rate, suggesting that soil conservation efforts should be prioritized for this community. We conclude that as long as the economic and productive needs of the communities are not solved simultaneously, the risk of soil erosion will increase in the future, which threatens the survival of these communities.

scholarly journals Uso de Técnicas de Geoprocessamento para Estudo da Erosão Hídrica Laminar em Bacia Hidrográfica do Sudoeste do Paraná.

2020 ◽  
Vol 13 (3) ◽  
pp. 1117
Author(s):  
Julio Caetano Tomazoni ◽  
Ana Paula Vansan
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Satellite Images ◽  
Water Erosion ◽  
Soil Samples ◽  
Universal Equation ◽  
Erosion Rates ◽  
Loss Estimate

Este trabalho tem como objetivo avaliar a erosão hídrica laminar do solo, por meio da Equação Universal de Perdas de Solos Revisada (RUSLE) na bacia hidrográfica do rio São José, localizada no município de Francisco Beltrão (PR).  A perda de solo média anual (A) foi determinada através da RUSLE para os anos 2000, 2005, 2009, 2015 e 2017 utilizando-se técnicas de geoprocessamento com o auxílio do software ArcGis 10.0. O fator erosividade da chuva (R) foi determinado utilizando-se dados pluviométricos correspondentes ao período de 1974 a 2016. O fator erodibilidade do solo (K) foi obtido através da análise de amostras de solo coletadas in loco. O fator topográfico (LS) foi estimado por meio dos dados altimétricos e hidrográficos da bacia. Os fatores de uso e manejo do solo (C) e de práticas conservacionistas do solo (P) foram determinados por meio da caracterização multitemporal do uso e ocupação do solo, através de imagens de satélite. O potencial natural de erosão (PNE) foi determinado pela multiplicação dos fatores R, K e LS.A estimativa de perda de solo (A) foi determinada pela multiplicação do PNE pelos fatores C e P.  Use of Geoprocessing Techniques to Study Laminar Water Erosion in Watershed of Southwest Paraná A B S T R A C TThe objective of this work is evaluate the soil erosion by the Universal Equation of Soil Losses Revised (RUSLE) in the São José river basin, located in the municipality of Francisco Beltrão (PR). The average annual soil loss (A) was determined through RUSLE for the years 2000, 2005, 2009, 2015 and 2017 using geoprocessing techniques with ArcGis 10.0 software. Rainfallerosivity (R) was determined using rainfall data from 1974 to 2016, being determined at 11521.26 11521,26 MJ.mm.ha-1.h-1.year-1. The soil erodibility factor (K) was obtained through the analysis of soil samples collected on the spot (0,03018 t.ha.h/ha.MJ.mm, 0,02771 t.ha.h/ha.MJ.mm e 0,02342 t.ha.h/ha.MJ.mm). The topographic factor (LS) was estimated by the altimetric and hydrographic data of the basin. Soil use and management (C) and soil conservation (P) were determined through multitemporal characterization of land use and occupation, using satellite images. The natural erosion potential (NEP) was determined by multiplying the R, K and LS factors, with more than half of the total area of the watershed with very strong PNE. The soil loss estimate (A) was determined by multiplying the NEP by factors C and P with predominance of the class called low (0 to 10 t/ha/year) denoting the reduction of erosion rates through factors C and P, helping to protect the soil from the erosion process.Key words: Soil Erosion; Watershed, Revised Universal Soil Loss Equation, Geoprocessing, Software.

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

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.

Using 137Cs to investigate net soil erosion at two soil benchmark sites in Quebec

1993 ◽  
Vol 73 (4) ◽  
pp. 515-526 ◽  
Author(s):  
Y. Z. Cao ◽  
D. R. Coote ◽  
C. Wang ◽  
M. C. Nolin
Keyword(s):  
Soil Erosion ◽  
Key Words ◽  
Soil Conservation ◽  
Soil Loss ◽  
Soil Samples ◽  
Grid Pattern ◽  
Erosion Rates ◽  
The Past ◽  
Soil Erosion Rates ◽  
Small Grains

137Cs in the soil was used to estimate soil erosion at two National Soil Conservation Program benchmark sites in the province of Quebec (sites 15-QU and 16-QU). The 137Cs baseline in an uneroded forest area was approximately 3100 Bq m−2. The 137Cs content at site 15-QU ranged from 1072 Bq m−2 to 6389 Bq m−2, while at site 16-QU it ranged from 663 Bq m−2 to 5444 Bq m−2. Computed net erosion over the past 30 yr at site 15-QU varied from a loss of 9.65 kg m−2 yr−1 to a gain of 10.88 kg m−2 yr−1 and at site 16-QU from a loss of 6.38 kg m−2 yr−1 to a gain of 1.73 kg m−2 yr−1. The average net erosion rates were 2.43 kg m−2 yr−1 at site 15-QU and 1.29 kg m−2 yr−1 at site 16-QU. Soil samples collected on a grid pattern indicated that 90% and 83% of the area at sites 15-QU and 16-QU, respectively, was subjected to net soil loss. A comparison of total 137Cs movement from eroded areas to depositional areas showed that 24.2% of 137Cs was lost from site 15-QU, while about 17.6% of 137Cs was lost from site 16-QU. Mapping of 137Cs content and calculated soil loss and deposition showed that soil erosion was closely related to topography.Under similar slope conditions, the soil erosion rates were 27–68% higher at site 15-QU than at site 16-QU. Higher tillage frequency and use of silage corn were the suggested reasons for the higher soil erosion rates at site 15-QU compared with site 16-QU, which had been used for hay and small grains. Key words: 137Cs, erosion, deposition, soil conservation

Sediment origins across the terrestrial-aquatic continuum: climate threat mitigation and promotion of water quality

2020 ◽  
Author(s):  
Katy Wiltshire ◽  
Toby Waine ◽  
Bob Grabowski ◽  
Miriam Glendell ◽  
Steve Addy ◽  
...  
Keyword(s):  
Water Quality ◽  
Soil Erosion ◽  
Soil Loss ◽  
River Channel ◽  
River Channels ◽  
Catchment Scale ◽  
Transport Pathways ◽  
Fine Grained ◽  
Erosion Rates ◽  
Erosion Modelling

&lt;p&gt;Although fine-grained sediment (FGS) is a natural component of river systems, increased fluxes can impact FGS levels to such an extent they cause detrimental, irreversible changes in the way rivers function intensifying flood risk and negatively affecting water quality.&lt;/p&gt;&lt;p&gt;Previous catchment scale studies indicate there is no simple link between areas of sediment loss and the organic carbon (OC) load in waterways; areas with a high soil loss rate may not contribute most sediment to the rivers and areas that contribute the most sediment may not contribute the most OC. Anthropogenic and climate changes can accelerate soil erosion and the role of soil OC transported by erosional processes in the fluxes of C between land, water and atmosphere is still debated. Tracing sediment pathways, likely depositional areas and connections to streams leads to better assumptions about control processes and better estimation of OC fluxes.&lt;/p&gt;&lt;p&gt;In this innovative study OC fingerprinting of sediment reaching a catchment&amp;#8217;s waterbodies is combined with OC stock and erosion modelling of the terrestrial catchment. Initial results show disconnect between catchment OC loss erosion modelling and fingerprinting results, which could be due to failure to model connectivity between the land and river channel. The current soil erosion model RUSLE (Revised Universal Soil Loss Equation) calculates only the spatial pattern of mean annual soil erosion rates. Using the WaTEM SEDEM model, which in includes routing (and possible en route deposition) of eroded sediments to river channels, we aim to determine the dominant source of OC within catchment streams by identification of both the land-use specific areas with the highest OC loss and the transport pathways between the sources and river channel.&lt;/p&gt;

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