Estimation of Soil Erosion in Three Northern Regions of Ghana Using RUSLE in GIS Environment

Soil erosion is a global problem with severe consequences, which has become a widespread environmental challenge in the northern parts of Ghana in recent times. This research integrated RUSLE into GIS to estimate the annual soil erosion rates for the Northern, North-East, and Savannah Regions of Ghana. A soil erosion map was generated with an annual soil erosion rate of 4.0 t ha−1y−1 for the Northern Region, 5.0 t ha−1y−1 for the North-East Region, and 7.0 t ha−1y−1 for the Savannah Region. Relatively higher erosion rates were observed in the Tatale Sangule and Kpandai districts of the Northern Region, with rainfall erosivity being the main driving factor. There was a landuse/cover erosion reduction effect of 66% in the Northern Region, 70% in the Northeast Region, and 58% in the Savannah Region. The cover management (C) factor was overwhelmingly the main erosion-reducing factor in erosion control as opposed to land conservation (P) factor.

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Assessment of soil erosion vulnerability in the heavily populated and ecologically fragile communities in Motozintla de Mendoza, Chiapas, Mexico

Solid Earth ◽

10.5194/se-9-745-2018 ◽

2018 ◽

Vol 9 (3) ◽

pp. 745-757 ◽

Cited By ~ 1

Author(s):

Selene B. González-Morales ◽

Alex Mayer ◽

Neptalí Ramírez-Marcial

Keyword(s):

Rural Communities ◽

Soil Erosion ◽

Erosion Rate ◽

Forest Products ◽

Tree Cover ◽

Rainfall Erosivity ◽

Erosion Rates ◽

Soil Erosion Rate ◽

Sierra Madre Del Sur ◽

Level Of Motivation

Abstract. Variability in physical rates and local knowledge of soil erosion was assessed across six rural communities in the Sierra Madre del Sur, Chiapas, Mexico. The average erosion rate estimated using the RUSLE model is 274 t ha−1 yr−1, with the estimated erosion rates ranging from 28 to 717 t ha−1 yr−1. These very high erosion rates are associated with high rainfall erosivity (17 000 MJ mm ha−1 h−1 yr−1) and steep slopes (mean slope  =  67 %). Many of the highest soil erosion rates are found in communities that are dominated by forestland, but where most of the tree cover has been removed. Conversely, lower erosion rates are often found where corn is cultivated for most of the year. According to the results of the soil erosion KAP (knowledge, attitude and practices) survey, awareness of the concept of soil erosion was reasonably high in all of the communities, but awareness of the causes of erosion was considerably lower. More than half of respondents believed that reforestation is a viable option for reducing soil erosion, but only a third of respondents were currently implementing reforestation practices. Another third of the respondents indicated that they were not following any soil conservation practices. Respondents indicated that adoption of government reforestation efforts have been hindered by the need to clear their land to sell forest products or cultivate corn. Respondents also mentioned the difficulties involved with obtaining favorable tree stocks for reforestation. The KAP results were used to assess the overall level of motivation to solve soil erosion problems by compiling negative responses. The relationship between the magnitude of the soil erosion problem and the capacity to reduce soil erosion is inconsistent across the communities. One community, Barrio Vicente Guerrero, had the highest average negative response rate and the second highest soil erosion rate, indicating that this community is particularly vulnerable.

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RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection: A Case of Fincha Catchment, Ethiopia

Air Soil and Water Research ◽

10.1177/11786221211046234 ◽

2021 ◽

Vol 14 ◽

pp. 117862212110462

Author(s):

Meseret Wagari ◽

Habtamu Tamiru

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Physical Factors ◽

Rainfall Erosivity ◽

Rusle Model ◽

Raster Calculator ◽

Gis Environment ◽

Elevation Model ◽

The Individual ◽

P Factor

In this study, Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) platforms were successfully applied to quantify the annual soil loss for the protection of soil erosion in Fincha catchment, Ethiopia. The key physical factors such as rainfall erosivity ( R-factor), soil erodibility ( K-factor), topographic condition (LS-factor), cover management ( C-factor), and support practice ( P-factor) were prepared in GIS environment from rainfall, soil, Digital Elevation Model (DEM), Land use/Land cover (LULC) respectively. The RUSLE equation was used in raster calculator of ArcGIS spatial tool analyst. The individual map of the derived factors was multiplied in the raster calculator and an average annual soil loss ranges from 0.0 to 76.5 t ha−1 yr−1 was estimated. The estimated annual soil loss was categorized based on the qualitative and quantitative classifications as Very Low (0–15 t ha−1 yr−1), Low (15–45 t ha−1 yr−1), Moderate (45–75 t ha−1 yr−1), and High (>75 t ha−1 yr−1). It was found from the generated soil erosion severity map that about 45% of the catchment area was vulnerable to the erosion with an annual soil loss of (>75 t ha−1 yr−1), and this demonstrates that the erosion reduction actions are immediately required to ensure the sustainable soil resources in the study area. The soil erosion severity map generated based on RUSLE model and GIS platforms have a paramount role to alert all stakeholders in controlling the effects of the erosion. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss protection practices.

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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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Assessing soil loss using GIS based RUSLE methodology. Case of the Bou Namoussa watershed – North-East of Algeria

Journal of Water and Land Development ◽

10.2478/jwld-2018-0003 ◽

2018 ◽

Vol 36 (1) ◽

pp. 27-35 ◽

Cited By ~ 3

Author(s):

Chemss Eddine Bouhadeb ◽

Mohamed Redha Menani ◽

Hamza Bouguerra ◽

Oussama Derdous

Keyword(s):

Vegetation Cover ◽

Soil Loss ◽

Erosion Rate ◽

Geographical Information ◽

Rainfall Erosivity ◽

Natural Environments ◽

North East ◽

The North ◽

Soil Erosion Rate ◽

Very High

AbstractThis study aims to estimating annual soil erosion rate and its spatial distribution in the Bou Namoussa water-shed located in the North-East of Algeria by applying the revised universal soil loss equation (RUSLE) within a Geographical Information System environment (GIS). The application of the RUSLE model in different natural environments and on every scale takes into account five key factors namely: the rainfall erosivity, the soil erodibility, the steepness and length of slopes, the vegetation cover and the conservation support practices. Each of these factors was generated in GIS as a raster layer, their combination, resulted in the development of a soil loss map indicating an average erosion rate of 7.8 t·ha−1·y−1. The obtained soil loss map was classified into four erosion severity classes; low, moderate, high and very high severity representing respectively 40, 30.48, 22.59 and 6.89% of the total surface. The areas, showing moderate, high and very high erosion rates which represent more than half of the basin area were found generally located in regions having high erodibility soils, steep slopes and low vegetation cover. These areas should be considered as priorities in future erosion control programs in order to decrease the siltation rate in the Cheffia reservoir.

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Within-Storm Rainfall Distribution Effect on Soil Erosion Rate

ISRN Soil Science ◽

10.5402/2012/310927 ◽

2012 ◽

Vol 2012 ◽

pp. 1-7 ◽

Cited By ~ 7

Author(s):

S. I. Ahmed ◽

R. P. Rudra ◽

B. Gharabaghi ◽

K. Mackenzie ◽

W. T. Dickinson

Keyword(s):

Soil Erosion ◽

Erosion Rate ◽

Rainfall Intensity ◽

Silica Sand ◽

Rainfall Erosivity ◽

Rainfall Distribution ◽

Erosion Rates ◽

Soil Erosion Rate ◽

Soil Erosion Rates ◽

Loam Soil

This study investigates the effect of rainfall temporal distribution pattern within a storm event on soil erosion rate and the possibility of using rain power type model for rainfall erosivity. Various rainfall distribution patterns, simulated by rainfall simulator, were used on 1.0 m2 plot of silica sand and loam soil with a minimum of three replications. The results show that the soil erosion rates spiked following every sharp increase in rainfall intensity followed by a gradual decline to a steady erosion rate. Transient effects resulted in the soil erosion rates for an oscillatory rainfall distribution to be more than two fold higher than those obtained for a steady-state rainfall intensity event with same duration and same average rainfall intensity. The 3-parameter and 4-parameter rain power models were developed for a process-based measure of rainfall erosivity. The 4 parameter model yielded better match with the observed data and predicted soil erosion rates more accurately for silica sand under all rainfall distributions, and good results for loam soil under low intensity rainfall. More research is necessary to improve the accuracy of soil erosion prediction models for a wider range of rainfall distributions.

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

10.5194/se-2017-85 ◽

2017 ◽

Cited By ~ 1

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.

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

10.21203/rs.3.rs-25478/v4 ◽

2020 ◽

Author(s):

Pawan Thapa

Keyword(s):

Land Use ◽

Soil Erosion ◽

Agricultural Land ◽

Decision Makers ◽

Management Planning ◽

Erosion Risk ◽

Spatial Estimation ◽

The North ◽

Soil Erosion Rate ◽

Severe Erosion

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

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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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Descriptive epidemiology of cholera outbreak in Nigeria, January–November, 2018: implications for the global roadmap strategy

BMC Public Health ◽

10.1186/s12889-019-7559-6 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 3

Author(s):

Kelly Osezele Elimian ◽

Anwar Musah ◽

Somto Mezue ◽

Oyeronke Oyebanji ◽

Sebastian Yennan ◽

...

Keyword(s):

Public Health ◽

Case Fatality ◽

Northern Region ◽

Watery Diarrhoea ◽

Cholera Outbreak ◽

North West ◽

Design And Implementation ◽

North East ◽

The North ◽

Outbreak Period

Abstract Background The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the global roadmap strategic goals for cholera elimination however seems lacking. Thus, this study aimed at addressing this gap by describing the epidemiology of the 2018 cholera outbreak in Nigeria. Methods This was a retrospective analysis of surveillance data collected between January 1st and November 19th, 2018. A cholera case was defined as an individual aged 2 years or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed and presented with respect to person, time and place using appropriate statistics. Results There were 43,996 cholera cases and 836 cholera deaths across 20 states in Nigeria during the outbreak period, with an attack rate (AR) of 127.43/100,000 population and a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) were the most affected age group, but the proportion of affected males and females was about the same (49.00 and 51.00% respectively). The outbreak was characterised by four distinct epidemic waves, with higher number of deaths recorded in the third and fourth waves. States from the north-west and north-east regions of the country recorded the highest ARs while those from the north-central recorded the highest CFRs. Conclusion The severity and wide-geographical distribution of cholera cases and deaths during the 2018 outbreak are indicative of an elevated burden, which was more notable in the northern region of the country. Overall, the findings reaffirm the strategic role of a multi-sectoral approach in the design and implementation of public health interventions aimed at preventing and controlling cholera in Nigeria.

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Evaluation of changes in soil erosion rates in Andalucia between 1990 and 2018

10.5194/egusphere-egu2020-863 ◽

2020 ◽

Author(s):

Filippo Milazzo ◽

Tom Vanwalleghem ◽

Pilar Fernández, Rebollo ◽

Jesus Fernández-Habas

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Management ◽

Aerial Photographs ◽

Frequency Distributions ◽

Erosion Rates ◽

Soil Erosion Rate ◽

Soil Erosion Rates ◽

Management Changes ◽

Soil Erosion By Water

<p>Land use and land management changes impact significantly on soil erosion rates. The Mediterranean, and in particular Southern Spain, has been affected by important shifts in the last decades. This area is currently identified as a hotspot for soil erosion by water. In the effort to achieve the SDG Target 15, we aim to show the effect of land management change, assessing soil erosion rate based on historical data. We analyzed the evolution of land use from historical aerial photographs between 1990 and 2018. We then calculated soil erosion with RUSLE. For this, we first determined the distribution frequency of cover-management factors for each land use class, comparing current land use maps with the European Soil Erosion Map (Panagos et al., 2015). Past C factors where then assigned using a Monte Carlo approach, based on the obtained frequency distributions.&#160;</p>

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