scholarly journals Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia

2013 ◽  
Vol 18 (1) ◽  
pp. 81 ◽  
Author(s):  
. Aflizar ◽  
Roni Afrizal ◽  
Tsugiyuki Masunaga

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia.  The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed.  Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%).  Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated  as having very less to moderate.  On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah.  The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81]

Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas

Abrupt changes in climatic factors, exploitation of natural resources, and land degradation contribute to soil erosion. This study provides the first comprehensive analysis of annual soil erosion dynamics in Pakistan for 2005 and 2015 using publically available climatic, topographic, soil type, and land cover geospatial datasets at 1 km spatial resolution. A well-accepted and widely applied Revised Universal Soil Loss Equation (RUSLE) was implemented for the annual soil erosion estimations and mapping by incorporating six factors; rainfall erosivity (R), soil erodibility (K), slope-length (L), slope-steepness (S), cover management (C) and conservation practice (P). We used a cross tabular or change matrix method to assess the annual soil erosion (ton/ha/year) changes (2005-2015) in terms of areas and spatial distriburtions in four soil erosion classes; i.e. Low (<1), Medium (1–5], High (5-20], and Very high (>20). Major findings of this paper indicated that, at the national scale, an estimated annual soil erosion of 1.79 ± 11.52 ton/ha/year (mean ± standard deviation) was observed in 2005, which increased to 2.47 ±18.14 ton/ha/year in 2015. Among seven administrative units of Pakistan, in Azad Jammu & Kashmir, the average soil erosion doubled from 14.44 ± 35.70 ton/ha/year in 2005 to 28.03 ± 68.24 ton/ha/year in 2015. Spatially explicit and temporal annual analysis of soil erosion provided in this study is essential for various purposes, including the soil conservation and management practices, environmental impact assessment studies, among others.


2020 ◽  
Vol 12 (9) ◽  
pp. 1365 ◽  
Author(s):  
Panos Panagos ◽  
Cristiano Ballabio ◽  
Jean Poesen ◽  
Emanuele Lugato ◽  
Simone Scarpa ◽  
...  

Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016. This small decrease of soil loss was due to a limited increase of applied soil conservation practices and land cover change observed at the EU level. The modelling results suggest that, currently, ca. 25% of the EU land has erosion rates higher than the recommended sustainable threshold (2 t ha−1 yr−1) and more than 6% of agricultural lands suffer from severe erosion (11 t ha−1 yr−1). The results suggest that a more incisive set of measures of soil conservation is needed to mitigate soil erosion across the EU. However, targeted measures are recommendable at regional and national level as soil erosion trends are diverse between countries which show heterogeneous application of conservation practices.


2019 ◽  
Vol 11 (2) ◽  
pp. 529-539 ◽  
Author(s):  
Mahmud Mustefa ◽  
Fekadu Fufa ◽  
Wakjira Takala

Abstract Currently, soil erosion is the major environmental problem in the Blue Nile, Hangar watershed in particular. This study aimed to estimate the spatially distributed mean annual soil erosion and map the most vulnerable areas in Hangar watershed using the revised universal soil loss equation. In this model, rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (P-factor) were considered as the influencing factors. Maps of these factors were generated and integrated in ArcGIS and then the annual average soil erosion rate was determined. The result of the analysis showed that the amount of soil loss from the study area ranges from 1 to 500 tha−1 yr−1 with an average annual soil loss rate of 32 tha−1 yr−1. Considering contour ploughing with terracing as a fully developed watershed management, the resulting soil loss rate was reduced from 32 to 19.2 tha−1 yr−1. Hence, applying contour ploughing with terracing effectively reduces the vulnerability of the watershed by 40%. Based on the spatial vulnerability of the watershed, most critical soil erosion areas were situated in the steepest part of the watershed. The result of the study finding is helpful for stakeholders to take appropriate mitigation measures.


Solid Earth ◽  
2017 ◽  
Vol 8 (1) ◽  
pp. 13-25 ◽  
Author(s):  
Tegegne Molla ◽  
Biniam Sisheber

Abstract. Soil erosion is one of the major factors affecting sustainability of agricultural production in Ethiopia. The objective of this paper is to estimate soil erosion using the universal soil loss equation (RUSLE) model and to evaluate soil conservation practices in a data-scarce watershed region. For this purpose, soil data, rainfall, erosion control practices, satellite images and topographic maps were collected to determine the RUSLE factors. In addition, measurements of randomly selected soil and water conservation structures were done at three sub-watersheds (Asanat, Debreyakob and Rim). This study was conducted in Koga watershed at upper part of the Blue Nile basin which is affected by high soil erosion rates. The area is characterized by undulating topography caused by intensive agricultural practices with poor soil conservation practices. The soil loss rates were determined and conservation strategies have been evaluated under different slope classes and land uses. The results showed that the watershed is affected by high soil erosion rates (on average 42 t ha−1 yr−1), greater than the maximum tolerable soil loss (18 t ha−1 yr−1). The highest soil loss (456 t ha−1 yr−1) estimated from the upper watershed occurred on cultivated lands of steep slopes. As a result, soil erosion is mainly aggravated by land-use conflicts and topographic factors and the rugged topographic land forms of the area. The study also demonstrated that the contribution of existing soil conservation structures to erosion control is very small due to incorrect design and poor management. About 35 % out of the existing structures can reduce soil loss significantly since they were constructed correctly. Most of the existing structures were demolished due to the sediment overload, vulnerability to livestock damage and intense rainfall. Therefore, appropriate and standardized soil and water conservation measures for different erosion-prone land uses and land forms need to be implemented in Koga watershed.


2007 ◽  
Vol 47 (6) ◽  
pp. 721 ◽  
Author(s):  
R. A. Cramb ◽  
D. Catacutan ◽  
Z. Culasero-Arellano ◽  
K. Mariano

‘Landcare’ is a group-based approach to the promotion of conservation farming. A case study of the Landcare program in Lantapan in the southern Philippines is presented to assess the farm-level impacts of this approach. The program was successful in promoting the formation of Landcare groups and a municipal Landcare association, resulting in rapid and widespread adoption of conservation practices, particularly among maize farmers. This in turn significantly reduced soil erosion, though the impact on crop yield and income was somewhat delayed. Adoption was thus not motivated primarily by short-term returns but by a concern to reduce soil erosion and provide a basis for diversification into agroforestry.


Author(s):  
S. Abdul Rahaman ◽  
S. Aruchamy ◽  
R. Jegankumar ◽  
S. Abdul Ajeez

Soil erosion is a widespread environmental challenge faced in Kallar watershed nowadays. Erosion is defined as the movement of soil by water and wind, and it occurs in Kallar watershed under a wide range of land uses. Erosion by water can be dramatic during storm events, resulting in wash-outs and gullies. It can also be insidious, occurring as sheet and rill erosion during heavy rains. Most of the soil lost by water erosion is by the processes of sheet and rill erosion. Land degradation and subsequent soil erosion and sedimentation play a significant role in impairing water resources within sub watersheds, watersheds and basins. Using conventional methods to assess soil erosion risk is expensive and time consuming. A comprehensive methodology that integrates Remote sensing and Geographic Information Systems (GIS), coupled with the use of an empirical model (Revised Universal Soil Loss Equation- RUSLE) to assess risk, can identify and assess soil erosion potential and estimate the value of soil loss. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the study area. The final map of annual soil erosion shows a maximum soil loss of 398.58 t/ h<sup>-1</sup>/ y<sup>-1</sup>. Based on the result soil erosion was classified in to soil erosion severity map with five classes, very low, low, moderate, high and critical respectively. Further RUSLE factors has been broken into two categories, soil erosion susceptibility (A=RKLS), and soil erosion hazard (A=RKLSCP) have been computed. It is understood that functions of C and P are factors that can be controlled and thus can greatly reduce soil loss through management and conservational measures.


Author(s):  
Sangeetha Ramakrishnan ◽  
Ambujam Neelakanda Pillai Kanniperumal

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.


2020 ◽  
Vol 17 ◽  
pp. 118-134
Author(s):  
Roshan Dahal

Revised Universal Soil Loss Equation (RUSLE) model is applied in this study to evaluate the risk of erosion in Kathmandu district. The calculation of erosion requires certain data from various sources available in different formats and scales. Geographic Information System (GIS) was used which allowed considerable time savings in the processing of spatial data, screening the effects of each factor affecting soil erosion. Among various erosion factors, topography, rainfall, soil properties, and soil conservation practices were used for the study. Average soil loss was calculated by multiplying these factors. Final results of soil erosion rates were separated into six classes based on erosion severity, in which 2.18% of land (> 80Mg ha-1yr-1), followed by 2.85% of land (40-80 Mg ha-1yr-1), 5.56% of land (20-40 Mg ha-1yr-1), 8.73% of land (10-20 Mg ha-1yr-1), 10.53% of land (5-10 Mg ha-1yr-1) and 70.14% of land (0-5 Mg ha-1yr-1), falls under very severe, severe, very high, moderate and low severity zone respectively. Area having high slope length (LS) factor has high erosion rate. In Dakshinkali, Nagarjun and Budanilkantha area, there is high erosion rate. From the result, spatial distribution of soil erosion across Kathmandu district, can be applied for management and controlling the erosion.


Author(s):  
N. W. Ingole ◽  
S. S. Vinchurkar

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


2020 ◽  
Vol 24 (9) ◽  
pp. 1693-1702
Author(s):  
Cosmas Parwada ◽  
Johan van Tol

The study aims to map areas sensitive to erosion by water and rainfall erosivity after addition of organic matter (OM) in highly unstable soils. A soil association map was created using digital soil mapping methodology. Soil samples from six soil associations were incubated and analysed for several soil erodibility measures and inferred to the soil association map. Soil stabilization against soil erosion by use of OM was evaluated for 30 weeks under two simulated rainstorms, intermittent rainstorms (IR) and single rainstorm (SR). Rainfall erosivity (R-factor) was calculated from theduration of a rainstorm and the total amount of rainfall received under rainfall simulations. Erodibility factor (K-factor) was estimated using the soil OM content and texture. Largest area (40%) was covered by shallow soils and K-factor range of 0.0693-0.0778 t.ha.hha-1MJ-1mm-1. Largest (60.2%) area had a structural stability index of 0.8 and 42.7% of the area was covered by a dispersion ratio value range of 0.65-0.70. The area size with erosion rates of > 15 t/ha/yr was drastically reduced from 1 to 8 weeks after OM application thereafter gradually increased under both IR and SR.  Soil erosion rates of < 5 t-1 ha-1 yr-1 and > 15 t-1 ha-1 yr-1 were most and least observed respectively under both storms. R-factor was higher under IR than SR and the smallest areas with soil erosion rates of > 15 t-1 ha-1 yr-1 contributed most to the lost soil. Organic matter confers soil resistance to erosion up to a certain period before losing its effectiveness. The study provided first assessment of erosion dynamics, basis for identifying  conservation priorities which may be applicable in similar areas. Keywords: Erosivity, planning, rainstorm, soil conservation, soil degradation


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