Soil Erosion Assessment in Kondoa Eroded Area in Tanzania using Universal Soil Loss Equation, Geographic Information Systems and Socioeconomic Approach

2013 ◽  
Vol 26 (4) ◽  
pp. 367-379 ◽  
Author(s):  
P. J. Ligonja ◽  
R. P. Shrestha
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Universal Soil Loss Equation ◽  
Soil Erosion Assessment ◽  
Soil Loss Equation

scholarly journals A review of soil erosion modeling by R/USLE in Morocco: Achievements and limits

2021 ◽  
Vol 234 ◽  
pp. 00067
Author(s):  
Mohamed Manaouch ◽  
Anis Zouagui ◽  
Imad Fenjiro
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Review Paper ◽  
Empirical Models ◽  
Universal Soil Loss Equation ◽  
Erosion Modeling ◽  
Future Studies ◽  
Current Concerns ◽  
Soil Erosion Assessment ◽  
Soil Loss Equation

Soil erosion is a major cause of land degradation. It can be estimated with several models, such as empirical, conceptual and physical based. One of the empirical models used worldwide nowadays for soil erosion assessment is the Universal Soil Loss Equation (USLE) and its updated form, the Revised Universal Soil Loss Equation (RUSLE). In Morocco, this model is being used to assess and quantify soil loss by water erosion. In spite of this, it was noted that limited studies employed correctly this important tool. The goal of this review paper was to identify potential usage of R/USLE models in Morocco. This was done by evaluating the conducted studies concerning these models and main gaps and challenges were determined accordingly. Improvement options and future requirements for using R/USLE models were recommended. In order to assess the statues of the R/USLE models applications, the 56 published documents related to R/USLE models conducted in Morocco during the first use till 2020 were collected and reviewed. These publications covered five main areas. The main benefits as well as gaps of the conducted studies were discussed for each area. Current concerns, need of future studies as well as related recommendations and suggestions were also presented.

scholarly journals Soil erosion estimation using Geographic Information System (GIS) and Revised Universal Soil Loss Equation (RUSLE) in the Siwalik Hills of Nawalparasi, Nepal

2021 ◽  
Author(s):  
Durga Bahadur Tiruwa ◽  
Babu Ram Khanal ◽  
Sushil Lamichhane ◽  
Bharat Sharma Acharya
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Universal Soil Loss Equation ◽  
Conservation Practices ◽  
Erosion Hotspots ◽  
Soil Loss Equation

Abstract Soil erosion is one of the gravest environmental threats to the mountainous ecosystems of Nepal. Here, we combined a Geographic Information System (GIS) with the Revised Universal Soil Loss Equation (RUSLE) to estimate average annual soil loss, map erosion factors, compare soil erosion risks among different land use types, and identify erosion hotspots and recommend land use management in the Girwari river watershed of the Siwalik Hills. The annual soil loss was estimated using RUSLE factors: rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover crops (C), and conservation practices (P), and erosion factors maps were generated using GIS. Results indicate highest total erosion occurring in hill forests (13,374.3 t yr–1) and lowest total erosion occurring in grasslands (2.9 t yr–1). Hill forests showed high to very severe erosion due to steepness of hills, open forest types, and minimal use of conservation practices. Also, erosion hotspots (>15 t ha–1 yr–1) occurred in only 4.2% of the watershed, primarily in steep slopes. Overall, these results provide important guidelines to formulate management plans and informed decisions on soil conservation at local to regional levels. While the study is the first effort to assess soil erosion dynamics in the Girwari river watershed, potential for application in other basins largely exists.

scholarly journals Comparison of different approaches to LS factor calculations based on a measured soil loss under simulated rainfall.

2017 ◽  
Vol 12 (No. 2) ◽  
pp. 69-77 ◽  
Author(s):  
M. Hrabalíková ◽  
M. Janeček
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Soil Erosion ◽  
Soil Loss ◽  
Geographic Information ◽  
Experimental Plot ◽  
Simulated Rainfall ◽  
Slope Length ◽  
Digital Elevation ◽  
Elevation Model

Geographic Information Systems (GIS) in combination with soil loss models can enhance evaluation of soil erosion estimation. SAGA and ARC/INFO geographic information systems were used to estimate the topographic (LS) factor of the Universal Soil Loss Equation (USLE) that in turn was used to calculate the soil erosion on a long-term experimental plot near Prague in the Czech Republic. To determine the influence of a chosen algorithm on the soil erosion estimates a digital elevation model with high accuracy (1 × 1 m) and a measured soil loss under simulated rainfall were used. These then provided input for five GIS-based and two manual procedures of computing the combined slope length and steepness factor in the (R)USLE. The results of GIS-based (R)USLE erosion estimates from the seven procedures were compared to the measured soil loss from the 11 m long experimental plot and from 38 rainfall simulations performed here during 15 years. The results indicate that the GIS-based (R)USLE soil loss estimates from five different approaches to calculation of LS factor are lower than the measured average annual soil loss. The two remaining approaches over-predicted the measured soil loss. The best method for LS factor estimation on field scale is the original manual method of the USLE, which predicted the average soil loss with 6% difference from the measured soil loss. The second method is the GIS-based method that concluded a difference of 8%. The results of this study show the need for further work in the area of soil erosion estimation (with particular focus on the rill/interrill ratio) using the GIS and USLE. The study also revealed the need for an application of the same approach to catchment area as it might bring different outcomes.

scholarly journals Estimation of annual soil erosion dynamics (2005 - 2015) in Pakistan using Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Climatic Factors ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Conservation Practice ◽  
Administrative Units ◽  
Soil Loss Equation

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.

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