GIS Based Universal Soil Erosion Estimation in District Chakwal Punjab, Pakistan

Soil erosion is a serious environmental problem faced by district Chakwal. Unpredictable short term and high intensity rainfall, improper cultivation and deforestation have accelerated the soil erosion in the district. The agricultural productivity of the study area can be enhanced by understanding, estimating and controlling the root causes of soil erosion. This study was undertaken to estimate and spatially represent the rate of average annual soil erosion in Chakwal using GIS/RS techniques. The soil erosion was estimated using Universal Soil Loss Equation (USLE) model. To find out parameters of USLE, ASTER GDEM of 30 m resolution was used to estimate slope length and elevation of the study area. Landsat 8 satellite imagery of year 2019, was used to prepare land use map using supervised classification. Soil map with texture and geomorphology was used to identify soils of study area and rainfall data of last 7 years was also studied. Finally, the soil loss has been computed using raster calculator of ArcGIS 10.2 software. The average annual soil loss was predicted up to 268,619 tons/acre/year, of which maximum soil erosion was occurring near the steep slopes and river channels. It is necessary to adapt sustainable land management practices to reduce the risk of further soil erosion, by adopting rainwater harvesting and choosing right crops for suitable soil types.

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

10.22541/au.160946369.92099648/v1 ◽

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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Prioritization of Watershed Using Remote Sensing and Geographic Information System

Sustainability ◽

10.3390/su13169456 ◽

2021 ◽

Vol 13 (16) ◽

pp. 9456

Author(s):

Devendra Kumar ◽

Arvind Dhaloiya ◽

Ajeet Singh Nain ◽

Mahendra Paal Sharma ◽

Amandeep Singh

Keyword(s):

Remote Sensing ◽

Information System ◽

Soil Erosion ◽

Natural Resources ◽

Best Management Practices ◽

Soil Loss ◽

Management Practices ◽

Agricultural Land ◽

Geographical Information ◽

Slope Length

Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI & QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha−1 yr−1 in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.

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Spatial Targeting of Soil Loss Using RUSLE in GIS: the case of Asokore Mampong Municipality, Ghana

Journal of Applied Geospatial Information ◽

10.30871/jagi.v3i1.1029 ◽

2019 ◽

Vol 3 (1) ◽

pp. 166-172 ◽

Cited By ~ 1

Author(s):

Gift Dumedah ◽

Evans Kyeremanteng ◽

Ema Dari

Keyword(s):

Soil Erosion ◽

Land Cover ◽

Soil Loss ◽

Vegetation Index ◽

Management Practices ◽

Graphical Model ◽

Thermal Emission ◽

Mitigation Measures ◽

Slope Length ◽

Public Data

Soil erosion is a serious environmental problem that is associated with societal impacts including flooding, poor water quality, and loss of plant nutrient leading to low agricultural productivity. Soil erosion wears away the top soil and is controlled by the interaction between several factors including rainfall, steepness of slope, length of slope, vegetation cover, and land management practices. This study developed Geographic Information System (GIS) graphical model based on the Revised Universal Soil Loss Equation (RUSLE), to calculate soil loss in the Asokore Mampong Municipality of the Ashanti region, Ghana. The estimated soil loss was examined the spatial patterns of soil loss and intensity per areas, as an important method for proper planning of management measures. The graphical model was developed using the popular open source GIS software, QGIS, ensuring the availability of the model, automation for any specific area, and its execution to the general public. Data sources used include Digital Elevation Model (DEM) derived from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), soil properties data obtained from the Global Soil Grids, land cover data from the Global Land Cover by National Mapping Organization (GLCNMO), NDVI (normalized difference vegetation index) data from MODIS (MOD13Q1, 16 Day), and rainfall data from GPCC version 7 (Global Precipitation Climatology Centre). Our results show high levels of soil loss (in tons per hectare per year) in the Municipality, with the capability to spatially target mitigation measures leading to cost effective environmental management.

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Impact Assessment of Land use / Land Cover Change on Soil Erosion and Rural Livelihood in Andit Tid Watershed, North Shewa, Ethiopia

Asia Pacific Journal of Energy and Environment ◽

10.18034/apjee.v4i2.242 ◽

2017 ◽

Vol 4 (2) ◽

pp. 49-56

Author(s):

Abrham Tezera Gessesse ◽

Tilashwork Chanie ◽

Tesfaye Feyisa ◽

Abdlesemed Jemal

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

Land Cover Change ◽

Soil Loss ◽

Rainwater Harvesting ◽

Animal Feed ◽

Landsat 8 ◽

Land Use Land Cover ◽

Social Data

Land use, which is use of land by human for different purposes, is influenced by two broad sets of forces human needs (socio-economic) and environmental features and processes (biophysical). The study was carried out at Andit Tid watershed one of SCRP research unit founded in 1982, located on 390 43’E 9048’N. This research has aimed to assess the trend and main driving force of land use and land cover change (LULCC) within the catchment / watershed during the last two decades and its impact on soil erosion. Structural questioner was used to collect social data from 8% of the total household. Landsat 5 and Landsat 8 Enhanced Thematic Mapper (ETM) and supervised image classification used to identify land use/ land cover change of the study area for 1994 and 2014 years, respectively. TESTMAIN and SPSS version 16 Statistical software’s were used for Soil loss calculation and social data analysis, respectively. The result indicates that, there is expansion of cultivated land by 11.33% (44.55ha) while reduction in natural shrub lands by 7.3 % (35.73ha). The main driving forces of land use land cover change are high number of family member, small land holding size and minimum asset own per household, lower educational level of the household, the household mainly occupied on agriculture and there is lack of animal feed. This change forced farmers to collect cereal crops based on suitability area, sale livestock, use organic and inorganic fertilizer and use improved variety due to low crop productivity. The LULC change has an impact on decline soil fertility, cause serious soil erosion problem with in farmland/watershed. The result also indicated that soil loss reached 3655 ton per annum from the watershed. Therefore, proper handling and land use system need to be implemented, rainwater harvesting structures and soil and water conservation practice need to be encouraged in order reduce soil loss.

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Soil erosion in sloping vineyards under conventional and organic land use managements (Saar-Mosel Valley, Germany)

Cuadernos de Investigación Geográfica ◽

10.18172/cig.3161 ◽

2017 ◽

Vol 43 (1) ◽

pp. 119 ◽

Cited By ~ 31

Author(s):

M. Kirchhoff ◽

J. Rodrigo-Comino ◽

M. Seeger ◽

J.B. Ries

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Management Practices ◽

Conventional Tillage ◽

Erosion Processes ◽

Natural Rainfall ◽

Total Runoff ◽

Lack Of Information ◽

Steep Slopes ◽

Runoff And Soil Loss

German vineyards are one of the land uses most prone to soil erosion. Due to their placement on mainly steep slopes and non-conservative cultivation practices, runoff and soil loss are a serious problem for wine growers. In the Saar-Mosel valley (Rhineland-Palatinate, Germany), there is a tendency towards organic management of vineyards with protective grass cover in the inter-rows. Since there is a lack of information about organic-conventional tillage in German vineyards related to soil erosion processes, this study presents a comparison between these two soil management practices. For this purpose, 22 rainfall simulations were performed as well as a medium-term monitoring by using 4-paired Gerlach troughs in two experimental sites in the Saar-Mosel valley. The mean simulated runoff coefficient and suspended sediment load in conventional vineyards amounted up to 23.3% and 33.75 g m-2, respectively. In the organic site, runoff and soil loss were only recorded in one out of the 11 simulations. Runoff and sediment was collected in the Gerlach troughs for 33 natural rainfall events. In the conventional vineyard, the total measured soil loss was 3314.63 g m-1 and 6503.77 g m-1 and total runoff volumes were 105.52 L m-1 and 172.58 L m-1. In the organic site, total soil losses reached 143.16 g m-1 and 258.89 g m-1 and total runoff was 21.65 L m-1 and 12.69 L m-1. When soil loss was measured without corresponding runoff or precipitation, soil erosion was activated by tillage or trampling. Finally, the conventional vineyard showed a higher variability in soil loss and runoff suggesting less predictable results.

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Prioritization of Sub-Watersheds to Sediment Yield and Evaluation of Best Management Practices in Highland Ethiopia, Finchaa Catchment

Land ◽

10.3390/land10060650 ◽

2021 ◽

Vol 10 (6) ◽

pp. 650

Author(s):

Wakjira Takala Dibaba ◽

Tamene Adugna Demissie ◽

Konrad Miegel

Keyword(s):

Soil Erosion ◽

Best Management Practices ◽

Sediment Yield ◽

Soil Loss ◽

Crop Production ◽

Management Practices ◽

Assessment Tool ◽

Swat Model ◽

Sediment Yields ◽

Soil And Water

Excessive soil loss and sediment yield in the highlands of Ethiopia are the primary factors that accelerate the decline of land productivity, water resources, operation and function of existing water infrastructure, as well as soil and water management practices. This study was conducted at Finchaa catchment in the Upper Blue Nile basin of Ethiopia to estimate the rate of soil erosion and sediment loss and prioritize the most sensitive sub-watersheds using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated using the observed streamflow and sediment data. The average annual sediment yield (SY) in Finchaa catchment for the period 1990–2015 was 36.47 ton ha−1 yr−1 with the annual yield varying from negligible to about 107.2 ton ha−1 yr−1. Five sub-basins which account for about 24.83% of the area were predicted to suffer severely from soil erosion risks, with SY in excess of 50 ton ha−1 yr−1. Only 15.05% of the area within the tolerable rate of loss (below 11 ton ha−1yr−1) was considered as the least prioritized areas for maintenance of crop production. Despite the reasonable reduction of sediment yields by the management scenarios, the reduction by contour farming, slope terracing, zero free grazing and reforestation were still above the tolerable soil loss. Vegetative contour strips and soil bund were significant in reducing SY below the tolerable soil loss, which is equivalent to 63.9% and 64.8% reduction, respectively. In general, effective and sustainable soil erosion management requires not only prioritizations of the erosion hotspots but also prioritizations of the most effective management practices. We believe that the results provided new and updated insights that enable a proactive approach to preserve the soil and reduce land degradation risks that could allow resource regeneration.

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Slope Length Effects on Soil Loss for Steep Slopes

Soil Science Society of America Journal ◽

10.2136/sssaj2000.6451759x ◽

2000 ◽

Vol 64 (5) ◽

pp. 1759-1763 ◽

Cited By ~ 154

Author(s):

B. Y. Liu ◽

M. A. Nearing ◽

P. J. Shi ◽

Z. W. Jia

Keyword(s):

Soil Loss ◽

Slope Length ◽

Steep Slopes ◽

Length Effects

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Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)

Remote Sensing ◽

10.3390/rs14020348 ◽

2022 ◽

Vol 14 (2) ◽

pp. 348

Author(s):

Yashon O. Ouma ◽

Lone Lottering ◽

Ryutaro Tateishi

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Soil Degradation ◽

Bare Soil ◽

Landsat 8 ◽

Arid Environments ◽

Degradation Index ◽

Erosivity Index ◽

Loss Index ◽

Very High

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

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RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

10.21203/rs.3.rs-250848/v1 ◽

2021 ◽

Author(s):

Habtamu Tamiru ◽

Meseret Wagari

Keyword(s):

Soil Erosion ◽

River Basin ◽

Soil Loss ◽

Annual Rainfall ◽

Rainfall Erosivity ◽

Landsat 8 ◽

Land Resources ◽

Rusle Model ◽

Factor C ◽

Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

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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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