Impact of land-use and land-cover change on soil erosion using the RUSLE model and the geographic information system: a case of Temeji watershed, Western Ethiopia

Abstract The impact of land-use land-cover (LULC) change on soil resources is getting global attention. Soil erosion is one of the critical environmental problems worldwide with high severity in developing countries. This study integrates the Revised Universal Soil Loss Equation model with a geographic information system to estimate the impacts of LULC conversion on the mean annual soil loss in the Temeji watershed. In this study, LULC change of Temeji watershed was assessed from 2000 to 2020 by using 2000 Landsat ETM+ and 2020 Landsat OLI/TIRS images and classified using supervised maximum likelihood classification algorithms. Results indicate that the majority of the LULC in the study area is vulnerable to soil erosion. High soil loss is observed when grassland and forest land were converted into cultivated land with a mean soil loss of 88.8 and 86.9 t/ha/year in 2020. Results revealed that about 6,608.5 ha (42.8%) and 8,391.8 ha (54.4%) were categorized under severe classes in 2000 and 2020, respectively. Accordingly, the soil loss severity class is directly correlated with the over-exploitation of forest resources and grasslands for agricultural purposes. These results can be useful for advocacy to enhance local people and stakeholder's participation toward soil and water conservation practices.

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Land Use and Land Cover Changes and Its Impact on Soil Erosion in Stung Sangkae Catchment of Cambodia

Sustainability ◽

10.3390/su13169276 ◽

2021 ◽

Vol 13 (16) ◽

pp. 9276

Author(s):

Nareth Nut ◽

Machito Mihara ◽

Jaehak Jeong ◽

Bunthan Ngo ◽

Gilbert Sigua ◽

...

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

Water Conservation ◽

Soil Loss ◽

Hot Spot ◽

Control Measures ◽

Economic Activities ◽

Mekong River Commission ◽

The Impact

Agricultural expansion and urban development without proper soil erosion control measures have become major environmental problems in Cambodia. Due to a high population growth rate and increased economic activities, land use and land cover (LULC) changes will cause environmental disturbances, particularly soil erosion. This research aimed to estimate total amounts of soil loss using the Revised Universal Soil Loss Equation (RUSLE) model within a Geographic Information System (GIS) environment. LULC maps of Japan International Cooperation Agency (JICA) 2002 and Mekong River Commission (MRC) 2015 were used to evaluate the impact of LULC on soil erosion loss in Stung Sangkae catchment. LULC dynamics for the study periods in Stung Sangkae catchment showed that the catchment experienced a rapid conversion of forests to paddy rice fields and other croplands. The results indicated that the average soil loss from the catchment was 3.1 and 7.6 t/ha/y for the 2002 and 2015 periods, respectively. The estimated total soil loss in the 2002 and 2015 periods was 1.9 million t/y and 4.5 million t/y, respectively. The soil erosion was accelerated by steep slopes combined with the high velocity and erosivity of stormwater runoff. The spatial distribution of soil loss showed that the highest value (14.3 to 62.9 t/ha/y) was recorded in the central, southwestern and upland parts of the catchment. It is recommended that priority should be given to erosion hot spot areas, and appropriate soil and water conservation practices should be adopted to restore degraded lands.

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

Journal of Water and Climate Change ◽

10.2166/wcc.2021.198 ◽

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.

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Impact of Land Use and Land Cover Change on Soil Erosion Using Rusle Model And Gis: A Case of Temeji Watershed, Western Ethiopia

10.21203/rs.3.rs-100340/v1 ◽

2020 ◽

Author(s):

Mitiku Badasa Moisa ◽

Daniel Assefa Negash ◽

Biratu Bobo Merga ◽

Dessalegn Obsi Gemeda

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

Water Conservation ◽

Soil Loss ◽

Mitigation Strategies ◽

Cultivated Land ◽

Rusle Model ◽

Erosion Risk ◽

The Impact

Abstract BackgroundThe impact of Land Use/Land Cover (LULC) conversion on soil resources is getting global attention. Soil erosion is one the critical environmental problems worldwide with high severity in developing countries due to land degradation. This study integrates the Revised Universal Soil Loss Equation (RUSLE) model with a Geographic Information Systems (GIS) to estimate the impacts of LU/LC conversion on the mean annual soil loss in Temeji watershed. In this study, LU/LC change of Temeji watershed were assessed from 2000 to 2020 by using 2000 Landsat ETM+ and 2020 Landsat OLI/TIRS images and classified using supervised maximum likelihood classification algorithms. ResultsResults indicates that majority of the LU/LC in the study area is vulnerable to soil erosion. Our findings show that cultivated land had the highest average soil loss rate in Temeji watershed. High soil loss is observed when grass and forest land were converted into cultivated land with mean soil loss of 88.8t/ha/yr and 86.9t/ha/yr in 2020. Results revealed that about 6608.5ha (42.8%) and 8391.8ha (54.4%) were categorized under severe classes in 2000 and 2020, respectively.ConclusionsThe results can definitely support policy makers and environmental managers in implementation of soil and water conservation practices and erosion risk prevention and mitigation strategies in Temeji watershed.

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Modeling Land Use and Land Cover Dynamic Using Geographic Information System and Markov-CA

Geosfera Indonesia ◽

10.19184/geosi.v5i2.17596 ◽

2020 ◽

Vol 5 (2) ◽

pp. 210

Author(s):

Millary Agung Widiawaty ◽

Arif Ismail ◽

Moh. Dede ◽

N. Nurhanifah

Keyword(s):

Land Use ◽

Information System ◽

Geographic Information System ◽

Land Cover ◽

Agricultural Land ◽

Dynamic Models ◽

Geographic Information ◽

Google Earth ◽

Road Density ◽

Lulc Change

The need for built-up area increases along with a rise in population growth in many regions. This phenomenon leads to a tremendous change in agricultural land and decrease in the environmental carrying capacity. Therefore, this study aims to determine Land Use and Land Cover (LULC) dynamics and the drivers used for its modeling in 2030. This is a quantitative study, which uses the dynamic models of Geographic Information System (GIS) and Markov-CA. Data were obtained from the CNES-Airbus satellite imageries in 2009, 2014, and 2019 by using Google Earth at East Cirebon. The drivers include road density, distance to CBD, total population, distance to settlements, land slope and distance to rivers. The interaction between drivers and LULC change was analyzed using binary logistic regression. The results showed that the rise of built-up area reached 36.4 percent and causes the loss of 0.78 km2 of agricultural land from 2009 to 2019. The LULC simulation in 2030 shows an increase in the built-up area by 82.85 percent with probabilities above 0.6. Meanwhile the significant drivers for changes include road density and distance to settlements. In conclusion, efforts to reduce LULC change in agricultural land into built-up area is by re-strengthening spatial planning-based environmental awareness for the community. Keywords: Built-up area; GIS; LULC; Markov-CA; Spatial modeling Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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