Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making
Sustainable agriculture and eco-environment conservation face constant threats from soil erosion in mountainous regions. This study utilizes remote sensing and GIS support to predict soil erosion and sediment yield by applying the Revise Universal Equation Soil Loss (RUSLE) and Sediment Delivery Rat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23011354 |
| _version_ | 1797655089691754496 |
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| author | Quang-Viet Nguyen Yuei-An Liou Kim-Anh Nguyen Duy-Phien Tran |
| author_facet | Quang-Viet Nguyen Yuei-An Liou Kim-Anh Nguyen Duy-Phien Tran |
| author_sort | Quang-Viet Nguyen |
| collection | DOAJ |
| description | Sustainable agriculture and eco-environment conservation face constant threats from soil erosion in mountainous regions. This study utilizes remote sensing and GIS support to predict soil erosion and sediment yield by applying the Revise Universal Equation Soil Loss (RUSLE) and Sediment Delivery Ratio (SDR) models. The findings highlight that the basin adversely experiences an average annual soil erosion rate of 108.47 t ha−1 yr−1, leading to a significant sediment influx of 206.03 × 106 t/yr at downstream. The RUSLE-SDR model performs satisfactorily, with percent bias (PBIAS) values below 25%. Based on the RUSLE output, the study integrates a threshold of over 100 t ha−1 yr−1 into the adapted slopeland capability classification (SLCC), along with slope gradient derived from Digital Elevation Model (DEM) and soil depth, to categorize the entire basin into five capability classes. Each class is associated with specific soil erosion control treatments for agricultural activities and forestry. The study suggests the four land use/land cover (LULC) scenarios with different prioritizations, aimed to optimize land resource utilization and conserve the eco-environment. Scenarios #3 and #4, in particular, demonstrate promising benefits for the eco-environment by substantially increasing forest coverage to 81.27% and 85.07% of the total area, respectively. In contrast, scenarios #1 and #2 prioritize agricultural development. Due to the challenge posed by rugged terrains, the application of LULC scenarios must be adhered strictly, considering a specific class of the SLCC with its treatments. The study offers a timely and feasible approach for soil erosion investigation and land use adjustment to support effective basin management. However, ensuring the health and sustainability of the basin ecosystem may necessitate additional measures, such as proper planning for riparian zones and engineering solutions. |
| first_indexed | 2024-03-11T17:09:05Z |
| format | Article |
| id | doaj.art-2b8df413bf304b60b7e0e5cfc8bb46a2 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-11T17:09:05Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-2b8df413bf304b60b7e0e5cfc8bb46a22023-10-20T06:38:39ZengElsevierEcological Indicators1470-160X2023-11-01155110993Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-makingQuang-Viet Nguyen0Yuei-An Liou1Kim-Anh Nguyen2Duy-Phien Tran3Center for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli District, Taoyuan City 320317, Taiwan, ROC; University of Sciences, Hue University, 77-Nguyen Hue, Hue 530000, Viet NamCenter for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli District, Taoyuan City 320317, Taiwan, ROC; Corresponding author.Center for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli District, Taoyuan City 320317, Taiwan, ROC; Institute of Geography, Vietnam Academy of Science and Technology, 18-Hoang Quoc Viet, Hanoi 100000, Viet NamCenter for Space and Remote Sensing Research, National Central University, No. 300, Jhongda Rd., Jhongli District, Taoyuan City 320317, Taiwan, ROC; Institute of Geography, Vietnam Academy of Science and Technology, 18-Hoang Quoc Viet, Hanoi 100000, Viet NamSustainable agriculture and eco-environment conservation face constant threats from soil erosion in mountainous regions. This study utilizes remote sensing and GIS support to predict soil erosion and sediment yield by applying the Revise Universal Equation Soil Loss (RUSLE) and Sediment Delivery Ratio (SDR) models. The findings highlight that the basin adversely experiences an average annual soil erosion rate of 108.47 t ha−1 yr−1, leading to a significant sediment influx of 206.03 × 106 t/yr at downstream. The RUSLE-SDR model performs satisfactorily, with percent bias (PBIAS) values below 25%. Based on the RUSLE output, the study integrates a threshold of over 100 t ha−1 yr−1 into the adapted slopeland capability classification (SLCC), along with slope gradient derived from Digital Elevation Model (DEM) and soil depth, to categorize the entire basin into five capability classes. Each class is associated with specific soil erosion control treatments for agricultural activities and forestry. The study suggests the four land use/land cover (LULC) scenarios with different prioritizations, aimed to optimize land resource utilization and conserve the eco-environment. Scenarios #3 and #4, in particular, demonstrate promising benefits for the eco-environment by substantially increasing forest coverage to 81.27% and 85.07% of the total area, respectively. In contrast, scenarios #1 and #2 prioritize agricultural development. Due to the challenge posed by rugged terrains, the application of LULC scenarios must be adhered strictly, considering a specific class of the SLCC with its treatments. The study offers a timely and feasible approach for soil erosion investigation and land use adjustment to support effective basin management. However, ensuring the health and sustainability of the basin ecosystem may necessitate additional measures, such as proper planning for riparian zones and engineering solutions.http://www.sciencedirect.com/science/article/pii/S1470160X23011354Basin sustainabilityLand use adjustmentRUSLE modelSlopeland capability classificationSoil erosion |
| spellingShingle | Quang-Viet Nguyen Yuei-An Liou Kim-Anh Nguyen Duy-Phien Tran Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making Ecological Indicators Basin sustainability Land use adjustment RUSLE model Slopeland capability classification Soil erosion |
| title | Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making |
| title_full | Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making |
| title_fullStr | Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making |
| title_full_unstemmed | Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making |
| title_short | Enhancing basin sustainability: Integrated RUSLE and SLCC in land use decision-making |
| title_sort | enhancing basin sustainability integrated rusle and slcc in land use decision making |
| topic | Basin sustainability Land use adjustment RUSLE model Slopeland capability classification Soil erosion |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23011354 |
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