Keywords
SWAT+, Soil erosion, crop phenology, MUSLE, LAI
Start Date
16-9-2020 9:20 AM
End Date
16-9-2020 9:40 AM
Abstract
Africa, like many other continents that largely depend on agriculture, is faced with soil erosion that has caused a serious challenge for food production and this is expected to persist in the 21st century. However, Africa has been under-represented in soil erosion and sediment yield studies with the existing African studies focusing on small spatial units (farms to small catchments) with less emphasis on agricultural land use representation. In this study, we developed a SWAT+ soil erosion yield model for Africa that incorporates crop phenology and management practices using global data sets. SWAT+ is a semi-distributed hydrological model that utilizes the Modified Universal Soil Loss Equation (MUSLE) equation as an erosion algorithm. During model set up, cropping seasons, irrigation application, fertilizer and manure applications were included in the model using decision tables for a more accurate representation. The relationship between soil erosion and Leaf Area Index (LAI) was explored at a monthly temporal scale and model outputs were evaluated by comparison with existing global soil erosion and sediment yield studies. The SWAT+ simulations revealed that the implementation of crop phenology and management practices resulted in a strong reduction of about 50% in the soil erosion estimates as compared to the default model set up, with months of higher LAI resulting in the greatest reduction in soil erosion. The relationship between soil erosion and LAI indicates that accurate representation of crop phenology has a significant impact on soil erosion and sediment yield estimates. This study findings present a critical step towards incorporation of crop phenology in continental SWAT+ soil erosion and sediment yield studies.
Modelling of erosion in Africa using SWAT+
Africa, like many other continents that largely depend on agriculture, is faced with soil erosion that has caused a serious challenge for food production and this is expected to persist in the 21st century. However, Africa has been under-represented in soil erosion and sediment yield studies with the existing African studies focusing on small spatial units (farms to small catchments) with less emphasis on agricultural land use representation. In this study, we developed a SWAT+ soil erosion yield model for Africa that incorporates crop phenology and management practices using global data sets. SWAT+ is a semi-distributed hydrological model that utilizes the Modified Universal Soil Loss Equation (MUSLE) equation as an erosion algorithm. During model set up, cropping seasons, irrigation application, fertilizer and manure applications were included in the model using decision tables for a more accurate representation. The relationship between soil erosion and Leaf Area Index (LAI) was explored at a monthly temporal scale and model outputs were evaluated by comparison with existing global soil erosion and sediment yield studies. The SWAT+ simulations revealed that the implementation of crop phenology and management practices resulted in a strong reduction of about 50% in the soil erosion estimates as compared to the default model set up, with months of higher LAI resulting in the greatest reduction in soil erosion. The relationship between soil erosion and LAI indicates that accurate representation of crop phenology has a significant impact on soil erosion and sediment yield estimates. This study findings present a critical step towards incorporation of crop phenology in continental SWAT+ soil erosion and sediment yield studies.
Stream and Session
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