ABSTRACT Cover crops, a promising strategy to increase soil organic carbon (SOC) storage in croplands and mitigate climate change, have typically been shown to benefit soil carbon (C) storage from increased plant C inputs. However, input‐driven C benefits may be augmented by the reduction of C outputs induced by cover crops, a process that has been tested by individual studies but has not yet been synthesized. Here we quantified the impact of cover crops on organic C loss via soil erosion (SOC erosion) and revealed the geographical variability at the global scale. We analyzed the field data from 152 paired control and cover crop treatments from 57 published studies worldwide using meta‐analysis and machine learning. The meta‐analysis results showed that cover crops widely reduced SOC erosion by an average of 68% on an annual basis, while they increased SOC stock by 14% (0–15 cm). The absolute SOC erosion reduction ranged from 0 to 18.0 Mg C−1 ha−1 year−1and showed no correlation with the SOC stock change that varied from −8.07 to 22.6 Mg C−1 ha−1 year−1at 0–15 cm depth, indicating the latter more likely related to plant C inputs. The magnitude of SOC erosion reduction was dominantly determined by topographic slope. The global map generated by machine learning showed the relative effectiveness of SOC erosion reduction mainly occurred in temperate regions, including central Europe, central‐east China, and Southern South America. Our results highlight that cover crop‐induced erosion reduction can augment SOC stock to provide additive C benefits, especially in sloping and temperate croplands, for mitigating climate change.
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Soil Loss Risk Analysis for Construction Activities
Construction-related ground-disturbing activities leave exposed land susceptible to soil loss and increase the risk of polluting adjacent waterbodies with sediment-laden discharge. State and federal regulations require stormwater pollution prevention plans to be implemented during construction to mitigate the impact of stormwater runoff. Areas prone to soil loss can be identified early in site planning using soil loss modeling. Identification of these critical areas could influence the design and placement of erosion and sediment control practices. The Revised Universal Soil Loss Equation (RUSLE) can be applied to estimate the soil loss on construction sites in tonnes per Ha per year (tons/acre/year) by considering factors of rainfall erosivity, soil erodibility, length of slope, erosion control, and sediment control. This study integrates geographic information system (GIS) with RUSLE to create soil loss models for residential, commercial, and highway construction scenarios in the contiguous U.S.A. These three construction types were modeled in various locations throughout the country to assess erosive risk. Soil loss outputs were categorized into five risk tiers ranging from very low to very high. Southeastern states had the highest estimated soil loss during residential, commercial, and highway construction, reaching rates of 1,464, 706, and 1,302 tonnes per Ha per year (653, 315, and 581 tons/acre/year), respectively. This study provides a customizable model for any site-specific slope-length factor outside of the three construction scenarios modeled. Integration of GIS provides a unique opportunity to apply RUSLE across a larger landscape. The presented macro-scale data can be used for the design of erosion and sediment control practices.
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- Award ID(s):
- 1828942
- PAR ID:
- 10350857
- Date Published:
- Journal Name:
- Transportation Research Record: Journal of the Transportation Research Board
- Volume:
- 2676
- Issue:
- 6
- ISSN:
- 0361-1981
- Page Range / eLocation ID:
- 503 to 513
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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