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  • 1
    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Hydrology: Regional Studies 4B (2015): 108-122, doi:10.1016/j.ejrh.2015.05.010.
    Description: This study assessed the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations was improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.
    Description: This study was supported by the US National Science Foundation (DEB-0949996, DEB-0743703), the Gordon and Betty Moore Foundation, and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, process 135648/2011-4).
    Keywords: Evapotranspiration ; Streamflow ; Modeling ; Xingu Basin ; Amazon ; Cerrado
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2022-10-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Costa Jr, C., Galford, G. L., Coe, M. T., Macedo, M., Jankowski, K., O’Connell, C., & Neill, C. Modeling nitrous oxide emissions from large-scale intensive cropping systems in the southern Amazon. Frontiers in Sustainable Food Systems, 5, (2021): 701416. https://doi.org/10.3389/fsufs.2021.701416.
    Description: Nitrogen (N) fertilizer use is rapidly intensifying on tropical croplands and has the potential to increase emissions of the greenhouse gas, nitrous oxide (N2O). Since about 2005 Mato Grosso (MT), Brazil has shifted from single-cropped soybeans to double-cropping soybeans with maize, and now produces 1.5% of the world's maize. This production shift required an increase in N fertilization, but the effects on N2O emissions are poorly known. We calibrated the process-oriented biogeochemical DeNitrification-DeComposition (DNDC) model to simulate N2O emissions and crop production from soybean and soybean-maize cropping systems in MT. After model validation with field measurements and adjustments for hydrological properties of tropical soils, regional simulations suggested N2O emissions from soybean-maize cropland increased almost fourfold during 2001–2010, from 1.1 ± 1.1 to 4.1 ± 3.2 Gg 1014 N-N2O. Model sensitivity tests showed that emissions were spatially and seasonably variable and especially sensitive to soil bulk density and carbon content. Meeting future demand for maize using current soybean area in MT might require either (a) intensifying 3.0 million ha of existing single soybean to soybean-maize or (b) increasing N fertilization to ~180 kg N ha−1 on existing 2.3 million ha of soybean-maize area. The latter strategy would release ~35% more N2O than the first. Our modifications of the DNDC model will improve estimates of N2O emissions from agricultural production in MT and other tropical areas, but narrowing model uncertainty will depend on more detailed field measurements and spatial data on soil and cropping management.
    Description: This work was supported by National Science Foundation (NSF#1257944) and CNPq-Ciências Sem Fronteiras Post-Doctoral Fellowship (249380/2013-7).
    Keywords: GHG emission ; Agriculture ; Nitrogen fertilization management ; Amazon ; Food system
    Repository Name: Woods Hole Open Access Server
    Type: Article
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