81.
Soil hydraulic response to land-use change associated with the recent soybean expansion at the Amazon agricultural frontier
Scheffler, Raphael; Neill, Christopher; Krusche, Alex V ...
08/2011
Publication
Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was ...
published in Agriculture, Ecosystems & Environment 144 (2011): 281–289, doi:10.1016/j.agee.2011.08.016.
Clearing for large-scale soy production and the displacement of cattle-breeding bysoybeans are major features of land-use change in the lowland Amazon that canalter hydrologic properties of soils and the runoff generation over large areas. Wemeasured infiltrability and saturated hydraulic conductivity (Ksat) under naturalforest, pasture, and soybeans on Oxisols in a region of rapid soybean expansion inMato Grosso, Brazil. The forest-pasture conversion reduced infiltrability from 1258 to100 mm/h and Ksat at all depths. The pasture-soy conversion increased infiltrabilityfrom 100 to 469 mm/h (attributed to shallow disking), did not affect Ksat at 12.5 cm,but decreased Ksat at 30 cm from 122 to 80 mm/h, suggesting that soybeancultivation enhances subsoil compaction. Permeability decreased markedly withdepth under forest, did not change under pasture, and averaged out at one fourth theforest value under soybeans with a similar pattern of anisotropy. Comparisons ofpermeability with rainfall intensities indicated that land-use change did not alter thepredominantly vertical water movement within the soil. We conclude that thislandscape is well buffered against land-use changes regarding near-surfacehydrology, even though short-lived ponding and perched water tables may occurlocally during high-intensity rainfall on pastures and under soybeans.
This research was supported by the US National Science Foundation (NSF) grantDEB-0640661 and the Fundação de Amparo à Pesquisa do Estado de São Paulo(FAPESP).
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82.
Water Quality Monitoring in Large Reservoirs Using Remote Sensing and Neural Networks
Ribeiro, H.M.C.; Almeida, A.C.; Rocha, B.R.P. ...
Revista IEEE América Latina,
09/2008, Letnik:
6, Številka:
5
Journal Article
Water quality monitoring in lakes and reservoirs using water samples and laboratorial analysis is expensive and time consuming. The use of artificial neural networks to predict water quality using ...
satellite images shows great potential to make this process faster and at lower costs. This article discusses an indirect method to estimate the concentration of pigments (chlorophyll-a), an optically active parameter in water quality. A model based on artificial neural networks, using radial base functions architecture, was developed to predict Tucurui's Reservoir chlorophyll-a concentrations. As input to the neural networks spectral information from Landsat imagery was used, while pigment concentration were used as output information. To train and validate the model we used data from the years 1987, 1988, 1995, 1999, 2000 and 2004. The tested model showed a correlation coefficient of 0.92 for the estimation of pigment (chlorophyll-a) concentrations, indicating its applicability to predict this water quality parameter.
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83.
Conversion to soy on the Amazonian agricultural frontier increases streamflow without affecting stormflow dynamics
Hayhoe, Shelby J; Neill, Christopher; Porder, Stephen ...
01/2011
Publication
This projectwas supported by grants from NSF (DEB-0640661) and the Fundaçao de Amparo àPesquisa do Estado de São Paulo (FAPESP 03/13172-2).
Large-scale soy agriculture in the southern Brazilian ...
Amazon now rivalsdeforestation for pasture as the region’s predominant form of land use change. Suchlandscape level change can have substantial consequences for local and regionalhydrology, which remain relatively unstudied. We examined how the conversion to soyagriculture influences water balances and stormflows using stream discharge (wateryields) and the timing of discharge (stream hydrographs) in small (2.5 to 13.5 km2)forested and soy headwater watersheds in the Upper Xingu Watershed in the state ofMato Grosso, Brazil. We monitored water yield for one year in three forested and foursoy watersheds. Mean daily water yields were approximately four times higher in soythan forested watersheds, and soy watersheds showed greater seasonal variability indischarge. The contribution of stormflows to annual streamflow in all streams was low (<13% of annual streamflow), and the contribution of stormflow to streamflow did notdiffer between land uses. If the increases in water yield observed in this study are typical,landscape-scale conversion to soy substantially alters water-balance, potentially alteringthe regional hydrology over large areas of the southern Amazon.
Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Global Change Biology 17 (2011): 1821–1833, doi:10.1111/j.1365-2486.2011.02392.x.
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84.
Amazon deforestation alters small stream structure, nitrogen biogeochemistry and connectivity to larger rivers
Deegan, Linda A; Neill, Christopher; Haupert, Christie L ...
08/2010
Publication
Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was ...
published in Biogeochemistry 105 (2011): 53-74, doi:10.1007/s10533-010-9540-4.
Human activities that modify land cover can alter the structure and biogeochemistry of small streams but these effects are poorly known over large regions of the humid tropics where rates of forest clearing are high. We examined how conversion of Amazon lowland tropical forest to cattle pasture influenced the physical and chemical structure, organic matter stocks and N cycling of small streams. We combined a regional ground survey of small streams with an intensive study of nutrient cycling using 15N additions in three representative streams: a second-order forest stream, a second-order pasture stream and a third-order pasture stream that were within several km of each other and on similar soils and landscape positions. Replacement of forest with pasture decreased stream habitat complexity by changing streams from run and pool channels with forest leaf detritus (50% cover) to grass-filled (63% cover) channel with runs of slow-moving water. In the survey, pasture streams consistently had lower concentrations of dissolved oxygen and nitrate (NO3-) compared with similar-sized forest streams. Stable isotope additions revealed that second-order pasture stream had a shorter NH4+ uptake length, higher uptake rates into organic matter components and a shorter 15NH4+ residence time than the second-order forest stream or the third-order pasture stream. Nitrification was significant in the forest stream (19% of the added 15NH4+) but not in the second-order pasture (0%) or third-order (6%) pasture stream. The forest stream retained 7% of added 15N in organic matter compartments and exported 53% (15NH4+ =34%; 15NO3- = 19%). In contrast, the second-order pasture stream retained 75% of added 15N, predominantly in grasses (69%) and exported only 4% as 15NH4+. The fate of tracer 15N in the third-order pasture stream more closely resembled that in the forest stream, with 5% of added N retained and 26% exported (15NH4+ = 9%; 15NO3- = 6%). These findings indicate that the widespread infilling by grass in small streams in areas deforested for pasture greatly increases the retention of inorganic N in the first- and second-order streams, which make up roughly three-fourths of total stream channel length in Amazon basin watersheds. The importance of this phenomenon and its effect on N transport to larger rivers across the larger areas of the Amazon Basin will depend on better evaluation of both the extent and the scale at which stream infilling by grass occurs, but our analysis suggests the phenomenon is widespread.
This work was supported by grants from the NASA Large-Scale Biosphere and Atmosphere Experiment (NCC5-686), the National Science Foundation (DEB-0315656) and the Fundação de Ámparo à Pesquisa do Estado de São Paulo.
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