ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2013-11-16
    Electronic ISSN: 1539-1663
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2013-11-16
    Description: To better understand flow pathways and patterns in the subsurface, a stable isotope monitoring network was established at the Susquehanna-Shale Hills Critical Zone Observatory (SSHCZO). Soil water samples were collected approximately biweekly using suction-cup lysimeters installed at multiple depths along four different transects in the catchment. Groundwater and stream water were collected daily in the valley using automatic samplers, while precipitation samples were collected automatically on an event basis. The 3+ years (2008–2012) of monitoring data showed strong seasonal precipitation isotope compositions, which were imprinted in seasonal patterns of soil water at different spatial locations and depths. The groundwater isotope composition remained relatively constant throughout the year and closely matched the yearly amount-weighted precipitation average, suggesting groundwater received recharge water in each season, although recharge mechanisms differed between growing and nongrowing seasons. Soil water samples showed clear attenuation with depth, with the largest variability in the shallow soil water (≤30 cm) mirroring precipitation inputs, moderate variability in the intermediate depths (40–100 cm), and the least variability in the deep soil water (≥120 cm) where the average remained near the groundwater average. Soil water isotope composition profiles also provided clear evidence for preferential flow occurring both laterally and vertically in different seasons and at various soil depths in the catchment. Putting all together, the extensive dataset of soil water isotopic compositions obtained in this study have provided a number of insights into complex subsurface hydrologic processes that are transferable to other similar landscapes.
    Electronic ISSN: 1539-1663
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    facet.materialart.
    Unknown
    Soil Science Society of America (SSSA)
    Publication Date: 2016-09-24
    Description: The Critical Zone (CZ) is the thin layer of the Earth’s terrestrial surface and near-surface environment that ranges from the top of the vegetation canopy to the bottom of the weathering zone and plays fundamental roles in sustaining life and humanity. The past few years have seen a number of Critical Zone Observatories (CZOs) being developed following the first CZOs established in the United States in 2007. This update summarizes major research findings in CZ science achieved in the past 5 yr or so (2011–2016), especially those obtained from recognized CZOs. A conceptual framework of "deep" science—deep time, deep depth, and deep coupling—is used to synthesize recent CZ studies across a broad range of spatial and temporal scales. This "deep" science concept emphasizes the integration of Earth surface processes that underlies the contributions of CZ science to terrestrial environmental research. We identify some main knowledge gaps and major opportunities to advance the frontiers of CZ science. We advocate that the CZ scientific community work toward a global network of CZOs to link sites, people, ideas, data, models, and tools. We hope that this update can stimulate continuous scientific advancement and practical applications of CZ science worldwide.
    Electronic ISSN: 1539-1663
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2015-07-21
    Description: Spatiotemporal patterns of soil moisture are important for understanding landscape hydrologic processes. While the spatiotemporal characteristics of soil moisture content () have been frequently studied, those of soil matric potential () remain sparse. We investigated the spatial variability and temporal stability of at multiple depths (10–100 cm) across a 7.9-ha forested catchment and their relationships with soil type, terrain, and season. The results from a 5.5-yr database consisting of 62 sites clearly showed a downward parabolic trend in spatial variability with decreasing spatial mean values (i.e., becoming drier) across all depths. The catchment’s overall spatial variability of generally increased with soil depth and was relatively high during summer and fall. Sand and silt contents were significant factors ( p 〈 0.05) influencing in surface layers (0–20 cm), while values in the subsurface (40–100 cm) were highly correlated with elevation. The temporal stability of spatial pattern was generally higher in the surface soil than the subsoil but weaker in the spring than in other seasons. Moreover, relatively dry areas tended to have less evident temporal stability at each depth, attributable to a higher sensitivity of to changes in when the soil is dry. Finally, at least one of the representative sites of the catchment mean at each depth was found within a south-facing concave hillslope at mid-elevation, and these sites were different from the representative sites of the catchment mean . The results of this study have implications for upscaling soil water from point-based observations to hillslope and catchment scales.
    Electronic ISSN: 1539-1663
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...