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  • 1
    In: Geophysical Research Letters, 16 July 2015, Vol.42(13), pp.5299-5308
    Description: Previous studies of streamwater transit time distributions (TTDs) used isotope tracer information from open precipitation (OP) as inputs to lumped watershed models that simulate the stream isotopic composition to estimate TTD. However, in forested catchments passage of rainfall through the canopy will alter the tracer signature of throughfall (TF) via interception. Here we test the effect of using TF instead of OP on TTD estimates. We sampled a 0.39 km catchment (Wüstebach, Germany) for a 19 month period using weekly precipitation and stream isotope data to evaluate changes in stream isotope simulation and TTDs. We found that TF had different effects on TTDs for δO and δH, with TF leading to up to 4 months shorter transit times. TTDs converged for both isotopes only when using TF. TF improved the stream isotope simulations. These results demonstrate the importance of canopy‐induced isotope tracer changes in estimating streamwater TTDs in forested catchments. TTDs are affected by throughfall isotope data A simple correction factor can partly account for throughfall effects Using throughfall isotope data is necessary for accurate TTD estimates
    Keywords: Interception ; Throughfall ; Transit Time Distribution ; Stable Isotopes ; Isotope Hydrology ; Catchment Hydrology
    ISSN: 0094-8276
    E-ISSN: 1944-8007
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  • 2
    In: Geophysical Research Letters, 16 August 2018, Vol.45(15), pp.7571-7579
    Description: For the first time, we combine depth‐specific soil information obtained from the quantitative inversion of ground‐based multicoil electromagnetic induction data with the airborne hyperspectral vegetation mapping of 1 × 1‐m pixels including Sun‐induced fluorescence () to understand how subsurface structures drive above‐surface plant performance. Hyperspectral data were processed to quantitative and selected biophysical canopy maps, which are proxies for actual photosynthetic rates. These maps showed within‐field spatial patterns, which were attributed to paleo‐river channels buried at around 1‐m depth. The soil structures at specific depths were identified by quantitative electromagnetic induction data inversions and confirmed by soil samples. Whereas the upper plowing layer showed minor correlation to the plant data, the deeper subsoil carrying vital plant resources correlated substantially. Linking depth‐specific soil information with plant performance data may greatly improve our understanding and the modeling of soil‐vegetation‐atmosphere exchange processes. Plants interact with soil. This is intuitive, although we know little about the subsurface structure because we cannot see it. At first glance, all soil may look the same, yet healthy plants can survive beside withered ones. We investigate the soil‐plant interaction in an agricultural field situated in an area characterized by ancient (paleo‐) river channels. These channels formed in sandy‐gravelly material due to melting water after last glaciation, were then filled up with fine aeolien sediments, overlaid with soils up to 1 m thick, and are no longer visible at the surface. However, crops grow in meandering/braiding patterns that can be seen on satellite images, for example. To explain this, the subsurface structural geometry must be known. We combine ground‐based electromagnetic induction data inversion results with airborne hyperspectral measurements to reveal the soil depths driving plant performance (photosynthetic activity and growth). Contrary to expectations, the deeper subsoil and not the plowing layer controls plant performance at the investigated site. Plants above the buried paleoriver channels find nutrients and water, whereas the surrounding plants in gravelly soil suffer, especially during drought. These results improve our understanding of soil‐plant interaction, which may improve soil‐vegetation‐atmosphere exchange process modeling and harvest predictability. Soil structures at depth were obtained by quantitative 3‐D electromagnetic induction data inversions not by apparent electrical conductivity maps Deeper subsoil characteristics correlate with airborne Sun‐induced fluorescence data indicating soil moisture effects on plant performance Quantitative inverted electrical conductivity model together with plant data help to inform and improve soil‐vegetation‐atmosphere models
    Keywords: Soil And Plant Interaction ; Ground‐Based Electromagnetic Induction Measurements And Quantitative Inversions ; Airborne Hyperspectral Measurements And Quantitative Plant Performance Data ; Relating Soil Structures At Specific Depths And Plant Performance ; Quantitative Quasi‐3d Emi Inversions Capture Responsible Soil Depths Driving Plant Performance ; Sun‐Induced Fluorescence Data May Contain Soil Moisture Information Beside Photosynthetic Activity
    ISSN: 0094-8276
    E-ISSN: 1944-8007
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  • 3
    In: Geophysical Research Letters, November 2007, Vol.34(21), pp.n/a-n/a
    Description: We propose an efficient integration path for the fast evaluation of the three‐dimensional spatial‐domain Green's function for electromagnetic wave propagation in layered media for the particular case of zero‐offset, source‐receiver proximal ground‐penetrating radar (GPR) applications. The integration path is deformed in the complex plane of the integration variable so that the oscillations of the dominant exponential term in the spectral Green's function are minimized. The contour does not need to be closed back on the real axis as the complex integrand rapidly damps. The accuracy and efficiency of the technique have been confirmed by comparison with traditional elliptic integration contours. The proposed algorithm appears to be promising development for fast, full‐wave modeling and inversion of GPR data.
    Keywords: Ground‐Penetrating Radar ; Layered Media ; Green'S Function
    ISSN: 0094-8276
    E-ISSN: 1944-8007
    Source: John Wiley & Sons, Inc.
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