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- Grabs, Thomas, 1980-
(författare)
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Water quality modeling based on landscape analysis: importance of riparian hydrology
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Several studies in high-latitude catchments have demonstrated the importance of near-stream riparian zones as hydrogeochemical hotspots with a substantial influence on stream chemistry. An adequate representation of the spatial variability of riparian-zone processes and characteristics is the key for modeling spatio-temporal variations of stream-water quality. This thesis contributes to current knowledge by refining landscape-analysis techniques to describe riparian zones and by introducing a conceptual framework to quantify solute exports from riparian zones. The utility of the suggested concepts is evaluated based on an extensive set of hydrometric and chemical data comprising measurements of streamflow, groundwater levels, soil-water chemistry and stream chemistry. Standard routines to analyze digital elevation models that are offered by current geographical information systems have been of very limited use for deriving hydrologically meaningful terrain indices for riparian zones. A model-based approach for hydrological landscape analysis is outlined, which, by explicitly simulating groundwater levels, allows better predictions of saturated areas compared to standard routines. Moreover, a novel algorithm is presented for distinguishing between left and right stream sides, which is a fundamental prerequisite for characterizing riparian zones through landscape analysis. The new algorithm was used to derive terrain indices from a high-resolution LiDAR digital elevation model. By combining these terrain indices with detailed hydrogeochemical measurements from a riparian observatory, it was possible to upscale the measured attributes and to subsequently characterize the variation of total organic-carbon exports from riparian zones in a boreal catchment in Northern Sweden. Riparian zones were recognized as highly heterogeneous landscape elements. Organic-rich riparian zones were found to be hotspots influencing temporal trends in stream-water organic carbon while spatial variations of organic carbon in streams were attributed to the arrangement of organic-poor and organic-rich riparian zones along the streams. These insights were integrated into a parsimonious modeling approach. An analytical solution of the model equations is presented, which provides a physical basis for commonly used power-law streamflow-load relations.
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| 5. |
- Tinetti, G., et al.
(författare)
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A chemical survey of exoplanets with ARIEL
- 2018
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Ingår i: Experimental Astronomy. - : Springer Science and Business Media LLC. - 0922-6435 .- 1572-9508. ; 46:1, s. 135-209
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Tidskriftsartikel (refereegranskat)abstract
- Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.
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