2,323 research outputs found

    The estimation of soil moisture content and actual evapotranspiration using thermal infra-red remote sensing

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    There are no author-identified significant results in this report

    Testing an Energy Balance Model for Estimating Actual Evapotranspiration Using Remotely Sensed Data

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    An energy-balance model is used to estimate daily evapotranspiration for 3 days for a barley field and a wheat field near Hannover, Federal Republic of Germany. The model was calibrated using once-daily estimates of surface temperatures, which may be remotely sensed. The evaporation estimates were within the 95% error bounds of independent eddy correlation estimates for the daytime periods for all three days for both sites, but the energy-balance estimates are generally higher; it is unclear which estimate is biassed. Soil moisture in the top 2 cm of soil, which may be remotely sensed, may be used to improve these evaporation estimates under partial ground cover. Sensitivity studies indicate the amount of ground data required is not excessive

    Evapotranspiration and remote sensing

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    There are three things required for evapotranspiration to occur: (1) energy (580 cal/gm) for the change of phase of the water; (2) a source of the water, i.e., adequate soil moisture in the surface layer or in the root zone of the plant; and (3) a sink for the water, i.e., a moisture deficit in the air above the ground. Remote sensing can contribute information to the first two of these conditions by providing estimates of solar insolation, surface albedo, surface temperature, vegetation cover, and soil moisture content. In addition there have been attempts to estimate precipitation and shelter air temperature from remotely sensed data. The problem remains to develop methods for effectively using these sources of information to make large area estimates of evapotranspiration

    Estimating water flow through a hillslope using the massively parallel processor

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    A new two-dimensional model of water flow in a hillslope has been implemented on the Massively Parallel Processor at the Goddard Space Flight Center. Flow in the soil both in the saturated and unsaturated zones, evaporation and overland flow are all modelled, and the rainfall rates are allowed to vary spatially. Previous models of this type had always been very limited computationally. This model takes less than a minute to model all the components of the hillslope water flow for a day. The model can now be used in sensitivity studies to specify which measurements should be taken and how accurate they should be to describe such flows for environmental studies

    Programming a hillslope water movement model on the MPP

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    A physically based numerical model was developed of heat and moisture flow within a hillslope on a parallel architecture computer, as a precursor to a model of a complete catchment. Moisture flow within a catchment includes evaporation, overland flow, flow in unsaturated soil, and flow in saturated soil. Because of the empirical evidence that moisture flow in unsaturated soil is mainly in the vertical direction, flow in the unsaturated zone can be modeled as a series of one dimensional columns. This initial version of the hillslope model includes evaporation and a single column of one dimensional unsaturated zone flow. This case has already been solved on an IBM 3081 computer and is now being applied to the massively parallel processor architecture so as to make the extension to the one dimensional case easier and to check the problems and benefits of using a parallel architecture machine

    A nod in the wrong direction : Does nonverbal feedback affect eyewitness confidence in interviews?

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    Eyewitnesses can be influenced by an interviewer's behaviour and report information with inflated confidence as a result. Previous research has shown that positive feedback administered verbally can affect the confidence attributed to testimony, but the effect of non-verbal influence in interviews has been given little attention. This study investigated whether positive or negative non-verbal feedback could affect the confidence witnesses attribute to their responses. Participants witnessed staged CCTV footage of a crime scene and answered 20 questions in a structured interview, during which they were given either positive feedback (a head nod), negative feedback (a head shake) or no feedback. Those presented with positive non-verbal feedback reported inflated confidence compared with those presented with negative non-verbal feedback regardless of accuracy, and this effect was most apparent when participants reported awareness of the feedback. These results provide further insight into the effects of interviewer behaviour in investigative interviewsPeer reviewedFinal Accepted Versio

    A sensitivity analysis of soil moisture retrieval from the t-w microwave emission model

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    The potential of the τ-ω model for retrieving the volumetric moisture content of bare and vegetated soil from dual polarisation passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure and consequently its microwave singlescattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the τ-ω model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated

    TELLUS: A combined surface temperature, soil moisture and evaporation mapping approach

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    There are no author-identified significant results in this report
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