Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Evaluation of the impact of low versus high resolution data on nitrous oxide emissions from a rural landscape
    Kros, J. ; Vries, W. de - \ 2011
    distikstofmonoxide - emissie - platteland - gegevensanalyse - resolutie - nitrous oxide - emission - rural areas - data analysis - resolution
    We compared N2O emission results of the simple process based model INITIATOR, using landscape scale data, national scale data and European scale data. All three methods where applied to the Noordelijke Friese Wouden. Abstract about a research project.
    Simulation of low flows and drought events in WATCH test basins: impact of climate forcing datasets
    Huijgevoort, M.H.J. van; Loon, A.F. van; Hanel, M. ; Haddeland, I. ; Horvát, O. ; Koutroulis, A. ; Machlica, A. ; Weedon, G.P. ; Fendeková, M. ; Tsanis, I. ; Lanen, H.A.J. van - \ 2011
    2011 : European Commission (Technical report / WATCH no. 44) - 19
    geohydrologie - gegevensanalyse - resolutie - aardoppervlak - afvloeiingswater - bodemwater - klimatologie - evaporatie - geohydrology - data analysis - resolution - land surface - runoff water - soil water - climatology - evaporation
    The impact of both spatial and temporal resolution on the components of the terrestrial hydrological cycle are investigated using the WATCH forcing dataset (WFD) and the JULES (Joint UK Land Environment Simulator) land surface model. The various spatial resolutions are achieved by degrading the native half degree latitude/longitude resolution WATCH dataset to both one degree and two degrees. The temporal resolutions are created by degrading the native three hourly WATCH forcing dataset to six hourly and using the WATCH interpolator to derive a one hour forcing dataset. There is little difference in the moisture stores of soil water and canopy water in the long term mean from the various resolutions, so the analysis presented is for the changes in evaporation and runoff. The evaporation is further analysed into its various components for the spatial resolution. Results suggest that there is little impact from spatial resolution, but the interpolation method for temporal resolution can have a significant effect on the total mean evaporation/runoff balance.
    Use of high resolution sonar for near-turbine fish observations (DIDSON) - We@Sea 2007-002
    Couperus, A.S. ; Winter, H.V. ; Keeken, O.A. van; Kooten, T. van; Tribuhl, S.V. ; Burggraaf, D. - \ 2010
    IJmuiden : IMARES (Report / IMARES Wageningen UR C0138/10) - 29
    resolutie - turbines - wind - windmolens - effecten - reacties - vis - pelagische visserij - visfauna - resolution - turbines - wind - windmills - effects - responses - fish - pelagic fishery - fish fauna
    In this study we investigate small scale distribution of pelagic fish within a windfarm by means of a high resolution sonar (DIDSON, Dual frequency IDentification SONar; Soundmetrics). In addition we assess the bias of small scale variations induced by the effects of wind turbines (monopiles) on distribution of the pelagic fish community in the hydro acoustic surveys carried out on the OWEZ Near Shore Wind farm (NSW).
    Spatial aggregation of land surface characteristics : impact of resolution of remote sensing data on land surface modelling
    Pelgrum, H. - \ 2000
    Agricultural University. Promotor(en): R.A. Feddes, co-promotor(en): M. Menenti. - S.l. : S.n. - ISBN 9789058082435 - 151
    landevaluatie - landclassificatie - landverdeling - landtypen - ruimtelijke variatie - aggregatie - remote sensing - gegevensanalyse - resolutie - aardoppervlak - land evaluation - land classification - land diversion - land types - spatial variation - aggregation - remote sensing - data analysis - resolution - land surface

    Land surface models describe the exchange of heat, moisture and momentum between the land surface and the atmosphere. These models can be solved regionally using remote sensing measurements as input. Input variables which can be derived from remote sensing measurements are surface albedo, surface temperature and vegetation cover. A land surface model using those land surface characteristics is presented i.e. the Surface Energy Balance Index (SEBI) model. This model uses the observed temperature difference between the land surface and atmosphere as an indicator for evapotranspiration.

    Spatially distributed land surface model results can be used as a boundary condition for numerical weather predicton models. The results should therefore be aggregated from the remote sensing pixel scale to the atmospheric model scale. However aggregated values will differ when derived from remote sensing data with different resolutions. This difference, the error due to aggregation is caused by two different aspects: land surface heterogeneity and non-linearity of the land surface model. Two approaches are presented to quantify the error due to aggregation: the linearization approach, where the land surface model is approximated by a Taylor expansion and a geometrical approach where the range of valid results for the land surface model is derived using a convex hull.

    To measure the heterogeneity of land surfaces, the concept of length scale is introduced. The wavelet transform is being used to derive the length scale of the land surface characteristics. The wavelet variance derived from the Fast Wavelet Transform using the Haar wavelet is a good indicator for the variability of land surface characteristics at different spatial scales. For three different data sets the length scale of land surface characteristics have been derived: Barrax, Spain, the Jornada Experimental Range, USA and the Central Part of the Netherlands.

    The two approaches for quantifying the error due to aggregation have been verified using the three data sets. The results obtained by the linearization show that aggregation error can indeed be estimated. For the three test sites the large scale error did not exceed 10 %. However the results based on the convex hull analysis show that the large scale error due to aggregation can be much larger than observed for the three test cases. Therefore low resolution remote sensing data cannot be used a priori as input for land surface models.

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