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Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa
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Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion Research: Studies regarding a soil erosion parameter in South Africa

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PhD Thesis Presentation Peter Löwe. …

PhD Thesis Presentation Peter Löwe.

The dissertation "Artificial Intelligence Methods in Radarmeteorology and Soil Erosion Research" discusses the assessment of potential rainfall erodibility in regard to soil erosion processes in South Africa.
Knowledge-based approaches are used to derive rainfall information from weather radar data for the recording of erosivity pulses from individual rainfall events.
This precipitation data is used as input for a erosivity modell consisting built out of cellular automata.
The results generated by the modell are presented and discussed.

Thesis Download: http://opus.bibliothek.uni-wuerzburg.de/volltexte/2004/759/

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  1. Artificial Intelligence Techniques applied to Radarmeteorology and Soil Erosion ResearchStudies regarding a soil erosion parameter in South Africa Dr. Peter Löwe (loewe@geomancers.net) University of Würzburg, Germany Geography Department
  2. Overview•Topic, theory and previous projects in the field•Hypothesis and approach I Technical framework II Modelling III Results
  3. Introducing the problemSoil erosion is the process of Terrain Vegetationsoil destruction, a natural process, Climatewhich can be initiated or amplified by Soils Humanshuman land management. ... Soilerosion can deminish the agricultural Control Enhanceyield significantly. Transportation Start (Scheffer Schachtschabel, 1992) Wind Water SOIL EROSIONIn addition to human use of theEarths surface, climate is a keyfactor. It provides a means oftransportation for soil material to becarried away.How can these processesbe modelled ?
  4. Modelling soil erosionUniversal Soil Loss Equation (USLE): Core problem: When-How much-Where? Soil Erosion as a function of When does how much soil loss occur where? Erosivity Erodibility When does how much erosivity occur where ? When does how much rain fall where ? Physical Rainfall properties Management Land PlantEnergy [EI30] Management Management Aim of the Dissertation Providing detailed information about erosivity by relying on the available data sources: A= R * K * LS * P * C How erosive is rain When ? How much ? Where ?
  5. Theory and precessor workThe DFG-project „The meridional and planetary differentiation of soilerosion in southern Africa and its causes“ postulates the RainfallErosivity Index (REI) as a locally „superior“ erosivity factor.REI-Components: • Quantity • Energy • Intensity • StructureApproach: Spatialinterpolation (1,22 Miokm²) from ca. 120 raingauge data sets [approx.10,000 km² per gauge]Results: Monthly- andannual maps of erosivitytotals for South Africa.
  6. Problems with thedatabaseWhen ? Precipitation data is recorded in 5- minute resolution: OKHow much ? Index values are calculated on these time series: OKWhere ? Results from singular rain 100 * 100 km gauges are spatially interpolated ? Example: Rain gauge from theHypothesis Liebenbergvlei network, Station: Bethlehem Airport, Tipping Gauge TypeThe described REI-processing does not capture the real-world distributionof convective, small-scaled erosivity „pulses“ - it is only affecting theproduced maps at random. There is a sampling and interpolation- problem if rain gauge data is used
  7. Alternative:weather radarData has been recorded since 1995 by the SAWS.•temporal resolution: 5 minutes OK•spatial resolution: 1km², full area coverage OK•Data: Reflectivity values [dBZ] three-dimensional distribution of hydrometeors in the lower tropossphere and their sizes.•Products: derived quantitative Usable ? precipitation values [mm/h] Radarpluviograms For the upcoming discussion, only data from a single radar station is being used: The MRL-5 in the Liebenbergvlei catchment (oldest station available, lots of expert knowledge available, 10cm S-band und 3cm X-band).
  8. Radarpluviograms daily precipitation totals + spatial dataUsability to derive REI-values:•When ? daily totals (24h)•How much? Sums, no intensities•Where? Inhomogenous content • missing meta data • artefacts • maps instead of dataPluviogram-products can be properlyjudged if radarmeteorological knowledgeis available, otherwise they areproblematic
  9. Idea and approachHypothesis: There are small, temporally fluctuating peaks of erosiviy dueto the convective weather situation, yet they are still uncharted.A sufficiently high temporal (When ?) and spatial data coverage (Where ?),is needed, and also a measure of confidence for the data content(How much ?).To answer „When-How much-Where“ the radar reflectivityproducts must be accessed and processed. Technical Modelling Results Framework Geoinformatics, Information- Analysis and •Verification logistics, encoding of the •Validation Remote sensing, REI. •Results (D)AI, Radarmeteorology I II III
  10. I Overview: Framework Structure and components Data Data base Import Geo- Expert information- systems system Multi Agent- Information simulation logistics (REI)The development of an expert system shell embedded within theGIS, a radar data import module, a simulation environment and thelogistic processes was based on Open Source/Free Software usingGRASS GIS, PostgreSQL, CLIPS, CAPE and the expert systemshell toolkit D3 of the U. of Würzburg, Germany (Chair for A.I.).
  11. I II REI-Modelling Precipitation- REI- data stream data stream Maps of „radar rain“For each spatial cell which has Init State 1 Index-radar coverage, a „virtual rain D Hibernate valuegauge“ needs to be simulated,which will derive REI-values P Daccording to its individual inputdata stream. REI- D Cell-For this reason, agent technology State 2 State 3is used, as each „gauge-agent“ Store Pause Agentmust keep its‘ own record of Pprevious precipitation events. P: Precipitation P D: Dry
  12. Data flow I II Reflectivity mapsWhat type of Xweather occurs X Xwhen, where? „same rain X X X X X X XX everywhere“ X X SSS REI-Model Erosivity XPS Z-R maps Constrat 1 a b - c 4 d 2 Rainfall maps, Pluviogram When does how much rain fall Where does erosivity potential where ? occur ?
  13. I II III Time seriesThe mapping of REI values by the Cell-Agents shows a pattern of „erosivityshadows“, trailing behind the tracks of precipitation zones. By calculating sumsfor each raster cell maps of daily totals can be created. 24h total Reflectivity Σ Reflectivity 16:18:50 Hours 16:43:30 Hours 16:59:56 Hours 24h total REI Σ REI-Erosivity
  14. I II III Daily totals Data set: 15. Dezember 1998 Reflectivities Precipitation REI-Erosivity Stormcell-tracks In the following, only the values of the northern half of the MRL-5 coverage area are shown.
  15. 3-D Visualization Reflectivity and Precipitation Reflectivity total Radar Precipitation total ? ?•Steps/Etages are artefacts of the radar processing.•Decreasing reflectivity totals with increasing range/distance are caused by the rising „radarscan horizon“. How does this affect the REI-values ?
  16. 3-D Visualization REI- values und Precipitation Altitude: REI values, Color: Precipitation The „rings“ also affect the REI-values,Altitude and Color: Precipitation but the amplitude of the erosive events is significantly higher.
  17. REI-Totals display local erosivity-pulses Rainfall Erosivity Index (REI) •Quantity •Energy •Intensity •Structure Despite overall decreasing precipitation- totals with increasing range are qualitative REI-pulses recorded.
  18. Conclusion I II IIIHypothesis is verified: The use of radar data shows powerfullocalized dynamics of convective weather phenomena within thetest region. It is possible to infer strongly localized erosivitypulses. The proposed full spatial coverage of occurring erosivity pulses in the given example just by means of interpolating from four rain gauges of the national precipitation network is not realistic (200*200 km).When does how much erosivity occurwhere ? •Any kind of erosivity modell (REI, EI30, KE>25, etc.) can be simulated, using the developed software-framework (how much ?) •qualitative answers with full spatial coverage by Radar Data - GIS integration(where ?,when ?)
  19. finhave a nice day
  20. I can see clearly now,the rain has gone.I can see all obstaclesin my way[Liza Minelli]Thank you for your attention

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