Slide 1

WEELS: Wind Erosion on European Light Soils EU Framework 5 Research Programme Slide 2 Partners : University College London (co-ordination): Andrew Warren, Dave Gasca-Tucker and others - subcontract to Wageningen University: Jan de Graaf, Wim Spaan, Dirk Goossens, Michel Riksen, Olga Vigiak and Floor Brouwer Soil Survey of Lower Saxony: Walther Schfer, Jens Gro, Annette Thiermann, Jan Sbresny - subcontract to Lund University: Lars Brring, Marie Ekstrm and others Salford University: Adrian Chappell Gttingen University (research group geosystem-analysis): Jrgen Bhner, Olaf Conrad, Andre Ringeler, Anke Wehmeyer and others Slide 3 All on glacial outwash sands, with similar mean annual rainfall; more snow and frost in the east Three Field Sites (Supersites) : Slide 4 The WEELS model, running with data on wind, temperature, rainfall, soil erodibility and land use Validation: (a) against a few event records in Grnheim and Barnham (b) against estimates of erosion based on the use of 137 Cs, for Barnham only Development of a risk-assessment system, for use where there are fewer data, for Grnheim Economic and policy analysis Sand and dust monitoring Climate change scenarios Main Elements :: Slide 5 Jrgen Bhner, Walther Schfer, Olaf Conrad, Jens Gro and Andre Ringeler Choices:Wind-Erosion Equation (WEQ) Revised Wind Erosion Equation (RWEQ) Wind Erosion Prediction System (WEPS) The WEELS Model - developed from EROKLI (Beinhauer and Kruse, 1994) The WEELS Model :: Slide 6 WIND: WA s P (Wind Atlas Analysis and Application Program) used to convert hourly wind observations at a meteorological station to values across the supersite according to variation in topography and roughness. WIND EROSIVITY: Several elements, mainly shear velocity U* and mass transport SOIL MOISTURE: The water content of the top 2 cm of soil layer, calculated with a simple model using standard meteorological data Components of the WEELS Model (1) Slide 7 SURFACE ROUGHNESS: soil roughness: aggregate size and tillage (from empirical data, with big assumptions) vegetation roughness: crop type and crop phenology SOIL ERODIBILITY: Essentially, the dimensionless soil erodibility factor K, depending on aggregate structure and derived from wind tunnel studies, and regressions against soil factors, such as texture and organic matter content. Components of the WEELS Model (2) Slide 8 Data + simulation for 1985 Coverage for 1985 (no data brown) LAND USE: Michel Riksen, David Gasca-Tucker, Olaf Conrad and others Components of the WEELS Model (3) Slide 9 Olga Vigiak and Annette Thiermann Windbreak Modelling Reduction of Friction Velocities Slide 10 Hourly assessment of mean wind speed (10 m above ground) and friction velocity Daily assessments of crop cover, tillage roughness and top soil moisture Hourly duration of erosive conditions Maximum sediment transport rate, calculated with and without top-soil moisture A simplified daily erosion/accumulation balance. Output: Slide 11 Events: Events recorded during field monitoring: about two at the monitoring site Events recorded by farmers: mostly rather inaccurate, but one very well recorded event on video: see later Slide 12 137 Cs is an artificial isotope created in nuclear reactions, as in bombs and nuclear power stations (cf Chernobyl) Output to the atmosphere reached a peak in the mid 1960s, so that one is measuring net erosion over about 35 years Direct measurement is difficult mainly because it is very episodic (as we found) It is now widely used to measure erosion. It is simple, but time-consuming to measure Adrian Chappell 137 Caesium Analysis Slide 13 137 Caesium Sampling Slide 14 137 Caesium Theory Slide 15 137 Caesium Profiles, Barnham Slide 16 Sampling Pattern Slide 17 Semi-variogram Slide 18 An existing model (Owens 1994) was modified to include the major factors controlling wind erosion: Erosion and deposition models are for each field and each day Land cover and phenology (including plough events) Rainfall to estimate daily 137 Cs fallout Wind speed and a fuzzy threshold (5-7 m s -1 ) for erosion Caesium Mass-Balance Model Slide 19 Testing sediment samplers (the now widely used MWAC sampler found to be best by many criteria Very detailed recording of one of the few events on 18 May 1999 Dirk Goossens and Jens Gro Sediment Transport Sampling Slide 20 Example (a) Slide 21 Example (b) Slide 22 Lars Brring, Marie Ekstrm and others Wind Erosion and Climate Change Slide 23 For Example: Benefits in /ha Michel Riksen, Jan de Graaf, and Floor Brouwer Economics Slide 24 Some Results: Risk Assessment, Grnheim Slide 25 Some Results: Event Modelling, Barnham Circulation Pattern over Europe 13.03.1994 Slide 26 Slide 27 Slide 28 Some Results: Event Modelling - Barnham Wind Speed [10 m a.G.] Honington Erosion/Accumulation Balance (12.03. - 15.03.1994) Slide 29 Some Results: Longterm Estimation (1970-98) Erosion/Accumulation Balance: -1.5 to 1.8 Kg/m Slide 30 Net loss: 0.6 t ha -1 yr -1 Area of erosion deposition Rate of erosion deposition Cs-derived estimates: soil flux ( Adrian Chappell) Top of scale 0.45 gain; bottom of scale 0.35 erosion (g cm 2 yr -1 ) Some Results: Cs-derived Estimates Slide 31 Model vs Measurements Crude comparison of the distribution of measured as against modelled erosion shows similar patterns, with erosion concentrated in the north- east of the site, but Model estimates:- 1.56 t ha -1 yr -1 vs 137 Cs Method: - 0.60 t ha -1 yr -1 Most models overpredict, but The disparity is even greater if we acknowledge removal on root crops (2.4 t ha -1 per crop).