Uncertainty Analysis of the GeoPEARL Pesticide Leaching Model
G.B.M. Heuvelink 1, F. Van Den Berg 1, S.L.G.E. Burgers 2 and A. Tiktak 3
1 Alterra, Wageningen University and Research Centre, PO Box 47, 6700 AA Wageningen, The Netherlands
2 Biometris, Wageningen University and Research Centre, PO Box 9101, 6700 HB Wageningen, The Netherlands
3 Netherlands Environmental Assessment Agency, PO Box 303, 3720 AH Bilthoven, The Netherlands
Abstract. GeoPEARL is a spatially distributed model describing the fate of pesticides in the soil-plant system. It calculates the drainage of pesticides into local surface waters and the leaching into the regional groundwater. GeoPEARL plays an important role in the evaluation of Dutch pesticide policy plans. This study analysed how uncertainties in soil and pesticide properties propagate through GeoPEARL for three representative pesticides. The GeoPEARL output considered is the 90 percentile of the spatial distribution of the temporal median of the leaching concentration (P90). The uncertain pesticide properties are the coefficient of sorption on organic matter and the half-life of transformation in soil. Both were assumed uncorrelated in space and were represented by lognormal probability distributions. Uncertain soil properties considered were horizon thickness, texture, organic matter content, hydraulic conductivity and the water retention characteristic. Probability distributions were derived from meta-data stored in the Dutch soil information system. A regular grid sample of 258 points covering the agricultural area in the Netherlands was randomly selected. At the grid nodes, realisations from the probability distributions of uncertain inputs were generated and used as input to a Monte Carlo uncertainty propagation analysis. The results show large uncertainties in P90, with interquartile ranges larger than the median for all three pesticides. Further analysis showed that the pesticide properties were the main source of uncertainty and that uncertainty in soil organic matter contributed to a lesser extent. Uncertainty contributions from other soil properties were negligible. These results suggest that improved assessment of soil properties will hardly improve the accuracy of the predicted pesticide leaching. Instead, more accurate assessment of the pesticide properties is required, but this is difficult because these uncertainties in fact reflect the simplified process descriptions of GeoPEARL.
Keywords: error propagation, Monte Carlo, stochastic simulation, upscaling.
In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).