Parameter uncertainty and the significance of simulated land use change effects

Abstract

Uncertainty in parameters characterising different land covers leads to uncertainty in model predictions of land use change effects. In this study, a new approach is presented which allows a model to be assessed to see whether it is suitable for investigating land use change scenarios in the sense that different land covers can be significantly distinguished in their effects on model output. It consists of the following steps: (a) The uncertainty in land cover-dependent parameters is quantified. (b) The model of an artificial catchment with representative characteristics and uniform land cover is established. (c) Using this artificial catchment, Monte Carlo simulations are carried out to determine the uncertainty in the model response to different land covers. (d) By comparing the results for two covers, respectively, a dimensionless test statistic, the distinction level, is calculated. The distinction level is a normalised probability that two independent realisations of land covers which are parameterised within their range of natural uncertainty will yield distinct model responses. If the distinction level is greater than or equal to 90%, the land covers are assumed to have a significantly different effect on the model output. An example of the application of the new method is provided using the eco-hydrologic model SWAT-G. The land covers forest, pasture and arable land can be significantly distinguished by their long-term means of surface runoff, groundwater recharge and streamflow. The minimum proportion of the catchment area on which land cover must change in order to obtain significantly distinct model responses depends on the land covers involved and the considered hydrologic variable. In the case of a change between pasture and forest and with regard to average streamflow, this minimum proportion amounts to about 25%, a value that compares well with the results of paired catchment studies.