Modelling the impact of within-storm variability of rainfall on the loading of solutes to preferential flow pathways

摘要

Rainfall variability within a storm can have a significant impact on the amount of chemical transported by surface runoff and preferential flow. Previously, studies have evaluated only a few slowly varying rainfall patterns and related sorption capacities. We use a bounded random cascade approach to generate 50 000 realizations of realistic rainfall intensity patterns within a single storm event (96 minutes duration, mean intensity of 18.75 mm hourp#) to explore the effects on the partitioning of rainfall and linearly sorbing solutes between fast preferential flow (loading) and slow flow in the soil matrix for a silt loam and a sandy clay. Loading and infiltration are modelled by a near-surface mixing model and Green-Ampt infiltration. The statistical properties of loading were evaluated from these simulations. For this storm the mean total of resident solute mixing from the soil to preferential flow reached a maximum for a retardation factor R ~ 5. Much smaller loadings occurred for more weakly sorbing and more strongly sorbing solutes. The variability of loading tended to decrease with increasing R. Ensemble averaged rainfall patterns were derived which related to the magnitude of loading. The patterns of rainfall generating large preferential flows did not necessarily lead to large solute loading. Early peaking, mid-storm peaking and late peaking rainfall contributed to large solute loadings, depending upon soil and chemical properties. These patterns result from a balance between the amount of preferential flow generated and the amount of solute available when preferential flow is triggered. The results suggest that the use of R as a measure of the mobility of resident solutes depends on the flow pathway considered. In addition, characterization of flux distributions in soil with weakly sorbing, resident tracers, may underestimate the potential for rapid transport of strongly sorbing solutes subject to natural variations in rainfall.