Perfectly parallel groundwater transport models partition water flow into isolated one-dimensional stream tubes which maintain total spatial correlation of all properties in the direction of flow. The case is considered of the temporal moments of a conservative tracer pulse released simultaneously into N stream tubes with arbitrarily different advective-dispersive transport and steady flow speeds in each of the stream tubes. No assumptions are made about the form of the individual stream tube arrival-time distributions or about the nature of the between-stream tube variation of hydraulic conductivity and flow speeds. The tracer arrival-time distribution gΓ°t; xΓ is an N -component finite-mixture distribution, with the mean and variance of each component distribution increasing in proportion to tracer travel distance x. By utilising moment relations of finite mixture distributions, it is shown (to r ΒΌ 4) that the rth central moment of gΓ°t; xΓ is an rth order polynomial function of x or /, where / is mean arrival time. In particular, the variance of gΓ°t; xΓ is a positive quadratic function of x or /. This generalises the well-known quadratic variance increase for purely advective flow in parallel flow systems and allows a simple means of regression estimation of the large-distance coefficient of variation of gΓ°t; xΓ. The polynomial central moment relation extends to the purely advective transport case which arises as a largedistance limit of advective-dispersive transport in parallel flow models. The associated limit gΓ°t; xΓ distributions are of N-modal form and maintain constant shapes independent of travel distance. The finite-mixture framework for moment evaluation is also a potentially useful device for forecasting gΓ°t; xΓ distributions, which may include multimodal forms. A synthetic example illustrates gΓ°t; xΓ forecasting using a mixture of normal distributions.