Aquifer heterogeneity in combination with data scarcity is a major challenge for reliable solute transport prediction. Velocity fluctuations cause non-regular plume shapes with potentially long tailing and/or fast travelling mass fractions.High monitoring cost and presumably missing simple concepts have limited the incorporation of heterogeneity to many field transport models up to now.We present a hierarchical aquifer model which combines large-scale deterministic structures and simple stochastic ap-5 proaches. Such a heterogeneous conductivity can easily be integrated into a numerical models. Depending on the modelling aim, the required structural complexity can be adapted. The same holds for the amount of available field data. The conductivity model is constructed step-wise following field evidence from observations; though relying on as minimal data as possible.Starting point are deterministic blocks, derived from head profiles and pumping tests. Then, sub-scale heterogeneity in form of random binary inclusions are introduced to each block. Structural parameters can be determined e.g. from flowmeter measure-10 ments.As proof of concept, we implemented a predictive transport model for the heterogeneous MADE site. The proposed hierarchical aquifer structure reproduces the plume development of the MADE-1 transport experiment without calibration. Thus, classical ADE models are able to describe highly skewed tracer plumes by incorporating deterministic contrasts and effects of connectivity in a stochastic way even without using uni-modal heterogeneity models with high variances. The reliance of 15 the conceptual model on few observations makes it appealing for a goal-oriented site specific transport analysis of less well investigated heterogeneous sites.

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