When reviewing the four papers for my first Water Management Editorial back in 2012, a key theme that emerged was the importance and availability of data and information. This was not an earth-shattering finding, since we would all hope and assume that decisions are going to be based on sound evidence. However, we cannot take it for granted that adequate information will always be available to us, and the collection and storage of appropriate data remains an important part of our scientific and technological endeavours.So when approaching the four papers in this issue, I wondered if a similar common theme would be apparent. Three papers are concerned with different river modelling approaches, whilst the final one deals with wastewater reuse in the Caribbean. In spite of this difference in topics, I would like to suggest that it is worth drawing out the balance between simplicity and complexity in how we describe and represent the natural environment. As with 'data', this is not a novel idea, but it is one that is valuable to reflect on from time to time since making things more complicated does not necessarily make them easier to understand, nor may it actually help us in our decision-making and analysis.It is probably fair to say that the overwhelming majority of papers presented in this journal are concerned with 'models' of the physical world, and as such, a simplification of the natural complexity. So even if a paper simply presents a review of collated information, say in the form of summary statistics, it represents a simplified model of the real world. In the case of computational hydraulic models, as covered in the first three papers, the representation of reality is clear, as is the uncertainty associated with such a simplification. As understanding has grown along with increased computational resources, so has the complexity of our models in the main. But it is worth remembering the aphorism, sometimes attributed to Einstein, that ''Everything should be made as simple as possible, but not simpler''. In introducing the following four papers, I will try to draw out this dichotomy and the benefits that can indeed be derived on occasions from a simpler view.The first paper (Zerfu et al., 2015) presents a modelling approach for predicting the erodible river corridor width, which can be important for land use planning and developing erosion protection measures. The modelling method is viewed by the authors as being 'relatively simple', but by using this in a probabilistic framework they are able to better understand the uncertainty inherent in their representation without the need for more complex models. Using a UK catchment they found that the variation in model inputs, resulting from the natural variability in the study area, had a significant impact on the model simulations.So a better understanding of the natural variability and how we sample it is just as important as any model methodology that we derive. The authors conclude that a better understanding of the uncertainty from the assumed model structu...

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