The challenge is to articulate the conditions under which scale imposed constraints are systematic and to develop models that compensate or standardize scale-based variation. Following this point of view, different model structures would be needed to accurately represent the phenomenon at different scales. For instance, studies of water demands at the national or sub-national scale would need lesser bundles of attributes to define the problem than studies at the local scale – wherein many more factors interact and become important (distance to water source, number of households having access, duration, timing etc.). Primary issues therefore center on gaining a better understanding of how to effectively measure and characterize scale; how to use scale information in judging the fitness of data for a particular use; how to automate scale change or scaling and simultaneously represent data at multiple scales; and how scale and change in scale affect information content, analysis, and conclusions about patterns and processes in water resources, hydrology, and climate. The papers in this issue address these concerns.