Getting your money's worth: Testing the value of data for hydrological model calibration

Despite the big data era, observational data continue to be a limiting factor in the environmental sciences. To collect the most informative field data, studies on the value of data are essential. This article describes a model‐based approach to assess the value of data. While we discuss the approach for hydrological model calibration, the approach is applicable across the environmental sciences. The overall goal is to provide guidance on optimal data collection strategies, that is, what to measure, where, and when. Observational data continue to be a limiting factor in the environmental sciences. Decisions on how to use the available resources for field data collection best are essential. This article describes a model‐based approach to assess the value of data and to provide guidance on what to measure, where and when.