Getting your money's worth: Testing the value of data for hydrological model calibration
Jan Seibert, Franziska Clerc-Schwarzenbach, Ilja van Meerveld
Abstract
Abstract 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.
Topics & Concepts
CalibrationComputer scienceMeasure (data warehouse)Value (mathematics)Field (mathematics)Data collectionLimitingData scienceBig dataObservational studyEconometricsData miningStatisticsMachine learningMathematicsEngineeringPure mathematicsMechanical engineeringHydrology and Watershed Management StudiesWater resources management and optimizationHydrology and Drought Analysis