EARS 12 Big Data Science in Hydrology
Technological advances that facilitate the routine collection of terabytes of data measuring Earth’s environment have resulted in the exponential growth of high-resolution hydrological digital databases spanning wide spatial and temporal dimensions. To take advantage of these new databases, hydrologists are increasingly using new tools developed for “big data” science to discover, manage, and analyze earth’s ever-changing hydrology. This course is an introduction to the methods and tools of big data science in hydrology, particularly environmental statistics and the R programming language, with application to understanding Earth’s hydrology at the local and regional scale. Topics include quantitative analysis of the hydrologic cycle, floods, droughts, and surface water quality. Prior computer programming experience is helpful, but not required.
Instructor
Renshaw