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Opportunities to improve hydrologic data
Author(s) -
Dozier Jeff
Publication year - 1992
Publication title -
reviews of geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.087
H-Index - 156
eISSN - 1944-9208
pISSN - 8755-1209
DOI - 10.1029/92rg01440
Subject(s) - hydrological modelling , water cycle , homogeneous , computer science , data science , data collection , water resources , data management , environmental science , hydrology (agriculture) , data mining , geology , climatology , ecology , statistics , physics , mathematics , geotechnical engineering , biology , thermodynamics
Hydrologic data collection over scales from centimeters to continents, from minutes to years is difficult and expensive, so hydrologic models usually conceptualize processes based on simple, often homogeneous, views of nature. This forced oversimplification impedes scientific understanding and management of water resources. As the focus of hydrologic research shifts to larger regional and global scales, the collection, management, distribution, and analysis of data will improve so that models and data can each drive and direct the other. Better models illuminate the type and quantity of data needed to test hypotheses. Better data permit development and validation of more complete models and new hypotheses. Coordinated hydrologic experiments (such as the Global Energy and Water Cycle Experiment) and remote sensing of hydrologic parameters examine hydrologic variables at these larger scales, and isotope geochemistry, paleohydrology, and biological methods allow analysis and retrieval of new kinds of information. Improvements in the management and accessibility of data will make them more easily available to hydrologic scientists.