Services / Cross-discipline
Data Management
New numerical methods and computers have made water resources planning an intensely quantitative science. Surface water models consume vast quantities of time-series data, sometimes at sub-hourly time-steps, specified at dozens or even hundreds of locations. Groundwater models can represent domains with mega-scale cell inventories and can be calibrated against observed conditions at thousands of wells. Maintaining the large databases required to support modern analyses is now as important as the model codes themselves. Hydrosphere is a leader in water resources and environmental data management.
- Data acquisition
- Data processing and conversion
- QA/QC
- Database design and population
- Time-series data management
- Process automation and interface design
- Model-to-database linkages
- Analysis and visualization
- Data delivery
We offer clients skills in:
We maintain a substantial inventory of water resources data, including complete databases from the USGS, National Climatic Data Center and EPA. We also maintain a number of data sets of regional interest. For data that we do not have in-house, Hydrosphere’s staff has experience with the broad spectrum of sources of both public domain and proprietary environmental and water resources data.
Often, data sets require some level of quality assurance before they can be used reliably for project purposes. We have subjected many incoming data sets to rigorous, methodical scrutiny before using them in analyses and models.
Management of time-series data presents a special challenge to the natural resource professional. Voluminous time-series data can overwhelm even the most capable relational database management system. Hydrosphere was a pioneer in the publication of gigabyte-scale water resource data sets on CD-ROM and from this early work has developed expertise and software tools that facilitate the management of time-series data.
An effective and efficient database requires intelligent design of the structure of that database, taking into account the characteristics of the data themselves as well as the needs of end users. We have experience with common database design protocols and we maintain close working relationships with specialty firms who are skilled in such areas as database hosting, security, and web-based access for distributed users. We have developed data management interfaces that allow our models to pull data directly from databases and store the results. We have also constructed utilities to move data into and out of commonly-used analytical tools such as GIS, spreadsheets, statistical packages and visualization tools.