Login / Signup

SFRmaker and Linesink-Maker: Rapid Construction of Streamflow Routing Networks from Hydrography Data.

Andrew T LeafMichael N FienenHoward W Reeves
Published in: Ground water (2021)
Groundwater models have evolved to encompass more aspects of the water cycle, but the incorporation of realistic boundary conditions representing surface water remains time-consuming and error-prone. We present two Python packages that robustly automate this process using readily available hydrography data as the primary input. SFRmaker creates input for the MODFLOW SFR package, while Linesink-maker creates linesink string input for the GFLOW analytic element program. These programs can reduce weeks or even months of manual effort to a few minutes of execution time, and carry the added advantages of reduced potential for error, improved reproducibility and facilitation of step-wise modeling through reduced dependency on a particular conceptual model or discretization. Two real-world examples at the county to multi-state scales are presented.
Keyphrases
  • electronic health record
  • big data
  • human health
  • public health
  • quality improvement
  • heavy metals
  • data analysis
  • drinking water
  • health risk
  • risk assessment
  • machine learning
  • gestational age