Norm Jones

TL;DR: The use of process-based hydrological models has a long history dating back to the 1960s as mentioned in this paper, and a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrologogical model.

TL;DR: The data model framework is described, a simplified version of the complete ground water data model that includes two‐dimensional and three‐dimensional object classes for representing aquifers, wells, and borehole data, and the 3D geospatial context in which these data exist.

TL;DR: Tethys is a Python-based scripting environment that leverages open source tools for geoprocessing of spatial data, map rendering and visualization, distributed computing, and database management that makes it possible to deploy a calibrated, high-resolution watershed or surface water model as a web-based application for decision support.

TL;DR: This work offers a starting point for the development of a more comprehensive toolset to validate the National Water Model (NWM) while also improving the ability to access and visualize NWM forecasts, and develop additional national‐scale‐derived products such as flood maps.

TL;DR: A framework to publish simplified MODFLOW groundwater modeling capabilities to a web interface for use by water managers and stakeholders is presented, allowing a user to simulate the effects of proposed well diversions and reduce modeling errors.