Towards an improved language for river data analysis: Demonstration for the highly-regulated Ohio River basin

We present the Network Analysis and Data Integration (NADI) System for extracting, organizing, analyzing, and visualizing river data with upstream/downstream relationships. The NADI System consists of a Geographical Information System (GIS) tool that uses spatial methods to generate the network, and a Domain Specific Language (DSL) that provides a concise and intuitive syntax for data analysis and is extensible through a plugin system. We demonstrate the capabilities of NADI using a case study of the Ohio River basin, showing it to be well-suited for large-scale metadata analysis based on river connections. The result of the case study shows that approximately half of the USGS streamflow gages in the Ohio Basin were constructed after dam(s) upstream, and only 35% of the gages remain without any dams upstream. These unaffected gages only account for 1.2% of the measured streamflow, showing the scarcity of natural streamflow data.