The America’s Water project, coordinated at Columbia’s Water Center by Upmanu Lall, is trying to understand the US water system as an integrated whole, and understand how that system will evolve over the next decades. Doing so will require a comprehensive model, incorporating agriculture, energy, cities, policy, and more.
We are just beginning to lay the foundation for that model. A first step is to create a network of links between station gauges around the US, representing upstream and downstream flows and counties served. The ultimate form of that model will rely on physical flow data, but I created a first pass using simple rules:
- Every gauge can only be connected to one downstream gauge (but not visa versa).
- Upstream gauges must be at a higher elevation than downstream gauges.
- Upstream gauges must be fed by a smaller drainage basin than downstream gauges.
- Of the gauges that satisfy the first two constraints, the chosen downstream gauge is the one with the shortest distance and the most “plausible” streamflow.
The full description is available on Overleaf. I’ve applied the algorithm to the GAGES II database from USGSU, which includes all station gauges with at least 20 years of data.
Every red dot is a gauge, black lines are upstream-downstream connections between gauges, and the blue and green lines connect counties with each of the gauges by similar rules to the ones above (green edges if the link is forced to be longer than 100 km).
This kind of network opens the door for a lot of interesting analyses. For example, if agricultural withdrawals increase in the midwest, how much less water will be available downstream? We’re working now to construct a full optimization model that accounts for upstream dependencies.
Another simple question is, how much of the demand in each county is satisfied by flows available to it? Here are the results, and many cities show up in sharp red, showing that their demands exceed the surface water by 10 times or more.