The water network consists of a streamflow network, consisting of connections between river gauges, reservoirs, and junctions, and a canal network. The canal network is a bipartite network, with links from nodes in the streamflow network and the counties. The initwaternet.jl
file loads these networks into the global environment. It uses cached Julia Data (.jld
) files to speed up the loading process, creating them if they aren't present in the data
directory.
The river network is documented here: https://www.overleaf.com/read/gftdkjjkdrsn
The columns in the waterdraws.jld
data are as follows:
network
variable of the waternet.RData
file.R
script that generates the countydraws.RData
file (network3/demand/allcounties.R
).wateridverts
dictionary, which allows easy access to the nodes in the river network by name.
In [8]:
using DataFrames
draws = deserialize(open("../data/waterdraws.jld", "r"))
Out[8]:
You can replace the data/countydraws.RData
file with another R Data file which contains the variable draws
. draws
should be a data.frame
minimally with the columns fips and source.
Until the script for generating the countydraws.RData
file is migrated into the repository, please do the following to extend the dataset:
countydraws.RData
file into a new sources/waternet
directory as countydraws.v1.RData
.countydraws.v2.RData
file. Copy this into the data
directory.countydraws.v(N).RData
(for $N \ge 2$) file, use the latest one as your input, and output a file countydraws.v(N+1).RData
.Future work:
By Laureline
Several utilities and facilities operate accros multiple counties. For instance, New York City water supply system source its water from the Catskill Mountains and the Delaware river in Delaware County and distribute the water to all of the boroughs.
Utilities of this type are not rare and occur at many locations across CONTUS. So that the water network allows to link the point of source and the point of use, additionnal connections have been added to the countydraws file.
The first step consists in finding the utilities and facilities that operate across multiple counties. This is done by finding all of the water utilities operating within a given county on the Drinking Water Mapping Application to Protect Source Waters website (https://dwmapspublic.rti.org/). The website then redirects to the Safe Drinking Water Information System (SDWIS) Federal Reporting Services, which provides the list of counties served by the given water system (such as https://ofmpub.epa.gov/apex/sfdw/f?p=SDWIS_FED_REPORTS_PUBLIC:PWS_SEARCH:::::PWSID:NY7003493). This led to the construction of a dataset canals.txt with the first column being the source county (referred by FIPS), and the other ones listing the counties the water facilities present in the source county serve.
The second step is to complete the countydraws dataset. This is done using the R script script_incorporation_missing_data.R, which simply adds a connection between each gauge within a source county to the point of use county.
As the number of water utilities is consequent, this task has not been accomplished for all counties yet. As a starting point, we focused our research on problematic areas: counties that presented a suspicious public supply withdrawals/population ratio, and counties with important population. The following plot (fig 1.a) shows the USGS 2010 public supply fresh water withdrawals in function of the population. The dots in green are the counties that have been added to the missing canals set.
The following figure shows the difference between withdrawals and the estimated demand for all CONTUS.