Linking optical data and nitrates in the Lower Mississippi River to
enable satellite-based monitoring of nutrient reduction goals
Abstract
Hypoxic zones and associated nitrate pollution from farms, cities, and
industrial facilities is driving declines in water quality that affect
ecosystems, economies and human health in major rivers and coastal areas
worldwide. In the Mississippi River, the United States Environmental
Protection Agency set a goal of reducing nitrogen loading 20% by 2025
but estimating progress toward this goal is difficult because data from
in-stream gauges and laboratory samples are too sparse. Satellites have
the potential to provide sufficient data across the Mississippi River,
if a key methodological challenge can be overcome. Satellites provide
data from visible light, but nitrates are only observable with
ultraviolet light. We address this methodological challenge by using a
two-step surrogate modeling procedure to link optical data and nitrates
in the Lower Mississippi River. First, we correlate in-situ nitrate
measurements to common water quality parameters, particularly turbidity
and chlorophyll, using data from water sensors installed at Baton Rouge,
Louisiana, USA, and a long-term data set from Louisiana State
University. Second, we correlate these water quality data to satellite
estimates of water quality parameters. We found a correlation between
these water quality parameters and nitrate concentrations, as indicated
by a coefficient of determination, when the relationship was viewed in
non-linear parameter space. The spatial extent of the correlation was
tested with an upstream nitrate sensor 140 km north of the estimation
location. These results provide proof-of-concept that we can develop
models that use satellite data to provide large scale monitoring of
nitrates across the Mississippi River Basin and other impaired rivers,
globally.