Why the delivery scale?

When it comes to monitoring water quality, there are quite a number of factors to consider: What are you monitoring for? How is land utilized within the targeted area?  How, when, where, and for how long will water samples be collected? Under what flow conditions? The scale at which you monitor really makes a difference!

The plot scale is valuable for looking at the impacts of specific in-field management practices. Plot scale (or field-scale) monitoring is where most of the pollutant export and delivery data come from that informed the Iowa Nutrient Reduction Strategy. Treatments can also be easily replicated on the plot scale. However, it’s challenging to properly scale up plot-level measurements to the area of practice implementation to truly assess water quality impacts across landscapes and with multiple practices.

Monitoring on the watershed scale allows us to look at the collective impacts over a much larger land area.  For instance, watershed-scale monitoring provides a broad picture of water quality challenges and aids in the identification of impaired waters. When monitoring on the watershed scale, measurements inherently include what’s happening on the land (field scale practices), plus field-to-stream transport, plus in-stream processes (bed and bank processes).  It certainly provides a comprehensive look the big picture, but you can’t “sort” out the different contributions of what’s happening in-field versus in-stream.

In between these two lies the delivery scale.  Delivery scale monitoring occurs at the point where water is delivered to a creek or stream. For instance, with drainage research, this would be the point where the tile main surfaces and water empties into a stream. In a nutshell, the delivery scale reflects the direct water quality impacts from an agricultural area, minus the potential confounding effects of in-stream processes like bed and bank erosion. Here at the Iowa Learning Farms, we’d argue that this is truly a sweet spot for looking at the impacts of specific conservation practices.

You need to monitor at the delivery scale if you want to know specifically what the agricultural impacts are.  That’s exactly what we’re striving towards with the Conservation Learning Labs project.

Within a small watershed area (several hundred acres), can we get a substantial percentage of producers adopting a conservation practice, like cover crops, and then measure corresponding water quality improvements at the delivery scale?  Modeling suggests so, and this project will quantify what nutrient load reductions are actually realized thanks to large scale, targeted adoption of cover crops.

Cover crops were seeded for the first time in fall 2017 within our two Conservation Learning Labs project sites.  Stay tuned for results as we look at the water quality (and soil health) impacts of substantial cover crop adoption on the delivery scale!

Ann Staudt