HowTo – Lake site characterization [30%]
Priority: low
Updating: rare while we are not finding much of interest in results
This covers eventual work at a lake to determine potential causal factors affecting pesticides we detect in a sampled lake. This would be triggered only if we find concentrations of interest.
Note: This HowTo formerly was about lake selection. That topic is no longer covered by any HowTo in this collection since the selection process was expedient.
Change log:
| When | Who | Comment |
|---|---|---|
| 2021 08 ?? | Sp17 | First version placeholder. |
| 2021 09 07 | Sp17 | Add change log. Add thoughts about map overlay to highlight CSLAP lakes to pursue. |
| 2022 | Sp17 | The earlier version is obsolete after we minimized resources devoted to lake selection, in light of the very few samples per year in the task. |
| 2023 06 16 | Sp17 | Rephrase to make this conditional on our finding something unexpected in our expediently selected lakes. Also convert to Markdown format. |
| 2023 06 22 | Sp17 | Adding more flesh to bare bones. |
1. Objectives:
- For pesticides detected in lakes at notable concentrations, determine potential causal factors based on land use in the watershed, lake circulation and volume turnover characteristics, weather conditions before sampling, and other factors.
2. Potential causal factors
- Some pesticides are applied in lakes near shorelines for aquatic weed control. We included two aquatic herbicides in the 2022 analyte list.
- We expect that pesticides will appear in surface layers of lakes primarily from fresh deliveries from tributaries or fresh washoff from shore properties. USGS work on Cayuga Lake found that first storms after unison atrazine application in spring would deliver atrazine, by an all-tributaries grab sampling campaign.
- USGS also found that atrazine lingered in Cayuga Lake at depths. This is due to long turnaround time. Thus lake diagnostic characterization should include turnover time (volume/annual total inflow).
- Long lived pesticide metabolites may also arrive via groundwater discharge into lakes.
3. Data inputs for rapid assessment
- Measured data during sampling
- CSLAP measured data at other sampling times for the same lake
- Meteorology and lake status before sampling
- Land use in watershed
- PSUR pesticide use data at zip code level
As with groundwater site characterization, the basis for refined lake characterization is a mix of other people’s published data, our own observation and measurement, and what the volunteers bring from their experience.
Many CSLAP lake watersheds have been mapped as part of lake studies. Watersheds can also be auto-delineated in QGIS using digital elevation maps.
Our project geographic map collection in QGIS contains PSUR pesticide intensity data, DEMs, and points representing FOLA / CSLAP member lakes; these points may be the outlets. We also have the special categorical users mapped from Google Earth. We have USDA Cropscape agricultural land uses and EPA MRL land cover mapsin the base QGIS map set, available to overlay with watershed boundaries.
We would create a polygon of the lake’s watershed and characterize concentrated pesticide uses in the watershed related to what is detected. Moderate to larger lakes will have enough watershed so that the overlay of PSUR pesticide use intensities by zip code on watershed boundaries will not be too bad of a geometric mismatch. For small lakes like Lake Waccabuc and Upper Little York Lake this overlay is not as helpful.
4. Resampling
The project’s protocol for surprisingly high results (not necessarily standard exceedances) is to sample again soon after the result is known, i.e. off-cycle sampling. The lag between sample collection and lab analysis of up to one year makes this an “Extra next year” result, which is constrained by ability and willingness of the volunteers on lakes sampled by volunteers.
The lake monitoring has a very low priority in the project due to the small number of samples allowed to be tested (8 per year across 4 lakes) thus the amount of labor to devote to lake watershed characterization should be kept to a minimum.