This is the third page at Level 1 in a three level set. It provides a simple look at analytical results by type of location sampled.

Navigate: ◄ 2: Sites and protocols | ▲ Abstract | ► 4: Interpretations.

3. Simple results (Level 1)

3.1 Groundwater: Categoricals

Table 1 enumerates all of the NYS DEC pesticide lab’s analytical detections at categorical sites, ordered by category, site, and position of the sampling location (upgradient, downgradient, or within site application area) for 2022 and 2023. Land use categories or specific sites not appearing in these tables had no analytical detections of active ingredients nor degradation products during this time period.

A large majority of the lab analytes were not found at any categorical site thus we omit them completely to simplify the table. (The full list of analytes is in a Level 2 page.)

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In addition to quantifiable detections, the tables list the number of non-quantifiable detections (NQD) where the analyte was clearly present but only at concentrations below the lower detection limit; thus our terminology is subtly wrong – the “detection” limit is actually a quantification limit. (In cases where NQDs were observed in the absence of any quantifiable detections, the maximum concentration displayed in the table is the lab’s estimate of the highest NQD magnitude, which is lower than the lower detection limit (LDL). The minimum and maximum LDLs for a given analyte reflect the range over analytical batches. Each batch can have a unique LDL per parameter.

Table 1: Summary of pesticide active ingredient and metabolite detections at categorical sites, 2022-2023 (μg/l), sites obfuscated for privacy
Site LOC Analyte DET NQD Maxμgl ND LDLμgl
Golf-r within Propiconazole 1 0 0.021 7 0.01-0.01
Golf-r within Metolachlor OA 0 1 0.033 7 0.05-0.1
Green-g within Thiamethoxam 1 0 0.058 7 0.025-0.100
Green-e downgradient Mefentrifluconazole 1 0 0.202 2 0.025-0.05
Green-e downgradient Myclobutanil 1 0 0.063 2 0.025-0.025
Green-e downgradient Paclobutrazol 1 0 0.051 2 0.025-0.025
Green-e downgradient S-Metolachlor 1 0 0.202 2 0.025-0.05
Nur-r within Metolachlor OA 1 0 0.068 7 0.05-0.1
Nur-n downgradient Carbaryl 0 1 0.042 6 0.05-0.05
Nur-n downgradient Metolachlor OA 1 0 0.050 6 0.05-0.1
Nur-n upgradient Atrazine 4 0 0.231 0 0.01-0.01
Nur-n upgradient De Ethyl Atrazine 0 1 0.043 3 0.05-0.25
Nur-n upgradient Hydroxy Atrazine 1 0 0.108 3 0.05-0.25
Nur-n upgradient Metolachlor OA 0 1 0.033 3 0.05-0.1
Nur-n within Metolachlor OA 1 1 0.050 2 0.05-0.1
Nur-j upgradient Atrazine 1 0 0.016 8 0.01-0.01
Nur-j upgradient Glyphosate 1 0 5.140 4 1.0-1.0
Nur-j upgradient Simazine 2 0 0.031 7 0.01-0.01
Nur-j upgradient Acetochlor ESA 1 0 0.058 3 0.05-0.05
Nur-j upgradient Metolachlor ESA 2 0 0.222 7 0.05-0.15
Nur-j within Acetochlor ESA 0 1 0.048 3 0.05-0.05
Nur-j within Metolachlor ESA 1 0 0.218 5 0.05-0.15
Nur-j within Metolachlor OA 0 1 0.037 5 0.05-0.1
ROW-r downgradient Simazine 1 0 0.012 7 0.01-0.01
ROW-l downgradient Metolachlor OA 2 0 0.273 1 0.05-0.1
ROW-l within Metolachlor OA 2 0 0.127 1 0.05-0.1
Sod-r within Carbaryl 1 0 0.187 3 0.05-0.05
Sod-r within Metolachlor OA 1 1 0.053 2 0.05-0.1
Sod-n within Imidacloprid 4 0 0.051 11 0.025-0.05
Sod-n within Hydroxy Atrazine 1 0 0.118 9 0.05-0.25
Sod-n within Metolachlor ESA 8 0 0.630 2 0.05-0.15
Sod-n within Metolachlor OA 8 0 0.799 2 0.05-0.1
VegF-t ad hoc Metolachlor OA 1 0 0.261 1 0.05-0.1
VegF-t downgradient Metolachlor ESA 1 0 0.252 6 0.05-0.15
VegF-t downgradient Metolachlor OA 4 0 0.105 3 0.05-0.1
VegF-t upgradient Metolachlor OA 0 3 0.044 2 0.05-0.1
VegF-t within De Ethyl Atrazine 2 0 0.098 4 0.05-0.25
VegF-t within Metolachlor ESA 2 0 0.755 4 0.05-0.15
VegF-t within Metolachlor OA 3 0 2.198 3 0.05-0.1
VegF-l within Bentazon 4 0 8.763 4 0.5-0.5
VegF-l within Propiconazole 1 0 0.043 7 0.01-0.01
VegF-l within Metolachlor ESA 7 0 0.832 1 0.05-0.15
VegF-l within Metolachlor OA 7 0 0.705 1 0.05-0.1
VegF-h within Carbaryl 1 0 0.279 5 0.05-0.05
VegF-h within Fluopyram 2 0 0.075 4 0.025-0.025
VegF-h within Simazine 4 0 0.050 2 0.01-0.01
VegF-h within Terbacil 0 1 0.379 5 0.5-0.5
VegF-h within Thiamethoxam 0 1 0.013 7 0.025-0.100
VegF-h within JSE76 1 0 0.070 5 0.05-0.05
Vine-t within Carbaryl 1 0 0.065 7 0.05-0.05
Vine-t within Imidacloprid 3 0 0.051 9 0.025-0.05
Vine-t within Oxadiazon 1 0 0.559 7 0.025-0.1
Vine-n within Carbaryl 1 0 0.253 7 0.05-0.05
Vine-n within Simazine 4 0 0.175 4 0.01-0.01
Vine-l upgradient Metolachlor OA 2 0 0.126 2 0.05-0.1
Vine-l within Diuron 1 0 0.013 7 0.01-0.01
Vine-l within Metolachlor OA 0 1 0.024 7 0.05-0.1

Explanations of table columns: - LOC: position of sampling point within the site, relative to onsite pesticide use - DET: count of test results above detection limit - Maxμgl: maximum reported detected value (micrograms per liter) - NQD: count of unquantified test results below detection limit but likely present - ND: count of test results reported as below deteciton limit and unlikely present - LDL: lowest to highest reported detection limit across 2022-2023 sample batches (micrograms per liter)

Metolachlor and atrazine metabolites are the most common detections. The categorical cooperators rarely use atrazine; a few do use metolachlor. We do not have many perfectly isolated sites thus a sample on a site may contain residues from off-property.

Upgradient sampling points, used at a portion of the categorical sites, provide a way to tell if the detection could be coming from pesticide use off-property. Two outdoor nursery sites have very few detections from their own pesticide use, but consistent residue detections consistent with land use on neighboring properties in their upgradient wells or groundwater-fed ponds.

The active ingredients found at “-within” and “-downgradient” sampling points were much more diverse than those at “-upgradient” sampling points. (In part this is due to site selection which favored sites that did not need an upgradient sampling point.)

Table 2: Summary of active ingredients detected in different kinds of sampling points at categorical sites
Within and downgradient Upgradient
Propiconazole Atrazine
Thiamethoxam Glyphosate
Mefentrifluconazole Simazine
Myclobutanil
Paclobutrazol
S-metolachlor
Carbaryl
Simazine
Imidacloprid
Bentazon
Fluopyram
Terbacil
Oxadiazon
Diuron

The metabolites detected (Table 3) were almost the same at different kinds of sampling points. Four families of metabolites are tested for, related to herbicides atrazine, metolachlor, and acetochlor, and insecticide cyantraniliprole. Atrazine and metolachlor are very popular, and their breakdown products found more widely than the parent compounds in upstate groundwater in our earlier projects and USGS work.

Table 3: Sumary of metabolites detected in different kinds of sampling points at categorical sites
Within and downgradient Upgradient
Metolachlor OA Metolachlor OA
Metolachlor ESA Metolachlor ESA
Hydroxy atrazine Hydroxy atrazine
De ethyl atrazine De ethyl atrazine
JSE76 (of cyantraniliprole) Acetochlor ESA

Categorical site detections versus active ingredient usage

Some of the categorical site cooperators provided pesticide use information which had been used to develop the lab analyte list. These lists can be compared against what was detected and also what should not have been detected for the same sites. In 2024 we refreshed some lists including discussings with most owners about detections in samples from their sites. We are most interested in two cases of what was analyzed for: used and detected, and not used and detected.

Table 4 examines the case of detections at categorical sites that are consistent with owner reports of their product uses. These are not from upgradient sampling points with two exceptions. The Outdoor nursery detection of glyphosate, the only glyphosate detection in the project through 2023, was in a groundwater fed pond that receives groundwater flowing from off property. However the owner does use spot treatments of glyphosate near the edge of the pond where we sample, and the detection could have been from that. The other exception is for a vegetable farm where there is definite metolachlor use and the site’s upgradient sampling point did contain faint traces (below detection limit) of metolachlor OA repeatedly. Topographically the metabolite is most likely from the upgradient neighboring dairy farm, but the chemical identity does not rule out its origin within the cooperator’s property. The site includes one ad hoc sampling point that is a stream below all treated fields at the same property, whose metabolite concentration could be from anywhere upstream or the cooperator’s property.

The within and downgradient points account for 38 out of the listed 43 cases. For the 38, only metabolites exceeded 1 μg/L. Seven different active ingredients were detected.

Table 4: Individual pesticide and metabolite detections at categorical sites, 2022 and 2023, with reported definite use (μg/l), individual sites suppressed for privacy
category loctype parameter result remark
Golf within Propiconazole 0.021 -
Greenhouse downgradient Myclobutanil 0.063 -
Outdoor nursery downgradient Carbaryl <*0.05 -
Outdoor nursery upgradient Glyphosate 5.14 spot use
Sod within Imidacloprid 0.028 -
Sod within Imidacloprid 0.035 -
Sod within Imidacloprid 0.049 -
Sod within Imidacloprid 0.051 -
Vegetable and fruit ad hoc Metolachlor OA 0.261 -
Vegetable and fruit downgradient Metolachlor ESA 0.252 -
Vegetable and fruit downgradient Metolachlor OA 0.105 -
Vegetable and fruit downgradient Metolachlor OA 0.096 -
Vegetable and fruit downgradient Metolachlor OA 0.105 -
Vegetable and fruit downgradient Metolachlor OA 0.054 -
Vegetable and fruit upgradient Metolachlor OA <*0.05 -
Vegetable and fruit upgradient Metolachlor OA <*0.05 -
Vegetable and fruit upgradient Metolachlor OA <*0.05 -
Vegetable and fruit within Carbaryl 0.279 -
Vegetable and fruit within Fluopyram 0.031 -
Vegetable and fruit within Fluopyram 0.075 -
Vegetable and fruit within Metolachlor ESA 0.748 -
Vegetable and fruit within Metolachlor ESA 0.488 -
Vegetable and fruit within Metolachlor ESA 0.755 -
Vegetable and fruit within Metolachlor ESA 0.217 -
Vegetable and fruit within Metolachlor ESA 0.553 -
Vegetable and fruit within Metolachlor ESA 0.371 -
Vegetable and fruit within Metolachlor ESA 0.783 -
Vegetable and fruit within Metolachlor ESA 0.55 -
Vegetable and fruit within Metolachlor ESA 0.832 -
Vegetable and fruit within Metolachlor OA 0.575 -
Vegetable and fruit within Metolachlor OA 0.646 -
Vegetable and fruit within Metolachlor OA 0.705 -
Vegetable and fruit within Metolachlor OA 0.079 -
Vegetable and fruit within Metolachlor OA 0.29 -
Vegetable and fruit within Metolachlor OA 1.618 -
Vegetable and fruit within Metolachlor OA 2.037 -
Vegetable and fruit within Metolachlor OA 2.198 -
Vegetable and fruit within Metolachlor OA 0.107 -
Vegetable and fruit within Metolachlor OA 0.312 -
Vineyard within Simazine 0.124 -
Vineyard within Simazine 0.175 -
Vineyard within Simazine 0.069 -
Vineyard within Simazine 0.054 -

Table 5 examines the case of detections at categorical sites that are for active ingredients that the owners confirmed were not used onsite, or are for metabolites when the active was confirmed not used. A majority are consistent with neighboring land uses as indicated in the remarks column. We have one carbaryl detection for a well having no nearby carbaryl use for at least five years. Of the 50 cases, 42 are for field crop herbicides metolachlor, atrazine, acetochlor or their metabolites. None of the categorical cooperators has field crop land; however metolachlor can be used on a broad array of land.

Mainly these illustrate the difficulty of isolating a cooperating pesticide user site from their surroundings; groundwater flow does not respect property lines. The NYSDEC original design included upgradient sampling points for exactly this reason.

Table 5: Individual pesticide and metabolite detections at categorical sites, 2022 and 2023, with reported non-use (μg/l), individual sites suppressed for privacy
category loctype parameter result remark
Golf within Metolachlor OA <*0.05 -
Greenhouse downgradient Mefentrifluconazole 0.202 ditch detect, neighbor?
Greenhouse downgradient Paclobutrazol 0.051 ditch detect, neighbor?
Greenhouse downgradient S-Metolachlor 0.202 ditch detect, neighbor?
Outdoor nursery downgradient Metolachlor OA 0.05 pond neighbor field crops?
Outdoor nursery upgradient Acetochlor ESA 0.058 uphill corn
Outdoor nursery upgradient Atrazine 0.016 pond neighbor field crops?
Outdoor nursery upgradient Atrazine 0.018 pond neighbor field crops?
Outdoor nursery upgradient Atrazine 0.016 pond neighbor field crops?
Outdoor nursery upgradient Atrazine 0.016 uphill corn
Outdoor nursery upgradient Atrazine 0.231 pond neighbor field crops?
Outdoor nursery upgradient De Ethyl Atrazine <*0.05 pond neighbor field crops?
Outdoor nursery upgradient Hydroxy Atrazine 0.108 pond neighbor field crops?
Outdoor nursery upgradient Metolachlor ESA 0.214 uphill corn
Outdoor nursery upgradient Metolachlor ESA 0.222 uphill corn
Outdoor nursery upgradient Metolachlor OA <*0.05 pond neighbor field crops?
Outdoor nursery upgradient Simazine 0.031 uphill corn
Outdoor nursery upgradient Simazine 0.024 uphill corn
Outdoor nursery within Acetochlor ESA <*0.05 uphill corn
Outdoor nursery within Metolachlor ESA 0.218 uphill corn
Outdoor nursery within Metolachlor OA 0.05 pond neighbor field crops?
Outdoor nursery within Metolachlor OA <*0.05 uphill corn
Outdoor nursery within Metolachlor OA <*0.05 pond neighbor field crops?
ROW downgradient Metolachlor OA 0.273 uphill field crops
ROW downgradient Metolachlor OA 0.237 uphill field crops
ROW within Metolachlor OA 0.126 uphill field crops
ROW within Metolachlor OA 0.127 uphill field crops
Sod within Hydroxy Atrazine 0.118 -
Sod within Metolachlor ESA 0.265 -
Sod within Metolachlor ESA 0.256 -
Sod within Metolachlor ESA 0.626 -
Sod within Metolachlor ESA 0.179 -
Sod within Metolachlor ESA 0.17 -
Sod within Metolachlor ESA 0.273 -
Sod within Metolachlor ESA 0.157 -
Sod within Metolachlor ESA 0.63 -
Sod within Metolachlor OA 0.3 -
Sod within Metolachlor OA 0.349 -
Sod within Metolachlor OA 0.799 -
Sod within Metolachlor OA 0.137 -
Sod within Metolachlor OA 0.12 -
Sod within Metolachlor OA 0.375 -
Sod within Metolachlor OA 0.128 -
Sod within Metolachlor OA 0.596 -
Vegetable and fruit within De Ethyl Atrazine 0.063 neighbor?
Vegetable and fruit within De Ethyl Atrazine 0.098 neighbor?
Vineyard within Carbaryl 0.065 >5 yrs ago
Vineyard within Diuron 0.013 -
Vineyard within Imidacloprid 0.044 -
Vineyard within Imidacloprid 0.045 -
Vineyard within Imidacloprid 0.051 -

There is actually only one surprise: presumed less leaching-vulnerable muckland sites for sod and vegetables are showing pesticide residues. If recharge water was flowing uniformly through the highly organic soil matrix, pesticide residues would be expected to be delayed by adsorbing to the organic matter, for long enough for biochemical processes to degrade them into undetectability. We believe this is from pesticides bypassing the organic matrix by passing through wormholes, former root holes, and other preferential pathways inside which the pesticide has little chance to avoid being washed downward quickly and with little opportunity to touch the organic matter. These only flow when the soil matrix becomes saturated, thus are air-filled most of the time.

3.2 Groundwater: Long term

As with categoricals, there were no pesticide detections at concentrations of concern in groundwater at long term sites in the first year of sampling, 2023 (Table 6). Nearly all of the 20 detections were of popular herbicides atrazine, metolachlor (including isomer S-metolachlor), and simazine, with the highest detections on the order of 1 microgram per liter (μg/l) and a large majority under 0.1 μg/l. Except for atrazine whose drinking water standard is 3.0 μg/l, these chemicals fall under New York State’s default drinking water standard of 50 μg/l. Values of 0.1 μg/l represent 3% (atrazine) to 0.2% (all others) of the applicable standard.

This repeats the finding of the six county monitoring projects in the 2000s and 2010s, in which no well among around 240 yielded any active ingredient concentration of health concern.

Detections of metabolites (Table 7) were more widespread (34 detections, all six tested metabolites) than the corresponding parent active ingredients (15 detections, five actives). Effectively the metabolites are also behaving consistently with findings in earlier upstate projects in which the most popular herbicides are being successfully degraded in the environment before they reach most drinking water wells.

The findings should be considered continuing good news for the pesticide users, whose routine practices are not causing detectable groundwater problems. The metabolites indicate that the wells are tapping recharge water through areas where the parent active ingredients have been applied, thus the soil is being effective.

Table 6: Detections of active ingredients at long term sites, 2023, μg/L
County parameter maxResult minDL NQD DET
Cayuga Atrazine 0.034 <0.01 0 1
Columbia Simazine 0.037 <0.01 0 1
Cortland Atrazine 0.035 <0.01 0 1
Cortland Bromacil 0.026 <*0.05 1 0
Cortland Atrazine 0.013 <0.01 0 1
Dutchess Simazine 0.025 <0.01 0 1
Genesee Atrazine 0.023 <0.01 0 1
Genesee Atrazine 0.067 <0.01 0 2
Genesee Metolachlor 0.992 <0.025 0 2
Genesee Propiconazole 0.063 <0.01 0 1
Genesee S-Metolachlor 1.642 <0.05 0 2
Genesee S-Metolachlor 0.068 <0.05 0 1
Onondaga Atrazine 0.017 <0.01 0 1
Onondaga Fluxapyroxad 0.360 <0.25 0 1
Onondaga Atrazine 0.012 <0.01 0 1
Ontario Atrazine 0.308 <0.01 0 1
Ontario S-Metolachlor 0.107 <0.05 0 1
Table 7: Detections of metabolites at long term sites, 2023, μg/L
County parameter maxResult minDL NQD DET
Broome Metolachlor OA 0.795 <0.05 0 1
Cayuga Metolachlor ESA 0.037 <*0.05 1 0
Cayuga Metolachlor OA 0.226 <0.05 0 1
Cayuga De Ethyl Atrazine 0.105 <0.05 0 1
Cayuga Hydroxy Atrazine 0.104 <0.05 0 1
Cayuga Metolachlor OA 0.155 <0.05 0 1
Columbia Acetochlor ESA 0.054 <0.05 0 1
Cortland De Ethyl Atrazine 0.056 <0.05 0 1
Cortland Metolachlor ESA 0.463 <0.05 0 1
Cortland Metolachlor OA 2.825 <0.05 0 1
Cortland Acetochlor ESA 0.206 <0.05 0 1
Cortland De Ethyl Atrazine 0.072 <0.05 0 1
Cortland Metolachlor OA 0.256 <0.05 0 1
Dutchess Metolachlor OA 0.075 <0.05 0 1
Genesee Acetochlor ESA 0.044 <*0.05 1 0
Genesee Acetochlor OA 0.038 <*0.05 1 0
Genesee De Ethyl Atrazine 0.058 <0.05 0 1
Genesee Metolachlor ESA 0.147 <0.05 0 1
Genesee Metolachlor OA 1.665 <0.05 0 1
Genesee Metolachlor ESA 0.314 <0.05 0 2
Genesee Metolachlor OA 1.681 <0.05 0 2
Onondaga Metolachlor OA 0.071 <0.05 0 1
Onondaga Metolachlor OA 0.036 <*0.05 1 0
Ontario De Ethyl Atrazine 0.063 <0.05 0 1
Ontario Hydroxy Atrazine 0.035 <*0.05 1 0
Ontario Metolachlor ESA 0.036 <*0.05 1 0
Ontario Metolachlor OA 0.060 <0.05 0 1
Orange Metolachlor OA 0.042 <*0.05 1 0
St. Lawrence Metolachlor OA 0.169 <0.05 0 1
Tompkins Metolachlor OA 0.302 <0.05 0 1
Wayne Metolachlor ESA 0.140 <0.05 0 1
Wayne Metolachlor OA 0.537 <0.05 0 1

Symbolism in tables:

  • Each row represents one detected analyte at one site; most sites had only one sample, but a few had two samples.
  • LDLμgl is the lowest detection limit for the analyte in μg/l,
  • Maxμgl is the highest result of samples covered by the row.
  • NQD means the count of samples reported with “present but below detection limit”,
  • DET means the count of samples reported at or above the detection limit.
  • An asterisk under LDLμgl, in <*n.nn means that the concentration was below the detection limit of n.nn, thus the number for concentration provided is uncertain.

3.3 Lakes

Table 8 and Table 9 enumerate all detected analytes in lake samples.

Lake Waccabuc has a largely forested watershed, with residential and golf course land uses near the lake. Only tiny traces of fungicides, perhaps used at the golf course, have shown up in samples from the current project and an earlier project.

In contrast, the other three lakes have watersheds containing considerable farmland thus the lake samples contain typical metabolites (metolachlor OA and ESA) and parent compounds (atrazine, S-metolachlor, 2,4-D) of popular upstate agricultural herbicides.

Table 8: Active ingredient detections at lakes by sampling point, 2022-2023
Lake loccode loctype parameter Maxμgl LDLμgl ND NQD DET
Canadarago Lake Oaks Creek outlet Lake - outlet Atrazine 0.019 0.01-0.01 1 0 1
Canadarago Lake Ocquionis Creek alt, inlet Lake - inlet Atrazine 0.112 0.01-0.01 0 0 1
Canadarago Lake Ocquionis Creek inlet Lake - stream inlet Atrazine 0.241 0.01-0.01 1 0 1
Canadarago Lake Ocquionis Creek inlet Lake - stream inlet S-Metolachlor 0.064 0.025-0.05 1 0 1
Chautauqua Lake ShallowCHQ Lake Imidacloprid 0.040 0.025-0.025 0 0 2
Chautauqua Lake NorthCSLAP Lake - CSLAP Atrazine 0.011 0.01-0.01 0 0 1
Chautauqua Lake ShallowCHQ Lake Atrazine 0.015 0.01-0.01 0 0 1
Chautauqua Lake ferry Lake - inlet Atrazine 0.013 0.01-0.01 0 0 1
Chautauqua Lake outlet Lake - outlet Atrazine 0.011 0.01-0.01 0 0 1
Chautauqua Lake mccrea Lake - outlet Atrazine 0.009 0.01-0.01 0 1 0
Lake Waccabuc Tribs Lake - near inlet Mefentrifluconazole 0.026 0.025-0.05 3 0 1
Upper Little York Lake Dam Lake - outlet 2,4-D 1.530 0.2-0.5 1 0 1
Upper Little York Lake Dam Lake - outlet S-Metolachlor 0.031 0.05-0.05 1 0 1
Upper Little York Lake Mid inlet Lake - near inlet 2,4-D 1.610 0.2-0.5 1 0 1
Upper Little York Lake Middle Lake 2,4-D 1.720 0.2-0.2 0 0 1
Upper Little York Lake North inlet Lake - near inlet 2,4-D 1.330 0.2-0.5 1 0 1
Upper Little York Lake North inlet Lake - near inlet Atrazine 0.013 0.01-0.01 1 0 1
Table 9: Pesticide metabolite detections at lakes by sampling point, 2022-2023
Lake loccode loctype parameter Maxμgl LDLμgl ND NQD DET
Canadarago Lake Mink Creek inlet Lake - stream inlet Metolachlor OA 0.056 0.05-0.1 1 0 1
Canadarago Lake Oaks Creek outlet Lake - outlet Metolachlor OA 0.085 0.05-0.1 1 0 1
Canadarago Lake Ocquionis Creek alt, inlet Lake - inlet Metolachlor OA 0.199 0.05-0.05 0 0 1
Canadarago Lake Ocquionis Creek inlet Lake - stream inlet Metolachlor OA 0.523 0.05-0.1 1 0 1
Canadarago Lake Ocquionis Creek inlet Lake - stream inlet Metolachlor ESA 0.045 0.05-0.15 1 1 0
Chautauqua Lake ferry Lake - inlet Metolachlor OA 0.054 0.05-0.05 0 0 1
Chautauqua Lake mccrea Lake - outlet Metolachlor OA 0.040 0.05-0.05 0 1 0
Chautauqua Lake outlet Lake - outlet Metolachlor OA 0.042 0.05-0.05 0 1 0
Upper Little York Lake Dam Lake - outlet Metolachlor ESA 0.278 0.05-0.15 1 0 1
Upper Little York Lake Dam Lake - outlet Metolachlor OA 0.147 0.05-0.1 1 0 1
Upper Little York Lake East inlet Lake - near inlet Metolachlor OA 0.171 0.05-0.05 0 0 1
Upper Little York Lake Mid inlet Lake - near inlet Metolachlor ESA 0.306 0.05-0.15 1 0 1
Upper Little York Lake Mid inlet Lake - near inlet Metolachlor OA 0.187 0.05-0.1 1 0 1
Upper Little York Lake Middle Lake Metolachlor ESA 0.279 0.15-0.15 0 0 1
Upper Little York Lake North inlet Lake - near inlet Metolachlor ESA 0.321 0.05-0.15 1 0 1
Upper Little York Lake North inlet Lake - near inlet Metolachlor OA 0.235 0.05-0.1 1 0 1

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Last updated: 2025-01-07, sp17 AT cornell.edu