Agricultural Chemical Concentrations and Loads in Rivers Draining

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Chapter 17

Agricultural Chemical Concentrations and Loads in Rivers Draining the Central Valley, California: Before, During, and After an Extended Drought Joseph Domagalski* California Water Science Center, U.S. Geological Survey, 6000 J Street, Placer Hall, Sacramento, California 95819, United States *E-mail: [email protected].

Drought or near drought conditions persisted in California from 2012 through 2016, followed by a high precipitation year in 2017. Long-term water quality monitoring of two key river stations, the Sacramento River at Freeport and the San Joaquin River near Vernalis, located within the largely agricultural Central Valley, allow for an examination of pesticide concentrations and mass loading. Daily models were constructed using an estimation procedure that links mean daily streamflow with pesticide concentration monitoring and time. There were 13 different pesticides and 3 degradation products modeled, including herbicides, fungicides, and insecticides. Not all pesticides were detected at each river site. There were 8 pesticides modeled for the Sacramento River and 14 for the San Joaquin River. There were 16 models for these two sites that showed decreasing trends, 5 with increasing, and 1 with no trend. Mass loads of the modeled compounds increased in 2017 because of the high river discharge. Most pesticides had measured or modeled concentrations that were below acute and chronic toxicity benchmarks. One exception was the neonicotinoid insecticide imidacloprid, which had an increasing trend in concentration with levels that exceeded chronic toxicity thresholds for invertebrates, especially after 2015. The use of some pesticides decreased during this period © 2019 American Chemical Society Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

of time, which partly explains the decreasing concentration trends. However, some pesticides had increased usage but with decreasing river concentration. The preponderance of negative trends in concentration of most pesticides suggested that lack of rainfall during the drought resulted in less transport from treated fields to the streams.

Introduction Pesticides have been monitored at many stream locations throughout California and especially within the Central Valley (Figure 1). The Central Valley is the largest agricultural region in the State providing vegetables, fruits, and nuts for both national and international consumption (1). The two main rivers draining the Central Valley are the Sacramento and San Joaquin rivers. Together, these two rivers drain over 100,000 km2, all of which are in California and which account for about one third of the area of the entire state. Water from these two rivers flow into the ecologically sensitive Delta of the Sacramento and San Joaquin rivers and then to the San Francisco Bay. As a result, the water quality of these two rivers is of critical management importance. The California Central Valley Regional Water Quality Control Board is the primary agency responsible for enforcing the Clean Water Act in California and currently has several Total Maximum Daily Load (TMDL) plans in effect (2) or under development. These TMDL plans include legacy pesticides such as organochlorine insecticides, organophosphorus insecticides including diazinon and chlorpyrifos, the herbicide diuron, and pyrethroid insecticides. The goal of these management plans is to decrease or eliminate instances of aquatic toxicity from pesticides to different organisms by reducing the amount of a pesticide that may be mobilized from a point of application. Numerous studies have shown that aquatic toxicity occurs episodically in the Central Valley rivers and streams (3–12). In addition, many of those studies showed that concentrations and loads are elevated following storm water runoff. Drought has the effect of lowering discharge in rivers that may lead to elevated concentrations, but it also may lead to less mobilization of pesticides from the land surfaces or vegetation after application. The climate of California is characterized as Mediterranean (13). Mediterranean climates are known to have periodic droughts, sometimes lasting for several years (14). A recent drought affected much of the State from 2012 to 2016 (15), which was then followed by an extremely wet year in 2017. The driest years of this drought period were between the end of 2011 and the fall of 2015. Although precipitation in northern California was average in 2016, it was not enough to alleviate the water deficit (15). The U.S. Geological Survey (USGS) has had a monitoring program since the mid-1990s at two downstream locations on the Sacramento and San Joaquin rivers. The two sampling locations, Sacramento River at Freeport and San Joaquin River at Vernalis (Figure 1), have continuous records of daily discharge, thereby allowing for calculations of mass loading. Water quality sampling for pesticides has taken place at either monthly or twice-monthly intervals with occasional storm sampling 334 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

throughout the years allowing for a rich data set to examine trends in concentration and mass load for specific time frames. The USGS utilizes its own laboratory for chemical analysis with low method detection limits and with a rigorous quality assurance/quality control program (16). Pesticides analyzed change with time in response to new use patterns, and the laboratory adds new analytes and degradation products, when applicable, as soon as the method validation is completed. Estimates of daily pesticide concentrations and loads can be obtained using models that regress discharge, time, and measured concentrations. Pesticides can be difficult to model because of the episodic nature of their occurrence in water. Our approaches to the modeling are discussed in the subsequent section. We compiled concentration and discharge data from 2010 through 2017. This time frame includes predrought conditions, drought, and one year postdrought. Not all pesticides were included in the method going back to 2010, and for those, we used the available record, which was 2012 to 2017. The model estimates included daily concentrations that we compared to aquatic-life benchmarks provided by the U.S. Environmental Protection Agency (17) to assess potential ecological risks during this time period.

Study Area, Data Sources, Methods The Central Valley is the largest agricultural region of California. It is made up of the Sacramento Valley to the north and the San Joaquin Valley to the south (Figure 1). Land cover surrounding the Central Valley is a mix of forests and grasslands. The entire Sacramento River watershed is about 70,000 km2 (18). The Sacramento Valley portion of the Sacramento River watershed is about 16,400 km2. The drainage basin of the entire San Joaquin River watershed is about 80,000 km2 (19); however, the lower half of the San Joaquin River watershed, sometimes referred to as the Tulare Basin, has closed drainage and does not contribute flow to the sampling location on the San Joaquin River. The northern portion of the San Joaquin River watershed within the Central Valley is about 11,450 km2 in area. Agriculture is diverse throughout the Central Valley. Major crop types in the Sacramento Valley by area are rice, alfalfa, and orchard crops such as almonds, peaches, prunes, and walnuts (20). The San Joaquin Valley has a diversity of orchards, row crops, and dairies. Although agriculture is the largest land use within the Central Valley, there are a number of urbanized areas, which also are sources of pesticides to the rivers. The two sampling stations for this study are the Sacramento River at Freeport (USGS Site Number 11447650) and the San Joaquin River near Vernalis (USGS Site Number 11303500). Discharge data for these two sampling locations are available from the USGS National Water Information System (21). We used the R package dataRetrieval (22) to obtain the mean daily discharge data for subsequent use in modeling calculations. Similarly, pesticide concentration data were obtained from the same source. Field level quality assurance/quality control data were also obtained. These include periodic blanks, replicates, and spiked samples. Further details on the design of the field quality procedures (23) and information on the USGS National Water Quality Laboratory (16) are available. 335 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Methods for pesticide extraction and analysis have changed or evolved over the years. Currently, most pesticides are analyzed by a liquid chromatography mass spectrometry/mass spectrometry (tandem mass spectrometry) method (24). There are 225 pesticides or degradates analyzed by this method along with various surrogate compounds used to assess method performance. The analyses of pesticides were completed on filtered water samples. Water samples are filtered through a glass fiber filter with a nominal pore size of 0.7 micrometers prior to be shipped to the laboratory. Therefore, we focus on dissolved pesticides in this analysis and not on sediment bound pesticides. A list of the current pesticides analyzed is given in Appendix 1. Most of those compounds were either not or rarely detected. We selected pesticides for modeling that had a preponderance of detections (25% or more) above the reporting limit for these calculations. Nondetects can be included in the model calibration as either using one half of the detection or reporting limit or simply using a zero concentration.

Figure 1. Map of California showing the locations of Central Valley, the Sacramento and San Joaquin River basin boundaries, and the two sampling sites.

336 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Calculations of daily pesticide concentrations and loads were completed using the “rloadest” statistical model (25) available from the Comprehensive R Archive Network (26). The Fortran version of the model has previously been described (27). There are two general approaches to modeling using this software. The first is to select one of nine models that regress concentration against discharge with the option to include seasonality using the sine and cosine of decimal time. A second option is to use a “seasonal wave” that simulates when a pesticide is likely to be present based on the water quality sampling (28). There is frequently a time of year, such as prior to crop emergence after planting or during flowering of fruit trees, when pesticides are applied to maximize their effectiveness. When a subsequent runoff event occurs, a pulse of pesticides can be mobilized from the field or vegetation to a stream. When these “seasonal waves” re-occur from year to year, an effective modeling tool allows for calculation of daily concentration or load. The seasonal wave can be used to predict when maximum concentrations are expected. Utilizing the observed concentrations, a particular form of the seasonal wave is chosen to best represent the data, such as how long (effective half-life) the pulse can be detected. The seasonal wave model has been used previously to estimate pesticide concentrations in streams or rivers of the western United States including the two sites of this study (29). The seasonal wave model works best when there is a clearly defined pulse or pulses of the modeled compound to the streams. As the drought progresses, the pulse may not be apparent and not necessarily produce the best statistical model. In that case, the nonwave model may provide the better statistical result. Both the seasonal wave and nonwave models compute the natural log of concentration using log transformed discharge, and the model provides summary statistics on the natural log of the resulting modeled concentrations. The Nash Sutcliff efficiency index calculates the summary statistics after the natural log of concentrations are back transformed. The best models chosen for an individual pesticide were based on various statistics such as the Nash Sutcliff efficiency index (using the nonlog values of modeled concentration) and other diagnostics including normality plots after trying all model possibilities. A Nash Sutcliff efficiency index near or greater than 0.5 with a model p value less than 0.05 was considered acceptable. Both the seasonal wave and the nonwave model were used depending on the pesticide and model statistics. Concentrations were compared with aquatic-life benchmarks provided by the U.S. Environmental Protection Agency (17).

Results Multiyear droughts occur in California and three severe droughts over the last 100 years happened from 1928 to 1934, from 1987 to 1992, and from 2012 to 2016 (30). The 1928 to 1934 drought took place before the construction of the current large reservoir systems. Time series plots of discharge for the Sacramento and San Joaquin rivers for the period of this study are shown in Figure 2. 337 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 2. Plots of mean daily discharge at the Sacramento River at Freeport (a) and the San Joaquin River at Vernalis (b), from 2010 through 2017. Note the different y-axis scale on these plots.

The effect of the drought appears to be more pronounced at the San Joaquin River site. Discharge on both rivers are a combined result of management actions by controlling the release of water from upstream reservoirs as well as storm water and irrigation runoff, which principally happens in the fall to winter and spring period. The reservoirs are located upstream of the agricultural and urban areas and thus enter the Central Valley mainly devoid of pesticides. Water is taken from the rivers and enters into various canal systems where it used for irrigation or domestic use. Rainfall is minimal to nonexistent throughout most of the summer growing season. The Sacramento River is the largest river in the State, and water releases from various reservoirs are necessary to meet downstream requirements for various uses including exports to southern California for drinking water, agricultural uses, and environmental requirements within the downstream Delta of the Sacramento and San Joaquin rivers (31). Although the drought affected most of the State of California, more water releases from the reservoirs of the Sacramento River system were apparently used to maintain necessary flows for those uses mentioned, relative to the reservoirs on the San Joaquin River system. For both watersheds, the highest flows for this period occurred in 2017 as a result of heavy rains, which effectively ended the drought. Pesticides detected with sufficient frequency (at least 25% of all samples above the reporting limit) to produce models of daily concentration and load include azoxystrobin, imidacloprid, diazinon, diuron, hexazinone, pendimethalin, metolachlor, carbenzadim, glyphosate, simazine, triallate, thiobencarb, and propanil. Azoxystrobin and carbenzadim are fungicides, imidacloprid is a neonicotinoid insecticide, diazinon is an organophosphorus insecticide, and the other compounds are herbicides. Diuron, hexazinone, simazine, pendimethalin, metolachlor, and glyphosate are used on a variety of crops. Thiobencarb and propanil are only or mostly used on rice. Carbendazim is also a degradate of a fungicide, thiophanate-methyl (32). Additional pesticides, such as fipronil, 338 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

bifenthrin, and others were detected, however the detection frequencies were too low to produce models of daily concentration or load. We also modeled three degradation products: metolachlor sulfonic acid (metolachlor degradate), aminomethylphosphonic acid (AMPA) (glyphosate degradate), and N-(3,4-Dichlorophenyl)-N′-methylurea (diuron degradate). In addition to the pesticides, ammonia concentrations and loads at the San Joaquin River site were modeled, as it had a repeating episodic appearance in the rivers during the wet season and is an important water quality constituent for downstream waters. Pesticides had different detection frequencies at these two sites. Azoxystrobin, diuron, hexazinone, simazine, pendimethalin, and metolachlor were detected at both the Sacramento River and San Joaquin River locations. Thiobencarb and propanil were only detected at the Sacramento River site as expected since most of the rice production in California occurs in the Sacramento Valley. Imidacloprid, diazinon, carbendazim, and glyphosate were only detected with sufficient frequency for modeling at the San Joaquin River location (Figure 3). In Figures 3–9, the slopes of the trend line representing the daily modeled concentrations are shown, which were calculated using the nonparametric MannKendall trend test (33). The slope is considered significant if the p value is less than 0.05. Aquatic-life benchmarks shown on the figures are mostly the lowest of the ones provided by the U.S. Environmental Protection Agency (17). Uniformly, the measured or modeled concentrations were much lower than the benchmarks for fish. Except for a few cases, such as pesticide degradates, those benchmarks for fish are not shown in Figures 3–9. All measured concentrations, including nondetects, are plotted in Figures 3–9. Reporting limits are shown on Table A1 in the Appendix. Imidacloprid and diazinon were the only insecticides with a sufficient detection frequency for modeling. Concentrations and fluxes for the San Joaquin River at the Vernalis site are shown in Figure 4. A suite of herbicides used on a variety of crops was detected in one or both rivers. Plots of concentrations and load are shown in Figures 5–8. The rice herbicides thiobencarb and propanil are used mainly in the Sacramento Valley. Plots of concentrations and loads of those two compounds are shown in Figure 8. Propanil at the Sacramento River site had a nonsignificant trend. Three degradates of herbicides were modeled, all for the San Joaquin River site. These included metolachlor sulfonic acid; (2-chloro-N- (2-ethyl-6methylphenyl)-N-(2-methoxy-1-methylethyl) acetamide), a metabolite of diuron (N-(3,4-Dichlorophenyl)-N′-methylurea); and AMPA, a metabolite of glyphosate (Figure 9). Although not a pesticide, ammonia was detected at the San Joaquin River site, and concentrations appeared to be episodic, with the highest concentrations occurring in the rainy season. Ammonia can occur in two forms (NH3 and NH4+), and the concentrations shown are the sum of the un-ionized and ionized forms. Concentrations and loads of ammonia are shown in Figure 10.

339 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 3. Azoxystrobin and carbendazim concentrations and fluxes at the Sacramento River at Freeport and/or the San Joaquin River at Vernalis locations. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

340 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 4. Imidacloprid and diazinon concentrations and fluxes at the San Joaquin River at the Vernalis location. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

341 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 5. Diuron and hexazinone concentrations and fluxes at the Sacramento River at Freeport and San Joaquin River at Vernalis locations. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

342 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 6. Simazine and pendimethalin concentrations and fluxes at the Sacramento River at Freeport and San Joaquin River at Vernalis locations. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

343 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 7. Metolachlor, glyphosate, and triallate concentrations and fluxes at the San Joaquin River at Vernalis and/or the Sacramento River locations. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations and fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17). Benchmarks for metolachlor are the lowest of those for the racemic or S-metolachlor form. The analytical method used sums the concentration of all forms.

344 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 8. Thiobencarb and propanil concentrations and fluxes at the Sacramento River at Freeport location. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations and fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

345 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 9. Concentrations and fluxes of pesticide metabolites (Metolachlor sulfonic acid, N-(3,4-Dichlorophenyl)-N′-methylurea, and AMPA detected at the San Joaquin River at Vernalis location. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines. Benchmarks are from the U.S. Environmental Protection Agency (17).

346 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Figure 10. Ammonia concentrations and fluxes at the San Joaquin River at Vernalis location. Blue lines are modeled concentrations and fluxes. Red and green dots are measured concentrations or fluxes on sampling days. Green lines are trend lines.

Discussion Many, but not all pesticides showed decreasing trends in concentration. There were 16 models of pesticides or degradates with decreasing trends while 5 showed increasing trends during this period. One pesticide, propanil, showed no trend. The model, whether wave or nonwave did not always capture the extreme concentrations, either high or low in many cases, but tended to capture the loads reasonably well. Azoxystrobin concentrations decreased at both the Sacramento and San Joaquin River sites, but carbendazim concentrations (only modeled for the San Joaquin River) showed an increasing trend. However, that trend was influenced by a few higher concentrations in 2016 and 2017 relative to the earlier part of the record. Imidacloprid, also only modeled for the San Joaquin River, showed a slight increase in concentrations over the period of the study. Diazinon, the other insecticide modeled, decreased during this time period. Diazinon concentrations and load were previously shown to be decreasing at the San Joaquin River (29) in an earlier study. It was expected to see diazinon concentrations continue to decrease, as the State of California has a TMDL management for that insecticide (34). Diuron concentrations measured at the Sacramento River location had a very slight upward trend, as did simazine concentrations. Pendimethalin concentrations decreased slightly at the Sacramento River site. Diuron concentrations decreased at the San Joaquin River location. Diuron is also under a TMDL management plan. Studies have indicated that aquatic life in these rivers should not be adversely affected if the four-day average concentration of diuron does not exceed 1,300 ng/L more than once every three years on average or if the one-hour average does not exceed 170,000 ng/L (35). Diuron concentrations were very much below 1,300 ng/L during this time frame, and that level was also not exceeded in the San Joaquin River. Hexazinone trends were downward for both the Sacramento and San Joaquin Rivers. Both simazine and pendimethalin concentrations decreased at the San Joaquin River location. Glyphosate concentrations only decreased slightly at the San Joaquin River while metolachlor and triallate showed a steeper decrease. All 347 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

three of the pesticide degradates modeled for the San Joaquin River location show a trend of decreasing concentration. Trends in pesticide concentrations might be attributable to trends in use hydrological factors, such as rainfall, and pesticide properties, such as half-life and solubility. It is beyond the scope of this report to assess environmental half-lives. It is assumed that the pesticides reported here are sufficiently water-soluble because all measurements of concentrations were completed on filtered samples. The State of California maintains detailed records of pesticide use, which include the date and location of application of active ingredients (36, 37). Pesticide use records from 2010 to 2016 for the Sacramento and San Joaquin Valley portions of the Central Valley from the California Department of Pesticide Regulation Pesticide Use Database were examined (36). Pesticide use data for 2017 were not yet available for this analysis. Azoxystrobin use in both portions of the Central Valley increased in use, especially after 2014. Azoxystrobin use in the Sacramento Valley increased from 17,860 kg in 2010 to 34,440 kg in 2016 and in the San Joaquin Valley from 12,640 kg in 2010 to 27,400 kg in in 2016. However, azoxystrobin concentrations decreased at both sampling locations. Imidacloprid use in the San Joaquin Valley increased from a low of 16,100 kg in 2010 to a high of 34,280 kg in 2015, with only a slight decrease in 2016. San Joaquin River concentrations increased slightly during this period. Diazinon use neither increased nor decreased in either valley during this period of record, but showed a drop of concentration at the San Joaquin River site. Diuron use in the Sacramento Valley varied over this period, but overall had a declining use trend from 23,500 to 12,000 kg with river concentrations showing a slight increase. Diuron use in the San Joaquin River also declined from near 47,370 kg to 25,000 kg, and river concentrations dropped. Hexazinone use in the Sacramento Valley dropped sharply from 10,910 to 1,800 kg, with a clear drop in river concentrations. In contrast, hexazinone use showed yearly variation in the San Joaquin Valley with a low of 5,900 to a high of 16,000 kg but with an overall flat trend in use over the years. Hexazinone concentrations decreased slightly in the San Joaquin River. Simazine use decreased in the Sacramento Valley from 25,000 to 8,900 kg, but concentrations increased slightly in the river. Simazine use also dropped in the San Joaquin Valley from 46,800 to 14,000 kg, and river concentrations decreased. Pendimethalin use increased in the Sacramento Valley from 68,000 to 123,600 kg, but river concentrations decreased. Pendimethalin use in the San Joaquin Valley increased slightly from 200,350 to 287,4300 kg, but river concentrations showed a decreasing trend. Metolachlor use increased sharply in the Sacramento Valley from 260 to 29,900 kg but river concentrations only slightly increased. Metolachlor use in the San Joaquin Valley increased from 10,900 kg in 2010 to 31,000 kg 2012 and then dropped to 10,600 kg in 2016. Metolachlor concentrations decreased in the San Joaquin River during this time. Glyphosate is a high use herbicide with different formulations with over 500,000 kg used yearly in the San Joaquin Valley. Despite the high use, river concentrations are low and decreased slightly during this period. Thiobencarb use increased in the Sacramento Valley from a low of 108,000 kg to a high of 420,480 kg in 2016. Despite this increase in use, concentrations in the Sacramento River had a decreasing trend. Propanil, the other rice herbicide, did not vary much in 348 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

use with a low of 766,000 kg to a high of 1,262,750 kg in the Sacramento Valley. Despite the very high use, concentrations did not vary in the Sacramento River during this period of record. Although trends in pesticide use do not always match with pesticide trends in the rivers, timing of application relative to rainfall may also be a factor in explaining the observed trends. Peak concentrations of pesticides within the Central Valley can occur throughout the year depending on the crop and application period, as well as to control specific outbreaks. For example, because of the nature of rice production with field treatment and seeding occurring in April and May, peak concentrations of thiobencarb and propanil happen in May and June, and peak concentrations can normally be expected to occur then. Similarly, for pre-emergent herbicides metolachlor and triallate, concentrations also peak in spring. Azoxystrobin peak concentrations mostly happened in late summer, but also in spring. This was apparent for the Sacramento River site, with more than one concentration peak appearing throughout a given year (Figure 3). Since azoxystrobin is a fungicide, it can be used whenever a particular problem has been identified, such as following rainfall when standing water is present in an orchard. Imidacloprid peak concentrations, only modeled for the San Joaquin River, tended to peak in the April to May time frame. Diuron concentrations tended to peak in the winter months in the San Joaquin River system and in the winter to early spring for the Sacramento River. Diuron can be used both preand postemergent, so it is not surprising that detections occur throughout the year. Hexazinone concentrations varied throughout the year at the Sacramento River location and peaked in winter through spring at the San Joaquin River location. Simazine and pendimethalin concentrations also tend to peak in winter to spring with lower concentrations throughout the rest of the year. Glyphosate is used on a large variety of crops and as a result can be detected throughout the year. Pesticide degradates are compounds that have been chemically or biologically altered from the parent pesticide by a variety of environmental processes and may be mobilized from soil following winter rains or may be transported to groundwater and mobilized to rivers by groundwater discharge to streams. It has long been known that metolachlor sulfonic acid is a common groundwater contaminant (38). Metolachlor sulfonic acid was detected at various times of the year. This degradate may be sourced from soil surfaces after alteration from the parent herbicide. Alternatively, it is possible that some of the concentrations of metolachlor sulfonic acid might be attributable to ground water discharge to the San Joaquin River. In contrast, the metabolites of diuron and glyphosate tended to be detected more frequently in the winter and early spring, suggesting that storm water runoff is the primary cause of the transport. Modeled and measured concentrations of pesticides were compared to aquatic-life benchmarks from the U.S. Environmental Protection Agency’s Office of Pesticide Programs (17). The benchmarks show acute and chronic toxicity to invertebrates and fish and acute toxicity to vascular and nonvascular plants. Numerical water-quality criteria for the protection of aquatic organisms have been established for only a few currently used pesticides. The benchmarks used here are not enforceable standards. Most of the pesticides did not show any clear evidence of potential toxicity to aquatic organisms during this period of 349 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

record. One exception was the neonicotinoid insecticide, imidacloprid. Although modeled and measured concentrations were below the threshold for acute toxicity to invertebrates, concentrations did frequently exceed those suspected to cause chronic toxicity to invertebrates. Modeled concentrations of imidacloprid and a cumulative frequency plot of those concentrations are shown in Figure 11.

Figure 11. Modeled concentrations of imidacloprid (a) and a cumulative frequency plot of modeled concentrations (b) showing percent of time that a concentration was exceeded. The dashed line in (a) and (b) is the level of chronic toxicity to invertebrates. Modeled imidacloprid concentrations exceeded the benchmark for chronic toxicity to invertebrates throughout the time frame of the study, and around the year 2015, concentrations that might cause chronic toxicity were exceeded all of the time. The cumulative frequency diagram shows that concentrations exceed 10 ng/L more than 70% of the time. A review of neonicotinoid toxicity to aquatic invertebrates shows that the mayfly (Ephemeroptera), caddis fly (Trichoptera), and midge (Diptera) species are highly sensitive to neonicotinoids (39). Neonicotinoid insecticides are less toxic to other aquatic invertebrates, such as species of Daphnia (39). The occurrence of neonicotinoid insecticides in the aquatic environment at potentially toxic concentrations to invertebrates has been previously reported on (40). Imidacloprid is also one the most widely used agricultural insecticides by weight (41). Because of the increasing trend of imidacloprid concentrations along with the potential of chronic toxicity, continued monitoring is especially warranted. Although no other pesticides were detected or modeled at concentrations above aquatic-life benchmarks, there are times when more than one pesticide was present. It was outside of the scope of this study to assess pesticide mixtures. The effects of mixtures could be assessed using the Pesticide Toxicity Index approach (42). Ammonia can have multiple sources to rivers. Ammonia can be present in the atmosphere from both vehicle emissions and agriculture, including dairies and feedlots and be transported to rivers by both wet and dry deposition (43). Ammonia is also used widely as a source of nitrogen in fertilizer (44). Other 350 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

sources of ammonia to aquatic systems are wastewater treatment plants (45). Ammonia concentrations peak in the winter, strongly suggesting that it is washed out of the atmosphere after rainfall and then transported to the river. Ammonia concentrations measured or modeled here are very much below those thought to be acutely toxic to aquatic organisms (46); however, it is possible that ammonia contributes to changes in primary productivity and the species composition of primary producers at relatively low concentrations (47). Peak ammonia concentrations are near 4 μmol/L, a level thought to cause adverse effects to phytoplankton (48).

Summary and Conclusion A variety of pesticides were detected in the Sacramento and San Joaquin Rivers between 2010 and 2017. This spanned a time of normal, drought, and above normal precipitation in California. Most of the pesticides detected were herbicides and fungicides. Two insecticides were also detected frequently enough to model and assess trends. Two different modeling approaches were used in this study. Of the 22 models for pesticides, 16 utilized the seasonal wave while 6 had better supporting statistics using the nonwave approach. Two of the three pesticide metabolites, metolachlor sulfonic acid and the diuron metabolite had better nonwave models, possibly because they are partly mobilized into groundwater rather than overland runoff, and their presence in the rivers is due to groundwater discharge. The glyphosate degradate, AMPA, was modeled using the wave approach, suggesting that overland flow was the primary route to the river. The majority of models indicated that concentrations decreased during the drought, but five pesticides did show increasing concentrations. Carbendazim and imidacloprid modeled concentrations indicated increasing trends at the San Joaquin River and diuron, simazine, and metolachlor modeled concentrations indicated increasing concentrations in the Sacramento River. Four of the pesticides discussed in this report are high use compounds. These include imidacloprid, pendimethalin, glyphosate, and azoxystrobin. Of those three, only imidacloprid concentrations had an increasing trend. The increasing trend of imidacloprid concentrations in the San Joaquin River is of cause for concern, as it was the only pesticide that exceeded a toxicity benchmark. There is also an increasing trend in imidacloprid use, which doubled in the San Joaquin Valley over this period of record. For some years, imidacloprid concentrations exceeded the benchmark for chronic toxicity to invertebrates. Comparing trends in pesticide use with river concentrations showed some inconsistencies. There were occurrences where increased use led to increased river concentrations; however, there were also cases with increasing pesticide use but decreasing pesticide concentration in the rivers. There were definitely times when more than one pesticide in the rivers and the effects of these pesticide mixtures should also be examined more carefully. The preponderance of negative trends in concentration suggests that lack of rainfall during the drought lowered the amount of pesticides mobilized from fields during that period. 351 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Appendix Table A1. Pesticides Analyzed Analyte

CAS Number

USGS Code

Reporting Limit

Units

1H-1,2,4-Triazole

68498

288-88-0

22

ng/L

2,4-D

68500

94-75-7

62

ng/L

2,4-D-d3, surrogate, water, filtered, percent recovery (surrogate)

91986

202480-67-9

2-(1-Hydroxyethyl)-6methylaniline

68611

196611-19-5

94

ng/L

2-Amino-N-isopropylbenzamide

68503

30391-89-0

4.0

ng/L

2-Aminobenzimidazole

68502

934-32-7

9.0

ng/L

2-Hydroxy-4-isopropylamino-6-ethylamino-s-triazine {OIET}

68660

2163-68-0

8.0

ng/L

2-Isopropyl-6-methyl-4pyrimidinol

68505

2814-20-2

20

ng/L

2-[(2-Ethyl-6methylphenyl)amino]-1propanol

68595

61520-53-4

5.0

ng/L

N-(3,4-Dichlorophenyl)-N′methylurea

68231

3567-62-2

5.0

ng/L

3,4-Dichlorophenylurea

68226

2327-02-8

144

ng/L

3-Phenoxybenzoic acid

68873

3739-38-6

61

ng/L

3-Phenoxybenzoic acid-13C6(surrogate)

90516

4-(Hydroxymethyl)pendimethalin

68511

56750-76-6

213

ng/L

4-Chlorobenzylmethyl sulfoxide

68514

934-73-6

3.2

ng/L

4-Hydroxy molinate

68515

66747-12-4

7.0

ng/L

4-Hydroxychlorothalonil

68336

28343-61-5

98

ng/L

4-Hydroxyhexazinone A

68517

72576-13-7

3.0

ng/L

Acephate

68519

30560-19-1

10

ng/L

Acetochlor

68520

34256-82-1

10

ng/L

Acetochlor oxanilic acid

68522

194992-44-4

90

ng/L

Acetochlor sulfonic acid

68523

187022-11-3

320

ng/L

%

%

Continued on next page.

352 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit 176

Units

Acetochlor sulfynilacetic acid

68524

618113-86-3

Acetochlor-d11 (surrogate)

90517

1189897-44-6

Alachlor

65064

15972-60-8

7.0

ng/L

2-Chloro-2′,6′diethylacetanilide

68525

6967-29-9

5.0

ng/L

Alachlor oxanilic acid

68526

171262-17-2

84

ng/L

Alachlor sulfonic acid

68871

142363-53-9

360

ng/L

Alachlor sulfynilacetic acid

68527

494847-39-1

169

ng/L

Alachlor-d13 (surrogate)

90518

1015856-63-9

Aldicarb

68528

116-06-3

8.0

ng/L

Aldicarb sulfone

68529

1646-88-4

20

ng/L

Aldicarb sulfoxide

68530

1646-87-3

2.2

ng/L

Ametryn

68533

834-12-8

2.6

ng/L

Asulam

68536

3337-71-1

50

ng/L

Atrazine

65065

1912-24-9

6.8

ng/L

Azinphos-methyl

65066

86-50-0

8.0

ng/L

Azinphos-methyl oxon

68211

961-22-8

15

ng/L

Azoxystrobin

66589

131860-33-8

3.0

ng/L

Bentazon

68538

25057-89-0

9.0

ng/L

Bifenthrin

65067

82657-04-3

19

ng/L

Bromacil

68542

314-40-9

5.6

ng/L

Bromoxynil

68543

1689-84-5

79

ng/L

Butachlor sulfonic acid (surrogate)

90624

187022-12-4

Butralin

68545

33629-47-9

5.0

ng/L

Butylate

65068

2008-41-5

10

ng/L

Carbaryl

65069

63-25-2

5.6

ng/L

Carbaryl-d7 (surrogate)

90519

362049-56-7

Carbendazim

68548

10605-21-7

Carbendazim-d4 (surrogate)

90520

291765-95-2

Carbofuran

65070

1563-66-2

5.0

ng/L

3-Hydroxycarbofuran

68508

16655-82-6

16

ng/L

ng/L %

%

%

% 10

ng/L %

Continued on next page.

353 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Carbofuran-d3 (surrogate)

90521

1007459-98-4

%

Carboxy molinate

68549

66747-13-5

50

ng/L

Chlorimuron-ethyl

68872

90982-32-4

8.8

ng/L

Chlorosulfonamide acid

68551

130-45-0

75

ng/L

Chlorpyrifos

65072

2921-88-2

3.0

ng/L

Chlorpyrifos oxon

68216

2.0

ng/L

Chlorsulfuron

61678

64902-72-3

50

ng/L

2-Chloro-4-isopropylamino6-amino-s-triazine

68552

6190-65-4

11

ng/L

cis-Bifenthrin acid/ cis-Cyhalothrin acid/cis-Tefluthrin acid

68553

68127-59-3

86

ng/L

cis-Permethrin

68769

61949-76-6

4.2

ng/L

cis-Permethrin-13C6 (surrogate)

90558

Cyanazine

66592

21725-46-2

50

ng/L

Dacthal monoacid

68560

887-54-7

2700

ng/L

Dechlorofipronil

68561

3.8

ng/L

Dechlorometolachlor

68562

2.0

ng/L

Deethylatrazine-d6 (surrogate)

90522

2-Chloro-4,6-diaminos-triazine {CAAT} (Didealkylatrazine)

68547

3397-62-4

24

ng/L

Deiodo flubendiamide

68563

1016160-78-3

10

ng/L

Deisopropyl prometryn

68564

4147-57-3

2.8

ng/L

2-Chloro-6-ethylamino-4amino-s-triazine {CEAT}

68550

1007-28-9

20

ng/L

Demethyl fluometuron

68591

3032-40-4

3.6

ng/L

Demethyl hexazinone B

68566

56611-54-2

3.0

ng/L

Demethyl norflurazon

68567

23576-24-1

4.0

ng/L

Desamino metribuzin

68568

35045-02-4

9.0

ng/L

Desamino-diketo metribuzin

68569

52236-30-3

200

ng/L

Desulfinylfipronil

66607

205650-65-3

3.8

ng/L

%

126605-22-9

%

Continued on next page.

354 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Desulfinylfipronil amide

68570

1115248-09-3

10

ng/L

Diazinon

65078

333-41-5

2.8

ng/L

Diazinon oxon

68236

4.0

ng/L

Diazinon-d10 (surrogate)

90523

100155-47-3

Dicamba

68571

1918-00-9

Dichlorvos

68572

Dicrotophos

68573

Didemethyl hexazinone F

% 2400

ng/L

52

ng/L

141-66-2

4.0

ng/L

68574

56611-54-2

10

ng/L

Diflubenzuron

68576

35367-38-5

6.0

ng/L

Diflubenzuron-d4 (surrogate)

90524

1219795-45-5

Diflufenzopyr

68577

109293-97-2

72

ng/L

Diketonitrile-isoxaflutole

68578

143701-75-1

62

ng/L

Dimethachlor sulfonic acid(surrogate)

90625

Dimethenamid

68580

87674-68-8

3.0

ng/L

Dimethenamid oxanilic acid

68581

380412-59-9

85

ng/L

Dimethenamid sulfonic acid

68582

205939-58-8

79

ng/L

Dimethenamid SAA

68583

189

ng/L

Dimethoate

66596

60-51-5

4.6

ng/L

Disulfoton

67595

298-04-4

11

ng/L

Disulfoton oxon

68586

126-75-0

2.0

ng/L

Disulfoton oxon sulfone

68588

2496-91-5

6.0

ng/L

Disulfoton oxon sulfoxide

68587

2496-92-6

6.0

ng/L

Disulfoton sulfone

68589

2497-06-5

9.0

ng/L

Disulfoton sulfoxide

68590

2497-07-6

4.0

ng/L

Diuron

66598

330-54-1

5.0

ng/L

Diuron-d6 (surrogate)

L903M

%

Diuron-d6 (surrogate)

90808

%

EPTC

65080

759-94-4

206

ng/L

EPTC degradate R248722

68594

65109-69-5

4.0

ng/L

Ethoprophos

68596

13194-48-4

5.0

ng/L

%

%

Continued on next page.

355 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Etoxazole

68598

153233-91-1

4.2

ng/L

Fenamiphos

68599

22224-92-6

2.0

ng/L

Fenamiphos sulfone

68600

31972-44-8

5.0

ng/L

Fenamiphos sulfoxide

68601

31972-43-7

5.0

ng/L

Fenbutatin oxide

68602

13356-08-6

100

ng/L

Fentin

68603

668-34-8

30

ng/L

Fipronil

66604

120068-37-3

4.0

ng/L

Fipronil amide

68604

205650-69-7

9.2

ng/L

Fipronil sulfide

66610

120067-83-6

4.2

ng/L

Fipronil sulfonate

68605

209248-72-6

96

ng/L

Fipronil sulfone

66613

120068-36-2

5.6

ng/L

Flubendiamide

68606

272451-65-7

4.4

ng/L

Flumetsulam

61679

98967-40-9

17

ng/L

Fluometuron

68608

2164-17-2

3.4

ng/L

Fonofos

65084

944-22-9

11

ng/L

Halosulfuron-methyl

61680

100784-20-1

22

ng/L

Hexazinone

65085

51235-04-2

3.6

ng/L

Hexazinone Transformation Product C

68612

72585-88-7

2.0

ng/L

Hexazinone Transformation Product D

68613

30243-77-7

294

ng/L

Hexazinone Transformation Product E

68614

72576-14-8

76

ng/L

Hexazinone Transformation Product G

68713

22

ng/L

Hexazinone-d6 (surrogate)

90527

Hydroxy didemethyl fluometuron

68619

Hydroxyacetochlor

68615

Hydroxyalachlor

68616

Hydroxy monodemethyl fluometuron

68617

Hydroxydiazinon

68618

1219804-22-4

% 50

ng/L

60090-47-3

20

ng/L

56681-55-1

6.0

ng/L

12

ng/L

11

ng/L

29820-16-4

Continued on next page.

356 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

Hydroxyfluometuron

68620

Hydroxymetolachlor

68622

Hydroxyphthalazinone

68623

Hydroxysimazine

68624

Imazamox

CAS Number

Reporting Limit

Units

8.0

ng/L

2.4

ng/L

46

ng/L

2599-11-3

100

ng/L

68625

114311-32-9

28

ng/L

Imazaquin

61682

81335-37-7

18

ng/L

Imazethapyr

61683

81335-77-5

20

ng/L

Imidacloprid

68426

138261-41-3

16

ng/L

Indoxacarb

68627

173584-44-6

5.2

ng/L

Isoxaflutole

68632

141112-29-0

18

ng/L

Isoxaflutole acid metabolite RPA 203328

68633

142994-06-7

9.2

ng/L

Kresoxim-methyl

67670

143390-89-0

5.0

ng/L

Lactofen

68638

77501-63-4

10

ng/L

Linuron

68639

330-55-2

5.6

ng/L

Linuron-d6 (dimethyl-d6) (surrogate)

L903K

1219804-76-8

%

Linuron-d6 (dimethyl-d6) (surrogate)

90529

1219804-76-8

%

Malaoxon

68240

1634-78-2

2.4

ng/L

Malathion

65087

121-75-5

5.4

ng/L

Malathion-d10 (diethyld10)(surrogate)

90552

347841-48-9

MCPA

68641

94-74-6

95

ng/L

Metalaxyl

68437

57837-19-1

6.0

ng/L

Metconazole

66620

125116-23-6

5.0

ng/L

Methamidophos

68644

10265-92-6

10

ng/L

Methidathion

65088

950-37-8

8.4

ng/L

Methomyl

68645

16752-77-5

3.0

ng/L

Methomyl oxime

68646

13749-94-5

1000

ng/L

Methoxyfenozide

68647

161050-58-4

2.2

ng/L

Methyl paraoxon

68648

950-35-6

19

ng/L

131068-72-9

%

Continued on next page.

357 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Metolachlor

65090

51218-45-2

9.0

ng/L

Metolachlor hydroxy morpholinone

68649

61520-54-5

10

ng/L

Metolachlor oxanilic acid

68650

152019-73-3

149

ng/L

Metolachlor sulfonic acid

68651

171118-09-5

68

ng/L

Metolachlor-d6 (propyl-d6)(surrogate)

90553

1219803-97-0

Metribuzin

68652

21087-64-9

20

ng/L

Metribuzin DK

68653

56507-37-0

236

ng/L

Molinate

65091

2212-67-1

50

ng/L

Myclobutanil

66632

88671-89-0

7.0

ng/L

Naled

68654

300-76-5

56

ng/L

Nicosulfuron

61685

111991-09-4

12

ng/L

Nicosulfuron-d6 (surrogate)

90554

1189419-41-7

Norflurazon

67685

27314-13-2

3.4

ng/L

Novaluron

68655

116714-46-6

50

ng/L

O-Ethyl S-methyl S-propyl phosphorodithioate

68657

76936-72-6

3.0

ng/L

O-Ethyl-O-methyl-Spropylphosphorothioate

68597

76960-87-7

5.0

ng/L

O-Ethyl-S-propyl phosphorothioate

68658

31110-62-0

64

ng/L

2-Hydroxy-6-ethylamino-4amino-s-triazine

68656

7313-54-4

100

ng/L

2-Hydroxy-4-isopropylamino-6-amino-s-triazine

68659

19988-24-0

4.0

ng/L

Omethoate (Dimethoate oxon)

68661

1113-02-6

2.0

ng/L

Orthosulfamuron

68662

213464-77-8

6.0

ng/L

Oryzalin

68663

19044-88-3

12

ng/L

Oxamyl

68664

23135-22-0

2.0

ng/L

Oxamyl oxime

68665

30558-43-1

5.0

ng/L

Oxyfluorfen

65093

42874-03-3

500

ng/L

Paraoxon

68666

311-45-5

3.4

ng/L

%

%

Continued on next page.

358 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Pendimethalin

65098

40487-42-1

10

ng/L

Phorate

68668

298-02-2

11

ng/L

Phorate oxon

68669

2600-69-3

100

ng/L

Phorate oxon sulfone

68670

2588-06-9

20

ng/L

Phorate oxon sulfoxide

68671

2588-05-8

7.0

ng/L

Phorate sulfone

68672

2588-04-7

9.0

ng/L

Phorate sulfoxide

68673

2588-03-6

4.6

ng/L

Phthalazinone

68675

90004-07-2

15

ng/L

Piperonyl butoxide

65102

51-03-6

60

ng/L

Profenofos

68676

41198-08-7

3.0

ng/L

Prometon

67702

1610-18-0

4.0

ng/L

Prometryn

65103

7287-19-6

4.2

ng/L

Propanil

66641

709-98-8

12

ng/L

Propargite

68677

2312-35-8

2.0

ng/L

Propazine

68678

139-40-2

3.2

ng/L

Propiconazole

66643

60207-90-1

6.0

ng/L

Propoxur

68679

114-26-1

3.2

ng/L

Propyzamide

67706

23950-58-5

2.4

ng/L

Prosulfuron

61687

94125-34-5

10

ng/L

Pyraclostrobin

66646

175013-18-0

2.4

ng/L

Pyridaben

68682

96489-71-3

2.4

ng/L

Pyriproxyfen

68683

95737-68-1

3.0

ng/L

2-Chloro-N-(2-ethyl-6methylphenyl)acetamide

68521

32428-71-0

5.0

ng/L

sec-Acetochlor oxanilic acid

68684

152019-74-4

52

ng/L

sec-Alachlor oxanilic acid

68685

628324-79-8

135

ng/L

Siduron

68686

1982-49-6

5.0

ng/L

Simazine

65105

122-34-9

7.2

ng/L

Sulfentrazone

68687

122836-35-5

18

ng/L

Sulfometuron-methyl

68688

74222-97-2

4.0

ng/L

Sulfosulfuron

68689

141776-32-1

11

ng/L

Continued on next page.

359 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

Table A1. (Continued). Pesticides Analyzed Analyte

USGS Code

CAS Number

Reporting Limit

Units

Sulfosulfuron ethyl sulfone

68690

2.8

ng/L

2,3,3-Trichloro-2-propene-1sulfonic acid (TCPSA)

68691

65600-62-6

54

ng/L

Tebuconazole

66649

107534-96-3

5.0

ng/L

Tebuconazole-d6 (surrogate)

90555

Tebufenozide

68692

112410-23-8

2.0

ng/L

Tebupirimphos

68693

96182-53-5

2.0

ng/L

Tebupirimfos oxon

68694

2.0

ng/L

Tebuthiuron

68695

34014-18-1

3.0

ng/L

Tebuthiuron TP 104

68575

59962-53-7

5.6

ng/L

Tebuthiuron Transformation Product 106

68714

16279-27-9

76

ng/L

Tebuthiuron TP el108

68696

39222-73-6

10

ng/L

Tebuthiuron TP 109

68621

59962-54-8

11

ng/L

Tebuthiuron TP 109 (OH)

68697

139888-73-6

38

ng/L

Terbacil

68698

5902-51-2

21

ng/L

Terbufos

68699

13071-79-9

6.8

ng/L

Terbufos oxon

68700

56070-14-5

4.0

ng/L

Terbufos oxon sulfone

68701

56070-15-6

11

ng/L

Terbufos oxon sulfoxide

68702

56165-57-2

4.0

ng/L

Terbufos sulfone

68703

56070-16-7

11

ng/L

Terbufos sulfoxide

68704

10548-10-4

3.0

ng/L

Terbuthylazine

66651

5915-41-3

3.6

ng/L

Tetraconazole

66654

112281-77-3

7.0

ng/L

Thiobencarb

65107

28249-77-6

4.2

ng/L

Thiobencarb-d10 (surrogate)

90556

1219804-12-2

trans-Permethrin

68708

61949-77-7

Triallate

68710

Tribufos

68711

Triclopyr Trifloxystrobin

%

% 3.8

ng/L

12

ng/L

78-48-8

2.0

ng/L

68712

55335-06-3

88

ng/L

66660

141517-21-7

2.8

ng/L

360 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.

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364 Goh et al.; Pesticides in Surface Water: Monitoring, Modeling, Risk Assessment, and Management ACS Symposium Series; American Chemical Society: Washington, DC, 2019.