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A probabilistic modeling assessment was conducted to identify potential sources of permethrin loadings to the Sacramento. River and its tributaries fr...
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Chapter 11

Predicted Runoff Loads of Permethrin to the Sacramento River and Its Tributaries 1

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S. Dasgupta , J. M. Cheplick , D. L. Denton , J. J. Troyan , and W. M. Williams Downloaded by MONASH UNIV on May 2, 2017 | http://pubs.acs.org Publication Date: August 19, 2008 | doi: 10.1021/bk-2008-0991.ch011

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Waterborne Environmental Inc., 897-B Harrison Street S E , Leesburg, V A 20175 U . S . Environmental Protection Agency, Region IX, Sacramento, C A 95814 Sacramento Regional County Sanitation District, 10545 Armstrong Avenue, Suite 101, Mather, C A 95655 3

A probabilistic modeling assessment was conducted to identify potential sources of permethrin loadings to the Sacramento River and its tributaries from runoff and furrow irrigation drainage. A Geographical Information System (GIS) was used to construct approximately 6,956 model simulations representing unique combinations of soil, land use, and permethrin use within the study area. Simulations were conducted using the U.S. Environmental Protection Agency's Pesticide Root Zone Model (PRZM). Information about permethrin use was obtained from the California Department of Pesticide Regulation's (CDPR's) Pesticide Use Reporting (PUR) database. Simulations were conducted for 30-years of historical weather to evaluate runoff loadings under a range of potential low, moderate, and high rainfall events. Mass loadings are presented in terms of temporal probability of occurrence. Areas predicted to have high loading may be candidates for detailed analysis, monitoring, or mitigation.

© 2008 American Chemical Society Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

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Introduction

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Permethrin is a synthetic pyrethroid that has been identified as one of 22 "high relative risk pesticides" by California's Central Valley Regional Water Quality Control Board (/). To quantify the potential movement of permethrin to aquatic habitats, a probabilistic modeling study was conducted to estimate potential loadings of permethrin to the Sacramento River and its tributaries in terms of spatial and temporal probability of occurrence.

Materials and Methods Pesticide losses for this study were calculated as edge-of-field loadings from runoff and erosion induced by both rainfall and furrow irrigation drainage. No attempt was made to model the transport or conveyance in creeks, streams, and rivers. The Pesticide Root Zone Model (PRZM) was selected for this study based on its ability to simulate the interaction factors relevant in the fate and transport of permethrin within the agricultural landscape and based on the preference for its use by the U.S. Environmental Protection Agency (USEPA) (2). P R Z M is a dynamic, compartmental model developed by U S E P A for use in simulating water and chemical movement in unsaturated soil systems within and below the plant root zone (3). The hydrologic component of P R Z M simulates the physical processes of rainfall, runoff, infiltration, erosion, and evapotranspiration. The chemical transport component of P R Z M calculates pesticide uptake by plants, surface runoff, erosion, decay, vertical movement, foliar loss, dispersion and retardation. P R Z M includes the ability to simulate pesticide metabolites and irrigation. For this study, 6,956 individual P R Z M simulations were conducted. Simulations were defined by the intersection of land areas designating different combinations of soil, land use, weather, chemical use, irrigation, and application dates within the Sacramento River watershed study area (Figure 1).

Chemical Applications Permethrin use records were obtained from the Pesticide Use Reporting (PUR) database (4), accessed from the California Pesticide Information Portal (CalPIP). The P U R database contains detailed information about chemical applications (application dates, application amounts, application method, and others) at the section (1 square mile) resolution.

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

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Figure 1. Sacramento River Watershed with subbasin delineation. (Obtainedfrom the California Interagency watershed map (Calwqter 221) (5). (See Page 1 of color inserts.)

Chemical Environmental Fate Properties Environmental fate properties for permethrin (Table I) were obtained from the U.S. Department of Agriculture, Agricutural Research Servie (USDA-ARS) Pesticide Property database (6). For the PRZM simulations, the combined soil photolysis and aerobic soil half-life was used in the model. Foliar degradation was assumed to occur at the rate given by soil photolysis.

Soil data and Land Use Soil parameters were identified from the State Soil Geographic (STATSGO) database (7). The STATSGO data set is a digital general soil association map developed by the National Cooperative Soil Survey and distributed by the USDA's Natural Resources Conservation Service (formerly Soil Conservation Service). The STATSGO soil regions within the study area are illustrated in

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

226 Table I. Environmental fate properties for permethrin Property

Value

C A S Number

52645-53-1

Empirical formula

C21H20CI2O3

Molecular weight, g/mole

391.3

Vapor pressure, mm Hg

2.10E-8

Aqueous solubility, ppm

0.006

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Henry's Law Constant, atm-m /mole

1.93E-10

Soil Koc, mL/g

39300

Soil photolysis half-life, days

33.00

Aerobic soil half-life, days

30.00

Combined soil photolysis and aerobic soil half-life, days

15.71

Anaerobic soil half-life, days

108.00

Hydrolysis at pH 7

Stable

Figure 2. There were up to 18 unique soil types within a single S T A T S G O soil polygon. The land uses at the section level were intersected with the soil polygons within a GIS framework to identify soil types. Since, it was not possible to identify the exact spatial location of a soil type within a single P U R section, all soil types associated with S T A T S G O polygon that intersected a PUR section were used for modeling. Results were scaled in proportion to the percentage a specific soil existed in a S T A T S G O polygon to reflect the relative probability that a given soil maybe associated with a P U R section. The land use data for the study area was obtained from the Pesticide Use Reporting (PUR) database (4), accessed from the California Pesticide Information Portal (CalPIP). Land uses were grouped into seven categories, namely corn, fruit, grain, grass, nut, vegetable, and vineyard.

Crop Parameters Cropping dates for emergence, maturation, and harvest and other crop parameters for interception storage, maximum coverage, active root depth, aerial coverage, maximum canopy height, and others were derived from U S E P A Standard Tier 2 scenarios (2).

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

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Figure 2. STATSGO Soil polygons within the Sacramento River Watershed. (See page I of color inserts.)

Weather Data Simulations were conducted for 30-years of historical weather (1961-1990) to evaluate runoff loadings under low, moderate, and high rainfall events. Five weather stations (Sacramento, C A ; San Francisco, C A ; Reno, N V , Medford, OR, and Santa Maria, C A ) were used to account for weather variability in the study area. The weather data was obtained from U S E P A ' s Center for Exposure Assessment Modeling ( C E A M ) in PRZM-ready format (#). C E A M developed these weather files by associating National Oceanic and Atmospheric Administration ( N O A A ) primary weather stations to Major Land Resource Areas ( M L R A s ) . M L R A s are a classification system developed by the U S D A to represent areas of similar climate, geomorphology, and natural resources. P U R sections were assigned a specific weather station based on the M L R A and S T A T S G O polygon in which it resides. The majority of simulations were associated with the Sacramento weather station (W23232).

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

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Irrigation Corn and vegetables are generally irrigated using furrow irrigation within the Sacramento watershed. Other crops (fruit, grain, vineyard, grass, and nut) are irrigated by other methods, including drip irrigation and micro-sprinkler irrigation systems. Corn generally requires the application of 3-3.5 acre-feet of water which is applied over 5-9 irrigation events throughout the season (9). Tomato production was used as the prototype crop for assessing irrigation for vegetables. Across California, an approximation for furrow irrigated fields would be 2.5-3 acre-feet of water to be applied throughout the season with 7-14 events (10). It was suggested by local expert (11) that runoff from furrow irrigated fields in the Sacramento River watershed can range between 10 to 30 percent of total water applied for irrigation. An approach was developed to simulate tailwater releases and chemical losses in irrigation water.

Design of Furrow Irrigation system Key water balance guidelines that were incorporated into the study are highlighted below: •

Amount of water that infiltrates the system should match overall water requirements for both corn and tomatoes.



A total volume of 2.7 acre-feet of water should be applied for both crops over 9 irrigation events which constitutes 0.3 acre-feet of water for each application event.



The amount of water generated as runoff by the system should be between 10 to 30 percent of total applied water.



The irrigation system should yield an overall efficiency between 60 to 75 percent.

The latter assumption was based on the information from Schwab et al., (12), that a gently sloping, well leveled and uniformly graded field usually has a furrow irrigation efficiency of 60 to 75 percent. Efficiency (as related to the water balance of the system) refers to the fraction of water that actually infiltrates into the system to the total amount of water that is applied to the system.

Calibration of PRZM to Simulate Furrow Irrigation Irrigation within the P R Z M model is activated when the average root zone soil moisture falls below a threshold value f defined by the user as a fraction of the available water capacity (PCDEPL). The soil moisture deficit is given by:

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

229 D = (0 -8J*Z fc

r

(1)

in which D is soil moisture deficit (cm), 0 is the average root-zone soil moisture content (cm cm" ), 6f is the average root-zone soil moisture content at field capacity (cm cm" ), and Z is the root-zone depth (cm). The amount of soil moisture deficit (D) is added per unit area to the system as irrigated water by the P R Z M model. Several input parameters in the P R Z M model were calibrated to achieve the water balance guidelines for the furrow irrigation system: Z

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Pan evaporation factor (PFAC)



Soil evaporation moisture loss (ANETD)



Universal soil loss cover management factor (USLELS)



SCS Runoff curve number (CN)



Fraction of available water capacity (PCDEPL)



Irrigation application rate ( R A T E A P )



Leaching factor as a fraction of irrigation water depth ( F L E A C H )

Since most furrows are set up as parallel strips between row crops, it was decided that a ratio of 7:3 be used (for ground applications) to divide the chemical/pesticide application mass between crops and furrows. In other words, 70 percent of the chemical/pesticide mass was assumed to be applied over crops and the remaining 30 percent was assumed to be applied over furrows within the particular area. For aerial applications however, a higher ratio of 1:1 was used meaning the total mass of the chemical/pesticide was equally distributed (50 percent for each) between crops and furrows. The rationale for this being that when a chemical is applied aerially, there is a more uniform distribution of the chemical between the crops and furrows as compared to when only the crops are targeted using a ground application technique. Two sets of P R Z M runs were conducted for 'corn' and 'vegetable'. The first run included either 70 or 50 percent (depending on ground or aerial application method) of the applied mass within the crop area. The second run included either the remaining 30 or 50 percent of the applied mass within the furrow.

Results and Discussion Calibration results Calibrated input parameters are compared to original input parameters in Table II. Calibrations were conducted for 30-years of historical weather (1961-

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

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230 1990) to evaluate runoff loadings under a range of soil moisture conditions using four different weather stations: Sacramento, C A (W23232), San Francisco, C A (W23234), Reno, N V (W23185), and Santa Maria, C A (W23273). The 30-year average values were used for comparing variations in results for the four weather stations (Table III). The first column lists various irrigation and water budget parameters that were used for comparisons. The second column contains values that are based on the furrow irrigation design and are consistent with observed practices in the Sacramento River watershed. The subsequent columns illustrate variations in parameters when different weather station data are used for the P R Z M simulations. The model predicts irrigation frequency (number of irrigation events), and components of the water balance (amount of irrigation, amount of runoff) with reasonable accuracy when compared to design results. The predicted amount of infiltration is greater due to the inclusion of daily precipitation events in the model which was excluded from the initial water balance guidelines.

Table II. Calibrated PRZM parameters for furrow irrigation

PRZM Parameter Pan evaporation factor (dimensionless) Soil evaporation moisture loss (cm) Universal soil loss equation cover management factor (dimensionless) SCS Runoff curve number (dimensionless) Fraction of available water capacity (dimensionless) Irrigation application rate (cm/hr) Leaching factor as a fraction of irrigation water depth (dimensionless)

Variable name PFAC ANETD

Original value 0.7

Calibrated value 0.5

17

25

USLEC

0.915

0.400

CN

84

60

PCDEPL

0.55

0.15

RATEAP

0.00

0.44

FLEACH

0.10

0.00

Predicted Permethrin Loadings Runoff and eroded losses were converted into combined annual loads for each simulation and then aggregated to the county scale for tabular reporting (Table IV) and to the township scale (36 square miles) for mapping (Figure 3 and Figure 4). In Table IV, applied mass is based on 2003 application data. Pesticide use is listed based on amount of aerial application (kg), amount of ground application (kg), percentage aerial application, and total application (kg). Predicted loads are listed based on amounts (kg) and percentages.

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

231 For those land uses that were subjected to furrow irrigation (corn and vegetable) the losses of both portions (70 percent for crop and 30 percent for furrow) were added together to generate total annual loads. The Weibull plotting position (73) was used to calculate the 50 and 90 percentile annual load for each aggregation level. The 50 and 90 percentiles express pesticide loadings into a temporal probability context (i.e., frequency of occurrence). For example annual loads at the 90 percentile values are estimated to occur on average once in a 10-year period. The 50 percentile values have a recurrence interval of 2years. Results indicate that highest loads occur around the tributaries and streams of the major rivers within the study area as opposed to the smaller water bodies and segments. Moreover, predicted loads are concentrated within nine counties, namely Butte, Colusa, Glenn, Sacramento, Solano, Sutter, Tehama, Yolo, and Yuba. th

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Table III. Calibration results for different weather stations Irrigation parameters and water Design budget for corn

r different Predicted(PRZM)pcirameters fc weather • stations W23185 W23234 W23273 W23232 7.37

8.67

67.23

77.79.

91.52

103.55

95.16

93.33

16.25

12.40

12.59

14.48

17.21

18.66

16.21

15.83

51.20

54.52

# of irrigation events per season

5-9

8.97

8.97

Amount of irrigation (cm)

95.76

94.69

Amount of infiltration (cm)

82.26

121.16

Amount of runoff (cm) Runoff as % of total water applied (irrigation only)

12.69 17.21

Evapotranspiration (cm)

59.36

48.50

1.69 1.55 1.99 \d) paramete >rs for Pred cted (PRZl Irrigation parameters and water is aafferent we ather statiot Design budget for tomato W23185 W23273 W23234 W23232 2.14

Sediment eroded (tonnes/ha)

6.87

8.13

62.30

72.51

85.89

99.87

91.40

89.96

11.63

11.69

13.51

# of irrigation events per season

5-9

7.87

5.90

Amount of irrigation (cm)

95.76

83.07

Amount of infiltration (cm)

82.26

112.17 14.43

Amount of runoff (cm) Runoff as % of total water applied (irrigation only)

12.69

17.50

18.92

16.21

15.80

Evapotranspiration (cm)

57.87

48.40

51.43

55.12

Sediment eroded (tonnes/ha)

1.05

0.83

0.84

1.01

17.21

Gan et al.; Synthetic Pyrethroids ACS Symposium Series; American Chemical Society: Washington, DC, 2008.

232 Table IV. Permethrin applications and predicted loadings Applied Mass (kg)

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County

Butte Colusa Glenn Sacramento Shasta Solano Sutter Tehama Yolo Yuba

Total 725.6 886.5 784.1 348.7 0.02 185.5 1152.7 239.3 445.6 616.0

% Aerial 11.7 62.4 46.2 0.5 0.0 2.5 8.6 6.5 32.7 0.1

Mass Loadings (kg) 50'" 0.03 0.09 0.40 0.18 0.00 0.03 0.22 0.09 0.155 0.034

h

9& 0.33 0.31 1.36 1.08 0.00 0.10 0.68 0.29 0.91 0.40

Mass Loadings (% of applied mass) lh

50