Pesticide Use Data in Water Quality Modeling

Transcription

1 Pesticide Use Data in Water Quality Modeling Yuzhou Luo Department of Land, Air, and Water Resources, University of California, Davis

2 Role of Pesticide Use Data Pesticide use Model simulation Pesticide loading t 0 [ U( τ ) LAPU( t τ )] d τ = L( t) U = Pesticide use rate (kg/day) L = Pesticide loading (kg/day) LAPU = Loading as percent of use (dimensionless)

3 Temporal and spatial scales Temporal PUR Agricultural: Daily (application time reported) Urban: Monthly Spatial Agriculture: Section (2.56 km 2 ) Urban: County (1,000 ~10,000 km 2 ) Water quality models Landscape processes: Daily In-stream processes: Sub-daily Watershed models: 1,000 km 2 Field-scale models: ha ~ km 2 Fine-resolution models: m 2

4 I. Watershed modeling Lower San Joaquin River Watershed, 15,000 km 2

5 OrestimbaCrek Orestimba Creek watershed, 500 km2

6 Chlorpyrifos: monthly uses in the lower San Joaquin River watershed, and monthly dissolved loads for the San Joaquin River at Vernalis (Luo et al., 2008)

7 Pesticide use (kg/day) Dissolved concentration (µg/l) Observation Prediction Year Chlorpyrifos: Observed and predicted dissolved concentrations at the watershed outlet of Orestimba Creek (Luo&Zhang, 2009)

8 II. Field-scale modeling Surface flows (water, sediment, & pesticide) Subsurface flows (water & pesticide) Edge-of-field flows

9 Natural vs. computational fields PUR Sections and DWR landuse map

10 Geo-referencing Spatial information in PUR site_code, site_loc_id acre_planted and acre_treated Mapping with landuse data DWR landuse survey database Local survey (e.g., Westside Coalition) Remote sensing data (e.g., Google Earth) Example: 7.4 million fields are defined for the Central Valley (Williams, 2011)

11 PUR records for 50M06S08E26 Site_code: (BEANS, DRIED-TYPE), 3001 (ALMOND), 3009 (WALNUT), 23001(ALFALFA).

12 Pesticide concentrations in soil Pesticide use Concentration Dissolved concentration (µg/l) Pesticide use (kg/day) Year Dissolved concentrations of diazinon (top) and chlorpyrifos (bottom) in soil, section M06S08E26 (Luo&Zhang, 2009) 0

13 Pesticide loads from fields The load as percent of use (LAPU) values for (a) diazinon and (b) chlorpyrifos over the Orestimba Creek watershed, average (Luo&Zhang, 2009)

14 LAPU for chlorpyrifos over Central Valley, (Luo&Zhang, 2010

15 Summary Types of PUR-related WQ modeling studies Watershed modeling, Field-scale modeling, Drift estimation, urban PUR downscaling, and more Modeling capability of pesticide WQ models depends on the availability, accuracy, and resolution of application data; Future development of WQ models should incorporate spatial analysis on chemical applications; Modeling of WQ protection also provides information/suggestions for PUR development.

16 References: PUR in WQ modeling Luo, Y. and M. Zhang, Environmental modeling and exposure assessment of sediment-associated pyrethroids in an agricultural watershed. PLoS ONE, 6(1): e Luo, Y. and M. Zhang, Spatially distributed pesticide exposure assessment in the Central Valley, California, USA. Environmental Pollution, 15(5): Luo, Y. and M. Zhang, Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling. Environmental Pollution, 157(12): Luo, Y. and M. Zhang, Multimedia transport and risk assessment of organophosphate pesticides and a case study in the northern San Joaquin Valley of California. Chemosphere, 75(7): Luo, Y. and M. Zhang, A geo-referenced modeling environment for ecosystem risk assessment: organophosphate pesticides in an agricultural dominated watershed. Journal of Environmental Quality, 38(2): Luo et al., Dynamic modeling of organophosphate pesticide load in surface water in the northern San Joaquin Valley of California. Environmental Pollution, 156(3):

17 Thank you Yuzhou Luo AGIS