A Pesticide Surface Water Mobility Index and Its Relationship With Concentrations in Agricultural Drainage Watersheds

Abstract

An index to benchmark pesticide mobility relevant to surface water runoff and soil erosion (surface water mobility index, or SWMI) was derived based on two key environmental fate parameters: degradation half-life and organic carbon-normalized soil/water sorption coefficient (Koc). Values assigned with the index of each individual compound correlate well with the concentration trend of 13 pesticides monitored in six Lake Erie, USA, tributaries from 1983 to 1991. Regression using a power function of SWMI fits concentration data well at various percentiles in the database for each tributary and all six tributaries combined, with r2 ranging from 0.71 to 0.94 for the concentrations at the 95th percentile. Good agreement was also obtained between SWMI and the time-weighted annual mean concentrations (r2 = 0.67-0.87). Although concentrations at or near peaks tend to be driven by rare hydrological events (intense precipitation immediately after application), SWMI explains the peak concentration data generally well (r2 = 0.53-0.86). The SWMI-concentration relationship was further evaluated with two other pesticide monitoring databases: the U.S. Geological Survey National Water Quality Assessment Program White River Study Unit (1991-1996) at Hazelton, Indiana, USA, and the Syngenta (previously Novartis) Voluntary Monitoring Program with Community Water Systems at the Higginsville City Lake, Missouri, USA (1995-1997). The ability of the proposed SWMI to discriminate pesticide runoff mobility and its correlation with surface water monitoring data can be significant in the development of screening methodologies and data-based models for government agencies and/or practitioners in general facing increasing pressure to assess pesticide occurrence in aquatic environments.

Estimating Catchment Vulnerability to Diffuse Herbicide Losses from Hydrograph Statistics

“…The difference in their sorption coefficients alone (factor of 2; Supplementary Table SI‐5) does most likely not explain this order. Additionally, Gustafson et al (2004) and Chen et al (2002; acetochlor not included) successfully modeled the surface water concentrations in the Lake Erie tributaries by assuming smaller half‐life values of acetochlor and alachlor than atrazine and metolachlor.…”

Pesticide soil sorption parameters: theory, measurement, uses, limitations and reliability

“…There are many situations where a relative mobility comparison between pesticides can provide a useful decision‐making aid without reference to any specific site or use. Examples are the GUS57 and Jury et al 58 leaching indexes, the NRCS leaching and runoff risk indices59 and the Surface Water Mobility Index (SWMI) 60. Risk index algorithms are used to suggest the least risky (for ground water, usually) choice of active ingredients in Integrated Pest Management programs 58–63.…”

The Acetochlor Registration Partnership Surface Water Monitoring Program for Four Corn Herbicides

“…The other main sources of variation in this figure are spring rainfall and environmental fate characteristics. This was shown by fitting a three‐parameter linear regression model to the detection frequencies (Table 5) The fitted regression equation ( r 2 = 0.98) is: where the effect of fate properties of the herbicides is represented by the unitless surface water mobility index (SWMI) (Chen et al, 2002). The surplus April–June precipitation (mm) is PRCP s , as defined in Table 4 The nationwide use on corn (kg ha −1 ) is USE, as plotted on the abscissa of Fig.…”

“…DT 50 is the time required for first 50% of applied compound to dissipate from soil. SWMI is the Surface Water Mobility Index (Chen et al, 2002). Data for these three columns are from Chen et al (2002), except for acetochlor data, which is from Gustafson et al (2004)…”