Water body and riparian buffer strip characteristics in a vineyard area to support aquatic pesticide exposure assessment

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Abstract

The implementation of a geodata-based probabilistic pesticide exposure assessment for surface waters in Germany offers the opportunity to base the exposure estimation on more differentiated assumptions including detailed landscape characteristics. Since these characteristics can only be estimated using field surveys, water body width and depth, hydrology, riparian buffer strip width, ground vegetation cover, existence of concentrated flow paths, and riparian vegetation were characterised at 104 water body segments in the vineyard region Palatinate (south-west Germany).

Water body segments classified as permanent (n = 43) had median values of water body width and depth of 0.9 m and 0.06 m, respectively, and the determined median width:depth ratio was 15. Thus, the deterministic water body model (width = 1 m; depth = 0.3 m) assumed in regulatory exposure assessment seems unsuitable for small water bodies in the study area. Only 25% of investigated buffer strips had a dense vegetation cover (> 70%) and allow a laminar sheet flow as required to include them as an effective pesticide runoff reduction landscape characteristic. At 77 buffer strips, bordering field paths and erosion rills leading into the water body were present, concentrating pesticide runoff and consequently decreasing buffer strip efficiency. The vegetation type shrubbery (height > 1.5 m) was present at 57 (29%) investigated riparian buffer strips. According to their median optical vegetation density of 75%, shrubberies may provide a spray drift reduction of 72 ± 29%.

Implementing detailed knowledge in an overall assessment revealed that exposure via drift might be 2.4 and via runoff up to 1.6 fold higher than assumed by the deterministic approach. Furthermore, considering vegetated buffer strips only by their width leads to an underestimation of exposure by a factor of as much as four. Our data highlight that the deterministic model assumptions neither represent worst-case nor median values and therefore cannot simply be adopted in a probabilistic approach.

Introduction

In recent years, the implementation of a probabilistic pesticide risk assessment has been discussed at the EU level; in 2001, such an assessment was recommended by the European Workshop of Probabilistic Risk Assessment for the Environmental Impacts of Plant Protection Products (EUPRA) (Hart, 2001). In Germany, a geodata-based probabilistic approach is currently being debated for aquatic pesticide exposure assessment, and a framework has been proposed for evaluation of spray drift in permanent crops (Schulz et al., 2009). In contrast to the current deterministic exposure model, the probabilistic approach uses distribution functions as input factors. It therefore yields a result that reflects variation and uncertainty rather than a fixed, deterministic result (Hart, 2001). A key argument for the use of probabilistic exposure estimation is thus the increased realism of results that are based on the actual spatial variability of exposure-relevant landscape characteristics (e.g., buffer strip width and water body width and depth). Furthermore, the probabilistic approach can consider additional landscape characteristics (e.g., spray drift reduction of riparian vegetation) that have not yet been included in the deterministic assessment.

The successful implementation of the geodata-based probabilistic concept requires detailed spatial information concerning exposure-determining landscape characteristics in the field, which can already be derived from various databases (Table 1). The main resource available in Germany is the nationwide digital landscape model, which has a scale of 1:25,000 (DLM 25) and is included in the topographic–cartographic information system (ATKIS). However, ATKIS to some extent lacks both important types of information concerning landscape characteristics (e.g., height and density of riparian vegetation) and appropriate levels of data precision (e.g., water surface width is only defined in classes of < 3 m, 3–6 m, and 6–12 m). Although this missing information is often available in other databases, only field surveys can exhaustively fill the data gaps (Table 1).

The results of field surveys can be used to calculate the distribution functions of landscape characteristics, which can be used either to directly describe landscape characteristics in a truly probabilistic approach or to derive more realistic, conservative values. Field results can be further analysed to develop rules for deriving unknown landscape characteristics from other available information. Moreover, the survey information serves as so-called “groundtruthing” or validation for ATKIS DLM 25 data by comparing it to actual field conditions and thereby improving the data system. Discrepancies between ATKIS and field data are currently one of the main unsolved problems facing geodata-based probabilistic risk assessment (Schulz et al., 2009). Without proper data validation, any probabilistic approach promises unrealistic accuracy and precision.

To date, the literature includes no field surveys that focused on detailed landscape characterisation for refining geodata-based probabilistic exposure assessment. However, Bach et al., 1994a, Bach et al., 1994b, Bach et al., 1997 investigated riparian buffer strips with regard to their potential nutrient reduction efficiency in three small catchment areas along a 300 km stretch of water in central Germany. They described buffer width and riparian vegetation type, but focused on identifying potential concentrated runoff flow paths.

Exposure estimations that consider landscape characteristics derived from currently available databases (Table 1) are currently inaccurate due to the following data gap categories:

  • (1)

    Water body characteristics (hydrology, width, depth), which influence calculations of in-stream pesticide exposure;

  • (2)

    characteristics of riparian buffer strips (width, ground vegetation cover percentage, existence of concentrated flow paths), which are relevant for pesticide runoff exposure estimations; and

  • (3)

    presence and characteristics of riparian vegetation in the shrub and tree layer (type, height, optical density), which are relevant for spray drift exposure estimations.

The present study focused on these data types and provided exposure-relevant landscape characteristics for a winegrowing region in southwest Germany. The data were collected at 104 water body segments in the study area and were assessed based on the assumptions currently made during the regulatory exposure estimation process.

Section snippets

Study area

Field surveys were carried out from July to October 2006 in the winegrowing region of Palatinate in the federal state of Rheinland-Pfalz in southwest Germany. Study sites were located along a 40 km section of the German wine route between Bad Bergzabern and Kallstadt. The region is characterised by intensive winegrowing, which accounts for approximately 53% of agricultural land use. About 2% of agricultural land is used for fruit-growing, and the remainder (45%) is used for the cultivation of

Water body characteristics

According to the Federal state water act of Rheinland-Pfalz Germany (LWG-RLP., 2004), all investigated water body segments were water bodies of the third order, which means that they are relative small and have only a subordinate importance for water supply. A total of 43 (41%) water body segments were classified as permanent, 18 (17%) were periodic and 43 (41%) were ephemeral. The latter were typically drainage ditches that only contained water after heavy rainfall events. More than half of

Effects of water body characteristics on in-stream pesticide exposure concentrations

A high percentage (58%) of water bodies were prone to drying in the summer in the study area. This is supported by the studies of Bach et al. (1994b), who evaluated a river catchment in an intensive cropland in the middle of Germany during January and February and found that 45.5% of river segments were dry. These findings are important for evaluating the extent to which temporary water bodies are relevant for pesticide risk assessment for surface waters. German pesticide risk assessment

Conclusion

Field surveys are a helpful tool to obtain the necessary information on exposure-relevant landscape characteristics and to fill the information gaps of nationwide available digital databases according to Table 1. The results of our field survey show that there is a strong need to implement detailed survey information on water body and riparian buffer strip characteristics in the exposure assessment of pesticides, otherwise an underestimation of exposure via spray drift and runoff has to be

Acknowledgments

The authors would like to thank K. Zenker for the help with the field surveys, B. Ehrlich for the support in developing practical field work methods, T. Schad for the help with site selection, M. Trapp and G. Tintrup for the software advice and Sebastian Stehle, Jörn Wogram and the two anonymous reviewers for the helpful comments on earlier drafts of the manuscript.

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