Elsevier

Environmental Pollution

Volume 157, Issue 12, December 2009, Pages 3370-3378
Environmental Pollution

Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

https://doi.org/10.1016/j.envpol.2009.06.024Get rights and content

Abstract

The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed.

Introduction

In recent years, non-point source pollution from agriculture is increasingly responsible for the degradation of surface water quality. This, in turn, increases the need of integral water-quality management with enhanced hydrologic models. Off-site movement of agrochemicals, such as organophosphate (OP) pesticides, to streams and aquifers, in agricultural watersheds, may potentially cause adverse effects on human health and ecosystem. OP pesticides are widely used in orchards and other crops. According to the pesticide market estimates by U.S. Environmental Protection Agency (USEPA, 2004), OP use as a percent of total insecticide use has increased from 58% in 1980 to 70% in 2001. In the San Joaquin Valley of California, one of the most productive agricultural regions in the world, about 450 tons of active ingredients of OP pesticides were used per year from 1990 to 2007, and OP pesticide residues have been routinely detected in surface water bodies of the San Joaquin River watershed. According to the sampling results during 1992–1995, pesticide levels in 37% of the streams in the San Joaquin Valley exceeded the criteria for the protection of freshwater aquatic life (Dubrovsky et al., 1998).

GIS-based distributed or semi-distributed modeling is widely applied to simulate chemical transport and predict pollution reductions with management practices in agricultural watersheds. The in-field and in-stream transport processes of OP pesticides are determined to a great extent by the dominant hydrologic processes of a river watershed. Therefore, a reliable hydrologic simulation has to be established for the dynamic pesticide exposure assessment. Modeling of pesticide fate and transport might be more complex and associated with more sources of uncertainty than hydrologic simulation (Dubus et al., 2003, Holvoet et al., 2005). Even if the rates and timing of a particular pesticide application are fully recorded for some agriculturally dominated areas such as the San Joaquin Valley, there are other data inputs associated with greater uncertainties, such as soil properties (e.g., curve number and erosion factors) and chemical properties of pesticides (e.g., half-lives and partition coefficient). Therefore, it is very important to present clearly the propagation of input variances into model outputs for environmental persistence of OP pesticides.

In most studies of water-quality modeling at watershed scale, sensitivity analysis is usually performed for one catchment as a whole, without the consideration for spatial arrangement of sub-catchments in the stream network. Therefore, the spatial effects on the model performance and management implications are not fully evaluated. As indicated by Arabi et al. (2006), for example, in-stream transport processes and associated conservation practices must be discussed at watershed scale because their effects cannot be detected at fields. In order to provide useful information for agricultural management strategies, simulation of pesticide transport should consider hydrometeorology and water-quality processes at various spatial scales. The spatial dependence of environmental fate of pesticide species were traditionally evaluated based on measurement data. For example, Capel et al. (2001) examined monitoring data of 39 pesticides as a function of scale across 14 orders of magnitude. There are a few but increasing number of studies modeling fate and transport of pesticides at area-varying watersheds (Brown et al., 2002, USEPA, 2006, Luo et al., 2008).

The Soil and Water Assessment Tool (SWAT) was chosen in this study to predict pesticide loads of OP species in surface water. In addition to hydrologic simulation, SWAT also allows dynamic predictions of pesticide outputs at various spatial scale (Gassman et al., 2007). In our previous study, SWAT had been calibrated for the hydrologic conditions in the San Joaquin River basin (14 983 km2), and applied to evaluate residue distribution of two OP pesticide diazinon and chlorpyrifos (Luo et al., 2008). Based on the calibrated model, effects of pesticide management practices on water quality were evaluated (Zhang et al., 2008). The modeling efforts were extended in this study by predicting pesticide transport and potential efficiency of structural best management practices (BMPs) at spatial scales of [1] small watershed (the Orestimba Creek watershed, a tributary watershed of the San Joaquin River, 563 km2), and [2] agricultural fields (agricultural drainage area in the Orestimba Creek watershed, 146 km2 in total). The objectives of this study were threefold: (1) to evaluate the modeling capability of SWAT in predicting the fate and transport of pesticides in agricultural watersheds with different spatial extents, by comparing with measured pesticide loads in surface water; (2) to identify the most influential model parameters for simulating pesticide distribution based on a management-oriented sensitivity analysis; and (3) to represent the functionality of selected management practices in SWAT, and to assess the water-quality impacts at both field and watershed scales. Results in this study were anticipated to provide useful information for agricultural BMP planning in reducing pesticide residues, and for future model development and evaluation in agrochemical transport and mitigation.

Section snippets

Site description

The Orestimba Creek watershed was selected as a representative sub-region in the San Joaquin River basin for further investigation (Fig. 1). Large amounts of organophosphate insecticides are sprayed to almonds and other stone-fruit orchards in the watershed (Cryer et al., 2001). Compared to other regions in the San Joaquin Valley, a greater variety of pesticides were detected in this watershed (Dubrovsky et al., 1998). Chlorpyrifos and diazinon loadings per unit area from the Orestimba Creek

Baseline modeling

The results of statistical evaluation of the model performance for stream flow, sediment, and pesticides predicted at the two USGS gauges during 1992–2007 are summarized in Table 4, reported for rainfall season, irrigation season, and the entire simulation period. The model efficiencies (NSE) by comparing the SWAT-predicted monthly stream flow and USGS measurements were 0.82 and 0.78 at gauges #11274500 and #11274538, respectively, for the entire simulation period (Fig. 2). This indicated good

Conclusion

In this paper, pesticide fate and transport in an agriculturally dominated watershed were evaluated by SWAT modeling. The model simulation was applied in the field conditions of the Orestimba Creek watershed, California, with two widely used organophosphate pesticides chlorpyrifos and diazinon during 1990–2007. The calibrated SWAT generated reliable simulation results for the stream flow, sediment, and pesticides in the studied watershed. By comparing with the results of SWAT model previously

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