Numerical simulation of agricultural sediment and pesticide runoff: RZWQM and PRZM comparison |
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| Authors: | Huajin Chen Xuyang Zhang Christopher Demars Minghua Zhang |
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| Institution: | 1. Department of Land, Air and Water Resources, University of California, Davis, Davis, CA, USA;2. California Department of Pesticide Regulation, Sacramento, CA, USA;3. iWATER, Key Laboratory of Watershed Science and Health of Zhejiang Province, Wenzhou Medical University, Zhejiang, China |
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| Abstract: | Agricultural sediment and pesticide runoff is a widespread ecological and human health concern. Numerical simulation models, such as Root Zone Water Quality Model (RZWQM) and Pesticide Root Zone Model (PRZM), have been increasingly used to quantify off‐site agricultural pollutant movement. However, RZWQM has been criticized for its inability to simulate sedimentation processes. The recent incorporation of the sedimentation module of Groundwater Loading Effects of Agricultural Management Systems has enabled RZWQM to simulate sediment and sediment‐associated pesticides. This study compares the sediment and pesticide transport simulation performance of the newly released RZWQM and PRZM using runoff data from 2 alfalfa fields in Davis, California. A composite metric (based on coefficient of determination, Nash–Sutcliffe efficiency, index of agreement, and percent bias) was developed and employed to ensure robust, comprehensive assessment of model performance. Results showed that surface water runoff was predicted reasonably well (absolute percent bias <31%) by RZWQM and PRZM after adjusting important hydrologic parameters. Even after calibration, underestimation bias (?89% ≤ PBIAS ≤ ?36%) for sediment yield was observed in both models. This might be attributed to PRZM's incorrect distribution of input water and uncertainty in RZWQM's runoff erosivity coefficient. Moreover, the underestimation of sediment might be less if the origin of measured sediment was considered. Chlorpyrifos losses were simulated with reasonable accuracy especially for Field A (absolute PBIAS ≤ 22%), whereas diuron losses were underestimated to a great extent (?98% ≤ PBIAS ≤ ?65%) in both models. This could be attributed to the underprediction of herbicide concentration in the top soil due to the limitations of the instantaneous equilibrium sorption model as well as the high runoff potential of herbicide formulated as water‐dispersible granules. RZWQM and PRZM partitioned pesticides into the water and sediment phases similarly. According to model predictions, the majority of pesticide loads were carried via the water phase. On the basis of this study, both RZWQM and PRZM performed well in predicting runoff that carried highly adsorptive pesticides on an event basis, although the more physically based RZWQM is recommended when field‐measured soil hydraulic properties are available. |
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| Keywords: | model evaluation numerical modeling pesticide sediment surface runoff |
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