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Effects of soil moisture on the diurnal pattern of pesticide emission: Comparison of simulations with field measurements

Reichman, Rivka, Yates, Scott R., Skaggs, Todd H., Rolston, Dennis E.
Atmospheric environment 2013 v.66 pp. 52-62
agricultural soils, atmospheric chemistry, diazinon, diurnal variation, ecosystems, field capacity, humans, prediction, silty clay soils, simulation models, soil temperature, soil water, soil water content, volatilization, water content
Pesticide volatilization from agricultural soils is one of the main pathways in which pesticides are dispersed in the environment and affects ecosystems including human welfare. Thus, it is necessary to have accurate knowledge of the various physical and chemical mechanisms that affect volatilization rates from field soils. A verification of the influence of soil moisture modeling on the simulated volatilization rate, soil temperature and soil-water content is presented. Model simulations are compared with data collected in a field study that measured the effect of soil moisture on diazinon volatilization. These data included diurnal changes in volatilization rate, soil-water content, and soil temperature measured at two depths. The simulations were performed using a comprehensive non-isothermal model, two water retention functions, and two soil surface resistance functions, resulting in four tested models. Results show that the degree of similarity between volatilization curves simulated using the four models depended on the initial water content. Under fairly wet conditions, the simulated curves mainly differ in the magnitude of their deviation from the measured values. However, under intermediate and low moisture conditions, the simulated curves also differed in their pattern (shape). The model prediction accuracy depended on soil moisture. Under normal practices, where initial soil moisture is about field capacity or higher, a combination of Brooks and Corey water retention and the van de Grind and Owe soil surface resistance functions led to the most accurate predictions. However, under extremely dry conditions, when soil-water content in the top 1 cm is below the volumetric threshold value, the use of a full-range water retention function increased prediction accuracy. The different models did not affect the soil temperature predictions, and had a minor effect on the predicted soil-water content of Yolo silty clay soil.