The need to quantitatively predict pesticide runoff and erosion under cropping system management has gained increasing importance. In Europe, predictive models have not yet been fully validated because of the lack of field data sets. The objective of this study was to validate the capability of PRZM (Pesticide Root Zone Model) 3.12 to predict water runoff, sediment erosion, and associated transport of atrazine (6-chloro-N(2)-ethyl-N(4)-isopropyl-1,3,5-triazine-2,4-diamine), terbuthylazine (N(2)-tert-butyl-6-chloro-N(4)-ethyl-1,3,5-triazine-2,4-diamine), and metolachlor [2-chloro-6'-ethyl-N-(2-methoxy-l-methylethyl)acet-o-toluidide] under common tillage management practices found in northern Italy. A 2-yr field data set was used to evaluate the model. Results showed that the model could qualitatively simulate significant differences of water runoff, soil erosion, and associated herbicide losses between conventional tillage (CT) and minimum tillage (MT) for a winter barley (Hordeum vulgare L.) cover crop. For MT, water runoff, soil erosion, herbicide losses in water runoff and eroded sediment, and the proportion of herbicide loss via sediment erosion were significantly lower than for CT. The model failed to correctly simulate event-based herbicide concentration, water runoff, and soil erosion. The model usually underestimated pesticide runoff events with high rainfall intensity and low daily precipitation volume, and overestimated runoff events with low intensity and high volume. The main reason was that the description of runoff and erosion processes is rather empirical in the model and not physically based. Moreover, model calculations do not adequately reflect the relationships between soil erosion intensity and chemical concentration in sediment losses, leading to discrepancies between predictions and field observations.
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http://dx.doi.org/10.2134/jeq2004.1720 | DOI Listing |
Sci Total Environ
January 2025
Temple University, Department of Civil and Environmental Engineering, 1947 North 12(th) Street, Philadelphia, PA 19122, United States. Electronic address:
The importance of pH in stormwater bioretention beds cannot be overstated since it impacts plant and microbial populations and removal of potentially toxic elements (PTEs) from stormwater runoff. This study investigated the effects of dolomite amendment on pH neutralization and subsequent PTE immobilization in bioretention media. To assess dolomite dissolution, pH neutralization, and PTE immobilization, engineered bioretention media was amended with different dolomite ratios and samples of dolomite-amended media were collected from two bioretention beds, one and two months after installation.
View Article and Find Full Text PDFPlants (Basel)
January 2025
School of Biological, Earth and Environmental Sciences, University College Cork, Distillery Fields, North Mall, T23 TK30 Cork, Ireland.
As a result of intensive agriculture, large quantities of liquid wastewaters are produced. Dairy soiled water (DSW) is produced in large volumes during the milking process of cattle. It comprises essential plant nutrients such as nitrogen, phosphorus, and potassium.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Mountain Societies Research Institute, University of Central Asia, Bishkek, Kyrgyzstan.
Mountain regions of Central Asia are experiencing strong influences from climate change, with significant reductions in snow cover and glacial reserves. A comprehensive assessment of the potential consequences under the worst-case climate scenario is vital for adaptation measures throughout the region. Water balance analysis in the Naryn River basin was conducted for the baseline period of 1981-2000 including potential changes under the worst-case SSP5-8.
View Article and Find Full Text PDFMar Pollut Bull
January 2025
Key Laboratory of Marine Ecosystem Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
Xiangshan Bay, one of China's most eutrophic semi-enclosed bays, was studied to examine the seasonal distributions of salinity, temperature, nutrients, and nitrate isotopes (δN and δO) to elucidate seasonal variations in nitrate sources and the key factors driving nitrogen level fluctuations. Based on nitrate δN (6.1-8.
View Article and Find Full Text PDFPLoS One
January 2025
Institute of Ocean Engineering, Ningbo University, Ningbo, Zhejiang, China.
Hydrological prediction in ungauged basins often relies on the parameter transplant method, which incurs high labor costs due to its dependence on expert input. To address these issues, we propose a novel hydrological prediction model named STH-Trans, which leverages multiple spatiotemporal views to enhance its predictive capabilities. Firstly, we utilize existing geographic and topographic indicators to identify and select watersheds that exhibit similarities.
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