期刊
JOURNAL OF HYDROLOGY
卷 386, 期 1-4, 页码 142-159出版社
ELSEVIER
DOI: 10.1016/j.jhydrol.2010.03.016
关键词
Macropore flow; Agrochemicals; Contaminant transport; Large scale assessment; Preferential flow; Risk assessment
资金
- Agriculture and Agri-Food Canada
Indicators of risk of water contamination (IROWCs) by agricultural contaminants are developed to assess sustainability of agriculture. Burrow flow (BF) is part of the transport hydrology algorithm used in IROWCs since it is a key pathway for sub-surface contaminant transport. The objectives of this study were to develop a methodology for predicting the likelihood of BF occurrence in agricultural soils across Canada at the landscape scale, and to determine its variation over a 25-year period (1981-2006). The BF algorithm considers the influence of climate, soil properties, and soil management on the likely frequency of BF and distribution of burrows (B) made by Lumbricus terrestris L. Nova Scotia, Prince Edward Island, Ontario, Quebec, followed by New Brunswick, had the highest likelihood of BF due to favourable humidity, sufficient heat, medium-textured soils, and strong runoff during the growing season and spring thaw. Alberta and Saskatchewan are too dry to favour BF. Areas with high risk of BF fall within locations of high potential for lateral flow due to shallow soils, or to the presence of tile drainage, which may connect BF pathways to important water bodies such as the Great Lakes and the St-Lawrence River. Sensitivity analyses on threshold values used in the BF algorithm indicated that Manitoba is the most sensitive province to changes in precipitation, Quebec to temperature, Prince Edward Island to soil depth, and Ontario to manure application. The BF algorithm can be used as a simple tool to predict the likelihood of water and contaminant transport along earthworm burrows with data available across Canada. It will be upgraded with new data (e.g. climate change) and with an improved algorithm after statistical analyses and correlations with actual water quality data. (C) 2010 Elsevier B.V. All rights reserved.
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