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Denitrification in the saturated zone of hydromorphic soils-laboratory measurement, regulating factors and stochastic modeling [An article from: Soil Biology and Biochemistry]
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PublisherElsevier
ISBN / ASINB000RR6TJ2
ISBN-13978B000RR6TJ4
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Description
This digital document is a journal article from Soil Biology and Biochemistry, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Denitrification capacity (D"c"a"p) was measured in 595 samples from the saturated zone of 18 hydromorphic soils by anaerobic incubation of K^1^5NO"3 amended slurries in the laboratory and analyzing ^1^5N"2+^1^5N"2O in the sample headspace. Furthermore, texture, pH, C (total, dissolved, hot-water soluble organic and inorganic C), total N and sulfide were measured in order to model D"c"a"p by multiple regression analysis. D"c"a"p was significantly correlated with most properties, but exhibited closest relationships to electron donors (C"o"r"g, sulfide). Mean D"c"a"p of the soil material groups sand, loam and peat was 0.13, 1.34 and 26.6mgNkg^-^1d^-^1. Regression models for predicting D"c"a"p were varied in the selection of independent variables and in the differentiation of the source data-set. The models were found to be suitable to estimate mean D"c"a"p of sites with medium or high activity. Best fits were obtained with the most complex models, but prediction for individual samples and for means of sites with low activity was not satisfactory with any of the models. The model based on organic C and total N and differentiating by type of soil material and position above or below the groundwater level was validated using an independent data-set of 46 samples from 10 sites of fluvial, glaciofluvial or glacial till sediments. The fluvial sediments exhibited satisfactory agreement between measured and predicted D"c"a"p, whereas the other sites were overestimated because D"c"a"p was too low and possibly because glacial till was not part of the source data-set. Our study provides for the first time statistical models of denitrification in shallow groundwater which are transferable to other sites with certain restrictions and which can thus be used for environmental modeling and soil mapping.
Description:
Denitrification capacity (D"c"a"p) was measured in 595 samples from the saturated zone of 18 hydromorphic soils by anaerobic incubation of K^1^5NO"3 amended slurries in the laboratory and analyzing ^1^5N"2+^1^5N"2O in the sample headspace. Furthermore, texture, pH, C (total, dissolved, hot-water soluble organic and inorganic C), total N and sulfide were measured in order to model D"c"a"p by multiple regression analysis. D"c"a"p was significantly correlated with most properties, but exhibited closest relationships to electron donors (C"o"r"g, sulfide). Mean D"c"a"p of the soil material groups sand, loam and peat was 0.13, 1.34 and 26.6mgNkg^-^1d^-^1. Regression models for predicting D"c"a"p were varied in the selection of independent variables and in the differentiation of the source data-set. The models were found to be suitable to estimate mean D"c"a"p of sites with medium or high activity. Best fits were obtained with the most complex models, but prediction for individual samples and for means of sites with low activity was not satisfactory with any of the models. The model based on organic C and total N and differentiating by type of soil material and position above or below the groundwater level was validated using an independent data-set of 46 samples from 10 sites of fluvial, glaciofluvial or glacial till sediments. The fluvial sediments exhibited satisfactory agreement between measured and predicted D"c"a"p, whereas the other sites were overestimated because D"c"a"p was too low and possibly because glacial till was not part of the source data-set. Our study provides for the first time statistical models of denitrification in shallow groundwater which are transferable to other sites with certain restrictions and which can thus be used for environmental modeling and soil mapping.
