Denitrification in Wetlands

Cleemput, Oswald Van; Boeckx, Pascal; Lindgren, Per-Eric; Tonderski, Karin

doi:10.1016/b978-044452857-5.50024-2

Cited by 12 publications

(15 citation statements)

References 25 publications

(22 reference statements)

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“…Furthermore, the algorithms only attempt to represent in-river uptake of N by algal growth and take no account of macrophytes (which are an important feature of the river Axe) in the river channel which might reduce river nitrogen concentrations during the spring and summer. Finally, data limitations meant that it was not possible to locate and simulate wetlands within SWAT which might be important local sinks of nitrogen [60][61][62]. Furthermore, in the process of building a model several adjustments of the parameters need to be made in order to improve simulations.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of River Water Quality Simulations at a Daily Time Step – Experience with SWAT in the Axe Catchment, UK

Glavan

White

Holman

2010

CLEAN Soil Air Water

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The Water Framework Directive (WFD) was established for the protection of surface waters (rivers, lakes, transitional and coastal waters) and ground waters in the European Union. The main environmental objective is to achieve and maintain a good status for all waters by the target date of 2015. Models which are able to address the majority of environmental objectives are proposed within the WFD to inform the management changes required to meet current water policy goals. The use of the Soil and Water Assessment Tool (SWAT) catchment model is widespread throughout the world, especially to support river basin management as required by the WFD. This paper provides a critical evaluation of the use of the model by placing model performance in the Axe catchment, UK, in the context of international performance of the model. Within the constraints of the available data, SWAT represents hydrology, sediment and ortho-phosphorus concentration well for this heterogeneous catchment, but the representation of daily nitrogen concentration dynamics is poor. Temporal aggregation of model outputs from daily to monthly improved the performance metrics for all the river outputs, including nitrate. Wider review of SWAT studies showed widespread reporting of monthly performance metrics within the SWAT studies, despite the model operating at a daily time step. Poor performance for nitrate identified in this current study may be a significant factor in the choice to not report daily results. This demonstrates the importance of ascertaining the reasons for the use of temporal aggregation in modelling studies.

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Section: Discussionmentioning

confidence: 99%

Evaluation of River Water Quality Simulations at a Daily Time Step – Experience with SWAT in the Axe Catchment, UK

Glavan

White

Holman

2010

CLEAN Soil Air Water

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“…In natural wetlands the direct loss of ammonia gas is negligible (Hemond 1983), and denitrification rates in global natural temperate wetlands on average is 4 kg N ha -1 year -1 (Van Cleemput et al 2007). However, in cultivated wetlands, such as rice paddies, N emissions can be much higher.…”

Section: Evidence Of Denitrification In Cultivated Cranberry Bedsmentioning

confidence: 99%

Looking beyond fertilizer: assessing the contribution of nitrogen from hydrologic inputs and organic matter to plant growth in the cranberry agroecosystem

Stackpoole

Kosola

Workmaster

et al. 2011

Nutr Cycl Agroecosyst

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Even though nitrogen (N) is a key nutrient for successful cranberry production, N cycling in cranberry agroecosystems is not completely understood. Prior research has focused mainly on timing and uptake of ammonium fertilizer, but the objective of our study was to evaluate the potential for additional N contributions from hydrologic inputs (flooding, irrigation, groundwater, and precipitation) and organic matter (OM). Plant biomass, soil, surface and groundwater samples were collected from five cranberry beds (cranberry production fields) on four different farms, representing both upland and lowland systems. Estimated average annual plant uptake (63.3 ± 22.5 kg N ha -1 year -1 ) exceeded total average annual fertilizer inputs (39.5 ± 11.6 kg N ha -1 year -1 ). Irrigation, precipitation, and floodwater N summed to an average 23 ± 0.7 kg N ha -1 year -1 , which was about 60% of fertilizer N. Leaf and stem litterfall added 5.2 ± 1.2 and 24.1 ± 3.0 kg N ha -1 year -1 respectively. The estimated net N mineralization rate from the buried bag technique was 5 ± 0.2 kg N ha -1 year -1 , which was nearly 15% of fertilizer N. Dissolved organic nitrogen represented a significant portion of the total N pool in both surface water and soil samples. Mixed-ion exchange resin core incubations indicated that 80% of total inorganic N from fertilizer, irrigation, precipitation, and mineralization was nitrate, and approximately 70% of recovered inorganic N from groundwater was nitrate. There was a weak but significant negative relationship between extractable soil ammonium concentrations and ericoid mycorrhizal colonization (ERM) rates (r = -0.22, P \ 0.045). Growers may benefit from balancing the N inputs from hydrologic sources and OM relative to fertilizer N in order to maximize the benefits of ERM fungi in actively mediating N cycling in cranberry agroecosystems.

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“…This flux is illustrated by high volume of water percolation losses (Table 6). As a result, the N-NO3 -formed in oxidizing zones are spread into soil profile (Aulakh and Bijay-Singh, 1996; and it triggers denitrification processes due to nitrate movement into anaerobic sites (Van Cleemput et al, 2007;. CF, SS, AWDL, AWDS might have low 15 N recovery compared to NF explained by it.…”

Section: The Isotopic Efficiencymentioning

confidence: 99%

“…Under continuous flooding the soil remains in a reduced anaerobic state and ammonium nitrification is restricted to a few oxidation sites, thus becoming negligible (Reddy et al, 1984;Van Cleemput et al, 2007). However, varying water regimes or high percolation rates can trigger nitrification and expose N to loss pathways such denitrification and leaching (Aulakh and Bijay-Singh, 1996;.…”

Section: Introductionmentioning

confidence: 99%

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Rice performance, water and nitrogen efficiency in different irrigation regimes in tropical lowland

Reis¹

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Denitrification in Wetlands

Cited by 12 publications

References 25 publications

Evaluation of River Water Quality Simulations at a Daily Time Step – Experience with SWAT in the Axe Catchment, UK

Evaluation of River Water Quality Simulations at a Daily Time Step – Experience with SWAT in the Axe Catchment, UK

Looking beyond fertilizer: assessing the contribution of nitrogen from hydrologic inputs and organic matter to plant growth in the cranberry agroecosystem

Rice performance, water and nitrogen efficiency in different irrigation regimes in tropical lowland

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