scholarly journals Agricultural phosphorus and water quality: sources, transport and management

1998 ◽  
Vol 7 (2) ◽  
pp. 297-314 ◽  
Author(s):  
Andrew Sharpley ◽  
William Gburek ◽  
Louise Heathwaite
Keyword(s):  
Water Quality ◽  
Land Use ◽  
East Central ◽  
Soil P ◽  
Agricultural Catchments ◽  
Central Pennsylvania ◽  
Chemical Factors ◽  
Mixed Land Use ◽  
Extractable Soil ◽  
Freshwater Eutrophication

Freshwater eutrophication is usually controlled by inputs of phosphorus (P). To identify critical sources of P export from agricultural catchments we investigated hydrological and chemical factors controlling P export from a mixed land use (30% wooded, 50% cultivated, 20% pasture) 39.5-ha catchment in east-central Pennsylvania, USA. Mehlich-3 extractable soil P, determined on a 30-m grid over the catchment, ranged from 7 to 788 mg kg-1. Generally, soils in wooded areas had low Mehlich-3P (

The influence of riparian vegetation on water quality in a mixed land use river basin

2019 ◽  
Vol 35 (3) ◽  
pp. 259-267 ◽  
Author(s):  
Evan M. Chua ◽  
Scott P. Wilson ◽  
Sue Vink ◽  
Nicole Flint
Keyword(s):  
Water Quality ◽  
Land Use ◽  
River Basin ◽  
Riparian Vegetation ◽  
Mixed Land Use

Modelling phosphorus pollution risk in agricultural catchments using a spatially distributed Bayesian Belief Network

2020 ◽  
Author(s):  
Camilla Negri ◽  
Miriam Glendell ◽  
Nick Schurch ◽  
Andrew J. Wade ◽  
Per-Erik Mellander
Keyword(s):  
Water Quality ◽  
Decision Making ◽  
Land Use ◽  
Land Management ◽  
Nutrient Loss ◽  
Mitigation Measures ◽  
Agricultural Practice ◽  
Pollution Risk ◽  
Agricultural Catchments ◽  
Good Agricultural Practice

<p>Diffuse pollution of phosphorus (P) from agriculture is a major pressure on water quality in Ireland. The Agricultural Catchments Programme (ACP) was initiated to evaluate the Good Agricultural Practice measures implemented under the EU Nitrates Directive. Within the ACP, extensive monitoring and research has been made to understand the drivers and controls on nutrient loss in the agricultural landscape. However, tapering P pollution in agricultural catchments also requires informed decisions about the likely effectiveness of measures as well as their spatial targeting.  There is a need to develop Decision Support Tools (DST) that can account for the uncertainty inherently present in both data and water quality models.</p><p>Bayesian Belief Networks (BBNs) are probabilistic graphical models that allow the integration of both quantitative and qualitative information from different sources (experimental data, model outputs and expert opinion) all in one model. Moreover, these models can be easily updated with new knowledge and can be applied with scarce datasets. BBNs have previously been used in multiple decision-making settings to understand causal relationships in different contexts. Recently, BBNs were used to support ecological risk-based decision making.</p><p>In this study, a prototype BBN was implemented with the Genie software to develop a DST for understanding the influence of land management and P pollution risk in four ACP catchments dominated by intensively farmed land with contrasting hydrology and land use. In the fist stage of the study, the spatial BBN was constructed visualising the ‘source-mobilisation-transport-continuum’, identifying the main drivers of P pollution based on previous findings from the ACP catchments. A second step involved the consultation of experts and stakeholders through a series of workshops aimed at eliciting their input. These stakeholders have expertise ranging from hydrology and hydrochemistry, land management and farm consulting, to policy and environmental modelling.</p><p>At present, the BBN is being parameterized for a 12km<sup>2</sup> catchment with mostly grassland on poorly drained soils, using a high temporal and spatial resolution dataset that includes hydro-chemo-metrics, mapped soil properties (drainage class and Soil Morgan P), landscape characteristics (i.e. land use and management, presence of mitigation measures and presence of point pollution sources). Preliminary results show that the model captures the difference in P loss risk between catchments, probably caused by contrasting hydrological characteristics and soil P sources.</p><p>Future research will be focussed on parameterizing and testing the BBN in three other ACP catchments. Such parametrization will be pivotal to testing the model in data sparse catchments and possibly upscaling the tool to regional and national scale. Moreover, climate change and land use change modelled scenarios will be crucial to inform targeting of mitigation measures.  </p>

scholarly journals Relationships between land use and nitrogen and phosphorus in New Zealand lakes

2011 ◽  
Vol 62 (2) ◽  
pp. 162 ◽  
Author(s):  
Jonathan M. Abell ◽  
Deniz Özkundakci ◽  
David P. Hamilton ◽  
Steven D. Miller
Keyword(s):  
Land Use ◽  
New Zealand ◽  
Nitrogen And Phosphorus ◽  
Nutrient Sources ◽  
Soil P ◽  
Agricultural Catchments ◽  
Relative Contribution ◽  
Naturally Occurring ◽  
Lake Catchment ◽  
The Relationship

Developing policies to address lake eutrophication requires an understanding of the relative contribution of different nutrient sources and of how lake and catchment characteristics interact to mediate the source–receptor pathway. We analysed total nitrogen (TN) and total phosphorus (TP) data for 101 New Zealand lakes and related these to land use and edaphic sources of phosphorus (P). We then analysed a sub-sample of lakes in agricultural catchments to investigate how lake and catchment variables influence the relationship between land use and in-lake nutrients. Following correction for the effect of co-variation amongst predictor variables, high producing grassland (intensive pasture) was the best predictor of TN and TP, accounting for 38.6% and 41.0% of variation, respectively. Exotic forestry and urban area accounted for a further 18.8% and 3.6% of variation in TP and TN, respectively. Soil P (representing naturally-occurring edaphic P) was negatively correlated with TP, owing to the confounding effect of pastoral land use. Lake and catchment morphology (zmax and lake : catchment area) and catchment connectivity (lake order) mediated the relationship between intensive pasture and in-lake nutrients. Mitigating eutrophication in New Zealand lakes requires action to reduce nutrient export from intensive pasture and quantifying P export from plantation forestry requires further consideration.

Impact of mixed land-use practices on the microbial water quality in a subtropical coastal watershed

2013 ◽  
Vol 449 ◽  
pp. 426-433 ◽  
Author(s):  
Zhanbei Liang ◽  
Zhenli He ◽  
Xuxia Zhou ◽  
Charles A. Powell ◽  
Yuangen Yang ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Microbial Water Quality ◽  
Coastal Watershed ◽  
Mixed Land Use ◽  
Land Use Practices

Modelling hydrology and water quality in a mixed land use catchment and eutrophic lake: Effects of nutrient load reductions and climate change

2018 ◽  
Vol 109 ◽  
pp. 114-133 ◽  
Author(s):  
Wang Me ◽  
David P. Hamilton ◽  
Christopher G. McBride ◽  
Jonathan M. Abell ◽  
Brendan J. Hicks
Keyword(s):  
Climate Change ◽  
Water Quality ◽  
Land Use ◽  
Eutrophic Lake ◽  
Nutrient Load ◽  
Mixed Land Use
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