Using generalized additive models to investigate drivers and controls on stream water nitrate concentrations in four agricultural catchments

IF 5.9 1区 农林科学 Q1 AGRONOMY
Jason Galloway , Golnaz Ezzati , Daniel Hawtree , Karl Richards , Bridget Lynch , Edward Burgess , Ogjnen Zurovec , Macdara O’Neill , Per-Erik Mellander
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Abstract

Nitrogen (N) is essential for agricultural production and additional inputs of N-containing mineral or organic fertilizers as part of modern agricultural practice followed by the subsequent loss of surplus N has led to a deterioration in water quality globally. In order to design effective mitigation measures and accurately assess progress towards meeting water quality improvement goals, an understanding of the processes that govern N loss is prerequisite. However, the complexity which governs N cycling in agricultural catchments and the timescales over which they occur make understanding the relative importance of the drivers and controls of N loss challenging. Here, we used an eight-year dataset to investigate stream water nitrate concentrations across four catchments with contrasting characteristics where agriculture accounted for greater than 95 % of the land use. We subdivided each catchment into subcatchments and investigated trends in stream water nitrate concentrations using explanatory variables representing farming intensity, land management, climatic conditions, and soil drainage. We adopted a systematic approach using generalized additive mixed models (GAMM) to capture complex relationships between explanatory variables and nitrate concentrations within each catchment and across all catchments. We found no clear relationship between source N loadings and stream water nitrate concentrations, with the most likely explanation for this being that N cycling in the study sites were transport- and not source-limited. Our results highlighted the key role played by climate and the hydrological characteristics of catchments driving N loss from agricultural catchments. We also found that site specific characteristics mediated the relative importance of the drivers and controls of N losses which suggests that effective mitigation measures should be determined by hydraulic properties of (sub)catchments.
利用广义加性模型研究了四个农业集水区水体硝酸盐浓度的驱动因素和控制因素
氮(N)对农业生产至关重要,作为现代农业实践的一部分,含氮矿物或有机肥料的额外投入以及随后剩余氮的损失导致了全球水质的恶化。为了设计有效的缓解措施和准确评估实现水质改善目标的进展,了解控制氮损失的过程是先决条件。然而,控制农业流域氮循环的复杂性及其发生的时间尺度使得理解氮损失的驱动因素和控制的相对重要性具有挑战性。在这里,我们使用了一个八年的数据集来调查四个集水区的溪流硝酸盐浓度,这些集水区的农业占土地利用的比例超过95% %。我们将每个集水区细分为子集水区,并使用代表耕作强度、土地管理、气候条件和土壤排水的解释变量调查了溪流中硝酸盐浓度的趋势。我们采用了系统的方法,使用广义加性混合模型(GAMM)来捕捉每个流域和所有流域内解释变量与硝酸盐浓度之间的复杂关系。我们发现源氮负荷与溪流硝酸盐浓度之间没有明确的关系,最可能的解释是研究地点的氮循环是运输而不是来源限制的。我们的研究结果强调了气候和流域水文特征在农业流域氮损失中的关键作用。我们还发现,特定地点的特征调节了氮损失驱动因素和控制因素的相对重要性,这表明有效的缓解措施应由(次)流域的水力特性决定。
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来源期刊
Agricultural Water Management
Agricultural Water Management 农林科学-农艺学
CiteScore
12.10
自引率
14.90%
发文量
648
审稿时长
4.9 months
期刊介绍: Agricultural Water Management publishes papers of international significance relating to the science, economics, and policy of agricultural water management. In all cases, manuscripts must address implications and provide insight regarding agricultural water management.
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