Modeling denitrification in a changing climate

Janet R. Barclay , M. Todd Walter
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引用次数: 7

Abstract

Although uncertainty exists in the specifics of climate change, sufficient consensus has emerged regarding the scale and direction of changes that it is important for managers to consider the implications of these changes for essential ecosystem services such as denitrification. For the northeastern United States, it is expected that by the end of the 21st century, annual precipitation will increase by 10% and annual temperatures by 3 °C. Because denitrification rates are highly influenced by soil moisture and soil temperature, we expect the projected changes in temperature and precipitation to alter the rates and patterns of denitrification. We developed three future weather scenarios based on the B1, A2, and A1F1 emission scenarios and utilized them as inputs to a coupled hydrologic-denitrification model to analyze the effects of changing temperature and soil moisture on denitrification rates, assuming nitrate availability remains unchanged. Our results suggest denitrification rates will increase by 5.1–11.8 kg N ha−1 yr−1 across the watershed. The greatest projected increases are in the areas and seasons with the highest baseline rates, with smaller increases in those with lower baseline rates. We found that changing temperature is likely to be a much stronger driver of change to denitrification rates (7.7 kg N ha−1 yr−1) than changing precipitation (1.4 kg N ha yr−1). This study utilizes scenario modeling and a field validated model to quantify the future benefits of the ecosystem service denitrification, addressing a lack of ecosystem service quantification studies and providing a model for quantification studies.

Abstract Image

气候变化下的反硝化模拟
尽管气候变化的具体情况存在不确定性,但关于变化的规模和方向已经形成了充分的共识,因此管理者必须考虑这些变化对反硝化等基本生态系统服务的影响。对于美国东北部,预计到21世纪末,年降水量将增加10%,年气温将上升3°C。由于反硝化速率受土壤湿度和土壤温度的高度影响,我们预计温度和降水的预测变化将改变反硝化速率和模式。我们基于B1、A2和A1F1排放情景开发了3种未来天气情景,并将它们作为水文-反硝化耦合模型的输入,分析温度和土壤湿度变化对反硝化速率的影响,假设硝酸盐有效性保持不变。我们的研究结果表明,整个流域的反硝化速率将增加5.1-11.8 kg N ha - 1 yr - 1。预估增幅最大的是基线率最高的地区和季节,而基线率较低的地区和季节增幅较小。我们发现,温度变化对反硝化速率的影响(7.7 kg N ha−1 yr−1)可能比降水变化(1.4 kg N ha−1 yr−1)更大。本研究利用情景建模和实地验证模型对生态系统服务反硝化的未来效益进行了量化,解决了生态系统服务量化研究的不足,为量化研究提供了模型。
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