模拟纽约中部农业集水区的反硝化作用

Janet R. Barclay , Todd R. Anderson , Josephine A. Archibald , M. Todd Walter
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引用次数: 3

摘要

反硝化作用是微生物介导的NO3−还原为N2、NO或N2O气体,通过减少下游水域的N负荷提供重要的生态系统服务。为了将反硝化服务纳入管理规划,重要的是量化其效益;然而,很难量化反硝化速率,更难以在空间和时间上推断反硝化速率以产生景观尺度的反硝化估计。我们开发了一个耦合的水文-反硝化模型,该模型预测了整个农业流域的每日反硝化速率,并使用原位反硝化测量和两种类型的水文观测(河流流量和高地土壤湿度)对其进行了校准。该模型与观测到的反硝化作用(R2 = 0.77, RMSE = 272 kg N ha−1 yr−1,NRMSE = 0.77)、河流流量(NSE = 0.66)和土壤湿度(NSE = 0.77)拟合良好,并量化了流域整体以及不同土地类别提供的反硝化生态系统服务。在7年模型运行中,流域平均年反硝化速率为21 kg N ha−1年−1,湿地为47 kg N ha−1年−1,种植区为52 kg N ha−1年−1,牧场和森林为4 kg N ha−1年−1。生态系统服务的量化是在管理决策中考虑这些效益的必要先决条件。这项研究是解决缺乏实地验证的生态系统服务量化研究的一步。在未来,该模型将使我们能够进一步研究反硝化的时空模式,并探索管理实践或气候变化的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Modeling denitrification in an agricultural catchment in Central New York

Denitrification, the microbially mediated reduction of NO3 to N2, NO, or N2O gas, provides an important ecosystem service by reducing N loads to downstream waters. To incorporate denitrification services into management planning, it is important to quantify the benefit; however, it is difficult to quantify denitrification rates and even harder to extrapolate them spatially and temporally to generate landscape-scale estimates of denitrification. We developed a coupled hydrologic-denitrification model that predicts daily denitrification rates across an agricultural watershed and calibrated it using in situ denitrification measurements and two types of hydrologic observations (streamflow and upland soil moisture). The model fits well with the observed denitrification (R2 = 0.77, RMSE = 272 kg N ha−1 yr−1, NRMSE = 0.77), stream discharge (NSE = 0.66) and soil moisture (NSE = 0.77), and quantifies the denitrification ecosystem service provided by the watershed as a whole, as well as by the various land classes. Over the seven year model run, mean annual denitrification rates were 21 kg N ha−1 yr−1 watershed-wide, 47 kg N ha−1 yr−1 in the wetland, 52 kg N ha−1 yr−1 in cropped areas, and 4 kg N ha−1 yr−1 in pastures and forests. Quantification of ecosystem services is an essential prerequisite to accounting for those benefits in management decisions. This study is one step towards addressing the lack of field validated ecosystem service quantification studies. In the future, the model will allow us to further examine the spatial and temporal patterns of denitrification and to explore the implications of changes in management practices or climate.

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