Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC
Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC
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DOI：
10.1029/2010jg001609
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发表时间：
2011-06
影响因子：
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通讯作者：
Jia Deng;B. Zhu;Zaixing Zhou;Xunhua Zheng;Changsheng Li;Tao Wang;Jia-liang Tang
中科院分区：
文献类型：
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作者：
Jia Deng;B. Zhu;Zaixing Zhou;Xunhua Zheng;Changsheng Li;Tao Wang;Jia-liang Tang
水质恶化是我国水环境污染的一个普遍现象，而农业系统氮素等营养盐的负荷是造成水环境污染的重要原因。基于过程的生态地球化学模型已被应用于量化非点源在流域尺度上的营养负荷。然而，这方面的努力往往是阻碍了一个事实，即很少有现有的生态地球化学模型的养分循环是能够模拟的二维土壤水文。为了克服这一挑战，我们发起了一个新的尝试，将两个基本的水文功能，土壤保持服务曲线和修改后的通用土壤流失方程功能，到一个生态地球化学模型，反硝化分解（DNDC）。这两个特征已被广泛用于一套水文模型中的地表径流和土壤侵蚀的量化。我们将这些功能纳入DNDC模型中，以允许地球化学和水文过程在每天的时间步长交换数据。通过引入新功能，DNDC获得了额外的能力来模拟水和营养物质的水平和垂直运动。在中国西南山区以农田为主的小流域观测数据集上对修正后的DNDC进行了检验。模拟的地表径流，地下排水流量，产沙量和氮负荷与观测结果一致。为了进一步观察新模型的行为，我们在不同的气候、土壤和管理条件下进行了敏感性测试。结果表明，降水量是决定氮素负荷的最敏感因子。进行了蒙特卡罗试验，以量化由四个选定输入参数的变化产生的潜在不确定性。本研究表明，它是可行的和有效的，使用增强的生态地球化学模型，如DNDC量化的N负荷，将基本的水文特征纳入模型框架。
Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process-based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two-dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification-Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework.