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Assessment of nitrate leaching on agriculture region using remote sensing and model

机译:基于遥感和模型的农业区硝酸盐淋失评估

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摘要

Overuse of chemical fertilizers raises the risk of nitrate pollution of groundwater in the North China Plain. To preserve the groundwater and reduce the economic losses, an efficiently and quickly assessment of nitrate leaching risk on regional farmland is crucial. In this research we developed a GIS-based model named 'Arc-NLEAP' based on NLEAP model, combined the statistical and Remote Sensing data, to estimate applied fertilizer rates and crop yields, which are two key variables indicating amount of input and output nitrogen in crop land, since crop greenness derived by MODIS may reflect the content of chlorophyll of canopy which is closely related to nitrogen content, and NDVI values of crop crucial growing periods determine crop production. The simulated results showed that the value for parameter NAL (Nitrate Available for Leaching) was between 8 kg / ha and 474 kg / ha and the average was 117 kg / ha, for NL (amount of Nitrate Leached) 18kg / ha (Low) , 59 kg / ha (Average) and 222 kg / ha(High).Percentages of parameter MRI(Movement Risk Index) accounted for 8%,77% and 15% for low risk, medium risk and high risk respectively. Taking water leaching index, nitrogen available for leaching, amount of Nitrate Leached, ammonia volatilization and denitrification into consideration, we defined the N hazard class to evaluate the nitrogen leaching risk and the result indicated that lager 74% of the study area was labeled as low N hazard class. Despite the spatial patterns for parameters NAL and NL were similar, the values for MRI was determined by site-specific soil type and the capacity of water movement principally, demonstrating that measures of controlling nitrate leaching should be based on the spatial pattern of MRI, along with decreasing the amount of application rate simultaneity.
机译:化肥的过度使用增加了华北平原地下水硝酸盐污染的风险。为了保护地下水并减少经济损失,有效,快速地评估区域农田中硝酸盐浸出风险至关重要。在这项研究中,我们基于NLEAP模型开发了一个基于GIS的名为“ Arc-NLEAP”的模型,结合了统计数据和遥感数据,以估算施肥量和农作物产量,这是指示输入和输出氮量的两个关键变量在农田中,由于MODIS产生的作物绿色可能反映了冠层的叶绿素含量,而该含量与氮含量密切相关,而作物关键生长期的NDVI值决定了作物的产量。模拟结果表明,参数NAL(可浸出硝酸盐)的值介于8 kg / ha和474 kg / ha之间,而NL(浸出硝酸盐的量)18kg / ha(低)的平均值为117 kg / ha。分别为59公斤/公顷(平均)和222公斤/公顷(高)。低风险,中风险和高风险的参数MRI(运动风险指数)分别占8%,77%和15%。考虑到水浸出指数,可浸出的氮,浸出的硝酸盐量,氨气挥发和反硝化作用,我们定义了N危害等级来评估氮浸出风险,结果表明,研究区域中较大的74%被标记为低N危险等级。尽管参数NAL和NL的空间模式相似,但MRI的值主要取决于特定地点的土壤类型和水的流动能力,这表明控制硝酸盐浸出的措施应基于MRI的空间模式,以及同时降低了同时施用量。

著录项

  • 来源
  • 会议地点 Berlin(DE)
  • 作者单位

    Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China;

    rnCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China Graduate University of Chinese Academy of Sciences, Beijing, 10049, China;

    rnCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China;

    rnCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang, 050021, China;

    rnCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Scienc;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境遥感;
  • 关键词

    nitrate; leaching; nleap; model; GIS; remote sensing;

    机译:硝酸盐浸出le模型;地理信息系统遥感;

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