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基于DRAINMOD的农田地表径流氮素流失动态模拟 被引量:12

Dynamic simulation of nitrogen losses in surface runoff from farmlands using the DRAINMOD model
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摘要 为了解水旱农田地表径流氮素流失机理及过程,于2008年6~9月在湖北省漳河灌区开展了田间试验,并利用DRAINMOD模型对其进行模拟。研究结果表明:水田地表径流铵态氮和硝态氮的流失率均高于旱地,水田地表径流以铵态氮为主,而旱地以硝态氮为主。水旱农田地表径流氮素流失模拟值与实测值都非常接近,水田地表径流硝态氮和铵态氮模拟的相对误差分别为8.35%和10.99%,旱地分别为5.45%和14.11%;水田硝态氮和铵态氮模拟的效率系数分别为0.961和0.974,旱地的分别为0.993和0.938,效果都很好。因此,利用DRAINMOD模型进行该地区农田氮素流失动态模拟是可行而有效的。 In order to understand the mechanism and process of nitrogen losses from paddy field and upland field,field experiment was conducted in the Zhanghe Irrigation District,Hubei Province of China.The experiment was from June to September 2008,and a dynamic simulation of nitrogen losses in surface runoff from farmlands was carried out using the DRAINMOD model.Results show that both ammonium-nitrogen loss and nitrate-nitrogen loss in surface runoff from the paddy field are higher than those from the upland field.While the loss of ammonium-nitrogen from the paddy field will be higher than that of nitrate-nitrogen,and the opposite is true for the corn field(upland field).The simulated accumulations of nitrogen losses in surface runoff from both farmlands are in good agreement with the observations as revealed by low relative errors and high model efficiency coefficients.Over the paddy filed,the relative errors are respectively 8.35% and 10.99% for nitrate-nitrogen and ammonium-nitrogen;and the corresponding model efficiency coefficients are 0.961 and 0.974,respectively.These values are 5.45% and 14.11% for relative errors and 0.993 and 0.938 for model efficiency coefficients,respectively in the corn field.The study demonstrates that the DRAINMOD model is feasible and effective in the dynamic simulation of nitrogen losses in surface runoff from farmlands in this district.
作者 洪林 罗文兵
出处 《水科学进展》 EI CAS CSCD 北大核心 2011年第5期703-709,共7页 Advances in Water Science
基金 国家自然科学基金资助项目(50639040 50979073)~~
关键词 水污染 地表径流 氮素 流失 动态模拟 DRAINMOD模型 water pollution surface runoff nitrogen losses dynamic simulation DRAINMOD model
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