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中国稻田地表水氮动态的改进估算

Improved estimation of nitrogen dynamics in paddy surface water in China.

作者信息

Ruan Shuhe, Zhuang Yanhua, Zhang Liang, Li Sisi, Chen Jingrui, Wen Weijia, Zhai Limei, Liu Hongbin, Du Yun

机构信息

Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430077, People's Republic of China; University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.

Hubei Provincial Engineering Research Center of Non-Point Source Pollution Control, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430077, People's Republic of China; University of Chinese Academy of Sciences, Beijing, 100049, People's Republic of China.

出版信息

J Environ Manage. 2022 Jun 15;312:114932. doi: 10.1016/j.jenvman.2022.114932. Epub 2022 Mar 23.

Abstract

Paddy surface water is the direct source of artificial drainage and surface runoff leading to N loss from rice paddy fields. Quantifying the N dynamics in paddy surface water on a large scale is challenging because of model deficiencies and the limitations of field measurements. This study analyzed the N dynamics and the influencing factors in paddy surface water in the three main Chinese rice-growing regions: Northeast Plain, Yangtze River Basin, and Southeast Coast. An improved first-order kinetic model was proposed to evaluate the total nitrogen (TN) dynamics at a countrywide scale by improving the calculation method of the initial TN concentration (C) and providing the optimum value of attenuation coefficient (k). The results show that: (1) the average reduction rate of TN concentration on the 7th day after fertilization increased with the growth period (85%, 90%, and 95% during the basal, tillering, and panicle fertilization periods, respectively); (2) the attenuation coefficient k for the growth periods was ranked as follows: panicle fertilization period > tillering fertilization period > basal fertilization period. The Yangtze River Basin had the highest average k value (0.31-0.34), followed by the Southeast Coast (0.24-0.41) and Northeast Plain (0.22-0.30); and (3) the improved first-order kinetic model performed well in the N dynamics estimation (R > 0.6). High TN concentration with high fertilizer application amounts and precipitation caused the Yangtze River Basin to have a high N runoff loss risk. The proposed universal model realizes the simulation of N dynamics from a single site to multi-sites while greatly saving multi-site monitoring costs. This study provides a basis for effectively optimizing N management and preventing N loss in rice paddies.

摘要

稻田地表水是导致稻田氮素流失的人工排水和地表径流的直接来源。由于模型缺陷和田间测量的局限性,大规模量化稻田地表水中的氮动态具有挑战性。本研究分析了中国三个主要水稻种植区(东北平原、长江流域和东南沿海)稻田地表水中的氮动态及其影响因素。通过改进初始总氮浓度(C)的计算方法并提供衰减系数(k)的最佳值,提出了一种改进的一级动力学模型,以评估全国范围内的总氮(TN)动态。结果表明:(1)施肥后第7天TN浓度的平均降低率随生育期增加(基肥期、分蘖期和穗肥期分别为85%、90%和95%);(2)各生育期的衰减系数k排序如下:穗肥期>分蘖期>基肥期。长江流域的平均k值最高(0.31 - 0.34),其次是东南沿海(0.24 - 0.41)和东北平原(0.22 - 0.30);(3)改进的一级动力学模型在氮动态估算中表现良好(R>0.6)。高施肥量和高降水量导致的高TN浓度使长江流域具有较高的氮径流流失风险。所提出的通用模型实现了从单站点到多站点的氮动态模拟,同时大大节省了多站点监测成本。本研究为有效优化稻田氮素管理和防止稻田氮素流失提供了依据。

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