Ruan Shuhe, Zhuang Yanhua, Zhang Liang, Li Sisi, Chen Jingrui, Wen Weijia, Zhai Limei, Liu Hongbin, Du Yun
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.
J Environ Manage. 2022 Jun 15;312:114932. doi: 10.1016/j.jenvman.2022.114932. Epub 2022 Mar 23.
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.
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。