The rainstorm influence on ecological restoration: A novel response ecological model for an urban shallow lake

IF 1.7 4区 环境科学与生态学 Q4 ENVIRONMENTAL SCIENCES
Zhiqiang Yan, Luming Wu, Fenghui Lu, Jingwen Huang, Qingwu Long
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引用次数: 0

Abstract

Environmental processes in cities and suburbs are significantly impacted by climate change. The development of reliable ecological models may successfully direct agricultural activities. Numerous models have been put forth as of late; however, because to the complexity of environmental microorganisms, their use in complex systems is still restricted. For a better understanding of the ecological restoration of an urban lake system that had been disturbed by rainfall, an improved ecological dynamic model that took into account inundation plants, phytoplankton and microorganisms was proposed based on the field survey. Observed data from a shallow urban lake with a surface area of approximately 66 600 m2 in the heart of Shunde district, Foshan, in South China, was used to validate the model. In this model, five hypotheses—phytoplankton, microorganisms, NH3-N, COD and TP in water—were selected as experimental variables. To assess the model's correctness and dependability, the correlation coefficients (R) and root mean square error-observations standard deviation ratio (RSR) were computed. The results from the establish model (0.446 < R < 0.985, RSR < 0.7) are very similar to those of actual observations. In addition, four microbe species (Aquabacium, Bradyrhizobium japonicum, Curvibacter and Cyanobacteria) multiplied when pollutant concentration dropped. Our model provides a useful tool for managing urban shallow water lakes by properly simulating the dynamic changes of aquatic species and microbes in urban shallow water lakes.
暴雨对生态恢复的影响:城市浅湖的新型响应生态模型
城市和郊区的环境过程受到气候变化的严重影响。开发可靠的生态模型可以成功地指导农业活动。近来已提出了许多模型,但由于环境微生物的复杂性,这些模型在复杂系统中的应用仍然受到限制。为了更好地了解受降雨干扰的城市湖泊系统的生态恢复情况,在实地调查的基础上,提出了一种考虑到淹没植物、浮游植物和微生物的改进型生态动态模型。该模型采用了华南佛山市顺德区中心一个面积约为 66 600 平方米的城市浅水湖泊的观测数据进行验证。在该模型中,选择了浮游植物、微生物、NH3-N、水中 COD 和 TP 这五个假设作为实验变量。为了评估模型的正确性和可靠性,计算了相关系数(R)和均方根误差-观测值标准偏差比(RSR)。所建立模型的结果(0.446 < R < 0.985, RSR < 0.7)与实际观测结果非常相似。此外,当污染物浓度下降时,四种微生物(水杆菌、日本农杆菌、卷曲杆菌和蓝藻)会大量繁殖。我们的模型通过正确模拟城市浅水湖泊中水生物种和微生物的动态变化,为管理城市浅水湖泊提供了有用的工具。
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来源期刊
Water and Environment Journal
Water and Environment Journal 环境科学-湖沼学
CiteScore
4.80
自引率
0.00%
发文量
67
审稿时长
18-36 weeks
期刊介绍: Water and Environment Journal is an internationally recognised peer reviewed Journal for the dissemination of innovations and solutions focussed on enhancing water management best practice. Water and Environment Journal is available to over 12,000 institutions with a further 7,000 copies physically distributed to the Chartered Institution of Water and Environmental Management (CIWEM) membership, comprised of environment sector professionals based across the value chain (utilities, consultancy, technology suppliers, regulators, government and NGOs). As such, the journal provides a conduit between academics and practitioners. We therefore particularly encourage contributions focussed at the interface between academia and industry, which deliver industrially impactful applied research underpinned by scientific evidence. We are keen to attract papers on a broad range of subjects including: -Water and wastewater treatment for agricultural, municipal and industrial applications -Sludge treatment including processing, storage and management -Water recycling -Urban and stormwater management -Integrated water management strategies -Water infrastructure and distribution -Climate change mitigation including management of impacts on agriculture, urban areas and infrastructure
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