太湖水体Chl-a预测模型ARIMA在引排水方案优化中的应用

李勇; 冯家成; 李娜; 单雅洁; 钱佳宁; 徐鸿

doi:10.13205/j.hjgc.202210010

太湖水体Chl-a预测模型ARIMA在引排水方案优化中的应用

doi: 10.13205/j.hjgc.202210010

李勇^1,2,3,
冯家成^2, ,,
李娜^1,2,
单雅洁²,
钱佳宁²,
徐鸿²

1. 河海大学浅水湖泊综合治理与资源开发教育部重点实验室, 南京 210098;
2. 河海大学环境学院, 南京 210098;
3. 河海大学水资源高效利用与工程安全国家工程研究中心, 南京 210098

基金项目:

国家重点研发计划项目(2018YFC0407906)

国家自然科学基金项目(51879081,51579074)

详细信息

作者简介:
李勇(1974-),男,教授,主要从事河湖水环境综合治理等方面的教学和研究工作。liyonghh@163.com

通讯作者:
冯家成(1997-),男,硕士研究生,主要研究方向为河湖水环境模型。student_fengran@163.com

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出版历程
- 收稿日期: 2021-09-14

APPLICATION OF CHL-A PREDICTION MODEL ARIMA IN OPTIMIZATION OF WATER DIVERSION AND DRAINAGE SCHEME IN LAKE TAIHU

LI Yong^1,2,3,
FENG Jiacheng^{2
, ,},
LI Na^1,2,
SHAN Yajie²,
QIAN Jianing²,
XU Hong²

1. Key Laboratory of Shallow Lake Comprehensive Control and Resource Development, Ministry of Education, Hohai University, Nanjing 210098, China;
2. School of Environment, Hohai University, Nanjing 210098, China;
3. National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China

摘要

摘要: 我国东部大型浅水湖泊太湖的富营养化和藻华暴发一直是困扰该地区社会经济高质量发展的重要水问题之一,其中水资源分配不均及部分营养盐浓度较高,严重制约了太湖水体生态环境的健康发展。基于1999-2019年太湖水质、气象等逐月观测资料,构建了基于协变量(TN、TP、COD_Mn、降水量和引排水量)的叶绿素a(Chl-a)预测模型ARIMA(1, 1, 1)(0, 1, 1)₁₂,并结合2007-2019年历史引排水方案经验和效果,提出了未来平水年情景下降低太湖藻华大面积暴发风险的引排水方案优化策略。结果表明:所构建的ARIMA(1, 1, 1)(0, 1, 1)₁₂模型能有效预测太湖水体Chl-a浓度;且在预设未来情景下,通过同步增加引、排水量可有效降低水体营养盐含量。引排水方案的优化关键在于季节性水资源的合理调配,在满足水安全的基础上适当加大冬春季节引排水,可达到改善水动力和排出营养盐的效果。
- ARIMA模型 /
- 引排水方案 /
- 优化 /
- 叶绿素a /
- 营养盐 /
- 太湖
Abstract: The eutrophication and algal blooms of Lake Taihu, a large shallow lake in eastern China, have always been one of the important water problems that troubled the high-quality development of this region. The uneven distribution of water resources and relatively high concentration of some nutrients have seriously restricted the healthy development of the ecological environment of Lake Taihu. Based on the monthly observation data of water quality and meteorology of Lake Taihu from 1999 to 2019, a Chl-a prediction model ARIMA(1, 1, 1)(0, 1, 1)₁₂ based on covariates (total nitrogen, total phosphorus, permanganate index, precipitation, water diversion and drainage volume) was established in this paper. An optimization strategy of water diversion and drainage schemes was proposed to decline the risk of algal blooms outbreak in Lake Taihu under the future normal year scenario. Results showed that the ARIMA(1, 1, 1)(0, 1, 1)₁₂ model could effectively predict the monthly Chl-a concen trations of Lake Taihu. In the preset future scenario, the nutrient content of water can be effectively reduced by synchronously increasing both water diversion and drainage. The key to the optimization of water diversion and drainage scheme is rational allocation of seasonal water resources, and based on meeting water safety, adeptly enhancing both diversion and drainage in winter and spring could improve the water dynamic and nutritional salt discharge.
- ARIMA model /
- water diversion and drainage scheme /
- optimization /
- chlorophyll a /
- nutrient /
- Lake Taihu

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