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

计量
- 文章访问数: 158
- HTML全文浏览量: 30
- PDF下载量: 1
- 被引次数: 0
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

HTML全文

参考文献(35)

[1]	LIN S S, SHEN S L, ZHOU A N, et al.Approach based on TOPSIS and Monte Carlo simulation methods to evaluate lake eutrophication levels[J].Water Research, 2020, 187:116437.
[2]	秦伯强.浅水湖泊湖沼学与太湖富营养化控制研究[J].湖泊科学, 2020, 32(5):1229-1243.
[3]	王栋, 梁忠民, 常文娟, 等.基于模糊集对分析的引江济太调水效益综合评价[J].水资源保护, 2017, 33(1):35-40.
[4]	刘永, 蒋青松, 梁中耀, 等.湖泊富营养化响应与流域优化调控决策的模型研究进展[J].湖泊科学, 2021, 33(1):49-63.
[5]	孙菲, 袁鹏, 程建光, 等.宜兴市殷村港叶绿素a与影响因子的多元分析[J].环境工程, 2017, 35(9):53-57.
[6]	CHEN Y Y, SONG L H, LIU Y Q, et al.A review of the artificial neural network models for water quality prediction[J].Applied Sciences, 2020, 10(17):5776-5776.
[7]	金竹静, 李金花, 张春敏, 等.基于时间序列法的滇池流域新宝象河污染风险预测[J].安全与环境学报, 2018, 18(4):1580-1585.
[8]	PENG J Y, ZHENG B H, CHU Z S, et al.Attaining sustainable water resource utilization in lake basins using progressive operational scenario analysis[J].Water Resources Management, 2020, 34(3):887-904.
[9]	QIAO Y, LEI X H, LONG Y, et al.Fast and optimal decision for emergency control of sudden water pollution accidents in long-distance water diversion projects[J].Water Supply, 2020, 20(4):1356-1367.
[10]	潘建波, 张挺, 石圣.基于AHP方法的湖泊群引水方案综合评价方法[J].福州大学学报(自然科学版), 2015, 43(1):111-117.
[11]	AYOB K, SHAMSUDDIN S, Morteza M.Modeling water quality and hydrological variables using ARIMA:a case study of Johor River, Malaysia[J].Sustainable Water Resources Management, 2018, 4(4):991-998.
[12]	LI L, ZHAO X L, LIU D, et al.Occurrence and ecological risk assessment of PPCPs in typical inflow rivers of Taihu Lake, China[J].Journal of Environmental Management, 2021, 285:112176.
[13]	胥瑞晨, 逄勇, 胡祉冰, 等."引江济太"工程对太湖水体交换的影响研究[J].中国环境科学, 2020, 40(1):375-382.
[14]	吴浩云, 林荷娟.引江济太调水试验[M].北京:中国水利水电出版社, 2010.
[15]	吴浩云, 孙海涛.太湖流域洪水与水量调度方案的制定和认识[J].中国防汛抗旱, 2012, 22(2):5-7.
[16]	水利部太湖流域管理局,江苏省水利厅,浙江省水利厅,上海市水务局.太湖健康状况报告[R].上海:2007-2019(2021-03-20 ).www.tba.gov.cn/slbthlyglj/sj/sj.html.
[17]	水利部太湖流域管理局.太湖流域及东南诸河水资源公报[R].上海:2003-2019(2021年-03-20 ). www.tba.gov.cn/slbthlyglj/sj/sj.html.
[18]	水利部太湖流域管理局.太湖流域引江济太年报[R].上海:2007-2019(2021-03-20 ).www.tba.gov.cn/slbthlyglj/sj/sj.html.
[19]	太湖流域水资源保护局. 太湖流域及东南诸河省界水体水资源质量状况通报[R].上海:1999-2019(2021-03-20 ).www.tba.gov.cn/slbthlyglj/sj/sj.html.
[20]	王燕.时间序列分析:基于R[M].北京:中国人民大学出版社, 2015.
[21]	HYNDMAN R J, ATHANASOPOULOS G.Forecasting:principles and practice[M].London:Bowker-Saur.Pharo, 2014.
[22]	NATHALIE H, JULIO C, FREDY M, et al.ARIMA as a forecasting tool for water quality time series measured with UV-Vis spectrometers in a constructed wetland[J].Tecnología y ciencias del agua, 2017, 8(5):127-139.
[23]	MOHAMMAD H S, EFAT S J.Forecasting models for flow and total dissolved solids in Karoun river-Iran[J].Journal of Hydrology, 2016, 535:148-159.
[24]	TIAO G C.Time series:ARIMA methods[M].Chicago:University of Chicago IL, USA, 2001:363-407.
[25]	李娜, 李勇, 冯家成, 等.太湖水体Chl-a预测模型ARIMA的构建及应用优化[J].环境科学, 2021, 42(5):2223-2231.
[26]	CHEN Q W, GUAN T S, YUN L, et al.Online forecasting chlorophyll a concentrations by an auto-regressive integrated moving average model:feasibilities and potentials[J].Harmful Algae, 2015, 43:58-65.
[27]	ZHUKOVA T V, RADCHIKOVA N P, MIKHEYEVA T M, et al.Long-term dynamics of suspended matter in Naroch lakes:trend or intervention[J].Inland Water Biology,2017, 10(3):250-257.
[28]	朱伟, 薛宗璞, 章元明,等."引江济太"对2016年后太湖总磷反弹的直接影响分析[J].湖泊科学, 2020, 32(5):1432-1445.
[29]	陈俪丹, 高成, 陈妍清, 等.考虑水质及水动力条件的滨江圩区最优活水方案[J].水电能源科学, 2021, 39(3):16-19 ,57.
[30]	YOU A J, HUA L.Optimization and effect of inner water diversion and distribution in the west lake of Hangzhou[J].IOP Conference Series:Earth and Environmental Science, 2019, 264(1):63-71.
[31]	朱广伟, 许海, 朱梦圆, 等.三十年来长江中下游湖泊富营养化状况变迁及其影响因素[J].湖泊科学, 2019, 31(6):1510-1524.
[32]	朱广伟, 秦伯强, 张运林, 等.2005-2017年北部太湖水体叶绿素a和营养盐变化及影响因素[J].湖泊科学, 2018, 30(2):279-295.
[33]	HUANG C C, LI Y M, YANG H, et al.Detection of algal bloom and factors influencing its formation in Taihu Lake from 2000 to 2011 by MODIS[J].Environmental Earth Sciences, 2014, 71(8):3705-3714.
[34]	HU W P, ZHAI S J, ZHU Z C, et al.Impacts of the Yangtze River water transfer on the restoration of Lake Taihu[J].Ecological Engineering, 2008, 34(1):30-49.
[35]	郝文彬, 唐春燕, 滑磊, 等.引江济太调水工程对太湖水动力的调控效果[J].河海大学学报(自然科学版), 2012, 40(2):129-133.