|
|
|
| Research of the WRTDS model on long-term changes in water quality: progress and perspectives |
| CHEN Hai-tao1, WANG Cheng-cheng1, SONG Meng-lai1, DING Han1, REN Qiu-ru1, REN Jia-xue2, WANG Yu-qiu1 |
1. College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China;
2. Research Institute for Environment Innovation (Tianjin Binhai), Tianjin 300452, China |
|
|
|
|
Abstract Evaluating changes and trends in surface water quality and obtaining accurate information on water quality or nutrient loading from upstream to downstream in a watershed is crucial to the effective management of water resources. Recently, along with the increase in the length of water quality datasets, the upgrading of statistical methods, and the improvement of computer software and hardware, a series of statistical methods have been used to explore and analyze water quality trends and flux changes. Weighted Regressions on Time, Discharge, and Season (WRTDS) have evolved into the primary model for long-term continuous water quality trend analysis due to the relative complexity and flexibility. This article reviewed the research progress of WRTDS model in water quality analysis, summarized the basic principles (concentration/flux and normalized flux concentration/flux estimation) and development of the model, sorted out the current methods and applications on water quality trends and flux estimation, and outlined the application of the model to long-term water quality changes and trends and comparison with other models. Lastly, we analyzed some shortcomings of the WRTDS model, and combined with the actual water environment problems in China, we foresee that the WRTDS model can be extended and combined with watershed models, remote sensing inversion, artificial intelligence and other technical means to better guide watershed water environment management in the future.
|
|
Received: 29 March 2023
|
|
|
|
|
|
[1] Zhang Q, Hirsch R M. River water‐quality concentration and flux estimation can be improved by accounting for serial correlation through an autoregressive model [J].Water Resources Research, 2019, 55:9705–9723.
[2] 孟伟.中国流域水环境污染综合防治战略[J].中国环境科学, 2007,27(5):712-716. Meng W. The strategy of comprehensive pollution prevention and cure of water environment in Chinese watershed [J].China Environmental Science, 2007,27(5):712-716.
[3] Galloway J N, Townsend A R, Erisman J W, et al. Transformation of the nitrogen cycle: recent trends, questions, and potential solutions [J].Science, 2008,320(5878):889–892.
[4] Ma T, Zhao N, Ni Y, et al. China’s improving inland surface water quality since 2003[J].Science Advances, 2020,6(1):eaau3798.
[5] Zhang W S, Swaney D P, Hong B, et al. Anthropogenic phosphorus inputs to a river basin and their impacts on phosphorus fluxes along its upstream-downstream continuum [J].Journal of Geophysical Research, 2017,122:3273–3287.
[6] Keller A A, Cavallaro L. Assessing the US Clean Water Act 303(d) listing process for determining impairment of a waterbody [J].Journal of Environmental Management, 2008,86(4),2008:699-711.
[7] Velthof G L, Lesschen J P, Webb J, et al. The impact of the Nitrates Directive on nitrogen emissions from agriculture in the EU-27 during 2000~2008[J].Science of the Total Environment, 2014,468-469: 1225-1233.
[8] 徐敏,张涛,王东,等.中国水污染防治40年回顾与展望[J].中国环境管理, 2019,11(3):65-71. Xu M, Wang T, Wang D, et al. Review and prospect of water pollution prevention and control of China in the forty years of reform and opening-up [J].Chinese Journal of Environmental Management, 2019, 11(3):65-71.
[9] Craig L S, Palmer M A, Richardson D C, et al. Stream restoration strategies for reducing river nitrogen loads [J].Frontiers in Ecology & the Environment, 2008,6(10):529-538.
[10] 国务院印发《水污染防治行动计划》推出238项治理措施,用15年时间,力争全国水环境质量总体改善[J].中国环境科学, 2015, 35(5):1534.
[11] Meals D W, Dressing S A, Davenport T E. Lag time in water quality response to best management practices: A review [J].Journal of Environmental Quality, 2010,39:85-96.
[12] Sarrazin F J, Kumar R, Basu N B, et al. Characterizing catchment-scale nitrogen legacies and constraining their uncertainties [J].Water Resources Research, 2022,58:e2021WR031587.
[13] Wu J, Lu J. Spatial scale effects of landscape metrics on stream water quality and their seasonal changes [J].Water Research, 2021,191: 116811.
[14] Hirsch R M, Moyer D L, Archfield S A. Weighted regressions on time, discharge, and season (WRTDS), with an application to Chesapeake Bay river inputs [J].Journal of the American Water Resources Association, 2010,46(5):857-880.
[15] Kendall M G. Rank correlation methods [M].London: Oxford University Press, 1975.
[16] Sen, K P. Estimates of the regression coefficient based on Kendall's Tau [J].Publications of the American Statistical Association, 1968, 63(324):1379-1389.
[17] Hirsch R M, Slack J R, Smith R A. Techniques of trend analysis for monthly water quality data [J].Water Resources Research, 1982,18(1): 107–121.
[18] Morton R, Henderson B L. Estimation of nonlinear trends in water quality: An improved approach using generalized additive models [J].Water Resources Research, 2008,44(7):308-318.
[19] Runkel R L, Crawford C G, Cohn T A. Load estimator (LOADEST): A FORTRAN program for estimating constituent loads in streams and rivers [J].Center for Integrated Data Analytics Wisconsin Science Center, 2004:4-A5.
[20] Schwarz G E, Hoos A B, Alexander R B, et al. The SPARROW Surface Water-Quality Model: Theory, application and user documentation [R].Vir-ginia: U S Geological Survey, 2006.
[21] Moyer D L, Hirsch R M, Hyer K E. Comparison of two regression-based approaches for determining nutrient and sediment fluxes and trends in the Chesapeake Bay watershed [R].Reston: U S Geological Survey, 2012.
[22] Chanat J G, Yang G. Exploring drivers of regional water-quality change using differential spatially referenced regression—A pilot study in the Chesapeake Bay Watershed [J].Water Resources Research, 2018,54(10):8120–8145.
[23] Wu K B, Hu M P, Zhang Y F, et al. Long-term riverine nitrogen dynamics reveal the efficacy of water pollution control strategies [J].Journal of Hydrology, 2022,607:127582.
[24] Mize S V, Murphy J C, Diehl T H, et al. Suspended-sediment concentrations and loads in the lower Mississippi and Atchafalaya rivers decreased by half between 1980 and 2015[J].Journal of Hydrology, 2018,564:1-11.
[25] Domagalski J L, Morway E, Alvarez N L, et al. Trends in nitrogen, phosphorus, and sediment concentrations and loads in streams draining to Lake Tahoe, California, Nevada, USA [J].Science of the Total Environment, 2021,752:141815.
[26] Chanat J G, Moyer D L, Blomquist J D, et al. Application of a weighted regression model for reporting nutrient and sediment concentrations, fluxes, and trends in concentration and flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, results through water year 2012[R].Reston: U S Geological Survey, 2016.
[27] Tukey J W. Exploratory data analysis [M].New York: Addition-Wesley Publishing Company, 1977.
[28] Hirsch R M, De Cicco L A. User guide to Exploration and Graphics for RivEr Trends (EGRET) and data Retrieval—R packages for hydrologic data (version 2.0, February 2015) [R]: Reston: U S Geological Survey, 2015.
[29] Hirsch R M. Large biases in regression-based constituent flux estimates: causes and diagnostic tools [J].Journal of the American Water Resources Association, 2014,50(6):1401–1424.
[30] Hirsch R M, Archfield S A, De Cicco L A. A bootstrap method for estimating uncertainty of water quality trends [J].Environmental Modelling & Software, 2015,73:148–166.
[31] Lee C J, Hirsch R M, Schwarz G E, et al. An evaluation of methods for estimating decadal stream loads [J].Journal of Hydrology, 2016,542: 185-203.
[32] Verma S, Markus M, Cooke R A. Development of error correction techniques for nitrate-N load estimation methods [J].Journal of Hydrology, 2012,s432–433:12–25.
[33] Zhang Q, Webber J S, Moyer D L, et al. An approach for decomposing river water-quality trends into different flow classes [J].Science of The Total Environment, 2021,755:143562.
[34] 康若熙,谢文理,赵文星,等.从水质变化趋势看常州市武南区域重点河流治理成效[J].中国环境科学, 2019,39(10):4186-4193. Kang R X, Xie W L, Zhao W X et al. Spatiotemporal trends in water quality and the effectiveness of water treatment projects for Wunan District, Changzhou [J].China Environmental Science, 2019,39(10): 4186-4193.
[35] 蒋爱萍,张丽萍,张迪,等.鄱阳湖出流长序列代表性水质指标变化及其驱动力[J].人民长江, 2021,52(12):65-71. Jiang A P, Zhang L P, Zhang D, et al. Changes of representative water quality indicators and their driving forces in long sequence of outflow in Poyang Lake [J].Yangtze River, 2021,52(12):65-71.
[36] 严广寒,殷雪妍,汪星,等.基于GAM模型的洞庭湖叶绿素a浓度与环境因子相关性分析[J].中国环境科学, 2022,42(1):313-322. Yan G H, Yin X Y, Wang X, et al. Analysis based on GAM model for the relationship between chlorophyll a concentration and environmental factors in Dongting Lake [J].China Environmental Science, 2022,42(1):313-322.
[37] Cochran W G. Sampling techniques [M].New York: US Wiley Publishing Company, 1977.
[38] Cohn T A, Caulder D L, Gilroy E J, et al. The validity of a simple statistical model for estimating fluvial constituent loads: An Empirical study involving nutrient loads entering Chesapeake Bay [J].Water Resources Research, 1992,28(9):2353-2363.
[39] Cohn T A. Estimating contaminant loads in rivers: An application of adjusted maximum likelihood to type 1censored data [J].Water Resources Research, 2005,41(7):361-367.
[40] Stenback G A, Crumpton W G, Schilling K E, et al. Rating curve estimation of nutrient loads in Iowa rivers [J].Journal of Hydrology, 2011,396(1/2):158-169.
[41] Richards R P, Alameddine I, Allan J D, et al. Discussion 'nutrient inputs to the laurentian great lakes by source and watershed estimated using sparrow watershed models' by dale m. robertson and david A. saad [J].Journal of the American Water Resources Association, 2013, 49(3):715–724.
[42] 张柏发,陈丁江.1980~2010年浙江某典型河流硝态氮通量对净人类活动氮输入的动态响应[J].环境科学, 2014,35(8):2911-2919. Zhang B F, Chen D J. Dynamic response of riverine nitrate flux to net anthropogenic nitrogen inputs in a typical river in Zhejiang Province over the 1980~2010 period [J].Environmental Science, 2014,35(8): 2911-2919.
[43] 金亚楠,张柏发,郝韵,等.基于LOADEST模型和小波变换的河流氮磷污染动态分析[J].浙江农业学报, 2020,32(9):1692-1701. Jin Y N, Zhang B F, Hao Y, et al. Dynamic analysis of river nitrogen and phosphorus pollution based on LOADEST model and wavelet transform [J].Acta Agriculturae Zhejiangensis, 2020,32(9):1692-1701.
[44] 李娜,盛虎,何成杰,等.基于统计模型LOADEST的宝象河污染物通量估算[J].应用基础与工程科学学报, 2012,20(3):355-366. Li N, Sheng H, He C J, et al. Pollutant fluxes estimation for Baoxiang River, Dianchi Lake by using LOADEST Model [J].Journal of Basic Science and Engineering, 2012,20(3):355-366.
[45] Parr T B, Inamdar S P, Miller M J. Overlapping anthropogenic effects on hydrologic and seasonal trends in DOC in a surface water dependent water utility [J].Water Research, 2019,148:407-415.
[46] Robertson D M, David A S, Greg F K. An extrapolation method for estimating loads from unmonitored areas using watershed model load ratios [J].Journal of Great Lakes Research, 2022,48:1550-62.
[47] Rumsey C A, Hammond J C, Jennifer Mu, et al. Spatial patterns and seasonal timing of increasing riverine specific conductance from 1998 to 2018 suggest legacy contamination in the Delaware River Basin [J].Science of the Total Environment, 2023,858:159691.
[48] Yates A G, Robert B B, Arthur F, et al. Nutrient and suspended solid concentrations, loads, and yields in rivers across the Lake Winnipeg Basin: A twenty year trend assessment [J].Journal of Hydrology: Regional Studies, 2022,44:101249.
[49] Choquette A F, Hirsch R M, Murphy J C, et al. Tracking changes in nutrient delivery to western Lake Erie: Approaches to compensate for variability and trends in streamflow [J].Journal of Great Lakes Research, 2019,45(1):21-39.
[50] Beck M W, Hagy J D I. Adaptation of a weighted regression approach to evaluate water quality trends in an estuary [J].Environmental Modeling & Assessment, 2015,20:637–655.
[51] Beck M W, Murphy R R. Numerical and qualitative contrasts of two statistical models for water quality change in tidal waters [J].Journal of the American Water Resources Association, 2017,53:197-219.
[52] Rumsey C A, Hammond J C, Murphy J, et al. Spatial patterns and seasonal timing of increasing riverine specific conductance from 1998 to 2018 suggest legacy contamination in the Delaware River Basin [J].Science of the Total Environment, 2023,858:159691.
[53] 何卓识,霍守亮,马春子,等.气候变化对小流域氮、磷通量的影响:以延安市河流流域为例[J].环境工程技术学报, 2020,10(6):964-970. He Z S, Huo S L, Ma C Z, et al. Impact of climate change on the variation of nitrogen and phosphorus fluxes at watershed scale: a case study in watersheds of Yan’an City [J].Journal of Environmental Engineering Technology, 2020,10(6):964-970.
[54] Sprague L A, Hirsch R M, Aulenbach B T. Nitrate in the Mississippi River and its tributaries, 1980 to 2008: Are we making progress? [J].Environmental Science & Technology, 2011,45:7209-7216.
[55] Rowland F E, Craig A S, Laura T J. Lake Erie tributary nutrient trend evaluation: Normalizing concentrations and loads to reduce flow variability [J].Ecological Indicators, 2021,125:107601.
[56] Zhang Q. Synthesis of nutrient and sediment export patterns in the Chesapeake Bay watershed: Complex and non-stationary concentration-discharge relationships [J].Science of the Total Environment, 2018,618:1268-1283.
[57] Goswami A, Pranesh K P, Ramesh R, et al. Evaluation of statistical models: Perspective of water quality load estimation [J].Journal of Hydrology, 2023,616:128721.
[58] Beck M W, Jabusch T W, et al. Four decades of water quality change in the upper San Francisco Estuary [J].Estuarine, Coastal and Shelf Science, 2018,212:11-22.
[59] Chanat J G, Moyer D L, Blomquist J D, et al. Application of a weighted regression model for reporting nutrient and sediment concentrations, fluxes, and trends in concentration and flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, results through water year 2012[R].U S Geological Survey Scientific Investigations Report, 2016,2015–5133.
[60] 陈海涛,王晓燕,南哲,等.输入数据精度与准确性对SWAT模型模拟的影响[J].中国环境科学, 2021,41(5):2151:2160. Chen H T, Wang X Y, Nan Z, et al. The influence of input data precision and accuracy on SWAT model simulation [J].China Environmental Science, 2021,41(5):2151:2160. |
|
|
|
