Assessment for water quality by artificial neural network in Daya Bay, South China Sea
Tóm tắt
In this study, artificial neural network such as a self-organizing map (SOM) was used to assess for the effects caused by climate change and human activities on the water quality in Daya Bay, South China Sea. SOM has identified the anthropogenic effects and seasonal characters of water quality. SOM grouped the four seasons as four groups (winter, spring, summer and autumn). The Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on the water quality in Daya Bay. Spatial pattern is mainly related to anthropogenic activities and hydrodynamics conditions. In spatial characteristics, the water quality in Daya Bay was divided into two groups by chemometrics. The monitoring stations (S3, S8, S10 and S11) were in these area (Dapeng Ao, Aotou Harbor) and northeast parts of Daya Bay, which are areas of human activity. The thermal pollution has been observed near water body in Daya Bay Nuclear Power Plant (S5). The rest of the monitoring sites were in the south, central and eastern parts of Daya Bay, which are areas that experience water exchanges from South China Sea. The results of this study may provide information on the spatial and temporal patterns in Daya Bay. Further research will be carry out more research concerning functional changes in the bay ecology with respect to changes in climatic factor, human activities and bay morphology in Daya Bay.
Tài liệu tham khảo
Astel A, Tsakovski S, Simeonov V, Reisenhofer E, Piselli S, Barbieri P (2008) Multivariate classification and modeling in surface water pollution estimation. Anal Bioanal Chem 390(5):1283–1292
Brodnjak-Voncina D, Dobcnik D, Novic M, Zupan J (2002) Chemometrics characterisation of the quality of river water. Anal Chim Acta 462(1):87–100
Cereghino R, Park YS (2009) Review of the Self-organizing map (SOM) approach in water resources: commentary. Environ Model Softw 24(8):945–947
Chau KW, Muttil N (2007) Data mining and multivariate statistical analysis for ecological system in coastal waters. J Hydroinformatics 9(4):305–317
Chen QW, Mynett AE (2006) Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches. Ecol Model 199(1):73–81
Chen CC, Shiah FK, Chung SW, Liu KK (2006) Winter phytoplankton blooms in the shallow mixed layer of the South China Sea enhanced by upwelling. J Mar Syst 59(1–2):97–110
Cinar O, Merdun H (2009) Application of an unsupervised artificial neural network technique to multivariant surface water quality data. Ecol Res 24(1):163–173
Dong JD, Zhang YY, Zhang S, Wang YS, Yang ZH, Wu ML (2010) Identification of temporal and spatial variations of water quality in Sanya Bay, China by three-way principal component analysis. Environ Earth Sci 60(8):1673–1682
Han WY (1998) Marine chemistry in South China Sea. Science Publishing House, Beijing
Icaga Y (2007) Fuzzy evaluation of water quality classification. Ecol Ind 7(3):710–718
Keser M, Swenarton JT, Vozarik JM, Foertch JF (2003) Decline in eelgrass (Zostera marina L.) in Long Island Sound near Millstone Point, Connecticut (USA) unrelated to thermal input. J Sea Res 49(1):11–26
Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43(1):59–69
Kohonen T (2001) Self-organizing maps. Springer, Berlin
Kont A, Jaagus J, Aunap R (2003) Climate change scenarios and the effect of sea-level rise for Estonia. Global Planet Change 36(1–2):1–15
Kotti ME, Vlessidis AG, Thanasoulias NC, Evmiridis NP (2005) Assessment of river water quality in Northwestern Greece. Water Resour Manag 19(1):77–94
Kuppusamy MR, Giridhar VV (2006) Factor analysis of water quality characteristics including trace metal speciation in the coastal environmental system of Chennai Ennore. Environ Int 32(2):174–179
Lin ZJ, Zhan HG (2000) Effects of thermal effluent on fish eggs and larvae in waters near Daya Bay Nuclear Plant. Trop Oceanol 19(1):44–51
Liu S, Huang LM, Huang H, Lian JS, Am Long, Li T (2006) Ecological response of phytoplankton to the operation of Daya Bay nuclear power station. Mar Environ Sci 25(2):9–12
Lu RS, Lo SL (2002) Diagnosing reservoir water quality using self-organizing maps and fuzzy theory. Water Res 36(9):2265–2274
Ocampo-Duque W, Ferre-Huguet N, Domingo JL, Schuhmacher M (2006) Assessing water quality in rivers with fuzzy inference systems: a case study. Environ Int 32(6):733–742
Poornima EH, Rajadurai M, Rao VNR, Narasimhan SV, Venugopalan VP (2006) Use of coastal waters as condenser coolant in electric power plants: impact on phytoplankton and primary productivity. J Therm Biol 31(7):556–564
Qiu YW (2001) The characteristics of nutrients variation in the Daya Bay. Acta Oceanol Sin 23(1):85–93
Qiu YW, Wang ZD, Zhu LS (2005) Variation trend of nutrient and chlorophyll contents and their effects on ecological environment in Daya Bay. J Oceanogr Taiwan Strait 24(2):131–139
Simeonov V, Stratis JA, Samara C, Zachariadis G, Voutsa D, Anthemidis A, Sofoniou M, Kouimtzis T (2003) Assessment of the surface water quality in Northern Greece. Water Res 37(17):4119–4124
Singh KP, Malik A, Mohan D, Sinha S (2004) Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Res 38(18):3980–3992
Singh KP, Malik A, Sinha S (2005) Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques—a case study. Anal Chim Acta 538(1–2):355–374
Song XY, Huang LM, Zhang JL, Huang XP, Zhang JB, Yin JQ, Tan YH, Liu S (2004) Variation of phytoplankton biomass and primary production in Daya Bay during spring and summer. Mar Pollut Bull 49(11–12):1036–1044
Song MY, Hwang HJ, Kwak IS, Ji CW, Oh YN, Youn BJ, Chon TS (2007) Self-organizing mapping of benthic macroinvertebrate communities implemented to community assessment and water quality evaluation. Ecol Model 203(1–2):18–25
Sun CC, Wang YS, Sun S, Zhang FQ (2006) Dynamic analysis of phytoplankton community characteristics in Daya Bay. China Acta Ecol Sin 26(12):3948–3958
Tang DL, Kester DR, Wang ZD, Lian JS, Kawamura H (2003) AVHRR satellite remote sensing and shipboard measurements of the thermal plume from the Daya Bay, nuclear power station. China Remote Sens Environ 84(4):506–515
Wang XP, Cai WG, Lin Q, Jia XP, Zhou GJ, Gan JL, Lu XY (1996) The distribution variation of the nutrition salts in the waters of Daya Bay. Trans Oceanol Limnol 4:20–27
Wang YS, Lou ZP, Sun CC, Wu ML, Han SH (2006a) Multivariate statistical analysis of water quality and phytoplankton characteristics in Daya Bay, China, from 1999 to 2002. Oceanologia 48(2):193–211
Wang ZH, Qi YZ, Chen JF, Xu N, Yang YF (2006b) Phytoplankton abundance, community structure and nutrients in cultural areas of Daya Bay, South China Sea. J Mar Syst 62(1–2):85–94
Wang YS, Lou ZP, Sun CC, Sun S (2008) Ecological environment changes in Daya Bay, China, from 1982 to 2004. Mar Pollut Bull 56(11):1871–1879
Wang ZH, Zhao JG, Zhang YJ, Cao Y (2009) Phytoplankton community structure and environmental parameters in aquaculture areas of Daya Bay, South China Sea. J Environ Sci China 21(9):1268–1275
Wang WW, Li DJ, Zhou JL, Gao L (2011) Nutrient dynamics in pore water of tidal marshes near the Yangtze Estuary and Hangzhou Bay. China Environ Earth Sci 63(5):1067–1077
Wang F, Zhou B, Liu XM, Zhou GD, Zhao KL (2012) Remote-sensing inversion model of surface water suspended sediment concentration based on in situ measured spectrum in Hangzhou Bay. China Environ Earth Sci 67(6):1669–1677
Wu ML, Wang YS (2007) Using chemometrics to evaluate anthropogenic effects in Daya Bay, China. Estuar Coast Shelf Sci 72(4):732–742
Wu ML, Wang YS, Sun CC, Wang HL, Dong JD, Han SH (2009a) Identification of anthropogenic effects and seasonality on water quality in Daya Bay, South China Sea. J Environ Manag 90(10):3082–3090
Wu ML, Wang YS, Sun CC, Wang HL, Lou ZP, Dong JD (2009b) Using chemometrics to identify water quality in Daya Bay, China. Oceanologia 51(2):217–232
Wu ML, Wang YS, Sun CC, Wang HL, Dong JD, Yin JP, Han SH (2010) Identification of coastal water quality by statistical analysis methods in Daya Bay South China Sea. Mar Pollut Bull 60(6):852–860
Xu GZ (1989) Environments and resources of Daya Bay. Anhui Science Publishing House, HeFei
Ye L, Cai QH, Liu RQ, Cao M (2009) The influence of topography and land use on water quality of Xiangxi River in Three Gorges Reservoir region. Environ Geol 58(5):937–942
Yeung IMH (1999) Multivariate analysis of the Hong Kong Victoria Harbour water quality data. Environ Monit Assess 59(3):331–342
Yu J, Tang DL, Oh IS, Yao LJ (2007) Response of harmful algal blooms to environmental changes in Daya Bay, China. Terr Atmos Ocean Sci 18(5):1011–1027
Yu J, Tang DL, Yao LJ, Chen PM, Jia XP, Li CH (2010) Long-term water temperature variations in Daya Bay, China using satellite and in situ observations. Terr Atmos Ocean Sci 21(2):393–399
Yung YK, Wong CK, Yau K, Qian PY (2001) Long-term changes in water quality and phytoplankton characteristics in Port Shelter, Hong Kong, from 1988–1998. Mar Pollut Bull 42(10):981–992
Zhan B, Zeng G, Li L (1990) Temperature and salinity of Daya Bay. In: Third Institute of Oceanography, S (ed) Collections of papers on marine ecology in the Daya Bay (II). Ocean Publishing House, Beijing
Zhang S, Huang HH, Chen HR, Peng YH, Wang ZD, Fang ZX, Gao HL (2000) Environmental effects of residual chlorine discharged from Daya Bay nuclear power station on the adjacent water. Mar Environ Sci 19(2):14–18
Zhang JH, Xiao YZ, Wang H, Lin D, Dong YH (2007) Analysis of community structure on macrobenthos in sea area around Daya Bay nuclear power station. Mar Environ Sci 26(6):561–564
Zhou F, Guo HC, Liu Y, Jiang YM (2007a) Chemometrics data analysis of marine water quality and source identification in Southern Hong Kong. Mar Pollut Bull 54(6):745–756
Zhou F, Liu Y, Guo HC (2007b) Application of multivariate statistical methods to water quality assessment of the watercourses in Northwestern New Territories, Hong Kong. Environ Monit Assess 132(1–3):1–13