| Lake Dianchi,also known as Lake Kunming,is the largest plateau freshwater lake in Yunnan Province,known as the "Pearl of the Plateau",and plays a vital role in the sustainable socio-economic development of Kunming.In recent years,due to the intensification of human activities,the exogenous pollution load of Dianchi has increased and the water quality has deteriorated,coupled with the unique geographical characteristics and climatic conditions of Dianchi that help the growth and reproduction of algae,making cyanobacteria blooms frequently,bringing serious harm to the Dianchi aquatic ecosystem.To effectively prevent and control cyanobacteria blooms,it is necessary to continuously monitor the cyanobacteria blooms and their environmental factors for a long time,to grasp the spatial and temporal distribution characteristics of cyanobacteria blooms,and to identify the driving factors of cyanobacteria bloom,to construct a three-dimensional hydrodynamic ecological model,and to predict the cyanobacteria blooms on different time scales.Due to the lack of day-by-day inflow data of Dianchi,the inflow water volume of Dianchi from 2007 to 2020 was estimated based on the one-dimensional hydrodynamic model(DYRESM)and the water compensation method developed by the group.Based on satellite remote sensing images,we analyzed the spatial and temporal distribution characteristics of cyanobacteria blooms in Dianchi from 2002 to 2018,and identified the single and combined driving factors.A three-dimensional hydrodynamic ecological model(AEM3D)was used to simulate the possible effects of Dianzhong Water Transfer Project on the water quality of Dianchi.The main conclusions are as follows.(1)From 2007 to 2020,the fitted correlation coefficient(r)between total annual inflow and total annual precipitation was 0.62(n=14),and the root mean square error(RMSE)between day-by-day simulated and measured water level was 0.0072 m and r was 0.99(n=5114).Using the monthly water temperature(WT),dissolved oxygen(DO),Chl-a,total nitrogen(TN),ammonia nitrogen(NH3-N)and total phosphorus(TP)monitoring data from January 2012 to December 2014,the constructed AEM3 D model of Dianchi was parameterized and calibrated with the measured water quality data from January to December 2015,during both the rate period and the validation period,the model can well reflect the variation patterns of WT,NH3-N and TP in the surface layer(0.5 m)off Dianchi,and the correlation coefficients r between the simulated and measured values of these indicators are above 0.6.(2)Based on the information of cyanobacteria bloom and Chl-a concentration data in the inversion of satellite remote sensing images from 2002 to 2018,the analysis found that the annual average proportion of cyanobacteria bloom area in the Waihai of Dianchi showed a decreasing trend,and the severity of cyanobacteria bloom(the ratio of cyanobacteria bloom area to regional area)gradually decreased from north to south.In the northern part of the Waihai,cyanobacteria bloom was more serious in the east than west,while in the central and southern parts,the severity of cyanobacteria bloom showed an opposite distribution pattern in the eastern and western zones.The results showed that the meteorological factors(wind speed and sunshine duration)were the main influencing factors for cyanobacteria blooms in the Waihai,with wind speed making the largest contribution and water quality(water temperature)the second.In the three zones of the Waihai,the water residence time(WRT)and the cyanobacteria bloom area were all significantly positively correlated,and the WRT gradually increased from north to south in space.(3)Using the AEM3 D model,the environmental effects of the " Dianzhong Water Transfer Project " were evaluated.Under the three water diversion scenarios(abundant,flat and dry years,with total annual water diversions of 298,445 and 223 million m3,respectively),the improvement rates of the surface TN of the whole lake under the abundant,flat and dry scenarios compared with the undiversion scenarios were: the improvement rates of TN in the surface layer of the lake were 3.03%,3.44% and 0.71%,and the improvement rates of TP were 9.37%,9.89% and 5.10%,respectively. |
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