Numerical simulation of microcystin distribution in Liangxi River, downstream of Taihu Lake.

Microcystins (MCs), the algal toxins produced by cyanobacteria, raised a worldwide concern in recent decades. Limited monitoring stations for MCs make it hard to map the MC spatial distribution in certain areas. To tackle such problems, we selected Liangxi River as our research area and developed an integrated model to get spatial continuous MC data without too many sampling sites, which integrates a hydro-environment model and an artificial neural network algorithm (ANN). The ANN algorithm can estimate concentration MCs via environmental factors. In this paper, we selected chl-a, TN, TP, NO 2 - , NO 3 - , NH3 -N, and PO 4 3 - as stressors. The ANN model we established showed good performances both in train (R2  = 0.8407) and test set (R2  = 0.7543). In the hydro-environment model, by inputting river geometry and model boundary data, the spatial continuous water quality data could be simulated. The water quality data returned from the hydro-environmental model were used as input variables of the well-trained ANN model; the continuous MC data were derived. To evaluate this model on geo-mapping the MC distribution in Liangxi River, we compared the performance of this model and spatial interpolation on the test set, it turns out the integrated model showed a better performance. © 2020 Water Environment Federation PRACTITIONER POINTS: The cost of microcystin (MC) detection is too high for routine monitoring. We integrated regression method and hydro-environment model to predict MCs. Results derived from spatial interpolation are not robust in unmonitored area. The new integration model can minimize the drawback of spatial interpolation.

Changes in nutrient transport from the Yangtze River to the East China Sea linked to the Three-Gorges Dam and water transfer project.

River-sea transition plays a key role in global geochemical cycles. The Yangtze River Estuary of China was selected as the research area, and the Section-Segmented Method was applied to determine the nutrient discharge from the Yangtze River to the East China Sea. A 3-D numerical model for the estuary was established and validated against the field investigated data. By numerical experiments the dynamics of hydrology and nutrient from 1950 to 2016 were simulated under four varied schemes. The individual and combined impacts on the nutrient flux induced by the Three-Gorges Dam (TGD) and the South-to-North Water Transfer Project (SNWTP) were explored. The following results were observed: (1) During the Pre-TGD period, the Yangtze River delivered the loads of 1.32 Tg/yr and 0.08 Tg/yr for TN and TP, respectively. July and Feb. were characterized by the highest and lowest monthly flux, respectively. (2) TGD played a significant role in regulating the temporal nutrient deliveries. After the closing of TGD, the discharges of TN and TP in the dry season respectively went up to 0.55 Tg and 0.032 Tg, with a mean increase of 28.3%. (3) SNWTP reduced the nutrient transport at a relatively stable level, and the total loads of 40.66 Gg and 2.4 Gg were reduced per year for TN and TP, respectively. (4) The combined impacts of TGD and SNWTP varied with seasons. October was characterized by the greatest cumulative effects. In dry seasons, the reduction caused by SNWTP was leveled by TGD-induced increase, limiting the flux variation linked to project operations.