Impact of phosphorus load reduction on water quality in a stratified reservoir-eutrophication modeling study

Exploring the type and strength of nonlinearity in water quality responses to nutrient loading reduction in shallow eutrophic water bodies: Insights from a large number of numerical simulations

Reducing the load of nutrients is essential to improve water quality while water quality may not respond to the load reduction in a linear way. Despite nonlinear water quality responses being widely mentioned by studies, there is a lack of comprehensive assessment on the extent and type of nonlinear responses considering the seasonal changes. This study aimed to measure the strength of nonlinearity of theoretically possible water quality responses and explore their potential types in shallow eutrophic water bodies. Hereto, we generated 14,710 numerical water body cases that describe the water quality processes using the Environmental Fluid Dynamics Code (EFDC) and applied eight load reduction scenarios on each water body case. Inflows are simplified from Lake Dianchi. The climate conditions consider three cases: Lake Dianchi, Wissahickon Creek, and Famosa Slough. We then developed a nonlinearity strength indicator to quantify the strength and frequency of nonlinear water quality responses. Based on the quantification of nonlinearity, we clustered all the samples of water quality responses using K-Means, an unsupervised Machine Learning algorithm, to find the potential types of nonlinear water quality responses for TN (total nitrogen), TP (total phosphorus), and Chla (chlorophyll a). Results show linear or near-linear response types account for 90%, 69%, and 20% of TN, TP, and Chla samples respectively. TP and Chla could perform more types of nonlinearity. Representative nonlinear water quality responses include disproportional improvement, peak change (disappear, move forwards or afterward), and seasonal deterioration of TN after load reduction. This study would contribute to the current understanding of nonlinear water quality responses to load reduction and provide a basis to study under which conditions the nonlinear responses may emerge.

Hydrodynamics and water quality of the Hongze Lake in response to human activities

The hydrodynamics and water quality of a lake in response to human activities is an important yet poorly understood issue. In this study, the responses of flow field, water level, and water quality of the Hongze Lake to changes in land use, project operation, and pollution accident were investigated using the 2D hydrodynamic model, water quality model, and hydrological model. The results show that project operations have more significant effects on the hydrodynamics and water quality of the Hongze Lake than changes in land use. In addition, the construction and operation of various water conservancy projects could increase pollutant diffusion and water exchange, thus contributing to improve the water quality of the Hongze Lake, but there is a need to solve the problem of rising water level in the Lihe depression lake area. The increase of urban and farmland area can significantly affect the flow of the Hongze Lake that could increase the flood risk. The simulations of the loosely coupled model imply that the coupling among the hydrodynamic model, water quality model, and SWAT model for the lake basin is feasible. Furthermore, a model based on the space grid was proposed in the study and combined with the verified loosely coupled model to assess the flood risk in the Hongze Lake, which could improve water resources and flood retarding basin operations.

Thermal stratification responses of a monomictic reservoir under different seasons and operation schemes

This study investigates the thermal stratification responses of a monomictic reservoir operated under different facilities. The analysis of 60-year long data showed that the reservoir's thermal regime varies with season and withdrawal scheme and is affected by upstream reach control through the vertical curtain. Isothermal conditions exist during winter (December-March) while stratification onsets in spring (starting April), intensifies in summer (August) and weakens during fall (October-November). Considering summer stratification, deep hypolimnetic withdrawals through the penstock intake promoted thicker epilimnion, with low values of thermal stability (Schmidt Stability Index, SSI) and thermocline strength index (TSI). Meanwhile, shallow withdrawals using selective outflow system resulted in narrower epilimnion, with larger TSI for no curtain scenario and larger SSI for with curtain scenario. Strongest thermoclines do not necessarily translate to largest magnitudes of thermal stability. Longer duration of stratification is associated with shallow withdrawals. Depending on the outflow depth and the occurrence of prolonged hot or cold atmospheric conditions, the onset of stratification could be likely shifted early or late. The 3D numerical simulation determined the individual effects of each operation, which strongly supported the results of the long term analysis. Since thermal stratification directly influences the reservoir's water quality regime, this study can be a helpful reference in optimizing the water quality management of the reservoir.

Autogenous Eutrophication, Anthropogenic Eutrophication, and Climate Change: Insights from the Antrift Reservoir (Hesse, Germany)

Climate change is projected to aggravate water quality impairment and to endanger drinking water supply. The effects of global warming on water quality must be understood better to develop targeted mitigation strategies. We conducted water and sediment analyses in the eutrophicated Antrift catchment (Hesse, Germany) in the uncommonly warm years 2018/2019 to take an empirical look into the future under climate change conditions. In our study, algae blooms persisted long into autumn 2018 (November), and started early in spring 2019 (April). We found excessive phosphorus (P) concentrations throughout the year. At high flow in winter, P desorption from sediments fostered high P concentrations in the surface waters. We lead this back to the natural catchment-specific geochemical constraints of sediment P reactions (dilution- and pH-driven). Under natural conditions, the temporal dynamics of these constraints most likely led to high P concentrations, but probably did not cause algae blooms. Since the construction of a dammed reservoir, frequent algae blooms with sporadic fish kills have been occurring. Thus, management should focus less on reducing catchment P concentrations, but on counteracting summerly dissolved oxygen (DO) depletion in the reservoir. Particular attention should be paid to the monitoring and control of sediment P concentrations, especially under climate change.

Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models

In this study, two artificial neural network models (i.e., a radial basis function neural network, RBFN, and an adaptive neurofuzzy inference system approach, ANFIS) and a multilinear regression (MLR) model were developed to simulate the DO, TP, Chl a, and SD in the Mingder Reservoir of central Taiwan. The input variables of the neural network and the MLR models were determined using linear regression. The performances were evaluated using the RBFN, ANFIS, and MLR models based on statistical errors, including the mean absolute error, the root mean square error, and the correlation coefficient, computed from the measured and the model-simulated DO, TP, Chl a, and SD values. The results indicate that the performance of the ANFIS model is superior to those of the MLR and RBFN models. The study results show that the neural network using the ANFIS model is suitable for simulating the water quality variables with reasonable accuracy, suggesting that the ANFIS model can be used as a valuable tool for reservoir management in Taiwan.

Spatiotemporal distribution pattern of cyanobacteria community and its relationship with the environmental factors in Hongze Lake, China

Hongze Lake, located in the east route of the South-to-North Water Diversion Project (SNWDP), is a potential drinking water source for the residents along this water diversion project. Based on a monthly sampling at 11 stations in three regions of Hongze Lake, the spatiotemporal distribution pattern of cyanobacteria community was comprehensively investigated from March 2011 to February 2013. A total of 23 cyanobacterial species which belong to 16 genera were identified, and Microcystis was the most predominant cyanobacterial genus mainly composed of Microcystis wesenbergii in Hongze Lake. The cyanobacterial abundance ranged from 0 to 2.6 × 10(7) cells/L, and the average cyanobacteria abundance of Northern region was significantly higher than those of Western region and Eastern region in the 2-year study. The total cyanobacteria abundance and the Microcystis abundance both took on a similar seasonal regularity in the three regions. The results of correlation analysis indicated that Microcystis abundance was correlated with water temperature, chemical oxygen demand (COD)Mn, nitrate (NO₃-N), and total nitrogen (TN)/total phosphorus (TP) mass ratio, among which water temperature had the highest correlation coefficient. In summer, cyanobacteria blooms may take place under suitable environmental conditions at some special areas in Hongze Lake, especially where the concurrence of slow water exchange and steady wind direction exists.