A Bayesian modeling approach for phosphorus load apportionment in a reservoir with high water transfer disturbance

Determination of degradation/reaction rate for surface water quality of recycled water using Lake2K model for large-scale water recycling

The depletion of groundwater resources in the water-stressed regions has led to the overuse of surface water reservoirs. Recharging groundwater by rejuvenating dried surface reservoirs using recycled water is a new sustainable solution. To ensure the prevention of groundwater contamination and associated health risks (as recycled water is used), it is crucial to assess the surface reservoir water quality. The study for the first time suggests the Lake2K model, a one-dimensional mechanistic mass-balance model, to simulate the changes in water quality in a series of man-made surface water reservoirs where recycled water flows under an indirect groundwater recharge scheme (soil aquifer treatment system). The model was developed, calibrated, and validated using field observations to estimate degradation/reaction rate constants for various water quality parameters. The observed average degradation/reaction rate constants for parameters including ammonia-N, nitrate-N, total nitrogen, total organic carbon, and organic phosphorous were 0.043 day-1, 0.04 day-1, 0.043 day-1, 0.055 day-1, and 0.056 day-1, respectively, which were found to be relatively high compared to existing literature, indicating a greater degradation of these parameters in warmer climates. The results showed that the water quality improved significantly as the water progressed through the reservoirs, aligning with field observations. Additionally, the simulated seasonal variations revealed that the maximum growth rate of phytoplankton occurred during July, August, and September for each reservoir, while the nutrient pool (nitrate-N and orthophosphates) experienced the greatest depletion during this growth period. These findings shed light on the dynamics of surface water quality in regions facing water scarcity and contribute to the development of sustainable groundwater management strategies.

Ammonium Nitrogen Streamflow Transport Modelling and Spatial Analysis in Two Chinese Basins

Ammonium nitrogen (NH4+-N), which naturally arises from the decomposition of organic substances through ammonification, has a tremendous influence on local water quality. Therefore, it is vital for water quality protection to assess the amount, sources, and streamflow transport of NH4+-N. SPAtially Referenced Regressions on Watershed attributes (SPARROW), which is a hybrid empirical and mechanistic modeling technique based on a regression approach, can be used to conduct studies of different spatial scales on nutrient streamflow transport. In this paper, the load and delivery of NH4+-N in Poyang Lake Basin (PLB) and Haihe River Basin (HRB) were estimated using SPARROW. In PLB, NH4+-N load streamflow transport originating from point sources and farmland accounted for 41.83% and 32.84%, respectively. In HRB, NH4+-N load streamflow transport originating from residential land and farmland accounted for 40.16% and 36.75%, respectively. Hence, the following measures should be taken: In PLB, it is important to enhance the management of the point sources, such as municipal and industrial wastewater. In HRB, feasible measures include controlling the domestic pollution and reducing the usage of chemical fertilizers. In addition, increasing the vegetation coverage of both basins may be beneficial to their nutrient management. The SPARROW models built for PLB and HRB can serve as references for future uses for different basins with various conditions, extending this model’s scope and adaptability.

The Long-Term and Retention Impacts of the Intervention Policy for Cage Aquaculture on the Reservoir Water Qualities in Northern China

To ensure the safety of the water supply of the Panjiakou reservoir, in 2016, the Chinese central government comprehensively banned the fishing cage culture that had lasted for almost 30 years. However, the long-term effects and retention impacts of the government’s mandatory intervention on the reservoir water quality are unknown. To determine the reservoir water quality, we employed statistical methods along with the mathematical model to investigate the internal relationship since the construction of the reservoir. We applied seasonal trend decomposition using loess (STL) to explore the long-term and seasonality trend of monthly total nitrogen (TN) and total phosphorous (TP). To separate the impact of upstream water quality changes from cage culture on reservoir water quality, we employed generalized additive models (GAMs). We created a model, the LAKE2K model, to investigate the internal sources of the sediment that accumulated during the aquaculture period and its retardant effect. The results revealed that the concentration of upstream TN was more affected by non-point sources than by TP. The long-term policy of encouraging aquaculture has greatly contributed to the increase in the reservoir TP concentration rather than an increase in TN; the prohibition of cage aquaculture has resulted in a sharp drop in TP. After the ban, the sediment became the main source of TP. We suspect that the TP concentration of the reservoir and sediment will decrease gradually until a new equilibrium is reached within 10 years. This study offers lake managers an opportunity to increase their insight into the interaction of management measures with water quality and provides valuable information for the natural recovery of the eutrophic system.

Characterizing the heterogeneous correlations between the landscape patterns and seasonal variations of total nitrogen and total phosphorus in a peri-urban watershed

Landscape patterns in a watershed potentially have significant influence on the occurrence, migration, and transformation of pollutants, such as nitrogen (N) and phosphorus (P) in rivers. Human activities can accelerate the pollution and complicate the problem especially in a peri-urban watershed with different types of land use. To characterize the heterogeneous correlations between landscape patterns and seasonal variations of N and P in a peri-urban watershed located upstream of Tianjin metropolis, China, observations of total nitrogen (TN) and total phosphorus (TP) at 33 locations were performed in the wet and dry seasons from 2013 to 2016. The data from individual locations were averaged for the wet and dry seasons and analyzed with geographical detector to identify influential landscape indices on seasonal water quality variations. The geographically weighted regression method, capable of analyzing heterogeneous correlations, was used to evaluate the integrated effects from different landscape indices. The results demonstrated that the location-weighted landscape contrast index (LWLI), the ratio of urban areas, and the ratio of forest areas were major influential indicators that affected TN and TP in river water. These indices also had integrated effects on variations of TN and TP together with other indices such as Shannon diversity index, landscape shape index, largest patch index, and contagion index. The integrated effects were different in the wet and dry seasons because of different effects of flushing and dilution by rainwater and the heterogeneity in landscape patterns. The LWLI had a positive relationship to water quality in the areas with high ratio of urban areas, indicating that domestic wastewater can be a major source of N and P pollution. The approaches and findings of this study may provide a reference for characterizing the major factors and integrated effects that control nonpoint source pollution in a watershed.

An Ensemble Kalman Filter approach to assess the effects of hydrological variability, water diversion, and meteorological forcing on the total phosphorus concentration in a shallow reservoir

Total phosphorus (TP) is a vitally important water quality index in shallow reservoirs and is closely connected with hydrological variability, anthropogenic water diversion and meteorological forcing. However, it is still unclear to what extent the TP concentration in a complex shallow reservoir system attributes to each type of forcing. To resolve this issue, this study proposed a TP concentration contribution index (TPI) to assess the contribution of each forcing, using the data assimilation (DA) method, the Ensemble Kalman Filter (EnKF), which was applied in the shallow Yuqiao Reservoir, China. The EnKF model was conducted based on the Vollenweider model and logistic regression models with datasets of 1989-2015. The results showed that human-originated activities forcing (water diversion) contributed the maximum TPI (40%), followed by hydrological variability forcing (37%). Finally, meteorological forcing (air temperature and wind included) only accounted for 23%. Furthermore, the seasonal analyses also showed that the TPI of hydrological variability dominated in spring and winter, with 65% and 73% respectively. However, the contributions of meteorological forcing (air temperature and wind) accounted for a larger proportion of 63% and 57% in summer and autumn. The benefit of our EnKF model denoises the Gaussian noise contained in observation and simulation, which offers a chance to isolate and identify even a minor driving factor (i.e., meteorological forcing) from a complex river and lake system with limited data. The study provides a method to assess the influence of direct and indirect forcing on TP concentration in shallow reservoirs from a quantitative perspective. Thus, it may serve as a useful tool for water quality management in water-receiving systems.