Identifying watershed-scale spatiotemporal groundwater and surface water mixing function in the Yiluo River, Middle of China

Comparison of multi-DLM approaches for predicting daily runoff: evidence from the data-driven model in one of China's largest wheat production-bases

Runoff forecasting is extremely important for various activities of water pollution research and agricultural. Data-driven models have been proved an effective approach in predicting daily runoff when combining deep learning methods (DLM). However, predicting accuracy of daily runoff still need improved. Here, we firstly proposed a combined model of Gate Recurrent Unit (GRU) and Residual Network (ResNet) and compared with one shallow learning method (Back Propagation Neural Network, BPNN) and one deep learning method (GRU) with data from 2010 to 2020 in three stations in daily runoff forecasting in the Yiluo River watershed. The results showed that the combined model with precipitation data and runoff data as input has the highest prediction accuracy (NSE = 0.9325, 0.8735, 0.9186, respectively). Input data with precipitation have higher prediction accuracy than that without. The performance of the model was better in the dry season than the wet season. The topographic and geomorphic factors may also the main factors affecting runoff forecast. Those results of this study can provide useful strategies to predict short runoff and manage watershed scale water resources especially in the important agriculture region.

Hydrochemical Characteristics and Hydrogeochemical Simulation Research of Groundwater in the Guohe River Basin (Henan Section)

With the implementation of the policy of ecological protection and high-quality development of the Yellow River Basin, the Guohe River Basin, which is close to the middle reaches of the Yellow River Basin, is also an important part of future development. Mathematical statistics, the Piper diagram, ion proportion coefficient method, Gibbs diagram and reverse hydrogeochemical simulation are used to analyze the chemical characteristics and evolution of groundwater in the Guohe River Basin (Henan Section). The dominant ions in the study area are HCO3− and Na+, and the three-layer aquifer has obvious zoning characteristics. The results show that the chemical types of shallow groundwater in this area are HCO3−Na • Mg • Ca, intermediate HCO3-Na and deep HCO3−Na. Using the ion proportion coefficient method, it is found that Na+, Ca2+, and Mg2+ in the groundwater aquifer undergo cation exchange in the aquifer. According to the reverse hydrogeochemical simulation, gypsum in the three aquifers is in a dissolved state, carbonate and sulfide ores in the shallow layer are dissolved, dolomite and halite in the intermediate layer are dissolved, calcite and sulfide ores are precipitated and carbonate, halite and sulfide ores in the deep layer are precipitated; the hydrogeochemical evolution model is established to find that Ca2+ in groundwater displaces Na+ in the aqueous medium. This research can provide a scientific basis for the rational development and utilization of groundwater and ecological protection in the Yellow River Basin.

Decreased levels and ecological risks of disinfection by-product chloroform in a field-scale artificial groundwater recharge project by colloid supplement

To bolster freshwater supply, artificial groundwater recharge with recycled water has increasingly attracted research attentions and interests. However, artificial groundwater recharge has potential risks to groundwater quality, as recharge water disinfection is frequently used for pathogen inactivation and causes the concerns of disinfection by-products (DBPs). Colloid supplement is a good approach solving this problem, but its roles in mitigating DBPs remains unclear. In this study, we collected 20 groundwater and soil samples from a field-scale groundwater recharge project, and explored the impacts of silica colloids on chloroform migration and groundwater bacterial communities during the recharge process. Water physicochemical variables changed along the recharge time, and colloid supplement significantly reduced chloroform formation and slowed its migration in groundwater. Bacterial communities in groundwater, river water and recharge water were significantly different. Gammaproteobacteria in recharge water (71.7%) was more abundant than in river water (30.5%) and groundwater (33.5%), while Actinobacteria dominated groundwater (40.6%). After recharge, Gammaproteobacteria increased more with colloid supplement (75.7%) than without (52.6%), attributing to its dominance in soils (74.6%). Our results suggested more bacterial lineages released from soils into aquifer by silica colloid supplement, owing to the competitive adsorption encouraging microbial transfer, especially Gram-negative bacteria. Our findings unraveled the effects of colloid supplement on chloroform formation and migration during artificial groundwater recharge, which consequently altered groundwater bacterial communities, and offered valuable suggestions for the safety management of DBPs in aquifer recharge.