There are many wetlands in China that play an important role in water resource conservation and ecological diversity maintenance. Wetlands have irreplaceable ecological significance for human survival [1
]. Although China has emphasized wetland protection over the past few decades, there remains a sharp decline in the area of wetlands [2
]. According to official statistics of the China Forestry Administration, China’s wetland area fell by 8.83% in 2013, compared with that of 2003. The shrinking of wetland area is closely related to the decrease of water resources in wetlands, and the atrophy of lake area is directly impacted by the shrinking of wetland area [3
]. Therefore, it is of vital importance to study the water flow in lakes to find out the feasible measures for wetland conservation [1
A large number of microbes, animals, and plants live in lakes. Therefore, improving purification ability is essential to maintaining the wetland ecological environment [5
]. In China, the area of lakes in wetlands has reduced greatly, and as a result, finding ways to slow down the shrinkage of lakes has become an increasingly important topic [6
]. The reduction of lake area is bound to the flow of water, and there is no doubt that the characteristics of the water flow is of great importance [5
]. In general, gravity, bed friction, rainfall, wind speed, and topography may influence the hydrodynamic conditions of lakes of different levels [6
]. In addition, vegetation in lakes can also have an important impact on water flow with its drag effect [8
Physical modelling and numerical simulation are the two main approaches to studying flow characteristics [10
]. With the development of computer science, numerical modeling has become prevalent [11
]. The MIKE series model, developed by the Danish Institute of Water Resources and Water Environment (DHI, Hørsholm, Denmark), is a general commercial package with a wide range of applications for water simulation [12
]. The Environmental Fluid Dynamics Code (EFDC) model, created by the Virginia Institute of Marine Science at the College of William and Mary (Williamsburg, VA, USA), has many functions for water quality modelling and its partially open-source code offers good flexibility [12
]. However, these commercial models are only based on the traditional finite difference method or the finite volume method, and further development is inhibited given that these models do not have a flexible external force term.
The lattice Boltzmann method (LBM) is a relatively new numerical method for fluid flows [15
]. The related theoretical basis of LBM was carried out in the 1980s [16
]. Salmon (1999) [17
] developed a lattice Boltzmann model for shallow water. Compared with traditional computational methods based on the direct approach of the flow equation, it proposes a new solution for the flow equation [18
]. The method is characterized by simple calculation and easy handling of boundary conditions [19
]. In recent years, it has become a promising approach in computational fluid dynamics [20
]. The use of the LBM to simulate different kinds of flow (e.g., open channel flows, tidal flows, and dam-break flows) has become popular. Ottolenghi et al. (2018) [21
] used lattice Boltzmann method to investigate the properties of graphene oxide for environmental applications. O’Brien et al. (2002) [22
] developed a lattice Boltzmann scheme to study reactive transport in porous media. Zhou (2007) [23
] developed a lattice Boltzmann model for groundwater flow. Tubbs and Tsai (2009) [24
] developed the parallel computation for multi-layer shallow water flows. Liu et al. (2012) [25
] worked out a large eddy simulation of turbulent shallow water flows using the LBM. Prestininzi (2016) [26
] presented a 2D multi-layer shallow water lattice Boltzmann model able to predict the salt wedge intrusion in river estuaries. Furthermore, Yang et al. (2017) [8
] developed a rigid vegetation model with 2D shallow water equations using the LBM.
In this paper, the LBM is used to study the hydrodynamic characteristics of Baihe Lake. This is also the first numerical simulation study of Baihe Lake in China, which is helpful for local ecological and hydrological restoration. Through the numerical study of different scenarios, the model provides a quantitative investigation of different impact factors and the results could provide a theoretical basis for local wetland restoration and hydraulic engineering construction.
In this paper, the LBM method is applied to Baihe Lake to reveal the temporal and spatial characteristics of water body. Overall, the water body of Baihe Lake suffered poor exchange, where the lowest flow rate based on simulation reached just 0.016 m/s. Simulations of different impact factors (e.g., wind speed, rainfall, vegetation density) were conducted here. The simulation results revealed that changes in inflow velocity, primarily as the result of water drainage from surrounding farmland, have the strongest effect. A 30% variation in the impact factors resulted in a 24.11% variation in the outflow rate at most. In addition, when the impact of wind speed was relatively small, the variation of the outflow rate reached just 18.87%. Relatedly, given the high distribution of aquatic vegetation in some areas of Baihe Lake, and that vegetation density varies with the season, the impact of vegetation on the flow field should be considered separately. The present model includes the change in vegetation density and investigates its effect on the flow fields. The simulation result revealed that vegetation density was negatively correlated with outflow rate. However, the influence of aquatic vegetation on flow distribution was relatively small, being only 9.59% when the vegetation density fluctuated 30%. On the whole, the outflow of Baihe Lake strongly depends on the drainage from upstream farmland, followed by the rainfall, and then by local wind speed. Aquatic vegetation can also have an impact. The inflow rate is the only factor that is easy to control. As a result, ecological protection and hydraulic engineering construction can be established upstream to control the water level and flow rate.
The monitored rainfall, wind speed, flowrate, and vegetation density data in different months was input into the present model in order to simulate and obtain the flow characteristics of Baihe Lake in July and September. Although the influence of wind speed and vegetation was relatively small in the single factor analysis, they can still have an impact on the flow as these two factors have potential uncertainty due to the change in climate. The monitored data revealed large drainage from the surrounding farmland in July, together with high rainfall. Consequently, based on the simulation results, the impact of wind speed and vegetation density was relatively small. In contrast, a reduction in rainfall with a similar farmland drainage happens in September. Importantly, this increases the influence of wind speed and vegetation density. The results indicated that the mean flow rate is much bigger in July than September, which also verifies the significance of different impact factors. Relatedly, the simulation results also demonstrate that the water exchange of Baihe Lake during the flood season from June to August is much better than it is in the dry season from September to November. Therefore, when developing an ecological restoration program, both the farmland drainage and the season should be emphasized.
Based on the lattice Boltzmann method (LBM), the present study has established a two-dimensional shallow water model that includes vegetation drag force. This paper for the first time puts forward a method to study the variation of flow field by establishing a numerical model of the Baihe Lake, which plays a guiding role in the construction of the ecological engineering of the Baihe Lake. The hydrodynamic model in this paper can be widely used in shallow lakes. Meanwhile, the drag force of aquatic vegetation to Baihe Lake is specially considered in the model, leading to that the model is most suitable for lakes with aquatic vegetation.
The model was used to explore the hydrodynamic impact of different influencing factors in Baihe Lake. Through a sensitivity test, drainage from surrounding farmland showed a dominant influence on the flow field, followed by rainfall, wind speed, and vegetation density. Furthermore, these factors may produce a noticeable variation in local flow characteristics in different seasons. As a result, the impact of these factors should be considered when developing an ecological restoration program. We should pay attention to different schemes corresponding to different seasons and control hydraulic construction to influence farmland receding water and improve lake fluidity.