The Integrated Valuation of Ecosystem Services and Trade-Offs (InVEST) model with the distributed hydrological model Soil and Water Assessment Tool (SWAT) were implemented. The SWAT model quantifies and visualizes water production and groundwater reserves in the Mudanjiang River Basin, employing the groundwater runoff modulus method to calculate groundwater recharge in the basin. This study aims to assess the model’s applicability in cold basins and subsequently analyze groundwater distribution characteristics, water reserves, and the exploitable volume. It serves as a reference for the judicious allocation of groundwater resources and the preservation of the local aquatic ecosystem. The study indicates the following: (1) Utilizing the monthly runoff data from the Mudan River hydrologic station, SWAT simulation and calibration were conducted, yielding a determination coefficient (R²) of 0.75 and a Nash–Sutcliffe efficiency coefficient (NS) of 0.77, thereby satisfying fundamental scientific research criteria. The water yield predicted by the InVEST model aligns closely with the water resources bulletin of the research region. (2) The data from the water production module of the InVEST model indicate that the average annual water production during the research period was 6.725 billion m³, with an average annual water production depth of 148 mm. In 2018, characterized by ample water supply, the water output was at its peak, with a depth of 242 mm. In 2014, the water depth recorded was merely 16 mm. (3) Throughout the study period, the average annual flow of the Mudan River was 4.2 billion m³, whereas the groundwater reserve was 24.13 (10⁸ m³·a⁻¹). In 2013, the maximum groundwater reserve was 38.42 (10⁸ m³·a⁻¹), while the minimum reserve in 2014 was 2.36 (10⁸ m³·a⁻¹), suggesting that the region was predominantly experiencing sustainable exploitation. (4) The mean groundwater runoff modulus is 0.28 L/(s·km²), with a peak annual recharge of 15.4 (10⁸ m³·a⁻¹) in 2013 and a lowest recharge of just 3.2 (10⁸ m³·a⁻¹) in 2011.

In this paper, the D3Q19 multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) for large eddy simulation (LES) was employed to optimize the shape of the vortex generator in a triangular vortex flowmeter. The optimization process focused on the vortex shedding frequency, lift force per unit area, and symmetry of the vortex street. The optimal shape of the vortex generator was determined to feature a 180° incoming flow surface, a concave arc side with a curvature radius of 25 mm, and a fillet radius of 4 mm at the end. Numerical simulations revealed that the optimized vortex generator achieves a 2.72~13.8% increase in vortex shedding frequency and a 17.2~53.9% reduction in pressure drop and can adapt to the flow conditions of productivity fluctuations (6.498 × 10⁵ ≤ Re ≤ 22.597 × 10⁵) in the gas well production. The results demonstrated significant advantages, including low pressure loss, minimal secondary vortex generation, high vortex shedding frequency, and substantial lift force. These findings underscore the robustness and efficiency of the LBM-LES method in simulating complex flow dynamics and optimizing vortex generator designs.

Phytoplankton under the ice of seasonally ice-covered lakes is a key indicator species for maintaining the health of lake ecosystems. However, there is a lack of a unified definition of cold lakes internationally. In addition, there are few studies on the distribution, driving mechanism and simulation prediction of phytoplankton under the ice, which have limited the development of winter limnology and the prevention and control of spring algal blooms. The average temperature of the coldest month, the duration of the ice period and the average annual water temperature were the main indicators for defining cold lakes based on the literatures review. The cross-action of subglacial hydrodynamics and biogeochemistry during the ice period and freeze-thaw period is the key to promoting the phytoplankton growth. The migration and transformation of nutrients and the formation of hypoxic zones of subglacial were driven by physical factors such as available light and water temperature. Cyanobacteria got advantages in the ice period and above the water column through their own gas vesicles and strong adaptation to low temperature and low oxygen. Diatoms are able to multiply rapidly with the increasing of available light and the water temperature in spring. However, the migration and transformation of nutrients induced by physical factors during the freezing-freezing-thawing process, the role of microorganisms in biogeochemical reactions, and the extent and direction of the combined effects of multiple environmental factors on phytoplankton functional groups are still unclear. At present, lake algal blooms have gradually expanded to higher latitudes under the climate change. How to accurately predict the development and response mechanism of algal blooms in cold lakes under the climate change has become a key direction in the development of winter limnology. This review explains the unique physical and chemical processes of phytoplankton growth competition in cold lakes from the perspectives of bibliometrics, mechanism analysis, method construction and future prospects. These findings would provide new insights into the field of winter limnology and provide theoretical support for the future management of spring algal blooms in cold lakes.

The balance of regional ecosystems has been increasingly disrupted by climate change and human activities. The Sanjiang Plain, an important commercial grain production base and a concentrated area of black-soil wetlands in China’s high-latitude region, has suffered a decline in regional ecosystem service functions as a result of large-scale agricultural development. However, the driving mechanisms and vulnerability of the ecological security pattern in the Sanjiang Plain remain poorly understood. This study integrates the Remote Sensing Ecological Index (RSEI) and the Ecological Service Function Index (ESI), uses the Optimal Geographical Detector (OPGD) to examine the Ecological network spatio-temporal evolution and driving mechanisms of the Sanjiang Plain, and employs circuit theory to delineate ecological corridors and identify ecological choke points and barriers. Finally, FANMOD software and robustness analysis were applied to evaluate the vulnerability of the ecological network. The results indicate: (1) Between 2000 and 2020, the coupling index of RSEI and ESI in the study area increased by 0.022. The OPGD results indicated that, during the study period, the interaction between the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBSI) had the strongest explanatory power for ecological evolution, followed by Wetness (WET) and Land Surface Temperature (LST).(2) The number of ecological source areas increased from 35 to 44, with the total area expanding by 6,033 km² and covering most nature reserves. The number of corridors increased from 60 to 83, with the total length extending by 425.81 km. The number of junction points also rose from 47 to 80. (3) Among all node types in the study area, the discrete pattern was the most widespread, with an average occurrence probability of 18.89%, followed by the single-gap pattern at 15.14%. (4) The results of the centralization analysis are consistent with those of the modularity analysis, indicating that connections among the various sources in the Sanjiang Plain tend to span long distances and form relatively few clusters. The network robustness assessment suggests that the network has weak resistance to node attacks. Therefore, while enhancing the influence of core nodes, it is also necessary to strengthen the connections between edge nodes and other nodes. This study provides new insights into the construction of ecological networks in black soil agricultural planting areas and offers a scientific basis for ecosystem conservation and regional sustainable development planning in large-scale agricultural expansion areas.