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Changes in the volume transport of Atlantic water into the Arctic Ocean can affect the heat and mass balance in the central Arctic Ocean. To understand the impacts of Arctic storms on the inflow through Fram Strait, we implemented the NEMO ocean model for the Arctic Ocean, to simulate the decadal variations of the water volume transport through Fram Strait. The simulations suggest that the water inflow tends to be weaker in the decades of the 1960 and 2010s but stronger in the 1980s. The decadal variation is associated with decadal variability of the storm density in the Greenland Sea. When there is an increased storm density near Fram Strait, the southerly wind anomalies dominate the Atlantic water pathway. As a response, there is an increased Atlantic inflow through Fram Strait. Plain Language Summary On decadal scales, Arctic storms near Fram Strait are highly correlated with the water volume transport into the Arctic Ocean through Fram Strait. When there are more storms near Fram Strait, the transport tends to increase. In addition, the heat flux associated with the water volume transport reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport. Key Points On a decadal scale, the storms in the Greenland Sea can affect the volume transport of Atlantic water inflow through Fram Strait Associated heat flux reflects the impacts of both the linear trend in ocean temperature and the decadal variation of water volume transport

Understanding water recharge mechanisms and accurately predicting water inflow are the fundamental objectives of mine hydrogeology investigation, particularly for ensuring deep mining safety. These investigation findings establish a scientific basis for planning drainage systems, optimizing mining layouts, and developing water hazard prevention and control measures. This paper takes the Maoping lead-zinc mine in Northeast Yunnan, China as a case study, which is a typical deep mine with significant water inflow challenges. Through systematic analysis of the mine’s hydrogeological structural characteristics, this study identifies the principal water sources and pathways causing mine water inrush hazards. A three-dimensional numerical model was developed using FEFLOW software to predict mine water inflow under wet, normal, and dry years during multi-level mining operations in the Maoping lead-zinc mine. Furthermore, the evolution pattern of deep flow field under the influence of mining activities was analyzed. The investigation results indicate that the regional groundwater recharge to the Maoping lead-zinc mine originates primarily from the carbonate rock karst fissure aquifer of the Permian Qixia and Maokou formations in the northern mining area, with secondary contributions from the Carboniferous-Devonian karst aquifer in the southern mining area. Atmospheric precipitation in the Xianji syncline located east of the mining area recharges mine water through major water-conducting faults F46, F16, and F50. In addition, there is no centralized recharge pathways for mine water along the Luoze River. The numerical simulation results demonstrate that as the mining section deepens, the inflow of mine water gradually increases. The deep groundwater depression cone expands along both northeast and northwest directions. Guided by the characterization of mine hydrogeological structures, four proactive water hazard management strategies are established: (1) targeted treatment of risk sources, (2) coupled stress-seepage field control, (3) real-time monitoring and early warning, and (4) controlled dewatering and pressure relief. This study provides a typical example for the analysis of water recharge mechanisms and prediction of water inflow in deep mines with complex hydrogeological structural characteristics, and can serve as a reference for prevention, control, and management of mine water inrush hazards in deep mines.

A key issue for effective management and operating of dam reservoirs is predicting the water inflow values into dam reservoir. To address this subject, here, genetic programming (GP) is used by proposing two cases. In the first case, water inflow values are predicted separately for each month. However, in the second case, these values are predicted simultaneously for all months. Furthermore, for each case, two approaches are proposed here. In the first approach, the hybrid method, called the ANN-NGSA-II method, is proposed to find proper input data sets. However, in the second approach, the useful input data sets are found automatically using the GP method. For comparison purpose, the ANN and SARIMA models are also used, to predict the water inflow values. As a case study, in this research, the Zayandehroud dam reservoir is selected. The results indicate that the ANN model outperforms both results of the GP and SARIMA methods. In other words, correlation coefficient (R2), Nash Sutcliffe (NS), and root means square error (RMSE) values of ANN are 0.97, (0.88), 0.954 (0.87), and 17.19 (30.54) million cubic meters, respectively, for training (test) data set.

Based on the fracture network model and the cubic law of a single fracture with laminar flow, a method suitable for calculating hydraulic-head distribution and flow behaviors in fractures was developed. The method regards the rock matrix as an impermeable medium, and groundwater only flows in the network formed by the fractures and faults. The equivalent porous medium approach can be used to consider fractured or fault zones in the traditional analytical methods. The proposed approach assumes that the discrete fractured aquifer behavior is equivalent to porous media behavior and, therefore, any fractured or fault zones can be considered using a layer with much higher hydraulic conductivity than that of the intact rock. A case study in Jiangsu Province, China, was employed to verify the applicability and effectiveness of the method, and the influences of fracture orientation and tunnel slope on water inflow were evaluated. The method was applied to the prediction of water inflow to tunnels in the Liyang pumped-storage power station, and the water inflow calculated with this method was compared with the observed inflow. The results show that, compared with the traditional methods, the proposed method incurs only small errors and fits measured values well. It can be applied to the prediction of tunnel inflow in fractured rock mass, especially in areas where the permeability of fractures and faults is much greater than that of the rock matrix.

The Arabian Gulf, a semi-enclosed basin in the Middle East, connects to the Indian Ocean through the Strait of Hormuz and is surrounded by seven arid countries. This study examines the water cycle of the Gulf and its surrounding areas using data from the GRACE and GRACE Follow-On missions, along with ERA5 atmospheric reanalysis data, from 05/2002 to 05/2017 and from 07/2018 to 12/2023. Our findings reveal a persistent water deficit due to high evaporation rates, averaging 370 ± 3 km3/year, greatly surpassing precipitation, which accounts for only 15% of the evaporative loss. Continental runoff provides one-fifth of the needed water, while the remaining deficit, approximately 274 ± 10 km3/year, is balanced by net inflow of saltwater from the Indian Ocean. Seasonal variations show the lowest net inflow of 26 ± 49 km3/year in March and the highest of 586 ± 53 km3/year in November, driven by net evaporation, continental input, and changes in the Gulf’s water budget. This study highlights the complex hydrological dynamics influenced by climate patterns and provides a baseline for future research in the region, which will be needed to quantify the expected changes in the hydrological cycle due to climate change.

Highly permeable geological structures such as dissolution channels, open fractures, and faults create environmental challenges regard to hydrological and hydrogeological aspects of underground construction, often causing significant groundwater inflow during drilling due to the limitations of empirical and analytical methods. This study aims to identify the geological factors influencing water flow into the tunnel. High-flow zones’ geological features have been identified and examined for this purpose. According to the geological complexity of the Nowsud tunnel, presence of different formations with different permeability and karstification have led to a high volume of underground inflow water (up to 4700 L/s) to the tunnel. The Nowsud tunnel faces significant geological and hydrogeological challenges due to its passage through the Ilam formation’s LI2 unit, characterized by dissolution channels, faults, and fractures. The highest inflow rate (4700 L/s) occurred in the Hz-9 zone within the Zimkan anticline. The relationship between geological features and groundwater inflow indicates that anticlines are more susceptible to inflow than synclines. Additionally, different types of faults exhibit varying hydraulic effects, with strike-slip faults having the most significant impact on groundwater inflow, thrust faults conducting less water into the tunnel, and inflow through normal faults being negligible compared to the other two types of faults. The novelty of this paper lies in its detailed analysis of geological features influencing groundwater inflow into the Nowsud tunnel, providing empirical data on high-flow zones and differentiating the hydraulic effects of various fault types, which enhances the understanding and prediction of groundwater inflow in underground constructions.

Predicting groundwater inflow into tunnels is essential to ensure the safe accessibility and stability of underground excavations and to attenuate any associated risks. Such predictions have attracted much attention due to their tremendous importance and the challenge of determining them accurately. Over recent decades, based on diverse methods, researchers have developed many relevant analytical solutions. Considering these research efforts, this article identifies and describes the most critical key factors that strongly influence the accuracy of groundwater inflow predictions in rock tunnels. In addition, it presents a synthesis of the latest advances in analytical solutions developed for this purpose. These key factors are mainly time dependency of groundwater inflows, water-bearing structures, aquifer thickness, hydraulic head and groundwater drawdown, rock permeability and hydraulic conductivity, fracture aperture, and rainfall data. For instance, groundwater inflows into tunnels comprise two stages. However, the transition between the stages is not always rapid and, for tunnels located in faulted karst terrains and water-rich areas, groundwater inflows can exceed 1,000 L/min/m. Under high stress, rock permeability can increase up to three times near the inevitable excavation-damaged zones, and groundwater inflows into tunnels can be significantly affected. Despite the enormous amount of research already conducted, improvements in the accuracy of predicting groundwater inflows into rock tunnels are still needed and strongly suggested.

Underground coal gasification (UCG) is an in-situ and non-conventional method for extracting coal by injecting steam, air, and oxygen into the target coal seam. The resultant gas from this process is transported via production pipes to a gas processing facility, where it can be used for electricity generation and the production of synthetic gas (syngas). The UCG process creates cavities within the coal seam, which requires groundwater as a natural barrier to prevent gas loss. However, groundwater entering the cavities can lead to a drawdown of groundwater head, and if this drawdown is excessive, subsidence may occur. This study aims to predict groundwater intrusion in the gasification zone and its effects on the aquifers above and below the gasification zone. UCG modeling was performed with a coal hydraulic conductivity value of 4.5 x 10−8 m/s and operational pressure variations of 10 bar and 20 bar. The hydrostatic pressure on the target coal is 32 bar. Simulations were conducted over 144 days or for the gasification of 100 meters (10 grid models) of coal. Simulation results with coal conductivity of 4.5 x 10-8 m/s and an operating pressure of 10 bar, the model predicts a groundwater intrusion of 61.96 m3/day into the gasification zone, 0.0998 m3/day from the upper aquifer, and 0.1088 m3/day from the lower aquifer, causing a drawdown of 1.42 meters in the upper aquifer and 2.47 meters in the lower aquifer. At operating pressure 20 bar, predictions are 27.34 m3/day intrusion into the gasification zone, 0.0803 m3/day from the upper aquifer, and 0.1052 m3/day from the lower aquifer, resulting in a drawdown of 1.28 meters in the upper aquifer and 2.16 meters in the lower aquifer.

The excavation and construction of tunnels in drained conditions essentially involves groundwater inflow, which results in water-table drawdown, groundwater inflow rate reduction, and pore-water pressure redistribution. A combined analytical-numerical method is proposed to estimate the groundwater inflow into circular tunnels in drained conditions. The method consists of three semianalytical formulas for shallow, deep, and lined tunnels, based on the trench model and the image method. Then, various two-dimensional cross-section numerical models are built, considering different model parameters like tunnel radius, initial water level, and lining. Based on the numerical results, the effects of the lining on the water inflow rate, drawdown, and water pressure are evaluated, and the semianalytical formulas are obtained by regression analysis. The most interesting finding is that the free surface intersects the tunnel boundary when r/h ≥ 0.062, which is regarded as a criterion for dividing shallow and deep tunnels in this study. The proposed semianalytical formulas, taking into account the effect of the drained condition, can provide better predictions of tunnel inflow compared to existing analytical formulas.

Pressurized confined water below coal seams are serious threats to mining. The conventional water inrush coefficient method fails to accurately assess the risk of floor water inrush under some specific conditions, such as high water pressure and low water yield in the source aquifers. Large amounts of water inrush data including water inrush flow rate, water inrush coefficient ( T s ), floor aquiclude thickness ( M ), and water abundance, were collected and statistically analyzed. The results indicated that inrushes mostly occurred when M was less than 30 m and that the critical T s increased linearly with M . The occurrence of a water inrush and water inrush yield amount ( Q in L/s) were related to both the values of T s and the unit water inflow ( q in L/(s m)). In addition, 97.7% of the large- and medium-sized inrush events occurred when q  > 2 L/(s m) and only a small proportion (3.2%) of the small-sized inrushes happened when q  < 0.1 L (s m). T s ,  M and q were comprehensively analyzed and used to evaluate vulnerability to floor water inrush. By analyzing the distribution of water inrush points and the scale of water inrush events, the vulnerability was divided into four levels (safe, moderately safe, potentially dangerous, and highly risky) based on T s – M and T s – q models. Successful application of these models in the Huaibei mining area proved that they are feasible in practice. The T s – M and T s – q charts can be used independently or jointly. These new methods should improve the accuracy of predictions and evaluations during deep exploitation where the aquifers are often characterized with high pressure but low water abundance. The results could also help reduce the amount spent on mine water prevention and control.