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With the development of a 300 m high dam and large reservoir construction, the emergency drawdown capacity of cascade reservoirs, especially high dams, has become a hot issue of concern to all sectors of society while giving play to huge comprehensive benefits. Based on a thorough investigation of the current situation of drawdown facilities for high dams and large reservoirs with a height of 200 m or more in the world, this paper finds that drawdown facilities currently face difficulties such as insufficient drawdown capacity, poor safety and stability of high head structures, extremely high lift hoisting equipment, and high difficulty in high head water seal technology. It is pointed out that the key technologies that need to be urgently addressed for a deep drawdown of high dams and large reservoirs are the pressure-bearing capacity of gates and the capacity limit of hoists. As a result, the elevation of the bottom tunnel of the drawdown building cannot be arranged and the orifice is limited, and the drawdown depth and discharge capacity are limited.

With the increased construction reservoirs, hydropower systems are becoming larger and more complex, which brings challenges of optimal operation of large-scale reservoirs to improve the power generation. To address this efficiently, we propose an aggregation-decomposition method based on cascade reservoir drawdown rule. Based on a two-stage method, we analyze the monotonicity of power generation increment of cascade reservoirs and propose the drawdown rule, which we used to guide the drawdown order of cascade reservoirs. On this basis, we propose an aggregation-decomposition coupling drawdown rule and progressive optimal algorithm (ADDR-POA) method of large-scale reservoirs. To confirm the viability of the proposed approach, we selected 29 series–parallel-mixed reservoirs in the upper Yangtze River Basin in China as the study subjects and optimized them with the goal of maximizing the total power generation. Results show that compared to conventional mathematical optimization method and heuristic algorithm, ADDR-POA can effectively express the compensation effect between reservoirs and has a good performance in improving the total power generation of the basin and reducing iteration times, which presents a novel approach for solving the problem of drawdown operation of large-scale reservoirs.

When a foundation pit is hydraulically connected with surroundings, the dewatering inside the excavation would both induce water-level decline and enclosure wall deflection, which together cause ground settlement outside the excavation. However, the current studies have not fully revealed the settlement behaviour under the combined actions of the above two factors; meanwhile, the individual effect of the two factors on the ground settlement is still indistinguishable. In this study, in situ pumping test and numerical simulations were both conducted to ascertain the above issues. Specifically, a fluid–solid coupling numerical model was developed to simulate a practical foundation pit dewatering test; measured ground settlement and groundwater drawdown were adopted to validate the numerical model; then, a series of numerical simulations were performed to revel the characteristics of ground settlement due to the combined actions of groundwater drawdown and wall movement; on this basis, the individual impacts of the two factors on the ground settlement were separated. Results show that the settlement ratio caused only by enclosure wall movement (ηb) varies in the range of 2.5–43%, depending on the pumping location, pumping time and hydraulic connectivity in strata; ηb is overall greater during the pumping of phreatic aquifer compared to the pumping of confined aquifer, while with the pumping time elapsed, ηb would both decrease apparently regardless of the pumping location.

Delta13C variation through OAE2 is a viable pCO2 proxy Drawdown of pCO2 accompanied organic carbon burial during OAE2 A major driver of Late Cretaceous global climate change was pCO2 Oceanic Anoxic Event 2 (OAE2), spanning the Cenomanian-Turonian boundary (CTB), represents one of the largest perturbations in the global carbon cycle in the last 100 Myr. The 13Ccarb, 13Corg, and 18O chemostratigraphy of a black shalebearing CTB succession in the Vocontian Basin of France is described and correlated at high resolution to the European CTB reference section at Eastbourne, England, and to successions in Germany, the equatorial and midlatitude proto-North Atlantic, and the U.S. Western Interior Seaway (WIS). 13C (offset between 13Ccarb and 13Corg) is shown to be a good pCO2 proxy that is consistent with pCO2 records obtained using biomarker 13C data from Atlantic black shales and leaf stomata data from WIS sections. Boreal chalk 18O records show sea surface temperature (SST) changes that closely follow the 13C pCO2 proxy and confirm TEX86 results from deep ocean sites. Rising pCO2 and SST during the Late Cenomanian is attributed to volcanic degassing; pCO2 and SST maxima occurred at the onset of black shale deposition, followed by falling pCO2 and cooling due to carbon sequestration by marine organic productivity and preservation, and increased silicate weathering. A marked pCO2 minimum (~25% fall) occurred with a SST minimum (Plenus Cold Event) showing >4°C of cooling in ~40 kyr. Renewed increases in pCO2, SST, and 13C during latest Cenomanian black shale deposition suggest that a continuing volcanogenic CO2 flux overrode further drawdown effects. Maximum pCO2 and SST followed the end of OAE2, associated with a falling nutrient supply during the Early Turonian eustatic highstand.

For deep excavations in residual soils that are underlain by highly fissured or fractured rocks, it is common to observe the drawdown of the groundwater table behind the excavation, resulting in seepage-induced ground settlement. In this study, finite element analyses are firstly performed to assess the critical parameters that influence the ground settlement performance in residual soil deposits subjected to groundwater drawdown. The critical parameters that influence the ground settlement performance were identified as the excavation width, the excavation depth, the depth of groundwater drawdown, the thickness of the residual soil, the average SPT N60 value of the residual soil, the location of the moderately weathered rock, and the wall system stiffness. Subsequently, an artificial neural network (ANN) model was developed to provide estimates of the maximum ground settlement. Validation of the performance of ANN model was carried out using additional data derived from finite element analyses as well as with measured data from a number of excavation sites.

Flow Characteristics (FC) is one of the few methods developed for predicting long-term sustainable borehole yield of single wells in typical fractured rock aquifers. The FC method uses drawdown derivatives and subjective information on no-flow boundaries to estimate a sustainable borehole yield that should not cause the water level to drop below the main water strike (fracture) during long-term operations. Since its development, the FC method has been widely applied in many research and consulting projects. Two decades after its development, a review of its technical capabilities and limitations is necessary to enhance understanding among groundwater practitioners while building a platform for further improvements. The main strength of the method is its simplicity of use, its ability to protect the main water strike/fracture, and its lower susceptibility to the influence of aquifer heterogeneities because it does not require the input of aquifer storativity and transmissivity. The FC method also caters to the negative influence of impermeable boundaries, thereby enabling planning for diferent low-yield-causing scenarios. However, the major limitation is in using the subjective closed no-flow boundary without factoring aquifer storativity and the distance of the closed no-flow boundary from the pumping well. Under the influence of the closed no-flow boundary, the water must come from aquifer storage, hence the storativity and the size of the bounded aquifer are very critical parameters. It is therefore incorrect to factor in the influence of the closed no-flow boundary without considering its exact location. This limitation is reflected in the absence of criteria to determine the distance of the closed no-flow boundary from the pumping well for validating the FC results using numerical models. The FC method still needs validation using field operational data; other recommendations for future research are highlighted in the discussion.

More than 5000 landslides or potential landslides have been induced in the Three Gorges Reservoir (TGR) region since the impoundment in 2003, which have caused great damage and remain a huge threat to the dam and people living in the reservoir area. Understanding the deformation characteristics and failure mechanism of the landslides can be helpful in stability evaluation and landslide prediction. The primary aim of this study is to research the characteristics of the landslide motion and its relationships with environmental triggers, taking the Quchi landslide, a large, slow-moving, reactivated landslide in the TGR region, as an example. The instability clearly showed visible signs of movements since 2002, and after that, the slope has been experiencing persistent deformation. By combining 4 years of meteorological, hydrological data with displacement measurements from open fractures, deep boreholes, and surface points, as well as in situ observations, this paper reports the geological and geotechnical investigations performed to define the movement. The deformation is believed to be governed by reservoir water levels, while the precipitation has a minor effect. Seasonally, the slope movement has a very distinctive pattern with large deformation starting abruptly right after reservoir drawdown in June and lasting into late summer (September). Then there is a rapid transition to constant deformation (almost no displacement) as the reservoir level rises. The slope displacements appear to gradually increase every year, which suggests very high possibility of the large and overall failure of the slide. Both monitoring results and geomorphological observations have highlighted that the two active slide masses Q1 and Q2 would probably collapse in different kinematic evolution modes, i.e., the multistage failure and whole sliding motion.

The foehn effect is well known as the warming, drying, and cloud clearance experienced on the lee side of mountain ranges during “flow over” conditions. Foehn flows were first described more than a century ago when two mechanisms for this warming effect were postulated: an isentropic drawdown mechanism, where potentially warmer air from aloft is brought down adiabatically, and a latent heating and precipitation mechanism, where air cools less on ascent—owing to condensation and latent heat release—than on its dry descent on the lee side. Here, for the first time, the direct quantitative contribution of these and other foehn warming mechanisms is shown. The results suggest a new paradigm is required after it is demonstrated that a third mechanism, mechanical mixing of the foehn flow by turbulence, is significant. In fact, depending on the flow dynamics, any of the three warming mechanisms can dominate. A novel Lagrangian heat budget model, back trajectories, high-resolution numerical model output, and aircraft observations are all employed. The study focuses on a unique natural laboratory—one that allows unambiguous quantification of the leeside warming—namely, the Antarctic Peninsula and Larsen C Ice Shelf. The demonstration that three foehn warming mechanisms are important has ramifications for weather forecasting in mountainous areas and associated hazards such as ice shelf melt and wildfires.

Soil organic carbon management has the potential to aid climate change mitigation through drawdown of atmospheric carbon dioxide. To be effective, such management must account for processes influencing carbon storage and re-emission at different space and time scales. Achieving this requires a conceptual advance in our understanding to link carbon dynamics from the scales at which processes occur to the scales at which decisions are made. Here, we propose that soil carbon persistence can be understood through the lens of decomposers as a result of functional complexity derived from the interplay between spatial and temporal variation of molecular diversity and composition. For example, co-location alone can determine whether a molecule is decomposed, with rapid changes in moisture leading to transport of organic matter and constraining the fitness of the microbial community, while greater molecular diversity may increase the metabolic demand of, and thus potentially limit, decomposition. This conceptual shift accounts for emergent behaviour of the microbial community and would enable soil carbon changes to be predicted without invoking recalcitrant carbon forms that have not been observed experimentally. Functional complexity as a driver of soil carbon persistence suggests soil management should be based on constant care rather than one-time action to lock away carbon in soils.Dynamic interactions between chemical and biological controls govern the stability of soil organic carbon and drive complex, emergent patterns in soil carbon persistence.

Slope stability in reservoirs depends on time-dependent triggering factors such as fluctuations of the groundwater level and precipitation. This paper assesses the stability of reservoir slopes over time, accounting for the uncertainty of the shear strength and hydraulic parameters. An intelligent surrogate model has been developed to reduce the computational effort. The capability of two machine learning algorithms, namely Support Vector Regression and Extreme Gradient Boosting, is considered to obtain the relationship between geomechanical parameters and the factor of safety. The probability of failure of a hypothetical reservoir slope is estimated employing Monte Carlo simulations for different scenarios of drawdown velocity. A sensitivity analysis is conducted to investigate the influence of the geomechanical parameters, regarded as random variables, on the probability of failure. The results revealed that the coefficient of variation in the effective friction angle and the correlation between effective cohesion and friction angle have the highest impact on the probability of failure. The intelligent surrogate model can predict the factor of safety of reservoir slopes under rapid drawdown with high accuracy and enhanced computational efficiency.