Abstract Predicting river flow is important for flood management, river erosion protection, navigability update, and so on. The traditional approach to predicting the flow using a hydrodynamic model (HM) requires manual calibration and recalibrations of uncertain parameters; it has faced inefficiency and uncertainty issues. This study aims to explore assimilating observational data of water level and velocity into the HM as a new approach to predicting open-channel flow. The background of this study is that ever advancing technologies for flow monitoring have offered or will soon offer good amounts of data in real time, making data assimilation (DA) practical. The new approach’s novelty lies in combining hydrodynamic laws (via the momentum principle) with data during HM run time without the need for calibrations and optimizing the prediction accuracy while minimizing computing costs. Its performance is validated using observational data from flume experiments and hydrometric stations in the Danube River. The results show that the adaptive proportional–integral–derivative–based DA technique is more efficient than the model-predictive-controller-based DA technique, enhancing the computation efficiency by an order of magnitude. Both techniques automate the correction of the channel-bed friction factor itself, which may also alleviate the impact of other uncertain parameters on the prediction. Both techniques have achieved low relative errors ( < 1 % ). The sequential selection method successfully locates optimal DA stations in the channel, supported by open-channel flow theories. The new approach improves the flow prediction for the entire HM channel. This study has contributed to the development of a robust framework for forecasting open-channel flow in real time.
Abstract This paper presents a numerical sediment transport model based on data from a series of experiments with flow hydrographs of varying lengths in a laboratory flume with a sand bed. The model was calibrated and validated using one flow hydrograph and then applied to other hydrographs. Digital flumes with different initial and boundary conditions were generated to assist numerical simulations and further explore additional scenarios, such as flow rates on the rising limb of the hydrograph, different sediment sizes, and longer hydrographs. Both numerical and experimental results demonstrate the influence of flow hydrograph duration on transport rates, which typically resulted in a counterclockwise hysteresis pattern. Different rising slopes of the flow rate had limited effects on the hysteresis pattern. Coarser sediment yielded lower transport rates, while finer particles led to increased transport rates, though neither caused appreciable changes to the hysteresis pattern. Limited sediment supply resulted in a change in hysteresis pattern from counterclockwise to figure-8. Longer hydrographs led to irregular hysteresis patterns due to the influence of bedforms that developed during peak flows.
Abstract Flood-induced forces on buildings are a key concern for designing resilient infrastructure in flood-prone areas. Standard guidelines in several countries provide simplified approaches to account for different types of loads, such as hydrostatic pressure, impact forces from flood waves or tsunamis, and drag forces. Each type of load depends on specific parameters usually related to the water depth and flow velocity. This study assesses the reliability of various strategies for estimating the forces exerted by floodwaters on buildings, using output from two-dimensional numerical simulations. A review of existing formulations for impact and drag forces was first conducted. In parallel, two computational approaches were investigated: the drag-based method, which relates the force to local momentum flux through empirical coefficients, and the physically based method, which integrates hydrostatic and hydrodynamic pressure contributions obtained from numerical simulations along the building walls. To achieve this, dam-break flow experiments impacting an isolated obstacle were conducted and pressure sensors were used to measure the resulting force. The same configurations were reproduced numerically with a finite-volume shallow-water solver. Simulation outputs were then used to compute forces through the two computational approaches and relevant formulations from the literature, with all results being compared to experimental measurements. Particular attention was paid to mesh resolution: while the physically based method requires a detailed grid explicitly representing the building geometry, the drag-based method can be applied on coarse meshes without geometric representation of the obstacle. The findings highlight that drag-based formulations, when properly calibrated, can provide accurate predictions at low computational cost. Conversely, physically based methods offer a detailed representation of the impact and quasi-steady phases but at the expense of significantly higher computational effort. These results provide new insights into the applicability of existing empirical formulas and guide the choice of modeling strategies for flood risk assessment and structural design.
Abstract Modeling effects of surrounding tree canopy and bluff topography on the wind introduction onto lakes surface remains an ongoing challenge in three-dimensional (3D) hydrodynamic modeling and requires extra costly modeling (e.g., via CFD) prior to the main modeling. We studied and suggested different less costly approaches in such lakes by using the 3D aquatic ecosystem hydrodynamic model. We modeled two adjacent groundwater-fed lakes, Sacrower See (SCR) and Gross-Glienicker See (GGS) in northeast Germany, over a decade. The two lakes with different morphologies are located within a similar forest, climatic, and hydrologic system. The effects of calibrating the wind drag coefficient ( C D ), validity of the Markfort correction, originally developed for one-dimensional (1D) models, and modifying the fetch on the model grid were evaluated and compared to the uncalibrated model and measured water temperature profiles and further compared to an equivalent round lake mimicking quasi-1D conditions in a 3D model. The results show that the Markfort approach does not change or may slightly increase the accuracy of 3D models in the case of the deeper lake (SCR). However, it significantly reduces the accuracy of the model in a shallow lake (GGS) due to neglection of the wind direction and higher sensitivity of the shallower lake to wind. Our results indicate that calibrating C D in tandem with calibrating the heat transfer coefficient ( C H ) results in the highest accuracy in a 3D model of a lake with tree canopy and may be considered a less time- and power-consuming approach, as these two coefficients reflect the most important surface exchanges between the lake and the atmosphere. By modeling two lakes with different morphologies and slightly different surroundings, we showed that our findings are applicable to different lakes.
Abstract Coastal dunes are naturally occurring barriers that serve as defense measures from wave action and storm inundation. To combat coastal erosion, sediment placement efforts consisting of man-made dune construction are commonplace to protect coastal communities and shoreline infrastructure. Few dune construction practices consider the differences between man-made dunes and naturally established dunes regarding engineering and ecosystem services. Vegetation’s role in dune stability has previously been well-documented through field data collection and laboratory experiments, including synthetic or transplanted vegetation. However, limited laboratory comparisons exist between these synthetic vegetation options and naturally formed vegetated dunes. A novel physical modeling experiment was conducted where a naturally established dune transect from the US Southeast Coast was sampled and transported to a wave flume facility for testing under controlled wave conditions. Here, a naturally formed dune with established vegetation is compared to a sand-only dune and a dune constructed with synthetic vegetation. It was confirmed that both the naturally formed dune and the constructed, synthetically vegetated dune were significantly more effective in preventing erosion than a constructed, unplanted, sand-only dune. During testing, the sand-only dune failed 68% sooner than the natural and synthetic dune, furthering the potential of synthetic vegetation as a viable surrogate material for improving dune resiliency during initial dune construction.
In the optimization of cascade reservoir operation for power generation,traditional methods such as dynamic programming suffer from bottlenecks like low computational efficiency,limiting their practical engineering applications.Although single-agent deep reinforcement learning(DRL)can achieve continuous control in an end-to-end manner,it struggles to effectively capture the dynamic couplings among cascade reservoirs,potentially leading to unstable policy gradients and training oscillations.Moreover,treating the cascade reservoir system as a single entity limits scalability.To address these issues,this paper proposes a multi-agent deep reinforcement learning(MADRL)method for cascade reservoir operation based on the"Centralized Training and Decentralized Execution"framework.Each reservoir is treated as an independent agent,and a collaborative network integrating local decision-making with global information sharing is constructed to enhance training stability.A global reward function is designed,combin-ing power generation benefit with constraint penalty terms.Furthermore,the Copula-Gibbs joint distribution is intro-duced to generate runoff scenarios,improving adaptability to inflow uncertainty.Finally,hyperparameter combina-tions,including network architecture,discount factor,and learning rate,are tuned through sensitivity analysis and grid search.Engineering application results show that,under identical hardware and data conditions,the proposed method can achieve faster convergence.While strictly adhering to end-of-period water level and operational safety constraints,it achieves online inference times of 6.5 to 8.5 ms in 4 and 6 reservoirs cascaded system,which is approximately two orders of magnitude faster than discrete differential dynamic programming(DDDP).Under dry,normal,and wet typical inflow scenarios,the annual power generation deviation is controlled within 0.65%,and the end-of-period water level control accuracy is satisfactory.In conclusion,the multi-agent collaborative mechanism effectively addresses challenges posed by high-dimensional decision-making and system coupling,enhancing the environmental adaptability and engineering practicality of operational strategies.This provides reliable methodologi-cal support for efficient operation of large-scale cascade reservoirs.
Abstract The paper investigates the turbulent flow generated by a wall jet. A numerical benchmark of six turbulence closures including two-equation and seven-equation models in their high- or low-Reynolds number formulations, is performed. The Standard k - ε , Realizable k - ε , k - ω SST, the linear and quadratic pressure-strain Reynolds Stress Models (RSM) and RSM based on ω available within Ansys Fluent 2023R2 and OpenFOAM v11 are systematically compared with reference experimental data available from the literature for the jet Reynolds number of R e j = 9,600 . Generally, the specific dissipation rate ω appears to be a better candidate than ε to determine the length scale of the turbulence for this particular configuration. Thus, the k - ω SST and RSM- ω models perform better than the others to predict the wall jet spreading rate, maximum Reynolds number or friction coefficient. The linear pressure-strain RSM fails to predict the mean streamwise velocity profile, exhibiting a large deficit in the log region. A budget analysis of the turbulence kinetic energy transport equation is also performed for the low-Reynolds number models. The intriguing behavior of the linear pressure-strain RSM is confirmed by the production term’s profile, which peaks earlier than the other models at about y + ≃ 5 . Overall, the k - ω SST model can be recommended because it offers a good trade-off between accuracy and computational efforts.
Abstract Gravel transport is difficult to measure in streams and rivers, but it is needed for assessing the impact of dam removal on river systems, for studies of streambed ecology, for steam restoration, and for engineering design of in-channel structures. The measurement of gravel transport is particularly challenging because it is both temporally and spatially heterogenous, it must sometimes be measured at remote locations, and it is labor-intensive and time consuming. Steel plates equipped with accelerometers that are installed in a channel bed can be used for automated measurement of gravel transport by detecting the impacts of gravel particles being transported in the channel. In this study, two accelerometer-equipped stainless-steel impact plates were installed in the Goodwin Creek Experimental Watershed (GCEW) near Batesville, MS. Flow and transport rates from 30 flow events are presented here to show the efficacy of the system and to study gravel bedload in Goodwin Creek. It was found that flow events typically produced clockwise transport rate hysteresis, likely indicating supply-limited conditions for gravel on the falling limbs of hydrographs. The data collected during the study are useful for modeling efforts, the development of gravel bedload measurement techniques and methods, and understanding GCEW hydrology.
The hydraulic friction parameters of pipelines are among the most crucial hydraulic parameters for the operation scheduling and digital-intelligent construction of long-distance water diversion projects.For a long time,issues such as a wide variation range of recommended values and a lack of field calibration based on measured data have persisted,affecting pipe design and accurate regulation.Based on the prototype tests conducted on DN2800 and DN3200 pressure water pipelines of the Yinchuojiliao Water Diversion Project,this paper systematically studies the values and variation patterns of the Manning roughness coefficient,Hazen-Williams coefficient and equivalent rough-ness.The results indicate that the pipeline roughness coefficient decreases with increasing flow velocity and increases with increasing pipe diameter,showing a positive correlation with flow velocity to the power of-0.1.When a constant roughness coefficient is used,the calculation error for head loss can range from 10%to 20%.The measured Hazen-Williams coefficient ranges from 145 to 150,which is greater than the recommended values in most specifications.Assuming a constant Hazen-Williams coefficient can lead to a calculation error of 5%to 10%in head loss.The equivalent roughness of PCCP pipelines with cement mortar-lining should be taken as 0.05 mm.When the equivalent roughness is reduced from 0.05 to 0.01 mm for the velocity of 1.5 m/s,the roughness coefficients of DN2800 and DN3200 pipelines decrease from 0.1071 to 0.010 34 and from 0.010 83 to 0.010 46,respectively,representing reductions of 3.45%and 3.42%.This indicates that the roughness coefficient of 0.009 or lower cannot be achieved.
The patrol inspection of water conservancy projects is a core management task for ensuring the safe and stable operation of critical infrastructures.Traditional patrol inspections suffer from high reliance on manual labor,low accuracy in hazard identification,and insufficient dynamic decision-making capabilities.This paper proposes a multi-agent collaborative intelligent decision-making framework that integrates Large Language Models(LLMs)and Graph Retrieval-Augmented Generation(GraphRAG)technologies.Adopting a modular architecture encompassing perception,memory,communication,planning,and action,the framework achieves full automation of the patrol inspection processes.A multi-modal dataset was constructed using multi-source patrol inspection data from the past three years.Domain-adaptive fine-tuning significantly improved the F1 scores of multi-modal large language models in equipment recognition and defect detection by 7.2%and 6.9%,respectively.Furthermore,a dynamic knowledge graph system based on Graph RAG was developed to bridge domain-specific knowledge gaps through knowledge infu-sion techniques,while simultaneously employing an entity-relation reasoning mechanisms to effectively mitigate model hallucinations.Experimental results demonstrate that patrol inspection reports generated by this method,upon dual evaluation by both domain experts and operational maintenance personnel,accurately reflect the professional expertise and technical depth required in operations and maintenance of water conservancy projects.This research provides a novel,interpretable,and reliable technical paradigm for intelligent operation and maintenance of water infrastructure,holding significant engineering application value for advancing digital transformation within the indus-try.
Report review serves as a core link in project quality control.Traditional manual review methods face chal-lenges such as inefficiency and inconsistent standard implementation,while existing general-purpose review systems struggle to adapt to the multiple challenges posed by the complex structural characteristics,multidimensional review tasks,and domain knowledge dependencies inherent in water resources science and technology reports.To address this,this study proposed an agent-based formal review system architecture for such reports.Through agent-driven dynamic task planning and collaborative review mechanisms,adaptive parsing of complex report structures and multi-task orchestration were realized.A water resources domain knowledge enhancement mechanism was established based on LoRA fine-tuning and Retrieval-Augmented Generation(RAG)technology.A terminology knowledge base con-taining 27,005 specialized water resources terms and a computational relationship database were constructed,form-ing a command fine-tuning dataset with 10,358 samples.The system's review capabilities in tasks involving special-ized terminology,computational logic,and contractual consistency was enhanced.Benchmarked against human review results,the agent system achieved an average F1 score above 80%across eight types of review tasks.Experi-mental results demonstrate that this system enables fully intelligent processing for the formal review of water resources science and technology reports,significantly improving efficiency while ensuring review accuracy.The intelligent review system developed in this study provides standardized tool support for quality management of water resources project documentation and offers a reference technical pathway for the intelligent review of texts in specialized domains.
In recent years,extreme flash flood events in mountainous watersheds under the combined influence of cli-mate change and human activities have occurred more frequently.Characterized by sudden onset and high destructive potential,these events pose significant challenges to China's disaster prevention and mitigation efforts.This study employs the spatiotemporally-variable-source distributed hydrological model(SKY-HydroSAT),independently developed by the China Institute of Water Resources and Hydropower Research,to establish a distributed hydrologi-cal model considering reservoir regulation in the upper catchment of the Guilin City in the Lijiang River Basin.The model demonstrates good applicability,with absolute peak flow errors of 3.7%and 5.4%during the calibration and validation periods,respectively,and Nash-Sutcliffe efficiency(NSE)values of 0.87 and 0.83.Taking the"6·19"extreme flash flood event in 2024 as a case study,with the accurate modelling results(peak flow error 10.5%,NSE 0.94),the research investigated the flood dynamics under reservoir influence.The analysis reveals that this event was triggered by a bimodal heavy rainfall pattern,with a three-day average rainfall of 442 mm across the watershed above Guilin and a maximum cumulative rainfall of 777 mm at Maolingjiao Station.Simulation results indicate the formation of combined infiltration-excess and saturation-excess runoff mechanisms,along with subsurface stormflow in major runoff-producing areas,leading to rapid runoff generation and posing severe challenges to midstream reservoirs and downstream flood safety.The joint operation of 4 upstream reservoirs upstream of Guilin played a crucial role in flood control and disaster mitigation.Without reservoir regulation,the peak flow at Guilin Station would have exceeded the 100-year return period level.After regulation by the upstream reservoirs,the peak flow at Guilin Stationwas reduced to 6380 m³/s(approximately equivalent to a 30-year return period flood),significantly mitigating downstream disas-ter losses.This study validates the applicability of the distributed hydrological model in the Guilin region,demonstrat-ing its capability to accurately characterize watershed runoff mechanisms and quantify the benefits of regulation by hydraulic projects.The proposed approach holds potential for extension to other mountainous watersheds in China and can provide scientific support for regional flood management decision-making.
To address the key problems in 3D finite element mesh generation for rockfill dams with complex dam foundation topography—such as difficulties in fitting the boundaries between different material zones and filling stages,controlling the meshes of the transition zone between the dam body and foundation,and accurately represent-ing the excavation boundaries—an adaptive 3D finite element mesh generation method for rockfill dams is proposed.The method employs element transformation to adaptively fit complex boundaries of material zones and filling stages.A transition factor for the meshes of the dam body and foundation is constructed using fractal theory to control the rate of element size variation and adaptively generate the foundation transition zone.A rigorous terrain cutting surface fit-ting algorithm for 3D meshes is developed based on a chained dimension-reduction scheme of"body-face-edge-vertex",enabling the generation of a 3D dam foundation mesh that accurately reflects the excavation surface.Statisti-cal analyses of mesh quality indicators—including aspect ratio,parallel deviation,maximum angle,and Jacobian ratio—for the 3D meshes of five dams generated using this method demonstrate that the method is featured by control-lable overall mesh quality meeting the shape quality requirements for subsequent finite element analysis,and signifi-cantly improved efficiency of 3D modeling.This method enables adaptive generation of rockfill-dam finite element meshes from 2D maximum cross sections to 3D finite element models,providing an efficient and reliable preprocess-ing approach for refined numerical simulation of rockfill dam body-foundation systems with complex dam foundation topography.
Fish passage facilities have been the subject of ongoing debate in China for decades regarding their neces-sity and effectiveness since the construction of the Gezhouba dam.The aim of the present study was to critically assess theories that support and question the efficacy of fish passage facilities.Through comparative case analysis and theo-retical examination,the present study moves beyond the superficial"fish rescue debate"to explore underlying eco-logical theoretical roots and practical challenges.Three typical cases—the Gezhouba dam,Poyang Lake Water Con-trol Project,and new Three Gorges shipping channel—reveals conflict between"human-led restoration"and"preser-vation of natural processes."Based on this,this paper introduces the theory of heavily disturbed river ecology,ana-lyzes the scientific validity and effectiveness of current fish protection measures for water conservancy and hydro-power projects such as ecological flow,fish passage facilities,and proliferation and release,and demonstrates the significance of prioritizing habitat protection and restoration.A systematic strategic framework for fish conservation is developed,proposing coordinated efforts across five dimensions:integrated planning of fish conservation measures,prioritizing the restoration of natural flow regimes,systemic advancement of habitat restoration,targeted implementa-tion of stock enhancement,and scientific design of fish passage facilities.Ultimately,this framework aims to shift from project-level compensation to holistic watershed ecosystem restoration,providing scientific guidance for promot-ing the ecological construction and high-quality development of water projects in China.
Following the impoundment of the Longyangxia Reservoir in 1986,the mean flood peak discharge recorded at the Guide hydrological station decreased by 46.62%,indicating significant non-stationarity.However,methods for quantifying the reservoir regulation effect are still immature,leading to difficulties in ensuring the accu-racy of design floods,thereby seriously compromising both flood control safety and the multiple-purpose benefits of water resources projects.This study,taking the Longyangxia Reservoir as the research object,proposes the Available Flood Control Reservoir Index(ACRI)as a quantitative indicator of reservoir regulation effects.By integrating the Copula theory with the mechanism-based reconstruction method(Me-RS),a nonstationary flood frequency analysis was conducted,incorporating historical flood investigation data.The results show that the source-tracing reconstruc-tion method based on ACRI can accurately represent the reservoir's regulation effect on downstream flood peak regimes and effectively reconstruct the flood peak series into a stationary state.The design flood peaks derived using the Pearson Type Ⅲ distribution deviate by less than 3%from the original design values.Incorporating historical flood investigation data further improves the goodness-of-fit of the probability distribution,reducing the RMSE by 12.87%and increasing the 10,000-year design flood peak by 10.23%compared to the estimate that excludes histori-cal flood.Owing to flow regulation by the Longyangxia Reservoir,the design flood peak discharges at Guide for return periods of 50 to 10,000 years show an average reduction of 38.30%relative to the original design values.The nonsta-tionary flood frequency analysis method proposed in this study—accounting for reservoir regulation effects and inte-grating historical flood investigation data—can more accurately characterize the probability distribution of flood peaks,enhance the reliability of design flood estimation,and support flood control and water resources management at the river basin scale.
Abstract In this paper, finite-depth seepage beneath weirs equipped with double sheet piles and a downstream step is analytically investigated. The Schwarz–Christoffel transformation is employed to conformally map both the physical plane and the complex potential plane onto an auxiliary semi-infinite lower-half plane. The seepage characteristics, such as seepage discharge, exit gradient, and pressure head distribution along the weir floor, are determined by applying the similarity conditions between the original and transformed planes. The results reveal that the seepage characteristics depend on several key parameters, including the upstream sheet pile depth, downstream sheet pile depth, upstream floor length, downstream floor length, and downstream step depth. The seepage discharge diminishes as the upstream sheet pile depth, downstream sheet pile depth, upstream floor length, and downstream floor length increase. Conversely, the seepage discharge increases with an increase in the downstream step depth. Additionally, the exit gradient decreases with an increase in the upstream sheet pile depth, downstream sheet pile depth, and upstream floor length. In contrast, it attains a peak magnitude at a specific value of the downstream floor length. Moreover, the exit gradient increases with an increase in the downstream step depth. For a given sheet pile location, the pressure head increases and decreases in the upstream and downstream regions, respectively. Furthermore, an increase in the downstream step depth induces a reduction in the pressure head. The predictions of the present study are consistent with those of existing studies.
