3D Hydrodynamic Model Research Articles

Dam Breach Analysis and Damage Assessment of Nova Kakhovka Dam using Satellite data and 1D and 2D Hydrodynamic Modeling

Dam Breach Analysis and Damage Assessment of Nova Kakhovka Dam using Satellite data and 1D and 2D Hydrodynamic Modeling

Embankment Breach Simulation and Inundation Mapping Leveraging High-Performance Computing for Enhanced Flood Risk Prediction and Assessment

Abstract. Embankment breaches represent significant hazards to communities and infrastructure, precipitating catastrophic flood occurrences. The precise prediction of floods and understanding the scope of inundation stemming from embankment failures are imperative for effective disaster preparedness and response. This research delves into a case study on simulating embankment breaches to evaluate the extent of flooding. Leveraging advanced hydrodynamic models validated through high-performance computing (HPC) systems, and integrating real-time data assimilation, we aim to improve accuracy in flood forecasting. The study endeavours to bolster flood risk management by furnishing detailed inundation maps and insights into embankment breach dynamics, thereby facilitating enhanced preparedness and response strategies. Our findings reveal that simulations conducted on multicore processors offer superior performance compared to single-core setups, yielding enhanced result accuracy and providing administrators with increased lead time. It unlocks high-resolution simulations for intricate basin details, explores a wider range of flood scenarios quickly, and allows for efficient ensemble modelling to assess model uncertainty. Through HPC utilization, we can harness high-resolution digital elevation models (DEMs) for 2D-hydrodynamic modelling, enabling rapid assessment of water spread resulting from embankment breaches within a mere 20-minute timeframe, a significant improvement from the previous 3–4 hours duration.

Impact of Three Gorges Dam construction on spatiotemporal variations in the hydrodynamic regime of Poyang Lake (China)

As an important large-scale river-connected lake in the middle–lower reaches of the Yangtze River, Poyang Lake has complex interactions with the main stream of the river. The full operation of the Three Gorges Dam (TGD) on the main stream of the Yangtze River has caused substantial changes in the relationship between the river and the lake, and the hydrological and hydrodynamic regime of Poyang Lake have also shown obvious variations in response. This study constructed a 2D hydrodynamic model of Poyang Lake based on GPU acceleration to realize a long-term simulation of the water flow evolution of Poyang Lake. By comparing the differences in water level at Hukou station between 20-year periods before and after TGD construction, the impact of TGD construction on Poyang Lake was characterized. Results showed that in comparison with the values for the pre-dam period, the water level of Poyang Lake decreased by 0.4–2.0 m and the flow velocity increased by 0.01–0.04 m/s in the post-dam period, and both showed a trend of reduction spatially from the north toward the south. Additionally, the inundation area of the lake decreased by 9 %, the 10-m characteristic water level at Xingzi station advanced by 27 days, the duration of low water extended by 37 days, and in typical dry, normal, and wet years, the time of occurrence of low water advanced. Moreover, TGD construction has aggravated the conditions of Poyang Lake in the dry season. The findings of this study are of great importance in relation to refining the spatiotemporal distribution characteristics of habitats, and supporting further investigation of the changes in the aquatic ecosystem of Poyang Lake under TGD regulation.

Glacial lake outburst flood risk assessment of a rapidly expanding glacial lake in the Ladakh region of Western Himalaya, using hydrodynamic modeling

The ongoing trend of warming climate has made Glacial Lake Outburst Floods (GLOFs) a major cryospheric hazard worldwide, especially in the Himalayas. GLOFs in the Himalayan region are mostly caused by moraine-dammed proglacial lakes and ice-dammed lakes. These sporadic disasters have resulted in significant loss of life and property. This study offers a comprehensive analysis of the GLOF hazard potential of a potentially dangerous proglacial lake (PDGL) in the Ladakh region. This research explores the GLOF threat from the lake using multi-criteria analysis and advanced 2D hydrodynamic modeling approaches. The mass balance response of the mother glacier, its flow dynamics, and glacier-lake interactions were examined for the past 22 years. The findings show that over this period, the PDGL has had a notable expansion of 78.7%, accompanied by a significant recession of 13.2% in its feeding glacier. The glacier has witnessed an average thickness loss of ⁓7 m at the rate of 0.32 m a−1 during this period. The average, lowest, and maximum depth of the glacier were found to be 30.95, 14.30, and 50.57 m, respectively and the average velocity of the glacier was estimated as 3.38 m a−1. Because of the lake’s rapid expansion and steep surrounding slopes, it was classified as a high-hazard lake. The risk to the downstream community was assessed through 2D hydrodynamic modeling using the HEC-RAS tool. The maximum discharge under the worst-case scenario for the piping and overtopping failures was estimated as 3890.99 m3s−1 and 5111.39 m3s−1, respectively. The area potentially under the threat of inundation was calculated to be 4.74 and 5.38 km2 for the moderate and worst-case scenarios respectively. The expected maximum flood velocities range from 18.26 to 23.78 meters, respectively for the moderate and worst-case scenarios. At several locations in the downstream area, routed hydrographs representing the GLOF propagation were generated. The findings show that the flood wave in the worst-case scenario would arrive at the first settlement in 50 min, with a peak velocity of 12.36 m s−1. The potentially inundated area includes critical infrastructure such as bridges, residential houses, and roads. To mitigate the potential risk associated with this lake, a more detailed and on-site study is highly recommended.

Buffer properties in the Guadalquivir Estuary (SW Iberian Peninsula)

The Guadalquivir Estuary (main source of continental waters to the Gulf of Cadiz) has a carbonate basin, which enables the transport of inorganic carbon to adjacent coastal areas. Therefore, in order to study the dynamic of the carbonate system and its buffer capacity, a total of 12 samplings were carried out from 2017 to 2022. Samplings included longitudinal transects and tidal cycles in different seasonal and tidal conditions. Total alkalinity (TA) and dissolved inorganic carbon (DIC) showed increased values upstream, while calcium (Ca2+) presented the highest values in most of the marine samples. The ranges values obtained for these three variables were of 2180–5140 μmol kg−1, 430–3950 μmol kg−1 and 1295–10,855 μmol kg−1 for TA, DIC and Ca2+, respectively. Two buffer factors (βDIC and βH) were also calculated to study the variability of the buffer capacity of the Guadalquivir Estuary. These indicate that the estuary is well buffered for salinities above 10, while the inner part is more vulnerable to acidification effects. Using a non-linear 1D hydrodynamic model, net inorganic carbon system transports were calculated, showing that the Guadalquivir Estuary is exporting TA, DIC and Ca2+ to the Gulf of Cadiz.

A multi-scale IMEX second order Runge-Kutta method for 3D hydrodynamic ocean models

Understanding complex physical phenomena often involves dealing with partial differential equations (PDEs) where different phenomena exhibit distinct timescales. Fast terms, associated with short characteristic times, coexist with slower ones requiring relatively longer time steps for resolution. The challenge becomes more manageable when, despite the varying characteristic times of fast and slow terms, the computational cost associated with faster terms is significantly lower than that of slower terms. Additionally, slower terms can also exhibit two distinct longer characteristic times, adding complexity to the system and resulting in a total of three characteristic timescales. In this paper, an innovative split second-order IMEX (IMplicit-EXplicit) temporal scheme is introduced to address this temporal complexity. It is used to solve the primitive equation ocean model. Extremely short times are handled explicitly with small time steps, while longer timescales are managed explicitly and semi-implicitly using larger time steps. The decision to solve a portion of the slower terms semi-implicitly is due to the fact that it does not significantly increase the total computational cost, allowing for greater flexibility in the time step without imposing a substantial burden on the overall computational efficiency. This strategy enables efficient management of the various temporal scales present in the equations, thereby optimizing computational resources. The proposed scheme is applied to solve 3D hydrodynamics equations encompassing three time scale: fast terms representing wave phenomena, slow terms describing horizontal aspects and stiff terms for vertical ones. Furthermore, the scheme is designed to respect crucial physical properties, namely global and local conservation. The obtained results on different test cases demonstrate the robustness and efficiency of the IMEX approach in simulating these complex systems.

Research on the hydraulic response characteristics during the water conveyance process of water diversion projects

Abstract During the initial trial period, the Hanjiang-to-Weihe River Valley Water Diversion Project (HWRVWD) sourced water from the Sanhekou water conservancy junction. It then transferred water through the Qinling water conveyance tunnel and distributed it at the Huangchigou water distribution hub, ultimately transporting it to the Guanzhong area. The hydraulic simulation and real-time control of the water conveyance system play a crucial role in ensuring the safe and efficient operation of this engineering project. To maintain water transfer safety and reasonable scheduling during the water supply process, the hydraulic characteristics of the transient process were calculated and analyzed in this paper. The one-dimension (1D) hydrodynamic mathematical model and advection-dispersion model were established to calculate the hydraulic factors of the 81.78 km Qinling water conveyance tunnel and the Huangchigou water distribution hub within the HWRVWD. Validation results showed that the root mean squared error tended toward zero and the coefficient of determination exceeded 0.97 between the measured values and the simulated values. The opening of gates and upstream inflow directly affected water level variations and storage. Smaller gate openings led to increased water level amplitudes before the gate and faster reaching of maximum water levels, but it also led to opposite trends in flow rates behind the gate compared to upstream water levels. The impact of incoming water flow rates on flow variations at different channel sections was significant. The time for water heads to reach each section and the rate of flow variation positively correlated with incoming water flow rates. Gradual increases in upstream inflow resulted in progressively larger water level amplitudes both before and behind the gate, with an increased maximum value, but more water might be discarded. When the water demand changes, the primary focus is on controlling the upstream inflow, with gate opening adjustments as a secondary measure, to achieve the goal of minimizing or eliminating water wastage.

A probabilistic framework for offshore aquaculture suitability assessment using bivariate copulas

Aquaculture at sea is gaining increasing importance, not only as a (local) food source but also due to its potential of being combined with other offshore activities such as wind parks. Nevertheless, experience of offshore aquaculture is limited. This study aims to provide a framework to evaluate offshore aquaculture suitability accounting for the probabilistic dependence between relevant variables. This framework is applied to obtain suitability maps of aquaculture for the North Sea for the blue mussel Mytilus edulis and the sugar kelp Saccharina latissima. For each of these species, three ecological variables are selected and the optimal growth and critical survival limits are defined. Here, suitability is defined as the probability of meeting these conditions. Data on the selected variables is extracted from a large-scale 3D hydrodynamic and ecological model of the northwest European Shelf, of which daily extremes are sampled. The probabilistic model is developed using bivariate copula models, which are fitted to each variable pair to describe their joint distribution function at each studied location. Empirical distribution functions are used to describe the univariate distribution function of each variable and location. Using Monte-Carlo simulations, the probability of meeting the optimal and critical limits is estimated and suitability maps accounting for the probabilistic dependence between the variables are generated. In addition, suitability maps disregarding the dependence are generated and compared to those accounting for the probabilistic dependence. It was found that considering the dependence between variables significantly improves the accuracy of the results for optimal and critical growth conditions for both species. The presented method allows to identify potential areas where blue mussel and sugar kelp cultivation is the most suitable. For instance, in this study, a north-south elongated area west of the German and Danish coast appears to be most suitable for blue mussels, while estuaries and rivers are found the most suitable for the sugar kelp.

The Development of Coupled 1D–2D Hydrodynamic Flood Model by Using HEC-RAS: a Case Study of the Panchganga River Basin, Kolhapur District, Maharashtra, India

The Development of Coupled 1D–2D Hydrodynamic Flood Model by Using HEC-RAS: a Case Study of the Panchganga River Basin, Kolhapur District, Maharashtra, India

Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques

Urban flood risks have intensified due to climate change and dense infrastructural development, necessitating innovative assessment approaches. This study aimed to integrate advanced hydrodynamic models with machine learning (ML) techniques to improve urban flood prediction and hazard analysis. Integrating 1D and 2D hydrodynamic models calibrated with precise parameters demonstrated exceptional predictive accuracy for flood dynamics. The high-resolution Lidar images and sophisticated modeling were used to simulate flood scenarios for the River Thames in West London. The socioeconomic data were incorporated to map vulnerable zones accurately. The findings revealed that 2D hydrodynamic models, while computationally intensive, offered superior accuracy in predicting flood dynamics. In contrast, 1D models could have been more accurate in predicting inundation depth and extent in adjacent urban areas. Advanced ML models, such as the Extra Trees-Principal Component Analysis (ET-PCA) model, further instilled confidence in the reliability of the research findings, demonstrating near-perfect predictive reliability with an R2 of 0.999. This model provided near-perfect predictions and enabled precise flood risk zoning. The integration of socioeconomic data further highlighted the vulnerability of certain urban areas. It emphasized the importance of targeted flood mitigation strategies. Beyond the specific case study, this research demonstrated the potential of combining hydrodynamic simulations with ML to enhance urban flood resilience globally. This framework helps urban planners and policymakers devise effective flood mitigation strategies and improve infrastructure resilience against future flood events.

Hydrodynamic reconstruction of the paleoflood from the Early Holocene ice-dammed lake Nedre Glomsjø, Norway

Study regionNorway Study focusNumerous geological traces provide evidence for the existence, size and catastrophic drainage of the Early Holocene glacial lake Nedre Glomsjø in southern Norway. We present, for the first time, a hydraulic reconstruction that links the three domains of the glacial lake outburst flood process chain: lake hypsometry, tunneling under the remnant ice sheet and subsequent deluge downstream. This is done by first reconstructing the hypsometry of the lake using paleo shorelines observed from modern high-resolution elevation data. The development of an ice tunnel under the remnant ice sheet is then simulated using an ensemble approach to determine a suite of hydrographs for the range of possible parameter combinations. These hydrographs are applied as upstream input to a 2D hydrodynamic model of the flood propagation. The flood marker dataset includes abundant landforms and flood traces at multiple scales, such as erosive paleostage indicators, sediment records and large-scale flood bars. The results from each domain are constrained by the flood marker dataset, which adds to the robustness of our interpretation. New hydrological insights for the regionThe reconstruction shows that glacial lake Nedre Glomsjø covered roughly 1250 km2, and that ∼100 km3 of water was available for drainage. The peak discharge of the glacier lake outburst flood was at least 1.5 ×106 m3/s and probably closer to 2.0 ×106 m3/s. Our results demonstrate the benefit of assembling the entire process chain from glacial lake, tunnel expansion and flood propagation in a single modeling framework to give robust results that satisfy multiple geological constraints for each component of the glacial lake outburst flood (GLOF) system. The methodology described in this paper can be applied to contemporary and future glacial lakes to better predict GLOFs in a changing climate.

Measurement of Anisotropies in Supernova Remnant Observations and Their Interpretation Using Numerical Models

Supernova remnants (SNRs) exhibit varying degrees of anisotropy, which have been extensively modeled using numerical methods. We implement a technique to measure anisotropies in SNRs by calculating power spectra from their high-resolution images. To test this technique, we develop 3D hydrodynamical models of SNRs and generate synthetic X-ray images from them. Power spectra extracted from both the 3D models and the synthetic images exhibit the same dominant angular scale, which separates large-scale features from small-scale features due to hydrodynamic instabilities. The angular power spectrum at small length scales during relatively early times is too steep to be consistent with Kolmogorov turbulence, but it transitions to Kolmogorov turbulence at late times. As an example of how this technique can be applied to observations, we extract a power spectrum from a Chandra observation of Tycho’s SNR and compare with our models. Our predicted power spectrum picks out the angular scale of Tycho’s fleecelike structures and also agrees with the small-scale power seen in Tycho. We use this to extract an estimate for the density of the circumstellar gas (n ∼ 0.28 cm−3), consistent with previous measurements of this density by other means. The power spectrum also provides an estimate of the density profile of the outermost ejecta. Moreover, we observe additional power at large scales, which may provide important clues about the explosion mechanism itself.

Flood Simulation in the Complex River Basin Affected by Hydraulic Structures Using a Coupled Hydrological and Hydrodynamic Model

Due to the complexity of terrain and climate in the mountain–plain transition zone, it is difficult to simulate and forecast the flow discharge of river basins accurately. The poor regularity of the river thus leads to uncertain flood control scheduling. Meanwhile, reservoirs and flood detention areas are constructed to store and divert water when severe floods threaten the safety of the basin. In order to improve the accuracy of flood forecasts and the effectiveness of flood control, a hydrological and 1D/2D hydrodynamic coupling model was developed to enable the joint computation of multiple objects, including mountainous streams, plains river networks, hydraulic control structures, and flood detention areas. For the hydrological component, the Xin’anjiang model with the Muskingum module is employed to simulate mountainous flow discharge. For the hydrodynamic component, the Saint–Venant equations and shallow water equations are applied to estimate flood processes in rivers and on land surfaces, respectively. The Dongtiaoxi River Basin in Zhejiang Province, China, serves as the case study, where river flow is influenced by both upstream mountainous floods and downstream backwater effects. Using the integrated model, flood routing and scheduling are simulated and visualized. Both the Xin’anjiang model and the 1D hydrodynamic model demonstrate over 80% acceptability in calibration and validation, confirming their robustness and reliability. Meanwhile, inundation in flood detention areas can be effectively estimated by coupling the 1D and 2D hydrodynamic models with a flood diversion scheduling model. The coupled model proves capable of simulating flood routing in complex river basins that include mountains, plains, and hydraulic control structures, accounting for the interactions between hydrological elements. These findings provide a new perspective on flood simulation in other similarly complex river basins.

Modelling Soil Moisture Content with Hydrus 2D in a Continental Climate for Effective Maize Irrigation Planning

In light of climate change and limited water resources, optimizing water usage in agriculture is crucial. This study models water productivity to help regional planners address these challenges. We integrate CROPWAT-based reference evapotranspiration (ETo) with Sentinel 2 data to calculate daily evapotranspiration and water needs for maize using soil and climate data from 2021 to 2023. The HYDRUS model predicted volumetric soil moisture content, validated against observed data. A 2D hydrodynamic model within HYDRUS simulated temporal and spatial variations in soil water distribution for maize at a non-irrigated site in Hungary. The model used soil physical properties and crop evapotranspiration rates as inputs, covering crop development stages from planting to harvest. The model showed good performance, with R² values of 0.65 (10 cm) and 0.81 (60 cm) in 2021, 0.51 (10 cm) and 0.50 (60 cm) in 2022, and 0.38 (10 cm) and 0.72 (60 cm) in 2023. RMSE and NRMSE values indicated reliability. The model revealed water deficits and proposed optimal irrigation schedules to maintain soil moisture between 32.2 and 17.51 V/V%. This integrated approach offers a reliable tool for monitoring soil moisture and developing efficient irrigation systems, aiding maize production’s adaptation to climate change.

Characterizing PFASs in aquatic ecosystems with 3D hydrodynamic and water quality models

Understanding how per- and polyfluoroalkyl substances (PFASs) enter aquatic ecosystems is challenging due to the complex interplay of physical, chemical, and biological processes, as well as the influence of hydraulic and hydrological factors and pollution sources at the catchment scale. The spatiotemporal dynamics of PFASs across various media remain largely unknown. Here we show the fate and transport mechanisms of PFASs by integrating monitoring data from an estuarine reservoir in Singapore into a detailed 3D model. This model incorporates hydrological, hydrodynamic, and water quality processes to quantify the distributions of total PFASs, including the major components perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS), across water, particulate matter, and sediments within the reservoir. Our results, validated against four years of field measurements with most relative average deviations below 40%, demonstrate that this integrated approach effectively characterizes the occurrence, sources, sinks, and trends of PFASs. The majority of PFASs are found in the dissolved phase (>95%), followed by fractions sorbed to organic particles like detritus (1.0–3.5%) and phytoplankton (1–2%). We also assess the potential risks in both the water column and sediments of the reservoir. The risk quotients for PFOS and PFOA are <0.32 and < 0.00016, respectively, indicating an acceptable risk level for PFASs in this water body. The reservoir also exhibits substantial buffering capacity, even with a tenfold increase in external loading, particularly in managing the risks associated with PFOA compared to PFOS. This study not only enhances our understanding of the mechanisms influencing the fate and transport of surfactant contaminants but also establishes a framework for future research to explore how dominant environmental factors and processes can mitigate emerging contaminants in aquatic ecosystems.

A large-scale hydrological and hydrodynamic coupled model for flow routing in the Yangtze-Dongting system

In lowland alluvial river systems consisting of mainstream, distributaries, and floodplain lakes, the flow dynamics are characterized by changing backwater effects and seasonal water storage and release, and the bed morphology is unstable due to frequent sediment deposition and erosion. Hence, models that can accurately and efficiently simulate hydraulic interactions with low topographic data demands are required for such water systems. In this study, we present a coupled flow routing model for the Yangtze River-Dongting Lake system by coupling a 1D hydrodynamic model for the mainstream with hydrological models for distributaries and the lake. A new approach is proposed to generate a set of rating curves to represent the combined impacts of the inflow and outlet stage on the lake storage volume, thereby an innovative hydrological routing method fully considering backwater effects is established. Additionally, an implicit fully coupled algorithm is presented to integrate the hydrodynamic and hydrological models, which demonstrates ideal numerical stability and high computational efficiency. The coupled model is applied to flow routing in the Yangtze-Dongting system, with the Nash-Sutcliffe efficiency coefficients above 0.960, and most of the mean absolute error below 0.4 m (1000 m3/s) for stage (discharge). The model is also used to evaluate the impact of topographic changes during 1998–2016 on the flow process. The results indicate that the mainstream stage has decreased notably, while the reduction of the storage capacity of the lake is not yet remarkable. For the model proposed in this paper, only hydrological data and mainstream topographic data are necessary during model development, calibration, and application. In the context of continuous channel/lake bed adjustment in the middle reach of the Yangtze River Basin, the coupled model provides an effective tool for quantitatively evaluating the hydrological regime and flood process of a river system at a full scale.

Three-Dimensional Hydrodynamic and CFD Modeling of a Tidal Barrage Power Plant without Sluicing in Buenaventura, Colombia

Recent research revealed the potential of tidal energy in the central coastal region of the Colombian Pacific. Buenaventura City, located in the Valle del Cauca department in Colombia, has an important opportunity to develop tidal power technologies near its marine coastal areas. This research implemented a 3D hydrodynamic model for simulating the hydrodynamics of the Buenaventura Bay to provide data as input for evaluating the hydraulics of a tidal barrage without sluicing through CFD modeling. According to the results, the velocities across the gates during Syzygy (April 2021) showed impressive velocities between 9 and 11 m/s, which suggest a high possibility of producing electricity through tidal turbines. The mean behavior of velocities in the gates pointed to values of 3 and 5 m/s in most of the cases. The results during the Stoa condition were interesting because flow velocities higher than 1 m/s were not expected. This is promising because the plant might produce electricity even during the Stoa condition. For the first time, the results of this research suggest that there exists a high possibility of implementing tidal barrage plants in Buenaventura City, Colombia.

Nondetections of Helium in the Young Sub-Jovian Planets K2-100b, HD 63433b, and V1298 Tau c

We search for excess in-transit absorption of neutral helium at 1.083 μm in the atmospheres of the young (<800 Myr) sub-Jovian (0.2–0.5 RJ ) planets HD 63433b, K2-100b, and V1298 Tau c using high-resolution (R∼25,000) transit observations taken with Keck II/NIRSPEC. Our observations do not show evidence of helium absorption for any of the planets in our sample. We calculate 3σ upper limits on the planets’ excess helium absorption of <0.47% for HD 63433b, <0.56% for K2-100b, and <1.13% for V1298 Tau c. In terms of equivalent width, we constrain these to <2.52, <4.44, and <8.49 mÅ for HD 63433b, K2-100b, and V1298 Tau c, respectively. We fit our transmission spectra with one-dimensional Parker wind models to determine upper limits on the planets’ mass-loss rates of <7.9 × 1010, <1.25 × 1011, and <7.9 × 1011g s−1. Our nondetections align with expectations from one-dimensional hydrodynamic escape models, magnetic fields, and stellar wind confinement. The upper limits we measure for these planets are consistent with predicted trends in system age and He equivalent width from 1D hydrodynamic models.

Associating reservoir operations with 2D inundation risk and climate uncertainty

ABSTRACT Bridging the research gap between reservoir operations and inundation risks under the future climate, this study integrates a hydrologic reservoir management model with a 2D hydrodynamic model, comparing the conventional regulations and the optimized reservoir operations based on the particle swarm optimization (PSO) algorithm. Results reveal that optimized operations using the PSO algorithm consistently outperform conventional strategies by better-managing peak discharges and controlling downstream inundation. The study further differentiates between PSO-optimized plans: PSO1, which focuses on minimizing inundation areas, and PSO2, which prioritizes peak reduction at the flood control point. Interestingly, PSO2 proves superior for single-point peak reduction, typically the primary objective in current practices, whereas PSO1, despite lesser peak reduction, achieves a smaller inundation area, enhancing basin-scale flood resilience. This discrepancy reveals the need to consider downstream inundation risks as critical evaluation metrics in reservoir optimization, a factor often overlooked in existing studies. The research underscores the importance of updating operational frameworks to incorporate 2D inundation risks and adapt to increased flood risks under changing climate conditions. Despite optimization, future climate scenarios predict increased flood exposure, indicating that the current safety discharge rates and flow regulations at control points are outdated and require revision.

An improved dynamic bidirectional coupled hydrologic–hydrodynamic model for efficient flood inundation prediction

Abstract. To improve computational efficiency while maintaining numerical accuracy, coupled hydrologic–hydrodynamic models based on non-uniform grids are used for flood inundation prediction. In these models, a hydrodynamic model using a fine grid can be applied to flood-prone areas, and a hydrologic model using a coarse grid can be used for the remaining areas. However, it is challenging to deal with the separation and interface between the two types of areas because the boundaries of the flood-prone areas are time dependent. We present an improved Multigrid Dynamical Bidirectional Coupled hydrologic–hydrodynamic Model (IM-DBCM) with two major improvements: (1) automated non-uniform mesh generation based on the D-infinity algorithm was implemented to identify the flood-prone areas where high-resolution inundation conditions are needed and (2) ghost cells and bilinear interpolation were implemented to improve numerical accuracy in interpolating variables between the coarse and fine grids. A hydrologic model, the 2D nonlinear reservoir model, was bidirectionally coupled with a 2D hydrodynamic model that solves the shallow-water equations. Three cases were considered to demonstrate the effectiveness of the improvements. In all cases, the mesh generation algorithm was shown to efficiently and successfully generate high-resolution grids in those flood-prone areas. Compared to the original M-DBCM (OM-DBCM), the new model had lower root-mean square errors (RMSEs) and higher Nash–Sutcliffe efficiencies (NSEs), indicating that the proposed mesh generation and interpolation were reliable and stable. It can be adequately adapted to the real-life flood evolution process in watersheds and provide practical and reliable solutions for rapid flood prediction.