Intersections between hydrological research and hydrological practice – a Natural Catastrophe modeller perspective

<p>This presentation is going to address some of the main commonalities between hydrological research and hydrological practice, from the perspective of the Natural Catastrophe (Nat Cat) model developer. For example, hydrological research on the one hand, has a strong focus on the advancement of understanding hydrological processes. The hazard component of Nat Cat flood models, on the other hand, tends to be focused more on model suitability, accuracy and precision. However, it does rely heavily on a thorough understanding of the main hydro-meteorological drivers to describe catchment processes across the relevant spatial and temporal scales, and these are incorporated to achieve model realism and robustness, in particular when extrapolating outside the range of observed regimes. The latter is of importance when modelling extremes, which by definition are scarce.</p><p>The presentation will also go into detail on the feedbacks between hydrological research and hydrological practice. For example, how the latest generation of Natural Catastrophe models benefit from the advances in hydrological research, e.g. research on large scale hydroclimatic patterns like ENSO, or climate change research. Incorporating the latest research in hydrological hazard modeling into Catastrophe Models ultimately improves the risk assessment for a set of assets. Also, large-scale flood risk models using coupled model chains that are relatively new in the hydrological research literature, have been part of the standard methodology for the Nat Cat models for a couple of decades, and might be seen as an indicator for the societal demand to perform novel research in these fields.</p>

A Phenology Model for Simulating Oobius agrili (Hymenoptera: Encyrtidae) Seasonal Voltinism and Synchrony With Emerald Ash Borer Oviposition

In North America, the emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), continues to spread, and its egg parasitoid, Oobius agrili Zhang and Huang (Hymenoptera: Encyrtidae), is being released for emerald ash borer biocontrol well beyond their endemic climatic ranges in China. We developed a multiple cohort rate summation model to simulate O. agrili F0, F1, and F2 generations, and emerald ash borer oviposition for examining host–parasitoid synchrony across a north–south gradient from Duluth, MN (latitude 46.8369, longitude −92.1833) to Shreveport, LA (latitude 32.4469, longitude −93.8242). Temporal occurrences of critical day length for O. agrili diapause induction were integrated into the model. We used O. agrili and emerald ash borer trapping data from south central and northwestern Lower Michigan for model validation. Simulations demonstrated that 1) F0 adult emergence consistently occurred 2–5 d before emerald ash borer oviposition began; 2) F1 adult emergence was most synchronized with peak emerald ash borer oviposition compared with other generations; and 3) emerald ash borer oviposition was complete, or near so, when F2 adult emergence was predicted across the north–south gradient. Comparison of O. agrili trap captures with model simulations demonstrated that primarily two adult O. agrili generations (F0 and F1) emerged per year in Michigan and almost all F2 larvae entered diapause despite day lengths longer than critical day length in south central Michigan. Critical day length varied temporally across the north–south gradient during emergence of O. agrili generations. Determining day lengths perceived by O. agrili larvae in the field should improve model realism for examining spatiotemporal variation in O. agrili population dynamics.

Comparison of error tree analysis and TRIPOD BETA in accident analysis of a power plant industry using hierarchical analysis

Introduction: Due to the importance and necessity of accident analysis, it is necessary to use the proper technique for precise accident analysis and provide corrective and preventive measures to prevent an accident's recurrence. Materials and Methods: In this descriptive-analytical paper, the most important criteria for investigating and selecting accident investigation and analysis techniques and selecting the best accident analysis method were identified in critical industrial accidents in the construction phase, were identified and analyzed. In this study, the most important criteria for selecting an accident analysis method were identified using previous research and gathering expert opinions. Then, two critical power plant accidents were analyzed using TRIPOD BETA and FTA accident analysis methods. Then the pairwise comparisons matrix was formed based on the strengths and weaknesses of the models. Finally, the prioritization of these two methods was done using the hierarchical analysis decision-making method. Results: In this paper, seven key factors, model realism, model descriptive, systematic modeling, run time, required training courses, ability to quantify, and visibility of events, were identified as the most important criteria for selecting an incident analysis method. Conclusion: The TRIPOD BETA method has been introduced as an optimal method for investigating specific events due to its capabilities.

Stepwise modeling and the importance of internal fluxes validation to improve hydrological model realism: three case studies in cold regions of China

<p>Model realism testing is of vital importance in science of hydrology, in terms of realistic representation of hydrological processes and reliability of future prediction. We conducted three modeling case studies in cold regions of China, i.e. the upper Heihe River basin, the Urumqi Glacier No.1 basin, and the Yigong Zangbu River basin, to test the importance of stepwise modeling and internal fluxes validation to improve model realism.</p><p>In the upper Heihe River basin, we used four progressively more complex hydrological models (FLEXL, FLEXD, FLEXT0 and FLEXT), to stepwisely account for distributed forcing inputs, tailor-made model structure for different landscapes, and the realism constraints of parameters and fluxes. We found that the stepwise modeling framework helped hydrological processes understanding, and the tailor-made model structure and realism constraints improved model transferability to two nested basins.</p><p>In the Urumqi Glacier No. 1 basin, with 52% of the area covered by glaciers, we developed a conceptual glacier-hydrological model (FLEXG) and tested its performance to reproduce the hydrograph, and separate the discharge into contributions from glacier and nonglacier areas, and establish estimates of the annual glacier mass balance (GMB), the annual equilibrium line altitude (ELA), and the daily snow water equivalent (SWE). We found that the FLEXG model, involving effects of topography aspect, was successfully transferred and upscaled to a larger catchment without recalibration.</p><p>In the Yigong Zangbu River basin, with 41.4% glacier area, we designed three models (FLEXD, FLEX-S, FLEX-SG) to stepwisely understand the impact of snow, glacier to reproduce historic streamflow. We found that by involving snow and glacier modules, the model performance was dramatically improved. Although the daily streamflow of FLEX-SG reached up to 0.93 Kling-Gupta Efficiency (KGE) in calibration, it significantly overestimated snow cover area (SCA) and glacier mass balance (GMB). With satellite measured precipitation lapse rate, we improved FLEX-SG model realism not only to reproduce hydrography but also SCA and GMB.</p>

Simulation of Dural Repair in Minimally Invasive Spine Surgery With the Use of a Perfusion-Based Cadaveric Model

BACKGROUND AND IMPORTANCE In an era of curtailed work hours and concerns over achieving technical proficiency in the repertoire of procedures necessary for independent practice, many residencies have turned to model simulation as an educational adjunct. Cerebrospinal fluid (CSF) leak repair after inadvertent durotomy in spine surgery is a fundamental skillset for any spine surgeon. While primary closure with suture is not always necessary for small durotomies, larger defects, on the other hand, must be repaired. However, the dire consequences of inadequate repair dictate that it is generally performed by the most experienced surgeon. Few intraoperative opportunities, therefore, exist for CSF leak repair by trainees. OBJECTIVE To simulate dural repair in spine surgery using minimal-access techniques. METHODS A cohort of 8 neurosurgery residents was evaluated on their durotomy repair efforts in a perfusion-based cadaveric model. RESULTS Study participants demonstrated consistent improvement across trials, with a significant reduction in closure times between their initial (12 min, 7 sec ± 4 min, 43 sec) and final attempts (7 min, 4 sec ± 2 min, 6 sec; P = .02). Moreover, all trainees—irrespective of postgraduate year—were able to accomplish robust dural closures resistant to simulated Valsalva maneuvers. Participants reported high degrees of model realism and exhibited significant increases in postprocedure confidence scores. CONCLUSION Our results support use of perfusion-based simulation models as a complement to neurosurgery training, as it affords unrestricted opportunities for honing psychomotor skillsets when resident learning is increasingly being challenged by work-hour limitations and stricter oversight in the context of value-based healthcare.

Queue Spillback and Demand Uncertainty in Dynamic Network Loading

In the field, queue spillback contributes substantially to urban congestion. Therefore, most dynamic network loading models either explicitly include spillback, or frame a failure to model spillback as an unfortunate consequence of mathematical or computational tractability that should be relaxed in future work. Although models with spillback are undeniably more realistic, they are also less robust to errors in input demand. We show that when there is high uncertainty in input demand, excluding spillback can actually reduce error by reducing sensitivity to demand errors. Our demonstrations include a small network that can be solved analytically, and dynamic user equilibrium on two real-world networks representing Austin, TX, and San Antonio, TX. We conclude that model realism must be carefully balanced against the accuracy of the input parameters, and the sensitivity of the model to any such errors in these inputs.