A comprehensive review of watershed flood simulation model

Shen, Yanxia; Jiang, Chunbo

doi:10.1007/s11069-023-06047-1

Cited by 9 publications

(2 citation statements)

References 77 publications

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“…Therefore, the hydrologic module is the basis of the UWSM. On the basis of the classification of the hydrologic module, 38 a UWSM can be categorized into lumped, semidistributed, distributed, and fully distributed models (Figure 1).…”

Section: Model Classificationmentioning

confidence: 99%

Watershed Models: Review of Approaches, Challenges, and Opportunities

Jiang,

Shen

2023

ACS EST Water

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Watershed modeling is a crucial tool needed for understanding, evaluating, and predicting the adverse impact of water pollution. The watershed model can be divided into an upland watershed model (UWSM) and a downstream waterbody model (DWBM). Neither a single UWSM nor DWBM are able to accurately simulate the pollutant transport along with the surface flow in complex upland watershed−waterbody systems. Therefore, coupled UWSM and DWBM are more desirable. This study categorized the coupled UWSM and DWBM into external and internal coupling models. The coupling mechanism, numerical accuracy, computational efficiency, and applications of these coupling models are discussed. A dynamic bidirectional coupled model for environment simulation (E-DBCM) is consistent with the natural flood and pollutant transport processes, which can improve computational efficiency while maintaining simulation accuracy. Compared with the original coupling models, it possesses three advantages: (1) reasonable coupling mechanisms, (2) complete function, and (3) high efficiency and simplicity. E-DBCM is a potential watershed water environment model, which can be widely used if improved further. The findings of this review will help accurately and efficiently predict and manage pollutants worldwide.

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Section: Model Classificationmentioning

confidence: 99%

Watershed Models: Review of Approaches, Challenges, and Opportunities

Jiang,

Shen

2023

ACS EST Water

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“…The study on oil spills in waters began in the 1960s. With the long-term development of hydrodynamic modeling, oil spill modeling, and numerical methods, the observation of the physical behavior of oil spills in watersheds using numerical simulation has been widely applied [2,[10][11][12][13][14][15][16][17][18][19]. Zhen and Li et al [20] established a two-dimensional hydrodynamic model of Daya Bay in the South China Sea and studied the behavior and fate of oil spills in both clockwise and anticlockwise currents.…”

Section: Introductionmentioning

confidence: 99%

Study on the Oil Spill Transport Behavior and Multifactorial Effects of the Lancang River Crossing Pipeline

Lu,

Chen,

2024

Applied Sciences

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As the number of long-distance oil and gas pipelines crossing rivers increases, so does the risk of river oil spills. Previous research on oil spills in water mainly focuses on the oceans, and there are relatively few studies on oil spills in rivers. This study established two-dimensional hydrodynamic and oil spill models for the Lancang River crossing pipeline basin and verified the model’s accuracy. The oil spill transport process under different scenarios was simulated, and the oil spill transport state data set was established. The effects of river flow, wind, and leakage mode on the transport behavior of oil spills were studied. The results show that an increase in flow rate accelerates the migration, diffusion, and longitudinal extension behavior of oil spills; Changes in wind speed have less effect on the transport behavior of oil spills under downwind and headwind conditions. The mode of leakage mainly affects the diffusion and longitudinal extension of the oil spill. The oil spill transport state prediction model was established using machine learning combination algorithms. The three combined machine learning algorithms, PSO-SVR, GA-BPNN, and PSO-BPNN, have the best performance in predicting the oil spill migration distance, oil spill area, and the length of the oil spill contamination zone, respectively, with the coefficient of determination (R2) and the 1-Mean Absolute Percentage of Error (1-MAPE) above 0.971, and the prediction model has excellent accuracy. This study can provide support for the rapid development of emergency response plans for river crossing pipeline oil spill accidents.

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Decision-making during training of a Swedish navy command and control team: a quantitative study of workload effects

Hindorf,

Bäckström,

Jonson

et al. 2024

Cogn Process

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The study compared two simulation environments for training of Swedish naval Command and Control teams by using indirect measures, including workload, combat readiness, and situation awareness. The literature explains simulation-based training as providing a safe avenue to practice relevant scenarios. Fidelity, the degree of realism in the simulation, and workload, the equilibrium between demands and assigned tasks, are crucial factors examined in this study of low- and high-fidelity naval simulations. This study was conducted to better understand the effects of various training methods. An experimental design with repeated measures was used with three consecutive escalating parts. The subjective, multidimensional assessment tool, NASA-Task Load Index was used to rate perceived workload. Combat readiness of the ship and mental demand yielded significant results. For combat readiness of the ship, there was a difference between the low and the high-fidelity setting, for the initial part of the scenario p = 0.037 and for the second part p = 0.028. Mental demand was experienced as higher in the low-fidelity setting, p = 0.036. Notably, the simulated internal battle training for onboard command teams in a low-fidelity setting was found to induce a level of stress comparable with that experienced in a high-fidelity setting. The results indicate that low-fidelity training results in a workload not distinguishable from high-fidelity training and has practical implications for increased use of low-fidelity training as part of (naval) command team training programmes.

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A comprehensive review of watershed flood simulation model

Cited by 9 publications

References 77 publications

Watershed Models: Review of Approaches, Challenges, and Opportunities

Watershed Models: Review of Approaches, Challenges, and Opportunities

Study on the Oil Spill Transport Behavior and Multifactorial Effects of the Lancang River Crossing Pipeline

Decision-making during training of a Swedish navy command and control team: a quantitative study of workload effects

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