Clustering-based hybrid inundation model for forecasting flood inundation depths

Chang, Li-Chiu; Shen, Hung-Yu; Wang, Yi-Fung; Huang, Jiung-Yao; Lin, Yen-Tso

doi:10.1016/j.jhydrol.2010.02.028

Cited by 83 publications

(48 citation statements)

References 26 publications

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“…[29] developed a two-stage procedure underlying the clustering-based hybrid inundation model, which is composed of linear regression models and ANNs (artificial neural networks) to build a 1-h-ahead regional flood inundation forecasting model. However, regarding to the study of modeling long lead-time continuous unsteady inundation level of an urban drainage system using ANNs still have not been researched.…”

Section: Solution Of Optimization Modelmentioning

confidence: 99%

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Huang

Hsu

Wei

et al. 2015

Water

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This study adopts rainwater harvesting systems (RWHS) into a stormwater runoff management model (SWMM) for the spatial design of capacities and quantities of rain barrel for urban flood mitigation. A simulation-optimization model is proposed for effectively identifying the optimal design. First of all, we particularly classified the characteristic zonal subregions for spatial design by using fuzzy C-means clustering with the investigated data of urban roof, land use and drainage system. In the simulation method, a series of regular spatial arrangements specification are designed by using statistical quartiles analysis for rooftop area and rainfall frequency analysis; accordingly, the corresponding reduced flooding circumstances can be simulated by SWMM. Moreover, the most effective solution for the simulation method is identified from the calculated net benefit, which is equivalent to the subtraction of the facility cost from the decreased inundation loss. It serves as the initially identified solution for the optimization model. In the optimization method, backpropagation neural network (BPNN) are first applied for developing a water level simulation model of urban drainage systems to substitute for SWMM to conform to newly considered interdisciplinary multi-objective optimization model, and a tabu search-based algorithm is used with the embedded BPNN-based SWMM to optimize the planning solution. The developed method is applied to the Zhong-He District, Taiwan. Results demonstrate that the application of tabu search and the BPNN-based simulation model into OPEN ACCESSWater 2015, 7 5174 the optimization model can effectively, accurately and fast search optimal design considering economic net benefit. Furthermore, the optimized spatial rain barrel design could reduce 72% of inundation losses according to the simulated flood events.

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Section: Solution Of Optimization Modelmentioning

confidence: 99%

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Huang

Hsu

Wei

et al. 2015

Water

View full text Add to dashboard Cite

show abstract

“…Artificial neural networks (ANNs) are a kind of information processing system with great flexib ility in modeling nonlinear systems. As to inundation forecasting, applications of NNs have been presented (Chang et al [3]; Pan et al [7]). The ASCE Task Co mmittee [1,2] and Maier and Dandy [6] have presented comprehensive reviews of the applications of ANNs in hydrology.…”

Section: Introductionmentioning

confidence: 99%

Effective real-time forecasting of inundation maps for early warning systems during typhoons

2018

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Abstract. Accurate forecasts of hourly inundation depths are essential for inundation warning and mitigation during typhoons. In this paper, an effective forecasting model is proposed to yield 1-to 6-h leadtime inundation maps for early warning systems during typhoons. The proposed model based on Support Vector M achine (SVM ) is composed of two modules, point forecasting and spatial expansion. In the first module, the rainfall intensity, inundation depth, cumulative rainfall and forecasted inundation depths are considered as model input for point forecasting. In the second module, the geographic information of inundation grids and the inundation forecasts of reference points are used to yield inundation maps for spatial expansion. The results show that the proposed model is able to provide accurate point forecasts at each inundation point. M oreover, the spatial expansion module is capable of producing accurate spatial inundation forecasts. Obviously, the proposed model provides reasonable spatial inundation forecasts, and is able to deal with the nonlinear relationships between inputs and desired output. In conclusion, the proposed model is suitable and useful for inundation forecasting.

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“…In the past decades, flash floods have occurred frequently due to land cover and climate change (Chang et al, 2010), especially in the urban areas of southern China, and have caused serious damage to urban properties. These problems present many challenges to urban management, such as storm-water pipeline maintenance, non-point source contamination, massive traffic jams.…”

Section: Introductionmentioning

confidence: 99%

Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata

Liu

Wang

et al. 2015

Nat. Hazards Earth Syst. Sci.

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Abstract. Flash floods have occurred frequently in the urban areas of southern China. An effective process-oriented urban flood inundation model is urgently needed for urban storm-water and emergency management. This study develops an efficient and flexible cellular automaton (CA) model to simulate storm-water runoff and the flood inundation process during extreme storm events. The process of infiltration, inlets discharge and flow dynamics can be simulated with little preprocessing on commonly available basic urban geographic data. In this model, a set of gravitational diverging rules are implemented to govern the water flow in a rectangular template of three cells by three cells of a raster layer. The model is calibrated by one storm event and validated by another in a small urban catchment in Guangzhou of southern China. The depth of accumulated water at the catchment outlet is interpreted from street-monitoring closed-circuit television (CCTV) videos and verified by on-site survey. A good level of agreement between the simulated process and the reality is reached for both storm events. The model reproduces the changing extent and depth of flooded areas at the catchment outlet with an accuracy of 4 cm in water depth. Comparisons with a physically based 2-D model (FloodMap) show that the model is capable of effectively simulating flow dynamics. The high computational efficiency of the CA model can meet the needs of city emergency management.

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Clustering-based hybrid inundation model for forecasting flood inundation depths

Cited by 83 publications

References 26 publications

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

Effective real-time forecasting of inundation maps for early warning systems during typhoons

Developing an effective 2-D urban flood inundation model for city emergency management based on cellular automata

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