Applicability Evaluation of Flood Inundation Analysis using Quadtree Grid-based Model

Abstract

Lately, intensity and frequency of natural disasters such as flood are increasing because of abnormal climate. Casualties and property damages due to large-scale floods such as Typhoon Rusa in 2002 and Typhoon Maemi in 2003 rapidly increased, and these show the limits of the existing disaster prevention measures and flood forecasting systems regarding irregular climate changes. In order to efficiently respond to extraordinary flood, it is important to provide effective countermeasures through an inundation model that can accurately simulate flood inundation patterns. However, the existing flood inundation analysis model has problems such as excessive take of analysis time and accuracy of the analyzed results. Therefore, this study conducted a flood inundation analysis by using the Gerris flow solver that uses quadtree grid, targeting the Baeksan Levee in the Nakdong River Basin that collapsed because of a concentrated torrential rainfall in August, 2002. Through comparisons with the FLUMEN model that uses unstructured grid among the existing flood inundation models and the actual flooded areas, it determined the applicability and efficiency of the quadtree grid-based flood inundation model of the Gerris flow solver.

Case Study of HEC-RAS 1D–2D Coupling Simulation: 2002 Baeksan Flood Event in Korea

“…The negative effect of the event lead to further interest in developing efficient dam breach flood models. This event also provides reliable field data suitable for verification, which previous research has used for flood analysis [6,14,15]. Figure 1 shows the geographical location of the study domain, the Baeksan-Nakdong river catchment.…”

“…The width and length of the failure were set as 10.3 m and 15 m, respectively, based on the survey conducted by the Korea Ministry of Construction and Transportation after the event. The homogeneous roughness coefficient is set to η = 0.06 according to the cultivated crop/pasture manning value in [30], since the flood area is mostly paddy field and vegetable crops [15]. The breach formation time was assumed to be 20 h, that is, the time it took for the surface water level in the flooded area side of the levee to recede after the breach.…”

“…Our literature review stated that the levee break occurred on 10 August 2002 at 1600, and the flood simulation time was therefore set up for 10 August at midnight to 12 August at 1600. The simulation times for the FLUMEN, Gerris and HEC-RAS coupled 1D-2D were 420 [29], 111.95 [15] and 1.82 min, respectively.…”

“…Since this update for the 1D-2D coupling simulation is quite recent, only a few researchers have tried this approach for flood simulation analysis [10][11][12][13]. Therefore, this study aims to assess the capability of the model technique in simulating a river levee break through a comparison with the observed results and simulated results from previously used 2D flood models, Gerris [6] and Fluvial modelling engine (FLUMEN) [14,15]. Gerris is an open-source software that solves shallow water computations using the adaptive quadtree grid technique [7], while FLUMEN (FLUvial Modelling Engine) solves the depth-averaged shallow water equations on unstructured adaptive meshes, which is used for modeling hydraulic complex situations [16].…”

Forecasting Water Demand With the Long Short-Term Memory Deep Learning Mode

“…However, LSTM also comes with some limitations. It can be computationally intensive and require substantial amounts of data for training to prevent overfitting (Lee et al, 2019). Additionally, LSTM models may struggle when faced with noisy or incomplete data, which can be a challenge in real-world urban water demand datasets.…”