Abstract
The real-time flood inundation extent plays an important role in flood disaster preparation and reduction. To date, many approaches have been developed for determining the flood extent, such as hydrodynamic models, digital elevation model-based (DEM-based) methods, and remote sensing methods. However, hydrodynamic methods are time consuming when applied to large floodplains, high-resolution DEMs are not always available, and remote sensing imagery cannot be used alone to predict inundation. In this article, a new model for the highly accurate and rapid simulation of floodplains, called “RFim” (real-time inundation model), is proposed to simulate the real-time flooded area. The model combines remote sensing images with in situ data to find the relationship between the inundation extent and water level. The new approach takes advantage of remote sensing images, which have wide spatial coverage and high resolution, and in situ observations, which have continuous temporal coverage and are easily accessible. This approach has been applied in the study area of East Dongting Lake, representing a large floodplain, for inundation simulation at a 30 m resolution. Compared with the submerged extent from observations, the accuracy of the simulation could be more than 90% (the lowest is 93%, and the highest is 96%). Hence, the approach proposed in this study is reliable for predicting the flood extent. Moreover, an inundation simulation for all of 2013 was performed with daily water level observation data. With an increasing number of Earth observation satellites operating in space and high-resolution mappers deployed on satellites, it will be much easier to acquire large quantities of images with very high resolutions. Therefore, the use of RFim to perform inundation simulations with high accuracy and high spatial resolutions in the future is promising because the simulation model is built on remote sensing imagery and gauging station data.
Highlights
Floods are one of the most common and harmful natural disasters in the world, having caused direct economic losses exceeding $1 trillion and killing more than 220,000 people over the last forty years [1]
Our research identified that the results of inundation simulation using RFim were acceptable in a large floodplain, East Dongting Lake
The method consists of six steps: (1) Discretizing the study area and resampling the images; (2) extracting historical flood extents based on remote sensing images; (3) relating the water level values to pixels; (4) forming inundation records for every grid cell in the study area; (5) establishing the relationship between inundation extent and water level; and (6) simulating and predicting flood extent with the relationship between inundation extent andRewmoatetSeernsl. e20v19e,l1.1, x FOR PEER REVIEW
Summary
Floods are one of the most common and harmful natural disasters in the world, having caused direct economic losses exceeding $1 trillion and killing more than 220,000 people over the last forty years [1]. Knowing the real-time flood inundated extent during a flood event is an important way to respond quickly and reduce disaster impacts [3]. One-dimensional hydrodynamic models are used to calculate the flow through a cross section, but they cannot directly simulate the flood extent. Two-dimensional hydrodynamic models, which describe floodplain flow in two dimensions, are popular models for inundation analysis. 2D models require a lot time [4] and are impractical to apply in large-floodplain scenarios [5], and some of them may need spatial parametric inputs that are not available. Three-dimensional hydrodynamic models, which add the vertical dimension to analyze the flood extent, still have limitations on computational costs and data requirements when they are utilized to simulate flood extent in a large-scale floodplain
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