A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration

Choo Choo,Jo Jo,Lee Lee,Yun Yun

doi:10.3390/w11091883

Abstract

Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). Flood concerns are raised around the world in the events of rain. Flood forecasting, a typical nonstructural measure, was developed to help prevent repetitive flood damage. However, it is difficult to apply flood prediction techniques using training processes because training needs to be applied at every usage. Other techniques that use predicted rainfall data are also not appropriate for small watershed, such as single drainage area. Thus, in this paper, a flood prediction method is proposed by improving four criteria (50% water level, 70% water level, 100% water level, and first flooding of water pipes) in an attempt to reduce flooding in urban areas. The four criteria nodes are generated using a rainfall runoff simulation with synthetic rainfall at various durations. When applying real-time rainfall data, these nodes have the advantage of simple application. The improved flood nomograph made in this way is expected to help predict and prepare for rainstorms that can potentially cause flood damage.

Highlights

Recent developments in global industrialization have led to a substantial increase in carbon emissions, which have driven global climate change
The hydrological aspects of urban basins have changed, and the number of flood areas has increased due to the expansion of buildings and road pavement, which has increased the amount of runoff that drains into rivers and streams [1]. This phenomenon can be attributed to frequent torrential rains during monsoons and after the wet season caused by climate change, high population density, and low-lying development and low gradients in urban areas [2,3]
Previous studies proposed new approaches to prepare for or prevent floods with various flood forecasting models in a non-structural measure. Research into these kinds of flood forecasting methods was necessitated by the increasing occurrence of floods in cities that has led to substantial damages to both humans and property

Summary

Introduction

Recent developments in global industrialization have led to a substantial increase in carbon emissions, which have driven global climate change. The hydrological aspects of urban basins have changed, and the number of flood areas has increased due to the expansion of buildings and road pavement, which has increased the amount of runoff that drains into rivers and streams [1]. This phenomenon can be attributed to frequent torrential rains during monsoons and after the wet season caused by climate change, high population density, and low-lying development and low gradients in urban areas [2,3]. A real-time flood prediction method using digital elevation data with a distributed model was developed [5], as was a method involving the comparison of real-time flood forecasting using short-term rainfall forecasting models [6]

Methods

Results

Conclusion