Title of the Case Study

Utilization of satellite photographs for the analysis of flood flooding uncertainty

Ohio River near Metropolis, Illinois, USA

b

-
-

b

a

In this study, it was evaluated whether satellite data could be used to analyze the uncertainty rate of flood inundation, and the uncertainty of the flood inundation area of ​​the Ohio river around Ohio Metropolis Illinois was quantitatively estimated using GUJE . The conclusions obtained from this study are as follows.
(1) The water level obtained from the Landsat 5 TM image using ISODATA has a vertical error of about 1.5 m when compared with the observation data. Based on these results, satellite images can be used as observational data in flood flood model. However, it is necessary to improve the horizontal and vertical accuracy of the DEM, the resolution of the satellite image, and various water classification methods for more accurate water classification. (2) The computational likelihood measurement using the F-statistic is relatively uniformly distributed within a given range for the roughness coefficient, whereas the high likelihood is distributed around the flow of about 35,000 m 3 / s for the flow. This shows that the error of the flow rate in the flood inundation area selected for this study is carrying more uncertainty than the error of the roughness coefficient. The distribution of the likelihood of the flow rate is considered to be able to change the error range of the flow rate of the posterior probability density function according to the threshold value. Also, given that the initial flow rate is 34,547 m3 / s, it can be inferred that the initial flow produced a simulated flood inundation area close to the observed flood inundation area. (3) In the Monte Carlo simulation for GLUE, the floodplain area from 51.62 km2 to 180.00 km2 was estimated, and the 90% uncertainty caused by the error in the roughness coefficient and flow condition using GLUE was 77.36 km2, It accounts for about 85%. This large uncertainty in flood risk management is the basis for improving the accuracy of the variables. More accurate flood forecasting is required for safe flood risk management. In order to meet these demands, it is necessary to improve the model and improve the quality of the observed data. In order to overcome the limitations of the data of flood inundation in North Korea, this study produced observation data using satellite images. The spatial observations of flood inundation obtained from satellite imagery have played an important role in estimating the uncertainty ratios generated by the luminous intensity and flow rate through GLUE. The availability of improved satellite imagery in the future is expected to make a significant contribution to the realization of various academic and industrial research themes.
Flood forecasting is used as one of the most costly materials to protect lives and assets in flood risk management, such as basic planning and flood insurance. Therefore, the importance of flood predi
when compared to past data, floods that have increased in strength due to climate change occur frequently in many parts of the world, making it difficult to predict the exact flood with the uncertainties caused by the flood forecasting process. Prior to assessing the impact of climate change and uncertainty factors in forecasting flood forecasting, it is necessary to assess the impact
When climate change is not taken into account . Because climate change affects uncertainty in the process of predicting floods, it ultimately conveys the effects of climate change on the flood plains and floodplain areas resulting from flood forecasting.
-
-
Quantification of uncertainty of flood flood area using roughness coefficient and flow rate using GLUE

Korea

Inje University

-

-

-

Young Won Chung

-

comicfilm@naver.com

Flood Prediction

Planning

Inundation prediction
Water level measuring

download

sample01

download

sample01

Opinion

  • No.
  • Opinion
  • Subject
  • Write
  • Date
  • Hit
  • no record.