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Analysis of Floods in North Korea Using Multiple Satellite Data on Precipitation (Flood Cases in August 2020)
  • 게시일2021-09-28
  • 조회수232

Analysis of Floods in North Korea Using Multiple Satellite Data on Precipitation (Flood Cases in August 2020)

 

 

▲ Research Fellow Kim Joo-hun, Department of Hydro Science and Engineering Research / Senior Researcher Choi Yun-seok, Department of Hydro Science and Engineering Research

 

Estimation of Precipitation Using Satellite Data


In the field of water resources and atmospheric science, remote sensing technology is widely recognized as a very useful tool that helps scientists observe global precipitation. Precipitation estimates obtained using satellite data target a broader spatial range than estimates obtained through ground observatories and weather radars and have the additional advantage of producing consistent and uniform precipitation information (Hong et al., 2016).


Satellite precipitation estimates first became possible in April 1960 with the launch of the TIROS-1 (Television Infra-Red Observation Satellite), a cutting-edge satellite that provided scientists with meteorological images for the first time ever. In 1979, the field of meteorology took another step forward when meteorologist Phillip Arkin developed a method for estimating precipitation using infrared (IR) data. Another development came in 1987, when the Defense Meteorological Satellite Program (DMSP) launched a satellite equipped with an SSM/I (Special Sensor Microwave/Imager) and a multi-channel passive microwave radiometer, allowing for active research on precipitation estimates. In the 1990s, the importance of global precipitation estimates gained increased recognition, prompting the US NASA's Mission to Planet Earth Program to begin measuring precipitation from outer space. In 1997, NASA and the Japanese Aerospace eXploration Agency (JAXA) ramped up their efforts to produce satellite precipitation data and jointly launched the Tropical Rainfall Measuring Mission (TRMM) to estimate rainfall in tropical and subtropical regions (35°N–35°S). Following these series of developments, the scientific community began acquiring vast amounts of hydrological knowledge related to rainfall. Since the launch of the TRMM, satellite precipitation data has continued to be obtained through: Multi-satellite Precipitation Analysis (TMPA); NOAA CPC Morphing (CMORPH) at the NOAA’s Climate Prediction Center in the United States; and Global Satellite Mapping of Precipitation (GSMaP) by JAXA (Joo-hun Kim et al., 2015).

 

 

The 2014 GPM Core satellite was designed to replace the TRMM satellite. The GMP Core satellite produces IMERG satellite precipitation data with a higher spatio-temporal resolution than previous satellites, boasting a temporal resolution of 30 minutes and a spatial resolution of 0.1 deg. for the spatial range of 60N–60S. Satellite precipitation data, such as that produced by the GPM Core satellite, promotes the scientific knowledge of global precipitation and accelerates the development of global eco-hydrological models. The data obtained from satellites is utilized for hydrological research in various ways and is used to analyze regional precipitation and/or flooding patterns (Hong et al., 2019). There are many regions worldwide—such as regions in East Asia, Southeast Asia, and Africa—where hydrological measurements have not yet been fully obtained and precipitation evaluation studies are actively being conducted using satellite precipitation data. Satellite precipitation data, such as IMERG and GSMaP, calculate precipitation estimates for most of the Earth' surface by combining information from the GPM satellite group pictured in Figure 1. This data is compiled to produce precipitation data on a global scale, as seen in Figure 2. NASA satellites produce IMERG date with 30-minute temporal resolution and 0.1deg. of spatial resolution, and JAXA satellites generate GSMaP satellite precipitation data with a 1-hour temporal resolution and 0.1 deg. of spatial resolution.

 

 

 

Analysis of Floods in North Korea Using Precipitation Data From Multiple Satellites


Hydrometeorological data for North Korea is produced at 6-hour intervals by compiling data from 27 observation stations in North Korea, reports from North Korean media, and the World Meteorological Organization (WMO). However, when researchers analyzed the precipitation data from the 27 North Korean observatories, from 03:00 on July 28, 2020 to 09:00 on August 7, 2020 through the Meteorological Data Open Portal site of the Korea Meteorological Administration, they found that the data from the aforementioned time period was 42.8% incomplete. These results led them to conclude that obtaining precipitation data from North Korea was disadvantageous because it is difficult to secure a full dataset for a specific time period, and the reliability of the data cannot be verified.


On June 6, 2020, a North Korean defector made an appearance on the MBC Program “Unification Observatory” and commented that “weather forecasters [in North Korea] deceive even the North Korean Supreme Leader.” A spokesperson from the Korea Meteorological Administration responded, saying, “In weather forecasting, loyalty alone isn't enough to deliver correct information.” Currently, North Korea's weather prediction and observation technologies are evaluated as being at the same level as South Korea's in the 1990s. In order to overcome some of these gaps in data availability and accuracy, researchers analyzed the rainfall in North Korea using satellite data on the damage caused by heavy rains in North Korea in August 2020. They also used satellite precipitation data and the rainfall-runoff model to estimate the approximate amount of flooding and to determine other characteristics of rainfall and flooding in North Korea.

 


In order to analyze the accuracy of the precipitation data obtained via satellite, researchers compared the satellite data with the total precipitation data obtained from three observation stations—Cheongyang-ri, Odeok Elementary School, and Sang-ri Elementary School—and GSMaP satellite precipitation data for the Han River system in Yeoncheon-gun, which is adjacent to North Korea. The correlation coefficient was determined to be about 0.996, meaning that the satellite precipitation data showed a high level of accuracy when compared to the data obtained through other means. Since the satellite data slightly underestimated the amount of precipitation, compared to measurements obtained on the ground, researchers calculated the precipitation distribution for North Korea by applying a correction factor of 1.69 to the satellite data, as shown in Figure 4.


The GRM model employed by the KICT (Korea Institute of Civil Engineering and Building Technology) was used as an analysis tool for flood volume evaluation. Since the flow of floodwaters in North Korea cannot be actually observed by South Korean scientists, it was difficult for researchers to verify the results of their floodwater simulations. Therefore, the default parameters of the GRM model were applied to the floodwater/runoff simulation without any separate application of other corrective measures. Given these limitations, the researchers of the floodwater simulation study presented their results on simulated flow as “estimates,” as opposed to actual values. Furthermore, when conducting the runoff/floodwater simulation, the impact of dams and watersheds were not considered, and it was assumed that all flows were natural runoffs. The simulation area (Figure 4) included the entire region of North Korea, as well as some parts of China and Russia, which belong to the Amnok River and Duman River basins. Some areas of South Korea were also included in the simulation area as part of the Imjin River and the Bukhan River basins. In terms of the precipitation data utilized for the runoff simulation, calibrated satellite precipitation was applied for the period of 00:00 on August 1, 2020, to 00:00 on August 16, 2020 at a time interval of 1 hour.

 


Figure 5 is a hydrograph comparing the simulated flow using the aforementioned calibrated satellite precipitation data and the observed flow at Hantan Bridge. The watershed area of Hantan Bridge is about 1,014 km2, and about 50% of the watershed is located in North Korea. There is also an additional reservoir with a watershed area of about 50 km2 in the upstream North Korean region. In Figure 5, the simulated flow at Hantan Bridge reflects the observed upward and downward trends of the hydrograph. However, the peak flooding that occurred around 15:00 on August 5 was estimated by the simulation to be higher (6,048㎥/s) than the flooding actually observed (4,785㎥/s).


The differences between the simulation results and onsite observations were attributed to a variety of factors, namely, the fact that: the runoff model was not calibrated; the default model values were applied; and the impact of the many dams distributed throughout North Korea and watershed changes were not considered. The accuracy of the simulation flood estimates for North Korea could be improved if these issues were rectified.


Despite these limitations, satellite precipitation data can be used as a substitute for ground observation data in areas where there is no ground observation data available, or in areas with a limited spatial and temporal range for ground observation. Satellite precipitation data also has the advantage of providing unified information on spatial expansion. In the future, the results from this study can be used to conduct further research on and improve the accuracy of precipitation data for the entire Korean Peninsula.

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