UNIST Scientists comes up with a New Technology to Monitor Drought Conditions in near Real-Time
Nithya Satheesh
The results of this study were published in the December 2020 issue of Remote Sensing of Environment, a leading publication in the field of remote sensing and was supported by the Korea Meteorological Institute and the Korea Meteorological Administration. This break-through was accomplished by Professor Myong-In Lee and Dr. Eunkyo Seo from the Department of Urban and Environmental Engineering at UNIST with the help of NASA Goddard Spaceflight Center.
Professor Myong-In Lee and Dr. Eunkyo Seo from the Department of Urban and Environmental Engineering at UNIST, in collaboration with NASA Goddard Spaceflight Center, have unveiled a novel technology that can be used to monitor near real-time drought conditions | Credits: UNIST
Drought is the most complex natural disaster and affects more people globally than any other natural disaster. Earlier, drought monitoring relied mainly on climate-based indicators. UNIST Researchers has revealed a nodal technology which can monitor near real-time drought conditions. The scientists has improved accuracy of satellite-based soil moisture estimates and processed large amount of satellite imagery quickly and accurately.
Satellites presently used in US and Europe uses microwave wavelengths in order to measure soil moisture at depths of 5 cm. But its use has been now restricted because of temporal and spatial limitations on soil moisture observations. This is because the microwave-length radio waves used for such an observation may not reach the root zone layer which is an important part for plant growth. Another reason is that he satellite rotates around the Earth almost from pole to pole which leads to large observing gaps. So in order to predict and prepare for drought, we need a technology to monitor drought conditions that too in near real-time.
Skill of soil moisture estimates from data assimilation experiments | credits: UNIST
In the new research, the scientist team developed a data assimilation system to blend soil moisture via satellite join it into the Joint U.K. Land Environment Simulator (JULES) and Land Surface Model (LSM) using LETKF. According to them, after the bias is corrected based on cumulative distribution function fitting, the system absorbs microwave soil moisture from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT).
In order to improve the accuracy of soil moisture estimates, the research team is using data assimilation method to collect soil moisture information from diverse satellite observations and also the advantage of LSM. The LSM simulation provides accurate information on soil moisture even after considering many factors such as surface temperature, precipitation, wind etc.. Thus the satellites soil moisture technology can be used in monitoring the current drought condition.