• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.665-679
• /
• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.

• Korean Journal of Remote Sensing
• /
• v.37 no.2
• /
• pp.321-335
• /
• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• Journal of the Korean earth science society
• /
• v.43 no.3
• /
• pp.367-385
• /
• 2022

This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.17 no.3
• /
• pp.139-148
• /
• 2012

The short-term variation of salinity and temperature in a dyked estuarine environment is mainly controlled by the freshwater discharge from the dyke. We examined the distribution of salinity and temperature by the freshwater discharge in the Yeongsan River estuary using the CTD data obtained from 8 stations through three surveys in June (weak discharge) and August (intensive discharge), 2010. During the weak discharge in June, the surface salinity showed 30-32.5 psu and its horizontal gradient was relatively high around Goha-do (0.25~0.32 psu/km). On the other hand, the salinity of the bottom layer was almost constant in the range of 33 psu. Water temperature ranged $19{\sim}21^{\circ}C$ and displayed higher gradient in north-south direction than the gradient of east-west direction. During the intensive freshwater discharge on August 12, the salinity dropped to 9~26 psu. The maximum horizontal gradient of surface salinity reached 3.8 psu/km in the north of Goha-do where the strong salinity front was formed, and the horizontal salinity gradient of bottom layer was 0.28 psu/km. The horizontal gradient of water temperature was $-0.45^{\circ}C/km$ in the surface and $-0.12^{\circ}C/km$ in the bottom with high surface temperature near the dyke and decreasing gradually to the river mouth. After 3 days of the intensive discharge ($3^{rd}$ survey), the surface salinity increased to 22~26 psu. However, there still existed relatively high horizontal gradient around Goha-do. In the mean time, the bottom salinity decreased to 26.5~27.5 psu, but its gradient was not big as much as the surface gradient. According to time series of CTD profile near the dyke, the discharged fresh water jetted down temporarily and then recovered gradually with the recovering speed of 0.4 m/hour for the discharge case of $13{\times}10^6$ ton. Due to the combined effects of freshwater discharge and surface heating during the summer of 2010, the Yeongsan estuary, in general, underwent intensified vertical stratification, which in turn caused the inhibition of vertical mixing, especially inside area of estuary. Based on the spatial distribution of salinity and temperature, the Yeongsan estuary can be divided into three regions: the Goha-do area with strong horizontal gradient of salinity and temperature, inner estuary from Goha-do to the dyke with low salinity, and outer estuary from Goha-do to the coasts with relatively high salinity.

• Journal of Korea Water Resources Association
• /
• v.57 no.8
• /
• pp.509-518
• /
• 2024

Flash drought is a rapid-onset drought that occurs rapidly over a short period due to abrupt changes in meteorological and environmental factors. In this study, we utilized satellite-based soil moisture product from the Advanced Microwave Scanning Radiometer-2(AMSR2) ascending X-band to calculate the weekly Flash Drought Intensity Index (FDII). We also analyzed the characteristics of flash droughts on the Korean Peninsula over a 10-year period from 2013 to 2022. The analysis of monthly spatial distribution patterns of the irrigation period across the Korean Peninsula revealed significant variations. In North Korea (NK), a substantial increase in the rate of intensification (FD_INT) was observed due to the rapid depletion of soil moisture, whereas South Korea (SK) experienced a significant increase in drought severity (DRO_SEV). Additionally, regional time series analysis revealed that both FD_INT and DRO_SEV were significantly high in the Gangwon province of both NK and SK. The estimation of probability density by region revealed a clear difference in FD_INT between NK and SK, with SK showing a higher probability of severe drought occurrence primarily due to the high values of DRO_SEV. As a result, it is inferred that the occurrence frequency and damage of flash droughts in NK are higher than those in SK, as indicated by the higher density of large FDII values in the NK region. We analyzed the correlation between DRO_SEV and the Evaporative Stress Index (ESI) across the Korean Peninsula and confirmed a positive correlation ranging from 0.4 to 0.6. It is concluded that analyzing overall drought conditions through the average drought severity holds high utility. These findings are expected to contribute to understanding the characteristics of flash droughts on the Korean Peninsula and formulating post-event response plans.

• Korean Journal of Environment and Ecology
• /
• v.34 no.2
• /
• pp.170-178
• /
• 2020

There are few landscape ecological analyses of Khingan fir (Abies nephrolepis) and other habitats of the sub-alpine zone in South Korea. In this study, we tried to quantitatively interpret and assess the habitat characteristics by analyzing 15 landscape indices according to the differences in tree layer coverage, in the Khingan fir habitat growing naturally in the sub-alpine zone of Seoraksan National Park. It was difficult to identify the tendency of landscape ecology to increase and decrease the tree layer coverage in the study site, which was the entire Khingan fir habitat in Seoraksan National Park. However, the Khingan fir habitat was found to be generally low in coverage, and population density as the tree layer coverage of less than 50 percent accounts for 85 percent of the total habitat. Moreover, the Khingan fir habitat in the 10 to 50 percent range was fragmented into a total of 286 patches, making it relatively less connected to the habitat. The total edge length and edge density, which could determine the edge effect of the main part according to the physical form, were the highest in the habitat of 26 to 50 percent coverage, indicating a relatively high impact from outside than habitats of other coverages. The shape with the tree layer coverage of between 10 and 50 percent was more complex even with patches of the same size, and it is believed that these characteristics make it more susceptible to habitat fragmentation and external confounding. We expect that the results of this study can be useful for time series analysis of spatial expansion or reduction of the Khingan fir habitat in Seoraksan National Park and provide the reference data for the morphological change and movement of patches and the connectivity and break-off between forests.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_2
• /
• pp.1819-1827
• /
• 2021

Land-use/cover change caused by rapid urbanization in South Korea is one of the concerns in flood risk management because groundwater recharge by precipitation hardly occurs due to an increase in impermeable surfaces in urban areas. This study investigated the hydrologic effects of land-use/cover on groundwater recharge in the Yeonje-gu district of Busan, South Korea. A statistical time series analysis was conducted with temporal variations of precipitation and groundwater level to estimate lag-time based on correlation coefficients calculated from auto-correlation function (ACF), cross-correlation function (CCF), and moving average (MA) at five sites. Landform and land-use/cover within 250 m radius of the monitoring wells(GW01, GW02, GW03, GW04, and GW05) at five sites were identified by land cover and digital map using Arc-GIS software. Long lag-times (CCF: 42-71 days and MA: 148-161 days) were calculated at the sites covered by mainly impermeable surfaces(GW01, GW03, and GW05) while short lag-times(CCF: 4 days and MA: 67 days) were calculated at GW04 consisting of mainly permeable surfaces. The results suggest that lag-time would be one of the good indicators to evaluate the effects of land-use/cover on estimating groundwater recharge. The results of this study also provide guidance on the application of statistical time series analysis to environmentally important issues on creating an urban green space for natural groundwater recharge from precipitation in the city and developing a management plan for hydrological disaster prevention.