Minha Choi

Impact of soil moisture on dust outbreaks in East Asia: Using satellite and assimilation data

This study is the first assessment of the effects of soil moisture on dust outbreaks using satellite-derived aerosol optical depth (AOD) and global assimilation data on the sand regions across East Asia. The relationships among dust outbreaks, soil moisture, and wind speed were estimated using data sets of the Moderate Resolution Imaging Spectroradiometer and Global Land Data Assimilation System collected over 11 years (2003–2013). The mean AOD exponentially decreased with increasing soil moisture under different wind speed conditions (average determination coefficient = 0.95). As the wind speed conditions became stronger, the probability of a dust outbreak became greatly affected by soil moisture. The threshold soil moisture for dust outbreaks increased with increasing wind speed and decreased with increasing dust-outbreak criteria of AOD. Our results have the capability to be applied to satellite-based dust-outbreak prediction and global-scale dust-emission studies.

Estimation of instantaneous and daily net radiation from MODIS data under clear sky conditions: a case study in East Asia

The Moderate Resolution Imaging Spectroradiometer-based net radiation (RN) model was built and applied in East Asia in 2005. Because there have hardly been simple parameterization schemes developed over a large area using remote-sensing technology, the model was aimed to present physical simplicity in complex topography at multiple spatiotemporal scales. The model successfully reproduced the instantaneous RN values obtained at four flux tower sites having individually different ecohydrology. The diurnal cycle of RN was contextually simulated using a simple sine curve to determine the daily and monthly average net radiation. The diurnal RN estimation method was proven to be a reliable model as long as accurate boundary conditions, sunrise and sunset times, for example, were obtained. The monthly average net radiation (MANR) was estimated using the diurnal patterns of the instantaneous RN. Distribution of the monthly RN demonstrated that elevation and latitude were the primary factors affecting the MANR. The proposed RN algorithm turned out to be a promising method for valuable applications in various fields due to systematic simplicity and fewer input parameters.

Evapotranspiration estimation using the Landsat-5 Thematic Mapper image over the Gyungan watershed in Korea

Even if there have been efforts to validate remote-sensing-based energy balance models, which provide evapotranspiration (ET) maps over a large spatial scale, few studies have been conducted to validate their performance in Korea. In this study, surface energy balance fluxes including ET were estimated and inter-compared with two different models using the Landsat-5 Thematic Mapper (TM) image over a watershed scale in Korea. While there were larger spatial discrepancies for net radiation, soil heat and sensible heat fluxes on a pixel-by-pixel basis between the two models, relatively smaller spatial discrepancies for the latent heat flux and daily ET were detected. The spatial discrepancies for the daily ET were larger in low topography and dense vegetation ranges. Despite the different partitioning of the surface energy fluxes due to spatial variability, a remote-sensing-based surface energy balance approach appears to deliver the operational capability for ET estimation and mapping over a watershed scale in Korea.

Evaluation of remotely sensed actual evapotranspiration products from COMS and MODIS at two different flux tower sites in Korea

Estimating the evapotranspiration (ET) is a requirement for water resource management and agricultural productions to understand the interaction between the land surface and the atmosphere. Most remote-sensing-based ET is estimated from polar orbiting satellites having low frequencies of observation. However, observing the continuous spatio-temporal variation of ET from a geostationary satellite to determine water management usage is essential. In this study, we utilized the revised remote-sensing-based Penman–Monteith (revised RS-PM) model to estimate ET in three different timescales (instantaneous, daily, and monthly). The data from a polar orbiting satellite, the Moderate Resolution Imaging Spectroradiometer (MODIS), and a geostationary satellite, the Communication, Ocean, and Meteorological Satellite (COMS), were collected from April to December 2011 to force the revised RS-PM model. The estimated ET from COMS and MODIS was compared with measured ET obtained from two different flux tower sites having different land surface characteristics in Korea, i.e. Sulma (SMC) with mixed forest and Cheongmi (CFC) with rice paddy as dominant vegetation. Compared with flux tower measurements, the estimated ET on instantaneous and daily timescales from both satellites was highly overestimated at SMC when compared with the flux tower ET (Bias of 41.19–145.10 W m−2 and RMSE of 69.61–188.78 W m−2), while estimated ET results were slightly better at the CFC site (Bias of –27.28–13.24 W m−2 and RMSE of 45.19–71.82 W m−2, respectively). These errors in results were primarily caused due to the overestimated leaf area index that was obtained from satellite products. Nevertheless, the satellite-based ET indicated reasonable agreement with flux tower ET. Monthly average ET from both satellites showed nearly similar patterns during the entire study periods, except for the summer season. The difference between COMS and MODIS estimations during the summer season was mainly propagated due to the difference in the number of acquired satellite images. This study showed that the higher frequency of COMS than MODIS observations makes it more ideal to continuously monitor ET as a geostationary satellite with high spatio-temporal coverage of a geostationary satellite.

Spatial Analysis of Drought Characteristics in Korea Using Cluster Analysis

최근에는 확률강우량을 산정할 경우 지점빈도해석의 단점을 보완한 지역빈도해석법이 자주 실무에 적용되고 있으나, 가뭄에 관련한 연구에서는 대부분 아직까지 지점자료를 이용한 가뭄분석을 실시하고 있다. 본 연구에서는 가뭄의 지역적 특성 분석을 실시하기 위하여 필요한 동질한 가뭄특성을 지닌 지역을 구분하는 연구를 수행하였다. 본 연구에서는 기상청 강우관측 지점자료 중 30년 이상의 강우자료를 보유한 58개의 관측지점을 대상으로 표준강수지수(SPI)를 산정하여 가뭄의 심도, 지속기간, 강도, 발생빈도 등과 같은 가뭄특성인자를 생성하였다. 가뭄특성인자는 수문학적으로 동질한 특성을 지닌 지역을 구분하는데 중요한 정보를 제공한다. 본 연구에서는 다양한 가뭄특성인자를 효율적으로 활용하여 K-means 기법을 적용한 군집분석을 실시하여 동질한 가뭄특성을 지닌 지역을 6개 지역으로 구분하였다. 이러한 지역구분은 가뭄 특성의 공간적 해석을 가능하게 할 수 있고, 지점빈도 해석의 단점을 보완하는 지역빈도 해석도 가능하게 할 수 있다. 【Regional frequency analysis is often used to overcome the limitation of point frequency analysis to estimate probability rainfall depths. However, point frequency analysis is still used in drought analyses. This study proposed a practical method to categorize the homogeneous regions of drought characteristics for the analyses of regional characteristics of droughts in Korea. Using rainfall data from 58 observation stations managed by the Korea Meteorological Administration, this study calculated drought attributes, i.e., mean drought indices for various durations using the Standardized Precipitation Index (SPI) and drought severities expressed by durations, depth, and intensity. The drought attributes provided useful information for categorizing stations into the hydrological homogeneous regions. This study introduced a cluster analysis with K-means techniques to group observation stations. The cluster analysis grouped observation stations into 6 regions in Korea. The data in the hydrological homogeneous region would be used in spatial analysis of drought characteristics and drought regional frequency analysis.】

Runoff Losses of Suspended Sediment, Nitrogen, and Phosphorus from a Small Watershed in Korea

Nutrients and sediments in runoff lead to the degradation of water quality of lakes and streams. The development of schemes to mitigate such degradation requires a characterization of the underlying transport processes. The objectives of this study were to develop annual and seasonal load-discharge relationships for suspended sediment (SS), total nitrogen (TN), and total phosphorus (TP) losses from a small mixed land use watershed and to use these relationships to explicate the annual and monthly patterns of losses of these species. Data from 1996 to 2004 were used to develop load-discharge relationships for SS, TN, and TP at the HP#6 watershed, a subwatershed of the Balhan reservoir watershed located in Bongdam-myun and Paltan-myun, Gyeonggi-do, Korea. Standard least squares curve fitting and S-estimation procedures were used to fit power functions to the data collected over this time period. The fitted load-discharge relationships are indicative of seasonal variations in SS and TN and of TP losses from HP#6. The exponents of the fitted power functions for TN and TP in the fall, for TP in summer season, and for SS in all seasons are >1, indicating that the concentrations of these species increase as flow rate increases. Most of the SS, TN, and TP transported in runoff left the watershed between April and September; thus, cost-efficient strategies can be established by focusing on this period. Further study of the seasonal variations is required for a better characterization of seasonal losses of SS, TN, and TP in runoff from the HP#6 watershed.

Evaluating Ecohydrological Impacts of Vegetation Activities on Climatological Perspectives Using MODIS Gross Primary Productivity and Evapotranspiration Products at Korean Regional Flux Network Site

Accurate assessments of spatio-temporal variations in gross primary productivity (GPP), evapotranspiration (ET), and water use efficiency (WUE) play a crucial role in the evaluation of carbon and water balance as well as have considerable effects on climate change. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) products were used to quantify the mean annual GPP and ET at Korean regional flux network site. We found that the seasonal mean values of WUE were 2.86 to 2.92 g∙C∙g∙H2O−1 in the dormant season and 1.81 to 1.88 g∙C∙g∙H2O−1 in the growing season during 2007 and 2008. The WUE was relatively stable during the growing season and tended to vary in the dormant season. Remote sensing data obtained by the MODIS satellite were appeared to be effective to improve our understanding of the spatio-temporal variation of ecohydrological parameters which have not yet been investigated in a number of previous articles. Based on the results of this study, we summarize the interactions between carbon and water circulation in terrestrial ecosystems and how their ecological procedures generated by the photosynthesis of vegetation influence in climatological perspectives.

Development and Assessment of the Sand Dust Prediction Model by Utilizing Microwave-Based Satellite Soil Moisture and Reanalysis Datasets in East Asian Desert Areas

For several decades, satellite-based microwave sensors have provided valuable soil moisture monitoring in various surface conditions. We have first developed a modeled aerosol optical depth (AOD) dataset by utilizing Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Global Land Data Assimilation System (GLDAS) soil moisture datasets in order to estimate dust outbreaks over desert areas of East Asia. Moderate Resolution Imaging Spectroradiometer- (MODIS-) based AOD products were used as reference datasets to validate the modeled AOD (MA). The SMOS-based MA (SMOS-MA) dataset showed good correspondence with observed AOD (-value: 0.56) compared to AMSR2- and GLDAS-based MA datasets, and it overestimated AOD compared to observed AOD. The AMSR2-based MA dataset was found to underestimate AOD, and it showed a relatively low -value (0.35) with respect to observed AOD. Furthermore, SMOS-MA products were able to simulate the short-term AOD trends, having a high -value (0.65). The results of this study may allow us to acknowledge the utilization of microwave-based soil moisture datasets for investigation of near-real time dust outbreak predictions and short-term dust outbreak trend analysis.

Constructing rainfall depth-frequency curves considering a linear trend in rainfall observations

Comprehensive flood prevention plans are established in large basins to cope with recent abnormal floods in South Korea. In order to make economically effective plans, appropriate design rainfalls are critically determined from the rainfall depth-frequency curves which take the occurrence of abnormal floods into consideration. Conventional approaches to construct the rainfall depth-frequency curves are based on the stationarity assumption. However, this assumption has a critical weak aspect in that it cannot reflect non-stationarities in rainfall observations. As an alternative, this study suggests the non-stationary Gumbel model (NSGM) which incorporates a linear trend of rainfall observations into rainfall frequency analysis to construct the rainfall depth-frequency curves. A comparison of various schemes employed in the model found that the proposed NSGM permits the estimation of the distribution parameters even when shifted in the future by using linear relationships between rainfall statistics and distribution parameters, and produces more acceptable estimates of design rainfalls in the future than the conventional model. The NSGM was applied at several stations in South Korea and then expected the design rainfalls to increase by up to 15–30% in 2050.

Reliable estimation of evapotranspiration on agricultural fields predicted by the Priestley-Taylor model using soil moisture data from ground and remote sensing observations compared with the Common Land Model

Evapotranspiration (ET) is a crucial factor in understanding the hydrological cycle and is essential to many applications in hydrology, ecology and water resources management. However, reliable ET measurements and predictions for a range of temporal and spatial scales are difficult. This study focused on the comparison of ET estimates using a relatively simple model, the Priestley–Taylor (P-T) approach, and the physically based Common Land Model (CLM) using ground and remotely sensed soil moisture data as input. The results from both models were compared directly with hourly eddy covariance measurements at two agricultural field sites during the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) in the corn soybean production region in the Upper Midwest, USA. The P-T model showed a significant overestimation of the potential ET compared to the measurements, with a root mean square error (RMSE) between 115 and 130 W m–2. Actual ET was better predicted by the CLM, with the RMSE ranging between 50 and 75 W m–2. However, actual ET from the P-T model constrained with a soil moisture dependency parameterization showed improved results when compared to the measurements, with a significantly reduced bias and RMSE values between 60 and 65 W m–2. This study suggests that even with a simple semi-empirical ET model, similar performance in estimating actual ET for agricultural crops compared to more complex land surface–atmosphere models (i.e. the CLM) can be achieved when constrained with the soil moisture function. This suggests that remote sensing soil moisture estimates from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and others such as the Soil Moisture and Ocean Salinity (SMOS) mission may be effective alternatives under certain environmental conditions for estimating actual ET of agricultural crops using a fairly simple algorithm.