• Economic and Environmental Geology
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• v.54 no.2
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• pp.161-176
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• 2021

In this study, one of the distributed hydrologic models, VELAS, was used to analyze the variation of hydrologic elements based on water balance analysis to evaluate the groundwater recharge in more detail than the annual time scale for the past and future. The study area is located in Yanggok-ri, Seobu-myeon, Hongseong-gun, Chungnam-do, which is very vulnerable to drought. To implement the VELAS model, spatial characteristic data such as digital elevation model (DEM), vegetation, and slope were established, and GIS data were constructed through spatial interpolation on the daily air temperature, precipitation, average wind speed, and relative humidity of the Korea Meteorological Stations. The results of the analysis showed that annual precipitation was 799.1-1750.8 mm, average 1210.7 mm, groundwater recharge of 28.8-492.9 mm, and average 196.9 mm over the past 18 years from 2001 to 2018 in the study area. Annual groundwater recharge rate compared to annual precipitation was from 3.6 to 28.2% with a very large variation and average 14.9%. By the climate change RCP 8.5 scenario, the annual precipitation from 2019 to 2100 was 572.8-1996.5 mm (average 1078.4 mm) and groundwater recharge of 26.7-432.5 mm (average precipitation 16.2%). The annual groundwater recharge rates in the future were projected from 2.8% to 45.1%, 18.2% on average. The components that make up the water balance were well correlated with precipitation, especially in the annual data rather than the daily data. However, the amount of evapotranspiration seems to be more affected by other climatic factors such as temperature. Groundwater recharge in more detailed time scale rather than annual scale is expected to provide basic data that can be used for groundwater development and management if precipitation are severely varied by time, such as droughts or floods.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.4
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• pp.61-67
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• 2019

The purpose of this research is to evaluate the salt tolerance of the Miscanthus sinensis and to characterize the content of pigments in the leachate in relation to calcium chloride ($CaCl_2$) deicing salt. Miscanthus sinensis were cultured at five different concentrations of calcium chloride deicing salt, 0, 1, 2, 5, and $10g{\cdot}L^{-1}$ (referred to Cont. C1, C2, C5, and C10) for four months. The salt tolerance and leachate while growing Miscanthus sinensis on soil which was artificially contaminated by calcium chloride deicing salt. Soil chemical properties (pH, E.C., $Ca^{2+}$, $Na^+$, $K^+$, and $Mg^{2+}$) and plant growth parameters (plant height, leaf length, leaf width, number of leaves, shoot fresh weight, root fresh weight, shoot dry weight, an root dry weight) were evaluated. Soil pH decreased, while electrical conductivity significantly decreased ($p{\leq}0.05$) with a higher concentration of deicing salt $0g{\cdot}L^{-1}$ (Cont.). The increase in the concentration of chloride-based exchangeable cations, along with the increase in the deicing salt treatments, were observed in $Ca^{2+}$ > $Na^+$ > $K^+$ > $Mg^{2+}$. Notably the $Ca^{2+}$ exchangeable cations were 83~90% higher than the others. The growth of Miscanthus sinensis significantly increased ($p{\leq}0.05$) with the concentration of deicing salt higher than $1g{\cdot}L^{-1}$ (C1) when compared to 0 g/L (Cont.), except for the $10g{\cdot}L^{-1}$ (C10) treatment. The results determined that the contamination of soil by deicing salt could negatively impact the soil and Miscanthus sinensis was a tolerant species for the deicing salts. Further research will be focused on soil improvement additives and the stable stimulated plant growth of Miscanthus sinensis and a formulation on that basis for the soil-plant continuum.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.21-36
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• 2019

Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.

• Korean Journal of Ecology and Environment
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• v.54 no.1
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• pp.24-38
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• 2021

Microhabitat In the upper stream is created by various environment variables such as the bottom substrate and the physicochemical factors, and may influence the distribution of benthic macroinvertebrates. We investigated the bottom substrate and environmental variables influencing the distribution of benthic macroinvertebrate in 26 stream-type waterways established at upper reaches of Geum River. During study period, total 85 families, 160 species, 9305 individuals of benthic macroinvertebrates were recorded. The stream-type waterways, where the bottom substrates consist mainly of pebble (16~64 mm) and cobble (64~256 mm) or with rapid water velocity (more than 0.2 m/s) and high dissolved oxygen (more than 120%), were supported by high species diversity of benthic macroinvertebrate. Hierological cluster analysis and the nonparametric multidimensional scale (NMDS) divided 26 stream-type waterways into a total of three clusters. In Cluster 1, the invertebrate species, such as Branchiura sowerbyi, Cloeon dipterum, Ischnura asiatica, Paracercion calamorum, and Radix auricularia, closely related to aquatic macrophytes, and Chironomidae spp., Limnodrilus gotoi, and Tanypodinae sp. were abundant in waterways, with high coverage of silt and clay as well as high turbidity and total nitrogen. The benthic macroinvertebrate species (Cheumatopsyche brevilineata, Drunella ishiyamana, Dugesia japonica, Ephemera orientalis, Gumaga KUa, Macrostemum radiatum, Potamanthus formosus, Semisulcospira libertine, Stenelmis vulgaris, and Teloganopsis punctisetae) included in Cluster 2 were dominated in sites with high cover rates of pebble and gravel. Cluster 3 was predominantly covered by the Cobbles, was supported by Simulium sp. Such a clear distinction in the study sites means that each stream-type waterways is governed by a clear habitat environment. In the case of some sites with low species diversity, improvement measures are required to restore nature, such as improving the function of inflows and outflows, creating meandering channel, and inducing the settlement of littoral vegetation.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1285-1300
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• 2022

Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.145-158
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• 2023

Constructed wetlands (CWs) are effective technologies for urban wastewater management, utilizing natural physico-chemical and biological processes to remove pollutants. This study employed a bibliometric analysis approach to investigate the progress and future research trends in the field of CWs. A comprehensive review of 100 most-recently published and open-access articles was performed to analyze the performance of CWs in treating wastewater. Spain, China, Italy, and the United States were among the most productive countries in terms of the number of published papers. The most frequently used keywords in publications include water quality (n=19), phytoremediation (n=13), stormwater (n=11), and phosphorus (n=11), suggesting that the efficiency of CWs in improving water quality and removal of nutrients were widely investigated. Among the different types of CWs reviewed, hybrid CWs exhibited the highest removal efficiencies for BOD (88.67%) and TSS (95.67%), whereas VSSF, and HSSF systems also showed high TSS removal efficiencies (83.25%, and 78.83% respectively). VSSF wetland displayed the highest COD removal efficiency (71.82%). Generally, physical processes (e.g., sedimentation, filtration, adsorption) and biological mechanisms (i.e., biodegradation) contributed to the high removal efficiency of TSS, BOD, and COD in CW systems. The hybrid CW system demonstrated highest TN removal efficiency (60.78%) by integrating multiple treatment processes, including aerobic and anaerobic conditions, various vegetation types, and different media configurations, which enhanced microbial activity and allowed for comprehensive nitrogen compound removal. The FWS system showed the highest TP removal efficiency (54.50%) due to combined process of settling sediment-bound phosphorus and plant uptake. Phragmites, Cyperus, Iris, and Typha were commonly used in CWs due to their superior phytoremediation capabilities. The study emphasized the potential of CWs as sustainable alternatives for wastewater management, particularly in urban areas.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.99-110
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• 2023

Non-point source (NP) pollutants in an agricultural landuse are discharged from a large area compared to those in other land uses, and thus effective source control measures are needed. To develop appropriate control measures, it is necessary to quantify discharge load of each source and evaluate the degree of water quality improvement by implementing different options of the control measures. This study used Hydrological Simulation Program-FORTRAN (HSPF) to quantify pollutant discharge loads from different sources and effects of different control measures on water quality improvements, thereby supporting decision making in developing appropirate pollutant control strategies. The study area is the Gyeseong river watershed in Changnyeong county, Gyeongsangnam-do, with agricultural areas occupying the largest proportion (26.13%) of the total area except for the forest area. The main pollutant sources include chemical and liquid fertilizers for agricultural activities, and manure produced from small scale livestock facilities and applied to agriculture lands or stacked near the facilities. Source loads of chemical fertilizers, liquid fertilizers and livestock manure of small scale livestock facilities, and point sources such as municipal wastewater treatment plants (WWTPs), community WWTPs, private sewage treament plants were considered in the HSPF model setup. Especially, NITR and PHOS modules were used to simulate detailed fate and transport processes including vegitation uptake, nutrient deposition, adsorption/desorption, and loss by deep percolation. The HSPF model was calibrated and validated based on the observed data from 2015 to 2020 at the outlet of the watershed. The calibrated model showed reasonably good performance in simulating the flow and water quality. Five Pollutants control scenarios were established from three sectors: agriculture pollution management (drainge outlet control, and replacement of controlled release fertilizers), livestock pollution management (liquid fertilizer reduction, and 'manure management of small scale livestock facilities) and private STP management. Each pollutant control measure was further divided into short-term, mid-term, and long-term scenarios based on the potential achievement period. The simulation results showed that the most effective control measure is the replacement of controlled release fertilizers followed by the drainge outlet control and the manure management of small scale livestock facilities. Furthermore, the simulation showed that application of all the control measures in the entire watershed can decrease the annual TN and TP loads at the outlet by 40.6% and 41.1%, respectively, and the annual average concentrations of TN and TP at the outlet by 35.1% and 29.2%, respectively. This study supports decision makers in priotizing different pollutant control measures based on their predicted performance on the water quality improvements in an agriculturally dominated watershed.

• Journal of Wetlands Research
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• v.25 no.3
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• pp.205-212
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• 2023

This study was attempted to find out how the ecological niche and interspecies relationship of Quercus aliena and Q. serrata, which are the main constituents of potential natural vegetation along the riverside of mountains in Korea, under climate change conditions. To this end, soil moisture and soil nutrients were treated with 4 grad ients under climate change conditions with elevated CO₂ and temperature, plants we re harvested at the end of the growing season, growth responses of traits were measured, ecological niche breadth and overlap were calculated, and it was compared with that of the control group(ambient condition). In addition, the relationship between the two species was analyzed by principal component analysis using trait values. As a result, the ecological niche breadth of Q. aliena was wider than that of Q. serrata under the moisture environment conditions under climate change. Under nutrient conditions, the ecological niche of the two species were similar. In addition, the ecological overlap for soil moisture of Q. aliena and Q. serrata was wider than the soil nutrient gradient under climate change. The species with traits in which the increase in ecological niche breadth due to climate change occurred more than the decrease was Q. aliena in both water and nutrient gradients. And in the responses of the population level, due to climate change, the adaptability of Q. aliena was higher than that of Q. serrata under the soil moisture condition, but the two species were similar under the nutrient condition. These results mean that the competition between the two species occurs more severely in the water environment under climate change conditions, and at that time, Q. aliena has higher adaptability than Q. serrata.