• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.1
• /
• pp.35-44
• /
• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

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

• Atmosphere
• /
• v.32 no.2
• /
• pp.87-101
• /
• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Economic and Environmental Geology
• /
• v.45 no.3
• /
• pp.307-315
• /
• 2012

In this paper, a laboratory model test was conducted to evaluate grouting efficiency of ordinary portland cement(OPC) and micro cement used in MIS(Micro-Injection Process System). For this research, a injection equipment was developed for pressure permeation which can evenly simulate various grouting tests in a laboratory and suggested a standard for the production of the test specimen. Using the injection device, the laboratory injection tests of grouts were prepared with water/cement ratio of 1:1, 2:1, 3:1, 4:1, and 5:1. The analysis of injection test for pressure permeation showed that the efficiency of injection increases linearly as the water/cement ratio increases. Comparison of efficiency of the injection indicates that MIS with a relatively smaller average diameter shows more efficient injection than the OPC. In the low ratio of water/cement as 2:1~1:1, the injection efficiency of OPC was especially poor. Also, a nonlinear grout volume-injection time is represented by a hyperbolic model and grout volume predicted by hyperbolic model was compared with the value measured. From the comparison, it shows that the hyperbolic model has the potential of evaluating the efficiency of grouting.

• Journal of Digital Convergence
• /
• v.15 no.11
• /
• pp.245-250
• /
• 2017

Flash floods is defined as the flooding of intense rainfall over a relatively small area that flows through river and valley rapidly in short time with no advance warning. So that it can cause damage property and casuality. This study is to establish the flash-flood warning system using 38 accident data, reported from the National Disaster Information Center and Land Surface Model(TOPLATS) between 2009 and 2012. Three variables were used in the Land Surface Model: precipitation, soil moisture, and surface runoff. The three variables of 6 hours preceding flash flood were reduced to 3 factors through factor analysis. Decision tree, random forest, Naive Bayes, Support Vector Machine, and logistic regression model are considered as big data methods. The prediction performance was evaluated by comparison of Accuracy, Kappa, TP Rate, FP Rate and F-Measure. The best method was suggested based on reproducibility evaluation at the each points of flash flood occurrence and predicted count versus actual count using 4 years data.

• Journal of Radiation Protection and Research
• /
• v.18 no.1
• /
• pp.9-24
• /
• 1993

The time-dependent radioecological model applicable to Korean environment has been developed in order to assess the radiological consequences following the short-term deposition of radionuclides in an accident of nuclear power plant. Time-dependent radioactivity concentrations in foodstuffs can be estimated by the model called 'KORFOOD' as well as time-dependent and time-integrated ingestion doses. Three kinds of critical radionuclides and thirteen kinds of foodstuffs were considered in this model. Dynamic variation of radioactivities were simulated by considering several effects such as deposition, weathering and washout, resuspension, root uptake, translocation, leaching, senescence, intake and excretion of soil by animals, intake and excretion of feedstuffs by animals, etc. The input data to the KORFOOD are the time of the year when the deposition occurs, the kinds of radionuclides and foodstuffs for estimation. The time-dependent specific activities in rice and the ingestion doses due to the consumption of all considered foodstuffs were calculated with deposition time using agricultural data-base in Kori region. In order to validate results of KORFOOD, the calculated results were compared with those by a leading German model, ECOSYS-87. The comparison of results shows good agreements within a factor of ten.

• Journal of Korean Society on Water Environment
• /
• v.29 no.3
• /
• pp.365-376
• /
• 2013

The purpose of this study was to evaluate effects of spatio-temporal changes in land uses and rainfall magnitude using the Soil and Water Assessment Tool (SWAT). Prior of application of the model to real-world problem, the model should be calibrated and validated properly. In most modeling approaches, the validation process is done assuming no significant changes occurring at the study watershed between calibration and validation periods, which is not proper assumption for agricultural watersheds. If simulated results obtained with calibrated parameters match observed data with higher accuracy for validation period, this does not always mean the simulated result represents rainfall-runoff, pollutant generation and transport mechanism for validation period because temporal and spatial variables and rainfall magnitude are often not the same. In this study SWAT was applied to Mandae study watershed in Korea to evaluate effects of spatio-temporal changes in landuses using 2009 and 2010 crop data for each field at the watershed. The Nash-Sutcliffe model efficiency (NSE) values for calibration and validation with either 2009 or 2010 was evaluated and the NSE value for calibration with 2009 and calibration with 2010 were compared. It was found that if there is substantial change in land use and rainfall, model calibration period should be determined to reflect those changes. Through these approaches, inherent limitation of the SWAT, which does not consider changes in land uses over the simulation period, was investigated. Also, Effects of changes in rainfall magnitude during calibration process were analyzed.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.3
• /
• pp.37-48
• /
• 2010

The purpose of this paper is to evaluate how the rainfall field effect on a runoff simulation using grid radar rainfall data and ground gauge rainfall. The Gwangdeoksan radar and ground-gauge rainfall data were used to estimate a spatial rainfall field, and a hydrologic model was used to evaluate whether the rainfall fields created by each method reproduced a realistically valid spatial and temporal distribution. Pilot basin in this paper was the Naerin stream located in Inje-gun, Gangwondo, 250m grid scale digital elevation data, land cover maps, and soil maps were used to estimate geological parameters for the hydrologic model. For the rainfall input data, quantitative precipitation estimation(QPE), adjusted radar rainfall, and gauge rainfall was used, and then compared with the observed runoff by inputting it into a $Vflo^{TM}$ model. As a result of the simulation, the quantitative precipitation estimation and the ground rainfall were underestimated when compared to the observed runoff, while the adjusted radar rainfall showed a similar runoff simulation with the actual observed runoff. From these results, we suggested that when weather radars and ground rainfall data are combined, they have a greater hydrological usability as input data for a hydrological model than when just radar rainfall or ground rainfall is used separately.

• Journal of the Korean Society of Groundwater Environment
• /
• v.7 no.2
• /
• pp.89-96
• /
• 2000

Slug tests are the most widely used field method for quantification of hydraulic conductivity of porous media. Well recovery is affected by well casing, borehole radii, screened length, hydraulic conductivity, and specific storage of porous media. In this study, a new slug tests model was developed through finite element approximation and the validity and usefulness of the model were tested in various ways. Water level fluctuation in a well under slug test and cons-equent groundwater flow in the surrounding porous medium were appropriately coupled through estimation of well-flux using an iteration technique. Numerical accuracy of the model was verified using the Cooper et al. (1967) solution. The model has advantages in simulations for monitored slug tests, partial penetration, and inclusion of storage factor. Volume coverage of slug tests is significantly affected by storage factor. Magnitude and speed of propagation of head changes from a well increases as storage factor becomes low. It will be beneficial to use type curves of monitored head transients in the surrounding porous formation for estimation of specific storage. As the vertical component of groundwater flow is enhanced, the influence of storage factor on well recovery decreases. For a radial-vertical flow around a partially penetrated well, deviations between hydraulic estimates by various methods and data selection of recovery curve are negligible on practical purposes, whereas the deviations are somewhat significant for a radial flow.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.8 no.4
• /
• pp.23-32
• /
• 1988

The rates of infiltration contributed to the flow fo water in an unconfined aquifer under the partially penetrated stream at an ungaged station and the corresponding base flow in channel are coupled by using the hydraulic and/or hydrologic characteristics obtained from the geomorphologic and soil maps. For the determination of groundwater flow, the linearized model which is originally Boussinesq's nonlinear equation is applied in this study. Also, a stream flow routing model for base flow in channel is based on a simplification of the Saint-venant. The distributed runoff model with piecewise spatial uniformity is presented for obtaining its solution based on a finite difference technique of the kinematic wave equations. The method developed in this study was tested to the Bocheong watershed(area : $475.5km^2$) of the natural stream basin which is one of tributaries in Geum River basin in Korea. As a result, it is suggested that the rationality of hydro-graph separation according to a wide variability in hydrogeologic properties be worked out as developing the physically based subsurface model. The results of the present model are shown to be possible to simulate a base flow due to an arbitrary rate of infiltration for ungaged basins.