• Korean Journal of Soil Science and Fertilizer
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• v.38 no.4
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• pp.218-221
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• 2005

The present study was investigated in the Chittagong hill forest of Bangladesh to assess the feasibility of ginger cultivation under multipurpose forest and fruit tree species. There were three treatments such as i) ginger grown under open field condition, ie. full sunlight (T1), ii) ginger grown under Gamar tree (spacing of $90{\times}90cm$ (T2) and iii) ginger grown under guava tree (spacing $180{\times}180cm$) tree (T3). The experiment was laid out in randomized block design (RBD) and each treatment was replicated three times. From data it was observed that some morphological parameters of ginger such as plant height, number of leaves per plant, leaf length and leaf breadth were higher in the treatments T2 and T3 as compared to the treatment T1. A positive and linear relationship was observed between the weight of rhizome and yield of ginger which caused the highest yield of ginger ($23.63Mg\;ha^{-1}$) under guava tree species at partial shaded condition in the T3 treatment ($180{\times}180cm$), whereas the lowest yield ($15.64Mg\;ha^{-1}$) was recorded in the T2 treatment when ginger was cultivated under Gamar tree species at closer spacing ($90{\times}90cm$). Therefore, it was revealed that partial shaded condition favoured the optimum growth and yield of ginger, whereas the dense shade from intensively planted tree species badly affected the dry matter production and yield of ginger.

• Water for future
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• v.29 no.4
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• pp.209-221
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• 1996

It may be difficult to make exact estimates of peak discharge or runoff depth of a flood and to establish the proper measurement for the flood protection since water stages or discharges have been rarely measured at small river basins in Korea. Three small catchments in the Su-Young river basin in Pusan were selected for the study areas. Various runoff parameters for the study areas were determined, and runoff analyses were performed using three different runoff models available in literatures; the storage function method, the discrete, linear, input-output model, and the linear reservoir model. The hydrographs calculated by three different methods showed good agreement with the observed flood hydrographs, indicating that the models selected are all capable of sucessfully modeling the flood events for small watersheds. The storage function method gave the best results in spite of its weakness that it could not be applicable to small floods, while the linear reservoir model was found to provide relatively good results with less parameters. The capabilities of simulating flood hydrographs were also evaluated based on the effective rainfall from the storage function parameters, the $\Phi$-index method, and the constant percentage method. For the On-Cheon stream watershed, the storage function parameters provided better estimates of effective rainfall for regenerating flood hydrographs than any others considered in the study. The $\Phi$-index method, however, resulted in better estimates of effective rainfall for the other two study areas.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.823-827
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• 2010

This study was conducted to assess the propriety of models for soil water characteristics estimation in anthropogenic soil through the measurement of soil water content and soil water matric potential. Soil profile was characterized with four different soil layers. Soil texture was loamy sand for the first soil layer (from soil surface to 30 cm soil depth), sand for the second (30~70 cm soil depth) and the third soil layers (70~120 cm soil depth), and sandy loam for the fourth soil layer (120 cm < soil depth). Soil water retention curve (SWRC), the relation between soil water content and soil water matric potential, took a similar trend between different layers except the layer of below 120 cm soil depth. The estimation of SWRC and air entry value was better in van Genuchten model by analytical method than in Brooks-Corey model with power function. Therefore, it could be concluded that van Genuchten model is more desirable than Brook-Corey model for estimating soil water characteristics of anthropogenic soil accumulated with saprolite.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.13-23
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• 2021

This study intended to assess the reliability of topographic data using satellite imaging data. The topographical data using actual instrumentation data and satellite image data were established and applied to the rainfall-leak model, S-RAT, and the topographical data and outflow data were compared and analyzed. The actual measurement data were collected from the Water Resources Management Information System (WAMIS), and satellite image data were collected from MODIS observation sensors mounted on Terra satellites. The areas subject to analysis were selected for two rivers with more than 80% mountainous areas in the Han River basin and one river basin with more than 7% urban areas. According to the analysis, the difference between instrumentation data and satellite image data was up to 50% for peak floods and up to 17% for flood totals in rivers with high mountains, but up to 13% for peak floods and up to 4% for flood totals. The biggest difference in the video data is Landuse, which shows that MODIS satellite images tend to be recognized as cities up to 60% or more in urban streams compared to WAMIS instrumentation data, but MODIS satellite images are found to be less than 5% error in forest areas.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Korean Journal of Ecology and Environment
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• v.52 no.2
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• pp.81-93
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• 2019

Phytoplankton is one of the important primary producers providing organic matter through photosynthesis in aquatic environments. In order to determine a temporal and spatial variation in primary productivity after weir construction in the Nakdong River, we investigated carbon uptake rates using in-situ $^{13}C$ labeling experiments and identified algal communities contributing to primary productivity using HPLC-CHEMTAX analysis from October to December, 2017. The primary productivity gradually decreased from fall to early winter season ($249{\sim}933mgC\;m^{-2}d^{-1}$ in October, $64{\sim}536mgC\;m^{-2}d^{-1}$ in November and $60{\sim}274mgC\;m^{-2}d^{-1}$ in December, respectively). This is attributed to the temporally declining light intensity and the decreasing biomass and physiological activity of phytoplankton in winter. The contribution of diatoms to the phytoplankton community in the Nakdong River was approximately 63% at all the sampling sites and seasons, while the contribution of cryptophytes increased from 9% in October to 32% in November and December. The temporal changes in the primary productivity and the dominant phytoplankton species in the mid and downstream weirs of the Nakdong River was investigated for the first time, after construction of the weirs, and major environmental factors controlling the temporal variation in primary productivity and phytoplankton communities were identified in this study. We suggest that seasonal field investigations will provide further information on the major environmental factors which affect the annual variation of primary productivity and phytoplankton communities.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.114-124
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• 2019

The objective of this study is to reduce the uncertainty of the river discharge estimation method using the stage-discharge relation curve. It is necessary to consider the quantitative and accurate estimation method because the river discharge data is essential data for hydrological interpretation and water resource management. For this purpose, the parameters estimated by Bayesian and Bootstrap methods are compared with the ones obtained by stage-discharge relation curve. In addition, the Bayesian and Bootstrap methods are applied to assess uncertainty and then those are compared with the confidence intervals of the results from standard error method which has t-distribution. From the results of this study, The estimated value of the regression analysis developed through this study is less than 1 ~ 5%. Also It is confirmed that there are some areas where the applicability is better than the existing one according to the water level at each point. Therefore, if we use more suitable method according to the river characteristics, we could obtain more reliable discharge with less uncertainty.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.4
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• pp.391-405
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• 2020

Leaching chracteristics of Andong-dam sediment was conducted for heavy metal and nutrients. Five mixed sediment samples were prepared and leaching was conducted under aerobic and anaerobic condition for 60 days. Cd, Cu, Pb, Cr, Zn, Hg, As, Fe, Mn, phosphorus, and nitrogen were analyzed at each sampling time. The leaching rate of phosphorus was higher in anaerobic condition comparing with that of under aerobic condition. Some samples showed higher than the water-quality level IV. In case of As and Cd which showed highest contamination level in the sediment, leached concentration were 0.028 mg/L and 0.003 mg/L in maximum, respectively. The leached concentration is below than the lake water quality standard of Korea. Other heavy metals including Cu, Pb, and Cr also showed similar trend. Five step sequential extraction showed that easily extractable 1-2 step portion such as ion-exchangeable and adsorbed one was less than 10% and the most of the portion was residual. For As and Cd, the residual portion were 80% and 95% respectively indicating the risk by the heavy metal leaching into the lake for a short period was not high in comparing with the contamination levels.