• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.105-123
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• 2018

Currently, satellite images act as essential and important data in water resources, environment, and ecology as well as information of geographic information system. In this paper, we will investigate basic characteristics of satellite images, especially application examples in water resources. In recent years, researches on spatial and temporal characteristics of large-scale regions utilizing the advantages of satellite imagery have been actively conducted for fundamental hydrological components such as evapotranspiration, soil moisture and natural disasters such as drought, flood, and heavy snow. Furthermore, it is possible to analyze temporal and spatial characteristics such as vegetation characteristics, plant production, net primary production, turbidity of water bodies, chlorophyll concentration, and water quality by using various image information utilizing various sensor information of satellites. Korea is planning to launch a satellite for water resources and environment in the near future, so various researches are expected to be activated on this field.

• Korean Journal of Ecology and Environment
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• v.50 no.1
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• pp.29-45
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• 2017

This study explored spatiotemporal variability of water quality in correspondence with hydro-meteorological factors in the four stations of Euiam Reservoir located in the upstream region of the North-Han River from May 2012 to December 2015. Seasonal effect was apparent in the variation of water temperature, DO, electric conductivity and TSS during the study period. Stratification in the water column was observed in the near dam site every year and vanished between August and October. Increase of nitrogen nutrients was observed when inflowing discharge was low, while phosphorus increase was distinct both during the early season with increase of inflowing discharge and the period of severe draught persistent. Duration persisting high concentration of Chl-a (>$25mg\;m^{-3}$: the eutrophic status criterion, OECD, 1982) was 1~2 months of the whole year in 2014~2015, while it was almost 4 months in 2013. Water quality of Euiam Reservoir appeared to be affected basically by geomorphology and source of pollutants, such as longitudinally linked instream islands and Aggregate Island, inflowing urban stream, and wastewater treatment plant discharge. While inflowing discharge from the dams upstream and outflow pattern causing water level change seem to largely govern the variability of water quality in this particular system. In the process of spatiotemporal water quality change, factors related to climate (e.g. flood, typhoon, abruptly high rainfall, scorching heat of summer), hydrology (amount of flow and water level) might be attributed to water pulse, dilution, backflow, uptake, and sedimentation. This study showed that change of water quality in Euiam Reservoir was very dynamic and suggested that its effect could be delivered to downstream (Cheongpyeong and Paldang Reservoirs) through year-round discharge for hydropower generation.

• Journal of The Korean Society of Grassland and Forage Science
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• v.3 no.2
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• pp.67-76
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• 1983

This experiment was carried out to investigate the effects of the different nitrogen rates and cutting heights on the dead stubble after cutting, and the carbohydrate reserved in stubble of sorghum-sudangrass hybrid (Sorghum bicolor (L.) Moench) Pioneer 988. The experiment was undertaken in the Experimental Livestock Farm of Agriculture Coll., Seoul Nat'l Univ. In Suweon, 1981 and 1982. The results obtained are summarized as follows: 1. The dead stubble after cutting was found to be great with high rate of nitrogen fertilizer and low cutting height. It was also learned that the rainfall during forage cutting period made the dead stubble increased. 2. A significant higher (p<0.05) carbohydrate reserves in the stubble was observed in the high stubble height at the first cutting time and 6th through 7th day after the first cutting. The results indicate that the high stubble height reserves more carbohydrate for the early regrwoth stage after the first cutting when comparing with the low stubble. 3. The content of carbohydrate reserves was influenced by climete. Drought is caused to high content of carbohydrate, whereas, rain is caused to low content of that. The critical soluble carbohydrate content causing the death of stubble supposed to be 3 to 6% at least. 4. It is suggest that carbohydrate reserves in plant do not play a distinctive role for the regrowth in a summer annual forage like sorghum-sudangrass hybrid, but it might be rather influenced by the other factors, for example, environmental conditions at harvest and new bud.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.344-352
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• 2019

Drought stress caused by global climate change is a serious problem for rice cultivation. Increasingly frequent abnormal weather occurrences could include severe drought, which could cause water stress to rice during the seedling stage. This experiment was conducted to clarify the effects of drought during the seedling period on yield and quality of rice. Drought conditions were created in a rain shelter house facility. The drought treatment was conducted at 3, 10, and 20 days after transplanting. Soil water content was measured by a soil moisture sensor during the whole growth stage. In this study, we have chosen 3 rice cultivars which are widely cultivated in Korea: 'Haedamssal' (Early maturing), 'Samkwang' (Medium maturing), and 'Saenuri' (Mid-late maturing). The decrease in yield due to drought treatment was most severe 3 days after transplanting because of the decrease in the number of effective tillers. The decrease in grain quality due to drought treatment was also most severe 3 days after transplanting because of the increased protein content and hardness of the grains. The cultivar 'Haedamssal' was the most severely damaged by water stress, resulting in about a 30% yield loss. Drought conditions diminished the early vigorous growth period and days to heading in early-maturing cultivars. The results show that drought stress affects yield components immediately after transplanting, which is a decisive factor in reducing yield and grain quality. This study can be used as basic data to calculate damage compensation for drought damage on actual rice farms.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.406-413
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• 2019

The purpose of this research was to analyze the effect of different sowing times on the flowering and maturing of major soybean cultivars by varying day length and temperature in the central plain region. The average of growth period and cumulative temperature in five test cultivars by sowing times were 121 days and 2,972℃ on June 1, respectively and gradually decreased to 85 days, 2,042℃, respectively on July 20. Analysis of the flowering response according to the sowing times showed that flowering was greatly influenced by the decrease of photoperiod until the sowing on July 10, and the minimum number of days for flowering were 27 days, 36 days, respectively in early and mid-rate maturing type in the central plain region. Daepung 2 is classified to the same ecotype with Daewonkong, the total number of growing days was not different between two cultivars, but ripening period (R2-R6) was longer by 5 days and yield was higher by 11% in Daepung 2. The maturity rate was also high and safe enough to maintain more than 90% through the entire sowing times. This ecological characteristic can be usefully applied as a section index for breeding environmental stress resistant and high yielding soybean varieties. The yield of 4 domestic cultivars (except TI196944) sowing on July 20 were 85~92% levels compared to sowing on June 20.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.11-18
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• 2018

The climate change impacts on hydrological components and water balance in Jeju Island were evaluated using multiple climate models and watershed model, SWAT-K. To take into account the uncertainty of the future forecast data according to climate models, climate data of 9 GCMs were utilized as weather data of SWAT-K for future period (2010-2099). Using the modeling results of the past (1992-2013) and the future period, the hydrological changes of each year were analyzed and the precipitation, runoff, evapotranspiration and recharge were increasing. Compared with the past, the change in the runoff was the largest (up to 50% increase) and the evapotranspiration was relatively small (up to 11% increase). Monthly results show that the amount of evapotranspiration and the amount of recharge are greatly increased as the amount of precipitation increases in August and September, while the amount of evapotranspiration decreases in the same period. January and December showed the opposite tendency. As a result of analyzing future water balance changes, the ratio of runoff, evapotranspiration, and recharge to rainfall did not change much, but compared to the past, the runoff rate increased up to 4.3% in the RCP 8.5 scenario, while the evapotranspiration rate decreased by up to 3.5%. Based on the results of other researchers and this study, it is expected that rainfall and runoff will increase gradually in the future under the assumption of present climate change scenarios. Especially summer precipitation and runoff are expected to increase. As a result, the amount of groundwater recharge in Jeju Island will increase.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.