• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.709-720
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• 2010

This paper describes the modeling of climate change impact on drought using a conceptual soil moisture model and presents the results of the modeling approach. The future climate series is obtained by scaling the historical series, informed by CCCma CGCM3-T63 with A2 green house emission scenario, using a daily scaling method that considers changes in the future monthly precipitation and potential evapotranspiration as well as in the daily precipitation distribution. The majority of the modeling results indicate that there will be more frequent drought in Korea in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.1
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• pp.32-37
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• 1999

The experiment was conducted to investigate emergence response of lowland weeds at different soil moisture contents, burying depths and upon changes in soil moisture. Rice germination was over 50% at all burying depths under aerobic condition, but the emergence rate of the soil surface placed seeds in saturated and flooded conditions decreased by 19% and 29%, respectively, as compared with that of aerobic condition. Rice seeds at burying depth of over 3 cm did not emerge at all. The emergence rate of Echinochloa crus­galli (L.) Beauv. in aerobic condition was lower than 30%, but the emergence pattern of E. crus galli (L.) Beauv. at different soil moisture contents and seeding depths was similar to that of rice. Emergence behavior of lschaemum rugosum Salisb., Ludwigia octovalvis (Jacq.) Raven and Sphenoclea zeylanica Gaertn. which are dominant lowland weed species in the Philippines also differed depending on soil moisture conditions and burying depths. lschaemum rugosum Salisb. emerged at all burying depths under aerobic condition, whereasLudwigia octovalvis (Jacq.) Raven emerged only at 0 cm deep under saturated and aerobic condition and Sphenoclea zeylanica Gaertn. at 0 cm deep under flooding condition. Weed seeds planted at 1, 3, and 5 cm deep in continuous flooded and saturated condition did not emerge at all, but upon a change of soil moisture condition from saturated to drainage (S$\rightarrow$D) and flooded to drainage (F$\rightarrow$D), grass weeds began to germinate again and the average emergence rate in S$\rightarrow$D and F$\rightarrow$D were 26% and 5% forE. crus­galIi (L.) Beauv., 9% and 8% forI. rugosum SaIisb., respectively. Weed seeds buried in soil in the pot showed great emergence at S$\rightarrow$D but did not emerge under continuous flooded condition. The diversity index accounting for dominance degree and occurrence aspect of weed, was the lowest at F$\rightarrow$D.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.569-583
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• 2013

This study is to evaluate the future climate change impact on hydrological components in the Seolmacheon ($8.54km^2$) mixed forest catchment located in the northwest of South Korea using SWAT (Soil and Water Assessment Tool) model. To reduce the uncertainty, the model was spatially calibrated (2007~2008) and validated (2009~2010) using daily observed streamflow, evapotranspiration, and soil moisture data. Hydrological predicted values matched well with the observed values by showing coefficient of determination ($R^2$) from 0.74 to 0.91 for streamflow, from 0.56 to 0.71 for evapotranspiration, and from 0.45 to 0.71 for soil moisture. The HadGEM3-RA future weather data of Representative Concentration pathway (RCP) 4.5 and 8.5 scenarios of the IPCC (Intergovernmental Panel on Climate Change) AR5 (Assessment Report 5) were adopted for future assessment after bias correction of ground measured data. The future changes in annual temperature and precipitation showed an upward tendency from $0.9^{\circ}C$ to $4.2^{\circ}C$ and from 7.9% to 20.4% respectively. The future streamflow showed an increase from 0.6% to 15.7%, but runoff ratio showed a decrease from 3.8% to 5.4%. The future predicted evapotranspiration about precipitation increased from 4.1% to 6.8%, and the future soil moisture decreased from 4.3% to 5.5%.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.53-61
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• 2020

The laboratory model test was conducted by dividing domestic reclaimed tideland into Sandy Loam (SL) and Silt Clay Loam (SiCL) to estimate soil moisture change and water supply according to soil characteristic when establishing irrigation plan for reclaimed tideland upland crop. In addition, the applicability of each scenario was verified using Van Genuchten model, which is the most widely used mathematical model for analyzing soil moisture characteristics of reclaimed tideland uplands crops. The required water supply according to the target soil moisture tension by reclaimed tideland is as follow. In the case of SL, soil depths of 0~10 cm, 10~20 cm were analyzed as 19 mm, 35 mm to reach the field capacity, and SiCL, 33 mm, 63 mm. The required water supply of SiCL was higher than that of SL. The study compared the simulation results from the scenarios of Van Genuchen model and the measured results from the laboratory model test based on according to the reclaimed tidelands. In the case of parameter, θ_s, θ_r, α, η were analyzed 0.55, 0.18, 0.064, 1.74 in SL and 0.46, 0.22, 0.105, 1.92 in SiCL. In terms of soil characteristics, SL with better water permeability was found to have higher applicability than SiCL. By Soil depth, applicability was found in 0~10 cm directly affected by water supply.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.587-607
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• 2020

Soil moisture is essential information for meteorological and hydrological analyses. To date, many efforts have been made to achieve the two goals for soil moisture data, i.e., the improvement of accuracy and resolution, which is very challenging. We presented an ensemble downscaling method for quality improvement of gridded soil moisture data in terms of the accuracy and the spatial resolution by the integration of BMA (Bayesian model averaging) and ATPRK (area-to-point regression kriging). In the experiments, the BMA ensemble showed a 22% better accuracy than the data sets from ESA CCI (European Space Agency-Climate Change Initiative), ERA5 (ECMWF Reanalysis 5), and GLDAS (Global Land Data Assimilation System) in terms of RMSE (root mean square error). Also, the ATPRK downscaling could enhance the spatial resolution from 0.25° to 0.05° while preserving the improved accuracy and the spatial pattern of the BMA ensemble, without under- or over-estimation. The quality-improved data sets can contribute to a variety of local and regional applications related to soil moisture, such as agriculture, forest, hydrology, and meteorology. Because the ensemble downscaling method can be applied to the other land surface variables such as temperature, humidity, precipitation, and evapotranspiration, it can be a viable option to complement the accuracy and the spatial resolution of satellite images and numerical models.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.1027-1036
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• 2005

Based on the correlation analysis result of preceding research, the biodegradabilities of cellulose fibers were closely related to the moisture regain of the samples, which reflects the hydrophilicity and internal structure of the fibers. In addition to this factor, it was expected that the biodegradation conditions influence the biodegradability of fibers. In this study, widely used cellulose fibers including cotton, rayon, and acetate were used. The biodegradabilities of cellulose fibers were measured by soilburial test, and then the degradation behaviors based on each condition were compared. Moreover, the effects of degradation conditions such as humidity of the soil were investigated. Changes in the internal structure of samples were also observed by X-ray analysis according to the soil burial time. It was shown that humidity of soil facilitated the degradation of cotton, rayon, and acetate fibers, showing higher degradation rate with higher humidity in soil. This effect was shown to be much greater in the fibers of high moisture regain such as cotton and rayon. In respect of microstructure change, crystallinities and their crystal size of fibers decreased remarkably in the soil of higher humidity. It was revealed that degradation of crystalline area was more dependent on the soil humidity than that of amorphous area.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.5
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• pp.77-87
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• 2014

The impacts of climate change on upland crops is great significance for water resource planning, estimating crop water demand and irrigation scheduling. The objective of this study is to predict upland crop evapotranspiration, effective rainfall and net irrigation requirement for upland under climate change, and changes in the temporal trends in South Korea. The changes in consumptive use and net irrigation requirement in the six upland crops, such as Soybeans, Maize, Potatoes, Red Peppers, Chinese Cabbage (spring and fall) were determined based on the soil moisture model using historical meteorological data and climate change data from the representative concentration pathway (RCP) scenarios. The results of this study showed that the average annual upland crop evapotranspiration and net irrigation requirement during the growing period for upland crops would increase persistently in the future, and were projected to increase more in RCP 8.5 than those in RCP 4.5 scenario, while effective rainfall decreased. This study is significant, as it provides baseline information on future plan of water resources management for upland crops related to climate variability and change.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.198-198
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• 2017

Climate change causes unpredictable and erratic climatic patterns which affects crop production in agriculture and threatens public health. To cope with the challenges of climate change, sustainable and sound growth environment for crop production should be secured. Recent attention has been given to the development of smart irrigation system using sensors and wireless network as a solution to achieve water conservation as well as improvement in crop yield and quality with less water and labor. This study developed the smart irrigation technique for farmlands by monitoring the soil moisture contents and real-time climate condition for decision-making support. Central to this design is micro-controller which monitors the farm condition and controls the distribution of water on the farm. In addition, a series of laboratory studies were conducted to determine the optimal irrigation pattern, one time versus plug time. This smart technique allows farmers to reduce water use, improve the efficiency of irrigation systems, produce more yields and better quality of crops, reduce fertilizer and pesticide application, improve crop uniformity, and prevent soil erosion which eventually reduce the nonpoint source pollution discharge into aquatic-environment.

• The Korean Journal of Quaternary Research
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• v.19 no.2
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• pp.24-27
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• 2005

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.