• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.37-47
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• 2017

In this study, we analyzed the variability of irrigation water amounts based on the combination of various crops and soil textures using the Irrigation Water Management Model (IWMM). IWMM evaluates the degree of agricultural drought using the Soil Moisture Deficit Index (SMDI). When crops are damaged by the water scarcity under the drought condition indicating that the SMDI values are in negative (SMDI<0), IWMM irrigates appropriate water amounts that can shift the negative SMDI values to "0" to crop fields. To test the IWMM model, we selected the Bandong-ri (BDR) and Jucheon (JC) sites in Gangwon-do and Jeollabuk-do provinces. We derived the soil hydraulic properties using the near-surface data assimilation scheme form the Time Domain Reflectrometry (TDR)-based soil moisture measurements. The daily root zone soil moisture dynamics (R: 0.792/0.588 and RMSE: 0.013/0.018 for BDR/JC) estimated by the derived soil parameters were matched well with the TDR-based measurements for validation. During the long-term (2001~2015) period, IWMM irrigated the minimum water amounts to crop fields, while there were no irrigation events during the rainy days. Also, Sandy Loam (SL) and Silt (Si) soils require more irrigation water amounts than others, while the irrigation water were higher in the order of radish, wheat, soybean, and potato, respectively. Thus, the IWMM model can provide efficient irrigation water amounts to crop fields and be useful for regions at where limited water resources are available.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.73-82
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• 2018

In this study, we assessed meteorological and agricultural drought based on the SPI(Standardized Precipitation Index), SMP(Soil Moisture Percentile), and SMDI(Soil Moisture Deficit Index) indices using satellite-based TRMM(Tropical Rainfall Measuring Mission)/GPM(Global Precipitation Measurement) images at the province of Chungcheongbuk-do. The long-term(2000-2015) TRMM/GPM precipitation data were used to estimate the SPI values. Then, we estimated the spatially-/temporally-distributed soil moisture values based on the near-surface soil moisture data assimilation scheme using the TRMM/GPM and MODIS(MODerate resolution Imaging Spectroradiometer) images. Overall, the SPI value was significantly affected by the precipitation at the study region, while both the precipitation and land surface condition have influences on the SMP and SMDI values. But the SMP index showed the relatively extreme wet/dry conditions compared to SPI and SMDI, because SMP only calculates the percentage of current wetness condition without considering the impacts of past wetness condition. Considering that different drought indices have their own advantages and disadvantages, the SMDI index could be useful for evaluating agricultural drought and establishing efficient water management plans.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.1-8
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• 2016

Crop damages due to agricultural drought has been increased in recent years. In Korea, water resources are limited indicating that proper management plans against agricultural drought are required for better water-use efficiency in agriculture. In this study, irrigation intervals and amounts for various crops and soil physical properties (sandy and silt loams) were estimated using the IWMM model. Five different crops (soybean, radish, potato, barley and maize) at the Bangdong-ri site in Chuncheon were selected to test the IWMM model. IWMM assessed agricultural drought conditions using the soil moisture deficit index (SMDI), and irrigation intervals and amounts were determined based on the degree of agricultural drought (SMDI). Additionally, we tested the effects of surface irrigation and sprinkler irrigation methods and various irrigation intervals of 2, 3, 5 and 7 days. In our findings, the irrigation intervals of 5 and 7 days showed the minimum rrigation amounts than others. When we considered that the intervals of 3 or 5 days are usually preferred to fields, the interval of 5 days was determined in our study. The estimated irrigation amounts for different crops were shown as maize > radish > barley > soybean > potato, respectively. The irrigation amounts for maize and barley were highly affected by soil properties, but other crops have less differences. Also, small differences in irrigation amounts were shown between the surface and sprinkler irrigation methods. These might be due to the lack of consideration of water loss (e.g., evapotranspiration, infiltration, etc.) in IWMM indicating model structural uncertainties. Thus, possible water loss (e.g., evapotranspiration, infiltration) need to be considered in application to fields. Overall, IWMM performed well in determining the irrigation intervals and amounts based on the degree of agricultural drought conditions (SMDI). Thus, the IWMM model can be useful for efficient agricultural water resources management in regions at where available water resources are limited.

• The Journal of the Acoustical Society of Korea
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• v.33 no.6
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• pp.400-406
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• 2014

This paper describes a robust watermark decoding model using a SVM(Support Vector Machine). First, the embedding process is performed inversely for a watermarked signal. And then the watermark is extracted using the proposed model. For SVM training of the proposed model, data are generated that are watermarks extracted from sounds containing watermarks by four different embedding schemes. BER(Bit Error Rate) values of the data are utilized to determine a threshold value employed to create training set. To evaluate the robustness, 14 attacks selected in StirMark, SMDI and STEP2000 benchmarking are applied. Consequently, the proposed model outperformed previous method in PSNR(Peak Signal to Noise Ratio) and BER. It is noticeable that the proposed method achieves BER 1% below in the case of PSNR greater than 10 dB.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.418-418
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• 2023

가뭄은 농업, 환경 및 사회경제적인 조건에 영향을 미치는 주요 자연 재해로 우리나라는 2015년부터 지속적인 가뭄 상황을 겪고 있다. 지속된 가뭄으로 인해 토양의 수분함량이 변화하여 농작물의 생장 활동 등에 영향을 미쳐 수확량이 낮아질 수 있다. 토양수분은 경사나 토질 등 지형학적인 특성에 따라 민감하게 반응하는 수문인자로, 특성을 광역적으로 정확하게 판단하기 어렵기 때문에 고해상도 원격탐사 자료를 활용하여 토양수분의 거동을 파악하는 연구들이 진행되고 있다. 특히, Synthetic Aperture Radar (SAR) 관측은 작물과 기본적인 토양의 유전체 및 기하학적 특성에 민감하게 반응하기 때문에, 토양수분 및 농업적 가뭄 분석 연구에 활용되고 있다. 본 연구는 2025년 발사될 예정인 C-band SAR 수자원 위성 산출물인 토양수분을 적용한 농업적 가뭄지수산정 알고리즘 기법 개발 연구를 위하여, 수자원 위성과 제원이 비슷한 Sentinel-1 자료를 통해 산정된 토양수분을 활용하여 농업적 가뭄지수인 Soil Moisture Drought Index (SMDI)를 산정하고자 한다. 산정된 SMDI의 검증을 위해 지점 관측된 토양수분 자료와 비교하여 Receiver Operating Characteristic (ROC) 분석 및 error matrix 기법 등을 활용하여 산정된 농업적 가뭄지수의 지역적 적용성을 파악하고자 한다. SAR 자료 기반의 농업적 가뭄지수 산정 알고리즘을 개발함으로써, 향후 제공될 수자원 위성의 자료를 활용한 가뭄 분석 연구에 활용될 수 있을 것으로 판단된다.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.