• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.1-12
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• 2020

The extreme 2017 spring drought affected a large portion of South Korea in the Southern Gyeonggi-do and Chungcheongnam-do districts. This drought event was one of the climatologically driest spring seasons over the 1961-2016 period of record. It was characterized by exceptionally low reservoir water levels, with the average water level being 36% lower over most of western South Korea. In this study, we consider drought response methods to alleviate the shortage of agricultural water in times of drought. It could be to store water from a stream into a reservoir. There is a cyclical method for reusing water supplied from a reservoir into streams through drainage. We intended to present a decision-making plan for water supply based on the calculation of the quantity of water supply and leakage. We compared the rainfall-runoff equation with the TANK model, which is a long-term run-off model. Estimations of reservoir inflow during non-irrigation seasons applied to the Madun, Daesa, and Pungjeon reservoirs. We applied the run-off flow to the last 30 years of rainfall data to estimate reservoir storage. We calculated the available water in the river during the non-irrigation season. The daily average inflow from 2003 to 2018 was calculated from October to April. Simulation results show that an average of 67,000 tons of water is obtained during the non-irrigation season. The report shows that about 53,000 tons of water are available except during the winter season from December to February. The Madun Reservoir began in early October with a 10 percent storage rate. In the starting ratio, a simulated rate of 4 K, 6 K, and 8 K tons is predicted to be 44%, 50%, and 60%. We can estimate the amount of water needed and the timing of water pump operations during the non-irrigation season that focuses on fresh water reservoirs and improve decision making for efficient water supplies.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1645-1648
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• 2010

The goal of this research is to apply the neural networks model for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks model consists of recurrent neural networks model (RNNM). The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks model, it is composed of training and test performances, respectively. The training and test performances consist of the historic, the generated, and the mixed data, respectively. From this research, we evaluate the impact of RNNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1439-1442
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• 2010

Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.272-272
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• 2022

Water and phosphorus (P) fertilizer are two of the most critical inputs in rice cultivation. Under climate change scenarios and urbanization, irrigation and fertilizer are becoming limiting factors often leading to significant decrease in yield whenever supplied scarcely. It has been shown that the Pup1 QTL confers tolerance to P starvation and improved early-stage root vigor in indica rice grown in the tropics. However, whether the QTL works in japonica rice genetic background grown in temperate regions remains to be elucidated. Here, we have introgressed the Pup1 QTL into three temperate rice varieties MS11, TR22183, and Dasan using marker-assisted backcrossing and next generation sequencing. The selected lines all harbored the full Pup1 QTL with recurrent parent genome recovery rates ranging from 66.5% to 99.8%. Evaluation of the introgression rice lines grown in South Korea under low inputs of P and water revealed early vegetative growth advantage relative to that of the recurrent parents. Under rainfed condition, Pup1 introgression lines had yield advantage ranging from 7.2 to 19.9% and 24 to 26% in P non-supplied soil and P-supplied soil, respectively compared to that of the recurrent parents suggesting that Pup1 confers enhanced yield under low P and water inputs in temperate rice genetic background grown in temperate climate. In terms of early vegetative growth, temperate Pup1 introgression lines showed a similar trend on the extent to which Pup1 promotes yield advantage in temperate rice in comparison with indica control Pup1 introgression line IR64-Pup1.

• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.3
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• pp.4184-4194
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• 1976

Located in the southwestern part of Korea, the Yong San Gang river flows generally northeast to southwest, and because of the specific location, topography and climate, the basin area is subject to recurrent drought and flood damages. To eliminate the cause of such damages and ensure an increase in the farm income by means of effective irrigation supply and increased cropping intensity, efforts are being made to speed up implementation of an integrated agricultural development project which would include construction. of an estuary dam and irrigation facilities as well as land development and tidal reclarnation. In formulating a basin development project plan, it is necessary to study a series of long-term runoff data. The catchment area at the proposed estuary damsite is 3,471$\textrm{km}^2$ with the total length of the river channel up to this point reaching 138km. An analysis of runoff in this area was carried out. Rainfall was estimated by the Thiessen Network based on records available from 15 of the rainfall observation stations within the area. Out of the 15 stations, Kwang Ju and Mok Po stations were keeping long-term precipitation records exceeding some 60 years while the others were in possession of only 5-10 years records. The long-term records kept by those stations located in the center of the basin were used as base records and records kept by the remaining stations were supplemented using the coefficient of correlation between the records kept by the base stations and the remainder. The analyses indicate that the average annual rainfall measured at Kwang Ju during 1940-1972 (33 years) amounts to 1,262mm and the areal rainfall amounts to 1,236mm. For the purpose of runoff analysis, 7 observatories, were set up in the middle and lower reaches of the river and periodic measurements made by these stations permitted analysis of water levels and river flows. In particular, the long-term data available from Na Ju station significantly contributed to the analysis. The analysis, made by 4-stage Tank method, shows that the average annual runoff during 1940-1972 amounts to 2,189 million ㎥ at the runoff rate of 51%. As for the amount of monthly runoff, the maximum is 484.2 million ㎥ in July while the minimum is 48.3 million ㎥ in January.