• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.1
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• pp.27-35
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• 2021

KRC (Korea Rural Community Corporation) is in charge of about 3,400 agricultural reservoirs out of 17,240 agricultural reservoirs, and automatic water level gauges in reservoirs and canals were installed to collect reservoir and canal water level data from 2010. In this study, 10-minute water level data of 173 reservoir irrigation canals from 2016 to 2018 are collected, and discharge during irrigation season was calculated using rating curves. For estimation of water supply, irrigation water requirement was calculated with HOMWRS (Hydrological Operation Model for Water Resources System), and the summation of reservoir water storage decrease was calculated with daily reservoir storage data from RAWRIS (Rural Agricultural Water Resource Information System). From the results, the total yearly amount of irrigation water supply showed less than 10% difference than the irrigation water requirement. The regional analysis revealed that reservoirs in Jeollanam-do and Chungcheongnam-do supply greater irrigation water than average. On the contrary, reservoirs in Gyeongsangnam-do and Chungcheongbuk-do supply less than others. This study was conducted with a limited number of reservoirs compared to total agricultural reservoirs. Nevertheless, it can indicate irrigation water supply from agricultural reservoirs to provide information about agricultural water use for irrigation.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.105-117
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• 2022

This study tested SVM(support vector machine), RF(random forest), and ANN(artificial neural network) machine-learning models that can predict net irrigation water requirements in paddy fields. For the Jeonju and Jeongeup meteorological stations, the net irrigation water requirement was calculated using K-HAS from 1981 to 2021 and set as the label. For each algorithm, twelve models were constructed based on cumulative precipitation, precipitation, crop evapotranspiration, and month. Compared to the CE model, the R² of the CEP model was higher, and MAE, RMSE, and MSE were lower. Comprehensively considering learning performance and learning time, it is judged that the RF algorithm has the best usability and predictive power of five-days is better than three-days. The results of this study are expected to provide the scientific information necessary for the decision-making of on-site water managers is expected to be possible through the connection with weather forecast data. In the future, if the actual amount of irrigation and supply are measured, it is necessary to develop a learning model that reflects this.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.4
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• pp.39-47
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• 2011

The aim of the study is to predict potential evapotranspiration and crop water requirement using meteorological data from MIROC3.2 with A1B scenario. Increase of evapotranspiration due to temperature rise can be observed out of the analysis, while effective rainfall decreased. The evapotranspiration elevation results in large amount of crop water requirement in the paddy farming. It can be seen that rainfall intensification at non-irrigation period brings effective rainfall decrease, while contributes to higher demand of crop water at irrigation period. It is necessary to secure additional water resources to adapt the climate change. It is expected that estimation on potentialevapotranspiration in this study can be used for formulation of master plan of water resources.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.97-104
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• 2019

The purpose of this study was to establish the estimation method of irrigation water amount for sewage treated water reuse for agricultural purpose. To calculate the irrigation water amount, we adopted Penman-Monteith for potential evapotranspiration estimation and applied crop coefficient and irrigation efficiency factor. We developed the irrigation water amount calculation program using C language in Xcode environment. The target district for calculation is having 259 ha of agricultural land located near the Jinyeong Clear Water Circulation Center in Hanrim-myeon, Gimhae city. The meteorological data of the study area were obtained from Changwon weather station from 1986 to 2017. Calculated average and maximum of annual mean potential evapotranspiration were 2.72 mm/day and 6.22 mm/day, respectively. We used K-S (Kolmogorov-Smirnov) for goodness-of-fit test to find optimal probability distribution of annual mean and maximum evapotranspiration. As a result, the normal distribution was selected for the appropriate distribution. The annual mean and maximum potential evapotranspiration for 10-year return period by applying normal distribution were 2.88 mm/day and 6.76 mm/day, respectively. Assuming that the irrigation efficiency is 80%, the irrigation water requirement was calculated as $36.05m^3/day/ha$ and $84.45m^3/day/ha$, respectively, when annual mean and maximum potential evapotranspiration were applied. The actual irrigation water amount can be calculated by applying the crop coefficient and cropping days for the study area based on the developed irrigation water amount estimation program in this study.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.31 no.4
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• pp.90-95
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• 1989

The purpose of this study is to seek out the harrow water requirement applicable for the irrigation plan of paddy field and to find out the factors influenced on a variation in the requirement. The plots of experiment were arranged with randomized block design which was compo- sed of three kinds of soil texture (sandy loam, loam and silty loam) and ploughing depth (12cm, 17cm, and 22cm). The results obtained from this experimental study are summarized as follows. 1. Harrow water reguirement is not only changed by soil texture, but influenced by soil water content just before irrigating 2. Magnitude of total harrow water reguirement appli(able for the irrigation plan, when surface water depth and the water content just before irrigating is fixed on the basis of 30 mm and a shrinkage limit respectively, generally becomes to be 177.5mm, 116.3mm and 113. 8mm in the sandy loam, loam amd silty loam block, respectively. 3. The more a percolation of soil layer occurs, the more the harrow water requirement increases, but it is not much influenced by the increase in ploughing depth. 4. The larger a porosity of soil layer is, the more a net harrow requirement increases 5. The factors that influence on a variation in the harrow water requirement are appea- red to be percolation of soil layer, soil water content just before irrigating, porosity of soil layer, ploughing depth and designed surface water depth etc.

• KCID journal
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• v.2 no.2
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• pp.54-58
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• 1995

• Current Research on Agriculture and Life Sciences
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• v.18
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• pp.33-42
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• 2000

A field case study was performed to investigate the effect of shallow ponding in paddy field on irrigation water requirement of direct seeded rice. In addition, an economic analysis was made to see the effect of no-till direct seeded rice on cost reduction. A field study was performed at a 2.1ha paddy field in Kimjae city, Chonbuk province from 1991 to 1999. Various direct seeding methods such as dryland seeding, wetland seeding, and no-till wetland seeding were introduced. Then, cost reductions due to the direct seeding and no-till were calculated. In addition, to investigate the effect of shallow ponding on irrigation water requirement, field measurements such as irrigation water volume, drainage water volume, rainfall depth, and ponding depth, were made at a 40a plot within the same area in 1988 and 1990. The results of the shallow ponding study showed that the irrigation water depth, rainfall, and the drainage depth were 379mm, 458mm, and 448mm in 1988 growing season, and 274mm, 819mm, and 736mm in 1990, respectively. The shallow ponding irrigation method saved irrigation water by about 20% with higher yield compared with the traditional method. The economic analysis showed that won \640,000 per ha can be saved by direct seeding due to no nursery cost, and \1,220,000 per ha due to no-till and no nursery cost. The yields ranged 540 to 640 kg per 10a during the study period with an average of 590kg per 10a. If these cropping techniques with no-till direct seeding and shallow ponding depth for rice cropping prove to be advantageous with further study, they can be adopted for the most of the paddy fields in Korea.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.1
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• pp.6-11
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• 2001

In this lysimeter experiment, temporal changes of water percolation rate, irrigation requirement and ${No}_3$－-N leaching were investigated under different cultural practices that were no-till direct seeding on flooded paddy (NTDSF), till direct seeding on flooded paddy (TDSF), and transplanting. The highest water percolation rate of 3,001 l/$m^2$ was measured in NTDSF. Others were 2,551 l/$m^2$ and 2,210 l/$m^2$ in TDSF and transplanting. Water percolation rate in NTDSF and TDSF was increased by 36% and 15% compared to transplanting. Water percolation rates in all cultural practices were increased remarkably from the reproductive growth stage and relatively large amount of water loss through percolation was measured even after the reproductive growth stage. A total irrigation requirement was 3,469 l/$m^2$ in NTDSF and 2,898 l/$m^2$ in TDSF. That was equivalent to 45% and 21 % of increase compared to 2,389 l/$m^2$ in transplanting. The largest ${No}_3$－-N leaching through the entire rice growing period was 701 mg/$m^2$ in NTDSF and was followed by 494 mg/$m^2$ in TDSF and 465 mg/$m^2$ in transplanting. The ratios to the total amount of ${No}_3$－-N leaching at the vegetative growth stage, reproductive growth stage and ripening stage were 31 %, 41 % and 28% in NTDSF; 21 %, 48% and 31 % in TDSF; and 18%, 48% and 35 % in transplanting.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.120-139
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• 2020

This study is to assess the future agricultural land use and climate change impacts on irrigation water requirement using CLUE-s(Conversion of Land Use and its Effects at Small regional extent) and RCP(Representative Concentration Pathway) 4.5 and 8.5 HadGEM3-RA(Hadley Centre Global Environmental Model version 3 Regional Atmosphere) scenario. For Nonsan city(55,517.9ha), the rice paddy, upland crop, and greenhouse cultivation were considered for agricultural land uses and DIROM(Daily Irrigation Reservoir Operation Model) was applied to benefited areas of Tapjeong reservoir (5,713.3ha) for Irrigation Water Requirement(IWR) estimation. For future land use change simulation, the CLUE-s used land uses of 2007, 2013, and 2019 from Ministry of Environment(MOE) and 6 classes(water, urban, rice paddy, upland crop, forest, and greenhouse cultivation). In 2100, the rice paddy and upland crop areas decreased 5.0% and 7.6%, and greenhouse cultivation area increased 24.7% compared to 2013. For the future climate change scenario considering agricultural land use change, the RCP 4.5 and RCP 8.5 2090s(2090~2099) IWR decreased 2.1% and 1.0% for rice paddy and upland crops, and increased 11.4% for greenhouse cultivation compared to pure application of future climate change scenario.