• 농업과학연구
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• 제48권2호
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.37-37
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• 2023

There is currently a high-accuracy modern forecasting method that uses machine learning algorithms or artificial neural network models to forecast river water levels or flowrate. As a result, this study aims to develop a mathematical model based on artificial neural networks to effectively forecast river water levels upstream of Tranh Culvert in North Vietnam's Bac Hung Hai irrigation system. The mathematical model was thoroughly studied and evaluated by using hydrological data from six gauge stations over a period of twenty-two years between 2000 and 2022. Furthermore, the results of the developed model were also compared to those of the long-short-term memory neural networks model. This study performs four predictions, with a forecast time ranging from 6 to 24 hours and a time step of 6 hours. To validate and test the model's performance, the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error, and root mean squared error were calculated. During the testing phase, the NSE of the model varies from 0.981 to 0.879, corresponding to forecast cases from one to four time steps ahead. The forecast results from the model are very reasonable, indicating that the model performed excellently. Therefore, the proposed model can be used to forecast water levels in North Vietnam's irrigation system or rivers impacted by tides.

• 한국관개배수논문집
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• 제1권2호
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• pp.22-28
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• 1994

The calculation method for the Drought index based on the principal hydrological factors, such as precipitation, reservoir storage and river discharge, can estimate the duration and intensity of drought. It is not easy to establish an universal criteria o

• 한국관개배수논문집
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• 제4권2호
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• pp.48-61
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• 1997

Drought index calculation method using principal hydrological factors, such as precipitation amount and reservoir storage ratio, can estimate the duration and the intensity of drought. It is not easy to establish an universal criteria of drought, since th

• 한국관개배수논문집
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• 제11권2호
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• pp.95-103
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• 2004

The objective of this study is to simulate streamflow and water quality for Gyeongan watershed (561.1 $km^2$) using AnnAGNPS (Bingner et al., 2000). The model was calibrated and verified for three years (2000, 2002, 2003) stream discharge and w

• 한국습지학회지
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• 제13권2호
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• pp.275-289
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• 2011

파주시 민간인 통제구역 내에 존재하는 둠벙의 수문 지형학적 분류를 위해 둠벙의 특성을 조사하였다. 물을 논농사에 이용하는 둠벙을 조사한 결과 모두 85개가 존재하였다. 조사된 둠벙을 수문학적 특성 중 계절별 수위변화 정도에 따라 나누면, 계절에 따라 수위가 크게 변하는 둠벙은 52개, 계절에 무관하게 항상 일정한 둠벙이 33개였다. 수원에 따라 분류하면 강수 의존 지표수인 경우가 12개, 지하수와 지표수인 경우가 29개, 지하수만인 경우가 44개였다. 4개는 산지에 33개는 평지에 48개는 계곡에 위치하였다. 40개는 논과 물의 교환이 일어나지 않았으며, 45개는 수위가 변함에 따라 교환이 일어났다. 멸종위기종 또는 특산종이 서식하는 둠벙은 모두 26개였으며, 주로 수위가 일정하며, 지하수를 수원으로 가지는 둠벙에 해당하였다. 이와 같은 특징을 바탕으로 둠벙을 샘통형, 물흐름형, 괸물샘통형, 괸물형으로 나누는 방법을 새로이 제시하였다. 이와 같이 둠벙의 유형을 제시함으로써 이들을 체계적으로 조사 정리하여, 둠벙을 유형적으로 관리하는 데 도움을 주고자 하였다.

• 한국농공학회논문집
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• 제54권1호
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• pp.27-38
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• 2012

This study is to analyse the hydrological behavior of agricultural reservoir using CAT (Catchment hydrologic cycle Assessment Tool). The CAT is a water cycle analysis model in order to quantitatively assess the characteristics of the short/long-term changes in watershed. It supports the effective design of water cycle improvement facilities by supplementing the strengths and weaknesses of existing conceptual parameter-based lumped hydrologic models and physical parameter-based distributed hydrologic models. The CAT especially supports the analysis of runoff processes in paddy fields and reservoirs. To evaluate the impact of agricultural reservoir operation and irrigation water supply on long-term rainfall-runoff process, the CAT was applied to Idong experimental catchment, operated for research on the rural catchment characteristics and accumulated long term data by hydrological observation equipments since 2000. From the results of the main control points, Idong, Yongdeok and Misan reservoirs, the daily water levels of those points are consistent well with observed water levels, and the Nash-Sutcliffe model efficiencies were 0.32~0.89 (2001~2007) and correlation coefficients were 0.73~0.98.

• 한국농공학회논문집
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• 제52권6호
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• pp.1-7
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• 2010

This study was carried out to investigate the effect of hydro power factors (e.g., irrigation area, watershed area, active storage, gross head) on annual generation capacity and operation ratio for agricultural reservoirs in Chungbuk Province with active storage of over 1 million $m^3$. The annual generation capacity and operation ratio were estimated using HOMWRS (Hydrological Operation Model for Water Resources System) from last 10-year daily hydrological data. The correlation coefficients between annual generation capacity and the hydro power factors except gross head were high (over 0.87), but the correlation coefficients between operational rate and the factors were low (below 0.28). The optimum multiple regression equations of the annual generation capacity were expressed as the functions of watershed area, active storage, and gross head. Also, the simple regression equation of annual generation capacity was expressed as a function of watershed area. The average relative root-mean-square-error (RRMSE) between observed and estimated values by the optimum multiple regression equations was smaller than that by the simple regression equation, suggesting that the former has more accuracy than the latter.

• 한국농공학회논문집
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• 제63권6호
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• pp.1-16
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• 2021

Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H₂O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.

• 한국물환경학회지
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• 제35권2호
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• pp.131-144
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• 2019

Climate Change affects the hydrological cycle in agricultural watersheds through rising air temperature and changing rainfall patterns. Agricultural watersheds in Korea are characterized by extensive paddy fields and intensive water use, a resource that is under stress from the changing climate. This study analyzed the effects of climate change on river flows for Geum Cheon and Eun-San Choen watershed using STREAM, a semi-distributed watershed model. In order to evaluate the performance and improve the reliability of the model, calibration and validation of the model was done for one flow observation point and three reservoir water storage ratio points. Climate change scenarios were based on RCP data provided by the Korea Meteorological Administration (KMA) and bias corrections were done using the Quantile Mapping method to minimize the uncertainties in the results produced by the climate model to the local scale. Because of water mass-balance, evapotranspiration tended to increase steadily with an increase in air temperature, while the increase in RCP 8.5 scenario resulted in higher RCP 4.5 scenario. The increase in evapotranspiration led to a decrease in the river flow, particularly the decrease in the surface runoff. In the paddy agricultural watershed, irrigation water demand is expected to increase despite an increase in rainfall owing to the high evapotranspiration rates occasioned by climate change.