• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.2
• /
• pp.59-71
• /
• 2023

As the frequency of drought increases due to climate change, water scarcity in agriculture would be a main issue. However, it seems difficult to solve the water scarcity by securing alternative water sources. The aim of this study is to analyze optimal water supply capacity of agricultural reservoir for emergency operation connecting reservoirs and dams. First, we simulated the water storage of agricultural reservoir playing the role emergency water supplier to other water facility such as dams and other reservoirs. In particular, the results of simulation of water storage through K-HAS model was calibrated using the optimization process based on ratio correction factors of outflow and inflow. Finally, the optimal amount of water supply securing water supply reliability in emergency interconnection operation was analyzed. The results of this study showed that Janchi reservoir could supply 12.8 thousand m³/day maintaining 90 % water supply reliability. The result of this study could suggest the standard for connecting water facilities as emergency water supply.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.65-65
• /
• 2020

기후변화에 관한 IPCC 제5차 평가보고서에 따르면 최근 나타난 기후 관련 극한 현상인 폭염, 홍수, 가뭄 등의 영향에 대해 생태계가 현재의 기후 변동성에 상당히 취약하게 반응하며, 기후변화를 위험에 초점을 맞추어 평가함으로써 대응책을 마련해야 한다고 강조하였다. 기후변화에 따라 강수량 패턴과 수문학적 시스템이 변하면서 수자원의 미치는 영향과 취약성, 적응에 대한 연구의 필요성이 요구되고 있으며, 농업용수를 비롯한 수자원 관리 기술 및 적응역량을 강화하는 것이 필요하다. 수리답 면적에 대한 농업용수 공급의 61%를 차지하는 농업용 저수지의 경우 과거 10년 한발빈도로 설계되어 최근의 연속적인 가뭄 사상으로 인한 낮은 저수율을 나타내어 가용 수자원의 부족이 발생하였다. 이에 따라 저수지 설계 당시와 상이한 환경 및 기후의 변화로 농업용수 공급체계의 상황변화에 따른 용수공급능력 및 이수안전도의 재평가가 요구된다. 일부 가뭄대책지구에 대하여 기후변화에 따른 현장여건 변화 (논면적, 영농패턴, 작부시기 등)를 반영한 이수안전도를 재평가함으로써 농업용 저수지의 용수공급에 대한 정량적 분석이 수행되었다. 저수지별로 기후변화 및 현장여건 변화에 따른 영향이 다르므로 전국 농업용 저수지를 대상으로 확대, 적용하기 위해서는 저수지 특성을 분석하여 비슷한 패턴을 갖는 저수지로 유형화하기 위한 작업이 필요하다. 본 연구에서는 농어촌공사 관할 3,394개의 농업용 저수지를 대상으로 지역에 따라 인자별 군집분석을 실시하여 국내 농업용 저수지의 이수안전도 변화에 따른 물 공급 잠재능을 재평가하고자 한다. 본 연구의 결과는 기후와 영농방식, 지역별 특성 등 상호간의 관계를 고려한 농업용수관리와 유사한 특성을 갖는 지역계획의 추진단위를 결정하거나 지역간의 비교우위를 고려한 한해 대책 등과 같은 농촌지역개발계획 등에 활용할 수 있을 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.14-14
• /
• 2020

일반적으로 수문빈도해석은 치수계획 수립에 이용되는 설계강수량, 계획홍수량 등을 산정하기 위해 연최대치계열 또는 연초과치계열 자료를 이용한 극치빈도해석을 수행하고, 확률분포의 우측꼬리(right tail) 부분을 이용하여 확장된 재현기간에 해당하는 확률수문량을 추정한다. 하지만 가뭄 관련 분석에서는 확률분포의 좌측꼬리(left tail) 부분은 이용해 확장된 재현기간별 확률수문량을 추정해야할 경우가 발생한다. 또한 물관리 실무에서 장 단기 운영계획 수립을 위해 이용하는 갈수빈도 유입량 산정 등에서도 평년보다 작은 수문량에 대한 빈도해석이 필요한 경우가 있다. 국가 가뭄정보분석센터에서는 기존에 K-water연구원에서 개발한 빈도해석 프로그램인 K-FAT의 분석모듈을 이용해 극소치계열 또는 갈수빈도 유입량 분석에 특화된 가뭄빈도해석 프로그램을 개발하였다. 본 프로그램은 GEV, Gumbel, Weibull 등 14개의 확률분포형을 포함하며, 모멘트법, 최우도법 및 L-모멘트법을 사용하여 매개변수를 추정한다. 적합도 검정의 경우 χ², K-S, CVM, PPCC 및 수정 Anderson-Darling test를 이용하여 다각적인 검정을 할 수 있도록 하였다. 분석을 위한 입력 자료의 경우 사용자가 전처리를 통해 준비한 연최소치계열 등 연도별 시계열자료를 이용할 수 있으며, 일단위 및 월단위의 강수량 또는 댐 유입량 자료를 이용해 사용자가 원하는 기간의 누적강수량, 평균 유입량으로 변환할 수 있는 자료변환 기능을 추가하여 실무 활용성을 높였다. 또한 최적 확률분포 선정을 위해 참고할 수 있도록 AIC(Akaike information criteria)와 BIC(Bayesian information criteria) 분석이 포함되어 있으며, Bootstrap 기법 등을 이용한 불확실성 산정을 통해 추정 값의 신뢰구간을 표시하도록 하였다. 개발된 프로그램은 베타버전 시험배포를 거쳐 가뭄정보포털을 통해 배포할 예정이다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.516-516
• /
• 2022

Agricultural reservoirs are critical water resources structures to ensure continuous water supplies for rice cultivation in Korea. Climate change has increased the risk of reservoir failure by exacerbating discrepancies in upstream runoff generation, downstream irrigation water demands, and evaporation losses. In this study, the variations in water balance components of 400 major reservoirs during 1973-2017 were examined to identify the reservoirs with reliable storage capacities and resilience. A conceptual lumped hydrological model was used to transform the incident rainfall into the inflows entering the reservoirs and the paddy water balance model was used to estimate the irrigation water demand. Historical climate data analysis showed a sharp warming gradient during the last 45 years that was particularly evident in the central and southern regions of the country, which were also the main agricultural areas with high reservoir density. We noted a country-wide progressive increase in average annual cumulative rainfall, but the forcing mechanism of the rainfall increment and its spatial-temporal trends were not fully understood. Climate warming resulted in a significant increase in irrigation water demand, while heavy rains increased runoff generation in the reservoir watersheds. Most reservoirs had reliable storage capacities to meet the demands of a 10-year return frequency drought but the resilience of reservoirs gradually declined over time. This suggests that the recovery time of reservoirs from the failure state had increased which also signifies that the duration of the dry season has been prolonged while the wet season has become shorter and/or more intense. The watershed-irrigated area ratio (W-I_ratio) was critical and the results showed that a slight disruption in reservoir water balance under the influence of future climate change would seriously compromise the performance of reservoirs with W-I_ratio< 5.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.309-309
• /
• 2022

특정 극치사상 자료에 대한 특성 분석 시 수문자료에 대한 빈도해석은 일반적으로 단일 확률 변수를 기준으로 이루어지는 단변량 해석 방법이 활용된다. 그러나 두 가지 이상의 변량이 서로 상관성을 가지는 경우 다변량 빈도해석이 요구되며, 이를 단변량으로 해석하는 경우 재현기간의 과소추정 등의 문제점이 발생할 수 있다. 최근 이러한 점을 개선하기 위하여 다변량 빈도해석에 관한 연구가 지속적으로 진행되고 있다(Kwon and Lall, 2016; Vaziri et al., 2018). 특히, 가뭄의 경우, 강도(intensity)뿐만 아니라 지속기간, 심도도 매우 중요한 인자로 고려되고 있다. 특히, 가뭄지속기간과 심도의 경우 두 인자 간의 상관성이 매우 크기 때문에 단변량(univariate) 가뭄빈도해석 보다 다변량으로(multivariate) 가뭄빈도해석을 수행하는 것이 가뭄위험도 평가 측면에서 유리하다고 알려져 있다(Shiau and Shen, 2001; Kim et al., 2017). 따라서 이 둘을 결합한 빈도 해석을 위해 Copula Function을 이용한 다변량 빈도 해석에 관한 연구들이 활발히 진행되고 있다. 홍수의 경우 지속시간별 연최대강수량 계열을 이용한 빈도해석 과정이 지침으로 정립되어 수자원 설계 실무에서 활용되고 있으나, 가뭄은 실무에서 활용할 수 있는 지침 및 분석 도구가 없는 실정이다. 이에 환경부와 국가가뭄정보분석센터에서는 '20년도에 단변량 가뭄빈도 해석을 위한 프로그램을 제작·배포하였다. 본 연구에서는 가뭄의 특성을 대변하는 상관도 높은 두 인자인 가뭄 심도(severity)와 가뭄 지속기간(duration)이라는 두 가지 특성을 함께 고려해 이변량(bivariate) 가뭄 빈도를 해석할 수 있는 도구를 개발하는 것을 목표로, 다양한 확률분포형을 이용한 최적 주변 확률분포형 선정과 최신 Copula Function들을 이용한 최적 결합확률분포 추정을 통해 신뢰도 높은 2변량 가뭄빈도 해석을 수행할 수 있는 프로그램을 제작하였으며, 테스트 버전 배포 등을 거쳐 누구나 사용할 수 있도록 공개할 예정이다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.208-208
• /
• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Journal of Integrative Natural Science
• /
• v.17 no.2
• /
• pp.33-41
• /
• 2024

Abnormal climate is a phenomenon in which meteorological factors such as temperature and precipitation are significantly higher or lower than normal, and is defined by the World Meteorological Organization as a 30-year period. However, over the past 30 years, abnormal climate phenomena have occurred more frequently around the world than in the past. In Korea, abnormal climate phenomena such as abnormally high temperatures on the Korean Peninsula, drought, heatwave and heavy rain in summer are occurring in March 2023. Among them, heatwaves are expected to increase in frequency compared to other abnormal climates. This suggests that heatwave should be recognised as a disaster rather than just another extreme weather event. According to several previous studies, greenhouse gases and meteorological factors are expected to affect heatwaves, so this paper uses logistic regression and discriminant analysis on meteorological element data and greenhouse gas data in Gwangju from 2008 to 2022. We analyzed the impact of heatwaves. As a result of the analysis, greenhouse gases were selected as effective variables for heatwaves compared to the past, and among them, chlorofluorocarbons were judged to have a stronger effect on heatwaves than other greenhouse gases. Since greenhouse gases have a significant impact on heatwaves, in order to overcome heatwaves and abnormal climates, greenhouse gases must be minimized to overcome heatwaves and abnormal climates.

• Journal of Korea Water Resources Association
• /
• v.54 no.12
• /
• pp.1317-1328
• /
• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.

• Journal of Korea Water Resources Association
• /
• v.41 no.7
• /
• pp.711-723
• /
• 2008

In this study, Hydrologic regime alterations(magnitude, magnitude and duration of annual extreme, frequency and duration of high and low pulse, rate and frequency of water condition changes, Range of Variability Approach) were analyzed by using Indicators of Hydrologic Alterations at the 11 major multi-purpose dam. The analysis result of the magnitude of monthly water conditions during drought season, inflow was $6.38m^3/sec{\sim}39.84m^3/sec$ and outflow was $20.36m^3/sec{\sim}49.43m^3/sec$, was increased $1.84%{\sim}200.98%$. The analysis result of the magnitude of monthly water conditions during flood season, inflow was from $79.06m^3/sec{\sim}137.12m^3/sec$ and outflow was from $65.32m^3/sec{\sim}80.16m^3/sec$, was decreased from $18.19%{\sim}40.39%$. The analysis result of the magnitude and duration of annual extreme, 1-day minimum was increased $82.86%{\sim}2,950%$, but 1-day maximum was decreased $34.78%{\sim}83.96%$. The analysis result of the frequency and duration of high and low pulse, low pulse count was decreased $29.67%{\sim}99.07%$ and high pulse count was also decreased $4.6%{\sim}92.35%$ after dam operation. Hydrograph rise rate was decreased $15.84%{\sim}79.31%$ and fall rate was $1.97%{\sim}107.10%$. RVA of 1-day minimum was increased $0.60{\sim}2.67$, also RVA of 1-day maximum was decreased $0.50{\sim}1.00$.

• Korean Journal of Environment and Ecology
• /
• v.24 no.6
• /
• pp.657-679
• /
• 2010

Mushroom fruiting was investigated in pine and oak dominated forest stands in Songni National Park located in central Korea for six years from 2003 to 2008, in order to understand the relationship between mushroom diversity and the environmental factors, precipitation, temperature, soil moisture and vegetation. The most frequent fruiting families were those of ectomycorrhizal mushrooms, Tricholomataceae, Amanitaceae, Russulaceae, Cortinariaceae, and Boletaceae. The frequency of mushroom fruiting varied from 94 to 167 species per year, with July and August having the highest(13~90 species). Mushroom fruiting was positively correlated to precipitation(r=0.897), using Palmer Drought Severity Index for the long term period and Standard Precipitation Index for short term period. Soil moisture content also affected mushroom fruiting, with Lactarius chrysorrheus and Russula virescens fruiting only at soil moisture content higher than 20%. Positive correlation between mushroom fruiting and temperature was also noted(r=0.77), with optimum rates at $21{\sim}25^{\circ}C$. Tricholoma flayayirens, Amanita gymnopus, Lactarius piperatus, Inocybe asteropora and Xerocomus chrysenteron were able to fruit at temperatures higher than $25^{\circ}C$. However, Laccaria amethystea, Amanita virosa and Russula mariae fruited at relatively wide temperature range. The influence of vegetation on mushroom fruiting was likewise noted, with 38 species, including Suillus bovinus and Boletopsis leucomelas being specific to pine dominated stands, while 42 species, including Polyporus arcularius and Hericium erinaceum were specific to oak dominated stands. On the other hand, around 50 species, including Laccaria laccata and Lycoperdon parlatum, were able to fruit in both types of vegetation. In conclusion, mushroom fruiting greatly varies with changes in precipitation, soil moisture, temperature and vegetation.