• 제목/요약/키워드: ABCD model

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Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks(I) -Comparative Study of Groundwater Recharge- (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구(I) -지하수 유입량의 비교 연구-)

  • Lee, In-Mo;Park, Gyeong-Ho;Im, Chung-Mo
    • Geotechnical Engineering
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    • v.8 no.1
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    • pp.81-102
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    • 1992
  • Landslides on hillside slopes with shallow soil cover over a sloping bedrock are frequently caused by increases in porewater pressures following of heavy rainfall and it is one of the most important factors of assessing the risk of landslide to predict the groundwater level fluctuations in hillslopes. This paper presents the comparative study of three unsaturated flow models developed by Sloan et al., Reddi, L.N., and Thomas, H.A., Jr., respectively, which are used to predict the increase of groundwater levels in hillside slopes. The parametric study for each of models is also presented. The Kinematic Storage Model(KSM) developed by Sloan et at. is utilized to predict the saturated groundwater flow. They are applied to the two sites in Korea so as to examine the possibility of use in the groundwater flow model. The results show that two unsaturated models developed by Sloan et al. and Reddi, L. N. are largely affected by the uncertain parameters like saturated permeability and saturated water content : the abed model has the potential of use in unsaturated flow model with the optimal estimates of model parameters utilizing available optimization techniques. And it is also found that the KSM must be modified to account for the time delay effect in the saturated zone. The results of this paper are able to be utilized in developing the predictive model of groan dwater level fluctuations in a hillslope.

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ANALYSIS OF MALARIA DYNAMICS USING ITS FRACTIONAL ORDER MATHEMATICAL MODEL

  • PAWAR, D.D.;PATIL, W.D.;RAUT, D.K.
    • Journal of applied mathematics & informatics
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    • v.39 no.1_2
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    • pp.197-214
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    • 2021
  • In this paper, we have studied dynamics of fractional order mathematical model of malaria transmission for two groups of human population say semi-immune and non-immune along with growing stages of mosquito vector. The present fractional order mathematical model is the extension of integer order mathematical model proposed by Ousmane Koutou et al. For this study, Atangana-Baleanu fractional order derivative in Caputo sense has been implemented. In the view of memory effect of fractional derivative, this model has been found more realistic than integer order model of malaria and helps to understand dynamical behaviour of malaria epidemic in depth. We have analysed the proposed model for two precisely defined set of parameters and initial value conditions. The uniqueness and existence of present model has been proved by Lipschitz conditions and fixed point theorem. Generalised Euler method is used to analyse numerical results. It is observed that this model is more dynamic as we have considered all classes of human population and mosquito vector to analyse the dynamics of malaria.

A Study on the Application of Thomas Monthly Runoff Prediction Model for Ungauged Watersheds (Thomas 월 유출모형의 미계측 영역 적용에 관한 연구)

  • 김원석;윤용남;최영박
    • Water for future
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    • v.24 no.4
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    • pp.85-91
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    • 1991
  • An effort was made to develop a monthly runoff predition method based on the Thomas model. For the 20watersheds selected the Thomas model was fitted, the parameters being determined by the Rosenbrok's rotating coordinate search method using the monthly rainfall and runoff data. The so determined parameters were correlated with the meteorologic, topographic and geologic characteristics of the watersheds. The model was tested by comparing the observed and simulated monthly runoff records from two test watersheds. The result showed that the model developed in the present study could satisfactorily be applied to ungauged watersheds It was noticed that the model had the tendency of slightly overestimating the runoff during winter periond and underestimating during the spring period.

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Coping with Climage Change through Coordinated Operations of the Andong & Imha Dams (안동-임하댐 연계운영을 통한 미래 기후변화 대응)

  • Park, Junehyeong;Kim, Young-Oh
    • Journal of Korea Water Resources Association
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    • v.46 no.12
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    • pp.1141-1155
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    • 2013
  • A number of studies have been performed to analyze climate change impacts of water resources system. In this study, a coordinated dam operation is compared with an existing operation strategy for coping with projected future runoff scenarios. GCMs (Global Circulation Models) and the LARS-WG downscaling method was used to project future climate scenarios. The water balance model called abcd was employed to estimate future runoff scenarios. The existing dam operation comes from the national dam construction guideline, which is called the "level-operation method." The alternative coordinated dam operation are constructed as a linear programming using New York City rule for refill and drawdown seasons. The results of annual total inflow in future is projected to decrease to 72.81% for Andong dam basin and 65.65% for Imha dam basin. As a result of applying future runoff scenarios into the dam operation model, the reliability of coordinated dam operation, 62.22%, is higher than the reliability of single dam operation, 46.55%. Especially, the difference gets larger as the reliability is low because of lack of water. Therefore, the coordinated operation in the Andong & Imha dams are identified as more appropriate alternative than the existing single operation to respond to water-level change caused by climate change.

Development of weekly rainfall-runoff model for drought outlooks (가뭄전망을 위한 주간 강우-유출 모형의 개발 및 적용)

  • Kang, Shinuk;Chun, Gunil;Nam, Woosung;Park, Jinhyeog
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.214-214
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    • 2019
  • 가뭄이 '심함' 단계 이상 도달 시에는 매주 수문분석을 수행하여 가뭄전망을 수행하여야 한다. 이를 위해서는 기상청의 강수량과 기온 등의 기상예측 자료가 필요하다. 현재 기상청에서는 3개월 기상전망으로 월단위 강수량과 평균기온을 매월 제공하고 있다. 1개월 전망에서 4주의 강수량합과 평균기온을 제공하고 있다. 하지만, 향후 4주간을 전망하는 1개월 전망에서는 1주단위의 강수량과 평균기온이 아닌, 4주간의 강수량합과 평균기온을 1주일 단위로 업데이트해 WINS에 제공하고 있다. 1주단위의 강수량과 평균기온을 취득하기 어려워, 평년 일단위 강수량과 평균기온 자료를 사용하여 4주간의 자료를 1주 단위로 분할하는 방법을 사용하였다. 주간단위 수문자료의 처리를 위해 국제표준기구(ISO)에서 제시하는 기준(ISO 8601)에 따랐다. ISO 8601은 월요일부터 일요일까지를 1주로 정의하며 현재 사용하고 있는 날짜체계와 1대1로 대응되도록 하였다. 예를 들면 1981년 2월 22일은 '1981-W07-7' 또는 '1981W077'로 표시한다. 표시된 형식은 1981년 7번째 주 일요일을 뜻한다. 이 기준에 따라 수문자료를 정리할 수 있도록 프로그램을 개발하였다. 주간 단위 잠재증발산량 계산은 월잠재증발산량 프로그램을 1주단위로 계산할 수 있도록 수정 및 보완하여 개발하였다. 수정 및 보완한 부분은 외기복사(外氣輻射)량 계산부분이다. 외기복사량은 지구가 태양을 1년 주기로 공전하므로 특정 위도에서 특정날짜에 따라 복사량이 달라지므로 주간단위의 월요일부터 일요일에 해당하는 날짜의 외기복사량을 각각 계산하고 이를 평균하여 주간단위 대푯값으로 사용하도록 하였다. 계산된 주간단위 외기복사량과 최고 최저기온을 입력하여 Hargreaves식에 의해 잠재증발산량을 계산한다. 융적설을 포함한 주단위 강우-유출 모형의 매개변수를 추정하기 위해 전국 24개 지점의 수문자료를 사용하였다. abcd 모형과 융적설모듈의 초기값 포함 11개 매개변수를 SCE-UA 전역최적화 알고리즘으로 추정하였다. 추정된 유역의 매개변수는 토양배수, 토양심도, 수문지질, 유역특성인자를 사용한 군집분석 결과에 의해 113개 중권역에 할당하였다. 개발된 주간단위 강우-유출 모형은 비교적 단기 가뭄전망을 위해 사용된다. 계산된 유량은 자연유량이며, 전국 취수장 수량, 하수처리장 방류수, 회귀수를 반영하여 지점별 유량을 계산하여 가뭄전망에 사용되고 있다.

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An analysis of effects of seasonal weather forecasting on dam reservoir inflow prediction (장기 기상전망이 댐 저수지 유입량 전망에 미치는 영향 분석)

  • Kim, Seon-Ho;Nam, Woo-Sung;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.52 no.7
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    • pp.451-461
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    • 2019
  • The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.

Identifying Personal Values Influencing the Lifestyle of Older Adults: Insights From Relative Importance Analysis Using Machine Learning (중고령 노인의 개인적 가치에 따른 라이프스타일 분류: 머신러닝을 활용한 상대적 중요도 분석 )

  • Lim, Seungju;Park, Ji-Hyuk
    • Therapeutic Science for Rehabilitation
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    • v.13 no.2
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    • pp.69-84
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    • 2024
  • Objective : This study aimed to categorize the lifestyles of older adults into two types - healthy and unhealthy, and use machine learning to identify the personal values that influence these lifestyles. Methods : This cross-sectional study targeting middle-aged and older adults (55 years and above) living in local communities in South Korea. Data were collected from 300 participants through online surveys. Lifestyle types were dichotomized by the Yonsei Lifestyle Profile (YLP)-Active, Balanced, Connected, and Diverse (ABCD) responses using latent profile analysis. Personal value information was collected using YLP-Values (YLP-V) and analyzed using machine learning to identify the relative importance of personal values on lifestyle types. Results : The lifestyle of older adults was categorized into healthy (48.87%) and unhealthy (51.13%). These two types showed the most significant difference in social relationship characteristics. Among the machine learning models used in this study, the support vector machine showed the highest classification performance, achieving 96% accuracy and 95% area under the receiver operating characteristic (ROC) curve. The model indicated that individuals who prioritized a healthy diet, sought health information, and engaged in hobbies or cultural activities were more likely to have a healthy lifestyle. Conclusion : This study suggests the need to encourage the expansion of social networks among older adults. Furthermore, it highlights the necessity to comprehensively intervene in individuals' perceptions and values that primarily influence lifestyle adherence.

Porewater Pressure Predictions on Hillside Slopes for Assessing Landslide Risks (II) Development of Groundwater Flow Model (산사태 위험도 추정을 위한 간극수압 예측에 관한 연구(II) -산사면에서의 지하수위 예측 모델의 개발-)

  • Lee, In-Mo;Park, Gyeong-Ho;Im, Chung-Mo
    • Geotechnical Engineering
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    • v.8 no.2
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    • pp.5-20
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    • 1992
  • The physical-based and lumped-parameter hydrologic groundwater flow model for predicting the rainfall-triggered rise of groundwater levels in hillside slopes is developed in this paper to assess the risk of landslides. The developed model consists of a vertical infiltration model for unsaturated zone linked to a linear storage reservoir model(LSRM) for saturated zone. The groundwater flow model has uncertain constants like soil depttL slope angle, saturated permeability, and potential evapotranspiration and four free model parameters like a, b, c, and K. The free model parameters could be estimated from known input-output records. The BARD algorithm is uses as the parameter estimation technique which is based on a linearization of the proposed model by Gauss -Newton method and Taylor series expansion. The application to examine the capacity of prediction shows that the developed model has a potential of use in forecast systems of predicting landslides and that the optimal estimate of potential 'a' in infiltration model is the most important in the global optimum analysis because small variation of it results in the large change of the objective function, the sum of squares of deviations of the observed and computed groundwater levels. 본 논문에서는 가파른 산사면에서 산사태의 발생을 예측하기 위한 수문학적 인 지하수 흐름 모델을 개발하였다. 이 모델은 물리적인 개념에 기본하였으며, Lumped-parameter를 이용하였다. 개발된 지하수 흐름 모델은 두 모델을 조합하여 구성되어 있으며, 비포화대 흐름을 위해서는 수정된 abcd 모델을, 포화대 흐름에 대해서는 시간 지체 효과를 고려할 수 있는 선형 저수지 모델을 이용하였다. 지하수 흐름 모델은 토층의 두께, 산사면의 경사각, 포화투수계수, 잠재 증발산 량과 같은 불확실한 상수들과 a, b, c, 그리고 K와 같은 자유모델변수들을 가진다. 자유모델변수들은 유입-유출 자료들로부터 평가할 수 있으며, 이를 위해서 본 논문에서는 Gauss-Newton 방법을 이용한 Bard 알고리즘을 사용하였다. 서울 구로구 시흥동 산사태 발생 지역의 산사면에 대하여 개발된 모델을 적용하여 예제 해석을 수행함으로써, 지하수 흐름 모델이 산사태 발생 예측을 위하여 이용할 수 있음을 입증하였다. 또한, 매개변수분석 연구를 통하여, 변수 a값은 작은 변화에 대하여 목적함수값에 큰 변화를 일으키므로 a의 값에 대한 최적값을 구하는 것이 가장 중요한 요소라는 결론을 얻었다.

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