• Title/Summary/Keyword: Rainfall-runoff model

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Characteristics of Water Budget on Throughfall and Stemflow in Pinus densiflora and Quercus acutissima (소나무와 상수리나무림의 임내우 물수지 특성)

  • 이헌호;박재철
    • Korean Journal of Environment and Ecology
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    • v.12 no.3
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    • pp.259-270
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    • 1998
  • This study, as an essential research to develope a mountainous runoff model, was conducted to clarify the hydrologic character and water budget equation of Pinus densiflora and Quercus acutissima. Net rainfall quantity division for two species was investigated at Youngsung experiment forest and Yeungnam University for 30 months(Sep. 1995-Jun. 1998). The results were summarized as follows; 1. The percentages of throughfall and stemflow to gross precipitation are 73.8% and 0.8% in the Pinus densiflora, and 76.9% and 3.8% in the Quercus acutissima, respectively 2. In the Pinus densiflora, regression fomula of stemflow, throughfall, and net rainfall to gross precipitation are S$_{f}$ = 0.01GP-2.05 ($r^2$=0.54) T$_{f}$ = 0.79Gp - 26.04 ($r^2$=0.92), N$_{r}$ = 0.81Gp - 28.09 ($r^2$=0.92). Stemflow and throughfall increased in direct proportion to gross precipitation. 3. In the Quercus acutissima, regression fomula of stemflow, throughfall, and net rainfall to gross precipitation are S$_{f}$ = 0.03Gp + 12.25 ($r^2$=0.74), T$_{f}$ = 0.78Gp + 19.75 ($r^2$=0.96), N$_{r}$ = 0.81Gp + 3199 ($r^2$=0.96), respectively. Comparing with two species, gross precipitation has a much larger effect on the stemflow and throughfall of Quercus acutissima than those of Pinus densiflora. 4. In the analysis of intercorrelation between stemflow and throughfall of each species and crown area(CA), diameter at breast height(DBH), and gross precipitation(Gp), correlation coefficient was higher by following order at each species; Gp>CA>DBH on stemflow of Pinus densinora, Gp>DBH>CA on stemflow of Quercus acutissima, and Gp>CA>DBH on throughfall of Pinus densiflora and Quercus acutissima.ssima.

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Development of lumped model to analyze the hydrological effects landuse change (토지이용 변화에 따른 수문 특성의 변화를 추적하기 위한 Lumped모형의 개발)

  • Son, Ill
    • Journal of the Korean Geographical Society
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    • v.29 no.3
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    • pp.233-252
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    • 1994
  • One of major advantages of Lumped model is its ability to simulate extended flows. A further advantage is that it requires only conventional, readily available hydrological data (rainfall, evaporation and runoff). These two advantages commend the use of this type of model for the analysis of the hydrological effects of landuse change. Experimental Catchment(K11) of Kimakia site in Kenga experienced three phases of landuse change for sixteen and half years. The Institute of Hydrology offered the hydrological data from the catchment for this research. On basis of Blackie's(l972) 9-parameter model, a new model(R1131) was reorganized in consideration of the following aspects to reflect the hydrological characteristics of the catchment: 1) The evapotranspiration necessary for the landuse hydrology, 2) high permeable soils, 3) small catchment, 4) input option for initial soil moisture deficit, and 5) othel modules for water budget analysis. The new model is constructed as a 11-parameter, 3-storage, 1-input option model. Using a number of initial conditions, the model was optimized to the data of three landuse phases. The model efficiencies were 96.78%, 97.20%, 94.62% and the errors of total flow were -1.78%, -3.36%, -5.32%. The bias of the optimized models were tested by several techniques, The extended flows were simulated in the prediction mode using the optimized model and the data set of the whole series of experimental periods. They are used to analyse the change of daily high and low-flow caused by landuse change. The relative water use ratio of the clearing and seedling phase was 60.21%, but that of the next two phases were 81.23% and 83.78% respectively. The annual peak flows of second and third phase at a 1.5-year return period were decreased by 31.3% and 31.2% compared to that of the first phase. The annual peak flow at a 50-year return period in the second phase was an increase of only 4.8%, and that in the third phase was an increase of 12.9%. The annual minimum flow at a 1.5-year return period was decreased by 34.2% in the second phase, and 34.3% in the third phase. The changes in the annual minimum flows were decreased for the larger return periods; a 20.2% decrease in the second phase and 20.9% decrease in the third phase at a 50-year return period. From the results above, two aspects could be concluded. Firstly, the flow regime in Catchment K11 was changed due to the landuse conversion from the clearing and seedling phade to the intermediate stage of pine plantation. But, The flow regime was little affected after the pine trees reached a certain height. Secondly, the effects of the pine plantation on the daily high- and low-flow were reduced with the increase in flood size and the severity of drought.

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Analysis on the Effects of Flood Damage Mitigation according to Installation of Underground Storage Facility (지하저류조 설치에 따른 침수피해 저감효과 분석)

  • Kim, Young Joo;Han, Kun Yeun;Cho, Wan Hee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.1B
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    • pp.41-51
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    • 2010
  • In this study, runoff simulation was carried out in the area of Bisan 7-dong, Seo-gu, Daegu as drainage basin and the effects of the installation of underground storage facilities were analyzed during heavy rainfall. SWMM model was used for the runoff and pipe network analysis on Typhoon Maemi, 2003. 2-D inundation analysis model based on diffusion wave was employed for inundation analysis and to verify computed inundation areas with observed inundation trace map. The simulation results agree with observed in terms of inundation area and depth. Also, the effects of flood damage mitigation were analyzed through the overflow discharge and 2-D inundation analysis, depending upon whether the underground storage facility is installed or not. When the underground storage facility ($W:120m{\times}L:180m{\times}H:1.7m$) is installed, volume of overflow could be reduced by 72% and flooding area could be reduced by 40.1%. When the underground storage facility ($W:120m{\times}L:180 m{\times}H:2.0m$) is installed, volume of overflow could be reduced by 84.8% and flooding area could be reduced by 50.6%. When the underground storage facility ($W:120m{\times}L:180m{\times}H:2.2m$) is installed, volume of overflow could be reduced by 94% and flooding area could be reduced by 91.2%. There is no overflow of manhole, when the height of storage facility is 2.5 m. It is expected that the study results presented through quantitative analysis on the effects of underground facilities can be used as base data for socially and economically effective installation of underground facilities to prevent flood damage.

Prediction of multipurpose dam inflow utilizing catchment attributes with LSTM and transformer models (유역정보 기반 Transformer및 LSTM을 활용한 다목적댐 일 단위 유입량 예측)

  • Kim, Hyung Ju;Song, Young Hoon;Chung, Eun Sung
    • Journal of Korea Water Resources Association
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    • v.57 no.7
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    • pp.437-449
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    • 2024
  • Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

Interactions between Soil Moisture and Weather Prediction in Rainfall-Runoff Application : Korea Land Data Assimilation System(KLDAS) (수리 모형을 이용한 Korea Land Data Assimilation System (KLDAS) 자료의 수문자료에 대한 영향력 분석)

  • Jung, Yong;Choi, Minha
    • 한국방재학회:학술대회논문집
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    • 2011.02a
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    • pp.172-172
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    • 2011
  • The interaction between land surface and atmosphere is essentially affected by hydrometeorological variables including soil moisture. Accurate estimation of soil moisture at spatial and temporal scales is crucial to better understand its roles to the weather systems. The KLDAS(Korea Land Data Assimilation System) is a regional, specifically Korea peninsula land surface information systems. As other prior land data assimilation systems, this can provide initial soil field information which can be used in atmospheric simulations. For this study, as an enabling high-resolution tool, weather research and forecasting(WRF-ARW) model is applied to produce precipitation data using GFS(Global Forecast System) with GFS embedded and KLDAS soil moisture information as initialization data. WRF-ARW generates precipitation data for a specific region using different parameters in physics options. The produced precipitation data will be employed for simulations of Hydrological Models such as HEC(Hydrologic Engineering Center) - HMS(Hydrologic Modeling System) as predefined input data for selected regional water responses. The purpose of this study is to show the impact of a hydrometeorological variable such as soil moisture in KLDAS on hydrological consequences in Korea peninsula. The study region, Chongmi River Basin, is located in the center of Korea Peninsular. This has 60.8Km river length and 17.01% slope. This region mostly consists of farming field however the chosen study area placed in mountainous area. The length of river basin perimeter is 185Km and the average width of river is 9.53 meter with 676 meter highest elevation in this region. We have four different observation locations : Sulsung, Taepyung, Samjook, and Sangkeug observatoriesn, This watershed is selected as a tentative research location and continuously studied for getting hydrological effects from land surface information. Simulations for a real regional storm case(June 17~ June 25, 2006) are executed. WRF-ARW for this case study used WSM6 as a micro physics, Kain-Fritcsch Scheme for cumulus scheme, and YSU scheme for planetary boundary layer. The results of WRF simulations generate excellent precipitation data in terms of peak precipitation and date, and the pattern of daily precipitation for four locations. For Sankeug observatory, WRF overestimated precipitation approximately 100 mm/day on July 17, 2006. Taepyung and Samjook display that WRF produced either with KLDAS or with GFS embedded initial soil moisture data higher precipitation amounts compared to observation. Results and discussions in detail on accuracy of prediction using formerly mentioned manners are going to be presented in 2011 Annual Conference of the Korean Society of Hazard Mitigation.

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Determination of Optimal Operation Water Level of Rain Water Pump Station using Optimization Technique (최적화 기법을 이용한 빗물펌프장 최적 운영수위 결정)

  • Sim, Kyu-Bum;Yoo, Do-Guen;Kim, Eung-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.7
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    • pp.337-342
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    • 2018
  • A rain water pumping station is a structural countermeasure to inland flooding of domestic water generated in a urban watershed. In this study, the optimal operation water level of the pump with the minimum overflow was determined based on the opinions of the person in charge of the operation of the rain water pump station. A GA (Genetic Algorithm), which is an optimization technique, was used to estimate the optimal operation water level of the rain water pump station and was linked with SWMM (Ver.5.1) DLL, which is a rainfall-runoff model of an urban watershed. Considering the time required to maximize the efficiency of the pump, the optimal operating water level was estimated. As a result, the overall water level decreased at a lower operating water level than the existing water level. For most pumps, the lowest operating water level was selected for the operating range of each pump unit. The operation of the initial pump could reduce the amount of overflow, and there was no change in the overflow reduction, even after changing the operation condition of the pump. Internal water flooding reduction was calculated to be 1%~2%, and the overflow occurring in the downstream area was reduced. The operating point of the pump was judged to be an effective operation from a mechanical and practical point of view. A consideration of the operating conditions of the pump in future, will be helpful for improving the efficiency of the pump and to reducing inland flooding.

Application and Comparison of Dynamic Artificial Neural Networks for Urban Inundation Analysis (도시침수 해석을 위한 동적 인공신경망의 적용 및 비교)

  • Kim, Hyun Il;Keum, Ho Jun;Han, Kun Yeun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.5
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    • pp.671-683
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    • 2018
  • The flood damage caused by heavy rains in urban watershed is increasing, and, as evidenced by many previous studies, urban flooding usually exceeds the water capacity of drainage networks. The flood on the area which considerably urbanized and densely populated cause serious social and economic damage. To solve this problem, deterministic and probabilistic studies have been conducted for the prediction flooding in urban areas. However, it is insufficient to obtain lead times and to derive the prediction results for the flood volume in a short period of time. In this study, IDNN, TDNN and NARX were compared for real-time flood prediction based on urban runoff analysis to present the optimal real-time urban flood prediction technique. As a result of the flood prediction with rainfall event of 2010 and 2011 in Gangnam area, the Nash efficiency coefficient of the input delay artificial neural network, the time delay neural network and nonlinear autoregressive network with exogenous inputs are 0.86, 0.92, 0.99 and 0.53, 0.41, 0.98 respectively. Comparing with the result of the error analysis on the predicted result, it is revealed that the use of nonlinear autoregressive network with exogenous inputs must be appropriate for the establishment of urban flood response system in the future.

Analysis of Groundwater Use in Kap-cheon Basin (갑천 유역의 지하수 이용 특성 분석)

  • Hong, Sung-Hun;Kim, Jeong-Kon
    • Journal of Korea Water Resources Association
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    • v.41 no.5
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    • pp.463-471
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    • 2008
  • The purpose of this study is to analyze the features of groundwater use to utilize as basic information for water-cycle analysis system development and effective groundwater management in the Kap-cheon basin. The cumulative relationship between groundwater use and the number of wells was analyzed to estimate the representative total groundwater use and the number of wells for the Kap-cheon basin. Then, the spatial distribution of groundwater use in the basin were figured out using the detailed information on groundwater use in each well. Finally, the reasonability of groundwater resources management in Kap-cheon basin was evaluated by comparing groundwater recharge and groundwater use in sub-basins and major stream basins. The results of the analysis showed about 25% of the total wells could represent 90% of groundwater use ($37,923,516\;m^3$/year) in the Kap-cheon basin. A detailed analysis on the groundwater uses in the vicinity of down-town areas of Daejeon metropolitan city showed high groundwater uses ($1.4{\sim}11.1$ times) compared to the groundwater recharge previously estimated using the rainfall-runoff model. The ratio of groundwater use and groundwater recharge for the major river basins in Kap-cheon basin ranged from 1.9 to 2.3 indicating that more sustainable groundwater management should be exercised. The results of this study can be used as basic information in evaluating the change of groundwater flow, stream flow and water-cycle for various groundwater uses in the Kap-cheon basin.

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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Estimation of Nonpoint Source Pollutant Loads for Rural Watershed by AvSWAT (AvSWAT를 이용한 농촌유역 비점원 오염물질 부하량 예측)

  • Kim, Jin-Ho;Lee, Jong-Sik;Kim, Won-Il;Jung, Goo-Bok;Han, Kuk-Heon;Ruy, Jong-Su;Kim, Suk-Cheol;Yun, Sun-Gang;Lee, Jeong-Taek;Kwun, Soon-Kuk
    • Korean Journal of Soil Science and Fertilizer
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    • v.40 no.1
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    • pp.12-17
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    • 2007
  • This study was conducted to evaluate the characteristics of nonpoint source pollutants discharge from a small rural watershed. A typical rural area in Gongju City, Korea, was selected as the research site. Water quality and quantity in streams and rainfall samples were analyzed periodically from May to October 2005. Pollutant loads were estimated from a nonpoint source pollution model (AvSWAT, Arcview Soil and Water Assessment Tool). During the rainy season, from June 26 to 30 September 2005 and the dry season, before 26 June and after 30 September 2005, biological oxygen demands and chemical oxygen demands accounted for 91.3% and 93.7% of annual load, respectively, while total-N and total-P were 97.1% and 91.1% of annual load, respectively. The observed stream flow was $66.5m^3sec^{-1}$, while simulation stream flow was $66.2m^3sec^{-1}$. That can be assumed that simulation can be used to estimate the stream flow without practical measurement. However, the runoff trend following the occurrence of a storm event was not recorded properly.