• Title/Summary/Keyword: Irrigation Simulation

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Application of the Artificial Neurons Networks for Runoff Forecasting in Sungai Kolok Basin, Southern Thailand

  • Mama, Ruetaitip;Namsai, Matharit;Choi, Mikyoung;Jung, Kwansue
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.259-259
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    • 2016
  • This study examined Artificial Neurons Networks model (ANNs) for forecast flash discharge at Southern part of Thailand by using rainfall data and discharge data. The Sungai Kolok River Basin has meant the border crossing between Thailand and Malaysia which watershed drains an area lies in Thailand 691.88 square kilometer from over all 2,175 square kilometer. The river originates in mountainous area of Waeng district then flow through Gulf of Thailand at Narathiwat Province, which the river length is approximately 103 kilometers. Almost every year, flooding seems to have increased in frequency and magnitude which is highly non-linear and complicated phenomena. The purpose of this study is to forecast runoff on Sungai Kolok at X.119A gauge station (Sungai Kolok district, Narathiwat province) for 3 days in advance by using Artificial Neural Networks model (ANNs). 3 daily rainfall stations and 2 daily runoff station have been measured by Royal Irrigation Department and Meteorological Department during flood period 2000-2014 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Coefficient of determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. $R^2$values for first day, second day and third day of runoff forecasting is 0.71, 0.62 and 0.49 respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and real-time operated. In conclusion, the ANNs model is suitable to runoff forecasting during flood incident of Sungai Kolok river because it is straightforward model and require with only a few parameters for simulation.

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A Study on Estimation of Pollutant Loads in Seonakdong River Using SWAT-SWMM Model (SWAT-SWMM 연계모의를 이용한 서낙동강 오염부하량 산정 방안 연구)

  • Kim, Jeong-Min;Kim, Young-Do
    • Journal of Korean Society of Water and Wastewater
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    • v.25 no.6
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    • pp.825-837
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    • 2011
  • Seonakdong river consists of stagnant sections whose flowrate is controlled by the Daejeo and Noksan gates. As a result, there is not a minimum flow during normal times. The Daejeo and Noksan gates are located at the upstream head and the downstream end of Seonakdong river, respectively. Seonakdong river is an estuarine tributary of Nakdong river, which is a reservoir-like river used for agricultural irrigation, with the gate at the estuary of the river to prevent the intrusion of saline. Since the construction of the water gates, the water quality of the river has become degraded. This could also be due to the internal loading of pollutants, especially nutrients, from the sediments of the river because of the elongated detention time by the water gates. This study was thus conducted for the purpose of evaluating the current hydrologic-cycle system and providing measures for the rehabilitation of the hydrologic cycle. In this research, the daily outflow in Seonakdong River was simulated using the SWAT and SWMM models, and the water quality concentration including BOD, SS, TN, and TP were analyzed. The possibility of the application of SWAT-SWMM hybrid simulation was determined through the verification of both models. The error analysis shows that the results of both SWAT and SWAT-SWMM simulations make good agreements with those of field observations. For the single simulation results of SWAT, $R^{2}$ and NSE are 0.758, 0.511, respectively. For the hybrid simulation results of SWAT-SWMM, those are 0.880, 0.452, which means that the hybrid simulation can give more accurate results for the watershed where both the agricultural and urban areas exist.

STOCHASTIC SIMULATION OF DAILY WEATHER VARIABLES

  • Lee, Ju-Young;Kelly brumbelow, Kelly-Brumbelow
    • Water Engineering Research
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    • v.4 no.3
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    • pp.111-126
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    • 2003
  • Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

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Performance and flow field assessment of settling tanks using experimental and CFD modeling

  • Nouri, Alireza Zamani;Heydari, Mohammad Mehdi
    • Membrane and Water Treatment
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    • v.8 no.5
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    • pp.423-435
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    • 2017
  • Settling Basins are one of the most important and popular methods for removal of suspended sediments irrigation and drainage networks or power canals taking off from an alluvial river and wastewater treatment plant. Improving the performance and so increasing sediment removal efficiency of settling basins by an alternative method is necessary. In the present work, the effect of baffle and its angle of attack with the flow (${\theta}$) on the sediment removal efficiency is investigated by conducting a series of experiments on a straight canal with 8 m length, 0.3 m width and 0.5 m height and 3 m length of basin equipped with an adjustable glass baffle. A numerical analysis has been carried out using ANSYS Fluent 3D software (a general purpose computational fluid dynamics simulation tool) for three Froude numbers from the experiments. The numerical and experimental results were found to match reasonably well.

Extraction of Snow Cover Area and Depth Using MODIS Image for 5 River Basins South Korea (MODIS 위성영상을 이용한 국내 5대강 유역 적설분포 및 적설심 추출)

  • Hong, U-Yong;Sin, Hyeong-Jin;Kim, Seong-Jun
    • KCID journal
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    • v.14 no.2
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    • pp.225-235
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    • 2007
  • The shape of streamflow hydrograph during the early period of spring is very much controlled by the area and depth of snow cover especially in mountainous area. When we simulate the streamfolw of a watershed snowmelt, we need some information for snow cover extent and depth distribution as parameters and input data in the hydrological models. The purpose of this study is to suggest an extraction method of snow cover area and snow depth distribution using Terra MODIS image. Snow cover extent for South Korea was extracted for the period of December 2000 and April 2006. For the snow cover area, the snow depth was interpolated using the snow depth data from 69 meteorological observation stations. With these data, it is necessary to run a hydrological model considering the snow-related data and compare the simulated streamflow with the observed data and check the applicability for the snowmelt simulation.

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Analysis on Canal System for Daily Irrigation Simulation (관개용수로 수리시뮬레이션을 통한 농업용수조직 거동 분석)

  • Park, Ki-Wook
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.673-682
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    • 2007
  • 본 연구에서는 관개용수로에서의 용수공급에 따른 용수분배 현상을 모의하고, 개선방안을 제시하기 위한 시뮬레이션 모형을 개발하였다. 관개용수로와 같은 인공적인 수로에서는 흐름의 상태가 취수공, 분수공, 수문 등과 같은 수리시설의 조작에 의해 흐름이 시간적, 공간적으로 변하게 되는 비정상류가 주가 된다. 이러한 비정상류 해석은 농업용수 관리를 위한 관개계획 수립, 농업용 수리시설물의 설계 및 관리에 있어서 중요한 요인이 된다. 용수로의 부정류 해석을 위한 유한차분식으로 구성되는 모형을 개발하여 용수로를 일정구간으로 분할하여 각 구간별 수위와 유속의 변화를 계산하게 된다. 계산된 결과는 현장에서 실측된 수위모니터링 자료와 현장 유량측정자료로 비교하여 모형의 적정성을 검정하였다. 용수로내의 흐름에 대하여 각 구간의 용수도달시간, 관개블록에 대한 분수유량을 산정한 결과는 현장 측정자료와 잘 일치하고 있는 것으로 나타나 관개계획을 수립하는 데 이용할 수 있을 것으로 판단되었다.

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A Study of Operation Standard and Method of Small Dams (소규모 댐의 운영기준 및 기법 연구)

  • Kim, Phil-Shik;Kim, Sun-Joo;Lee, Joo-Yong
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.260-265
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    • 2005
  • The purpose of this study is to established a storage management method and operation standard for irrigation dams occupying the largest portion of small dams using storage management system. The system can be applied to seongju dam for effective management. The storage management method was established considering hydrology simulation and statistical analysis using the system. This method and operation standard are capable of analyzing additional available water, considering the water demand and supply of basin actually. It can improve the flood control capacity and water utilization efficiency by the flexible operation of storage space.

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Nonstationary Frequency Analysis of Hydrologic Extreme Variables Considering of Seasonality and Trend (계절성과 경향성을 고려한 극치수문자료의 비정상성 빈도해석)

  • Lee, Jeong-Ju;Kwon, Hyun-Han;Moon, Young-Il
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.581-585
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    • 2010
  • This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

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A study on estimating the quick return flow from irrigation canal of agricultural water using watershed model (유역모델을 이용한 농업용수 신속회귀수량 산정 연구)

  • Lee, Jiwan;Jung, Chunggil;Kim, Daye;Maeng, Seungjin;Jeong, Hyunsik;Jo, Youngsik;Kim, Seongjoon
    • Journal of Korea Water Resources Association
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    • v.55 no.5
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    • pp.321-331
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    • 2022
  • In this study, we tried to present a method for calculating the amount of regression using a watershed modeling method that can simulate the hydrological mechanism of water balance analysis and agricultural water based on watershed unit. Using the soil water assessment tool (SWAT), a watershed water balance analysis was conducted considering the simulation of paddy fields for the Manbongcheon Standard Basin (97.34 km2), which is a representative agricultural area of the Yeongsan river basin. Before evaluating return flow, the SWAT was calibrated and validated using the daily streamflow observation data at Naju streamflow gauge station (NJ). The coefficient of determination (R2), Nash-Sutcliffe Efficiency (NSE), Root-Mean-Square Error (RMSE) of NJ were 0.73, 0.70, 0.64 mm/day. Based on the calibration results for three years (2015-2017), the quick return flow and the return rate compared to the water supply amount for the irrigation period (April 1 to September 30) were calculated, and the average return flow rate was 53.4%. The proposed method of this study may be used as foundation data to optimal agricultural water supply plan for rational watershed management.

A Study on the Development of a Simulation Model for Predicting Soil Moisture Content and Scheduling Irrigation (토양수분함량 예측 및 계획관개 모의 모형 개발에 관한 연구(I))

  • 김철회;고재군
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.19 no.1
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    • pp.4279-4295
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    • 1977
  • Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka+Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

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