• Title/Summary/Keyword: Estimation of solar radiation

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Estimation of Net Biome Production in a Barley-Rice Double Cropping Paddy Field of Gimje, Korea (김제 보리-벼 이모작지에서의 순 생물상생산량의 추정)

  • Shim, Kyo-Moon;Min, Sung-Hyun;Kim, Yong-Seok;Jung, Myung-Pyo;Choi, In-Tae
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.17 no.2
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    • pp.173-181
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    • 2015
  • Fluxes of carbon dioxide ($CO_2$) were measured above crop canopy using the Eddy Covariance (EC) method, and emission rate of methane ($CH_4$) was measured using Automatic Open/Close Chamber (AOCC) method during the 2012-2013 barley and rice growing season in a barley-rice double cropping field of Gimje, Korea. The net ecosystem exchange (NEE) of $CO_2$ in the paddy field was analyzed to be affected by crop growth (biomass, LAI, etc.) and environment (air temperature, solar radiation, etc.) factors. On the other hand, the emission rate of $CH_4$ was estimated to be affected by water management (soil condition). NEE of $CO_2$ in barley, rice and fallow period was -100.2, -374.1 and $+41.2g\;C\;m^{-2}$, respectively, and $CH_4$ emission in barley and rice period was 0.2 and $17.3g\;C\;m^{-2}$, respectively. When considering only $CO_2$, the barley-rice double cropping ecosystem was estimated as a carbon sink ($-433.0g\;C\;m^{-2}$). However, after considering the harvested crop biomass ($+600.3g\;C\;m^{-2}$) and $CH_4$ emission ($+17.5g\;C\;m^{-2}$), it turned into a carbon source ($+184.7g\;C\;m^{-2}$).

Parameter Regionalization of Hargreaves Equation Based on Climatological Characteristics in Korea (우리나라 기후특성을 고려한 Hargreaves 공식의 매개변수 지역화)

  • Moon, Jang Won;Jung, Chung Gil;Lee, Dong Ryul
    • Journal of Korea Water Resources Association
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    • v.46 no.9
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    • pp.933-946
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    • 2013
  • The quantitative analysis of evapotranspiration (ET) is a key component in hydrological studies and the establishment of water resources planning. Generally, the quantitative analysis of ET is performed by the estimation method of potential or reference ET based on meteorological factors such as air temperature, wind speed, etc. Hargreaves equation is one of empirical methods for reference ET using air temperature data. In this study, in order to estimate more exact reference ET considering climatological characteristics in Korea, parameter regionalization of Hargreaves equation is carried out. Firstly, modified Hargreaves equation is presented after the analysis of the relationship between solar radiation and temperature. Secondly, parameter ($K_{ET}$) optimization of Hargreaves equation is performed using Penman-Monteith method and modified equation at 71 weather stations. Lastly, the equation for calculating $K_{ET}$ using temperature data is proposed and verified. As a result, reference ET from original Hargreaves equation is overestimated or underestimated compared with Penman-Monteith method. But modified equation in this study is more accurate in the climatic conditions of Korea. In addition, the applicability of the equation between $K_{ET}$ and temperature is confirmed.

Estimation of spatial evapotranspiration using Terra MODIS satellite image and SEBAL model in mixed forest and rice paddy area (SEBAL 모형과 Terra MODIS 영상을 이용한 혼효림, 논 지역에서의 공간증발산량 산정 연구)

  • Lee, Yong Gwan;Jung, Chung Gil;Ahn, So Ra;Kim, Seong Joon
    • Journal of Korea Water Resources Association
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    • v.49 no.3
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    • pp.227-239
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    • 2016
  • This study is to estimate Surface Energy Balance Algorithm for Land (SEBAL) daily spatial evapotranspiration (ET) comparing with eddy covariance flux tower ET in Seolmacheon mixed forest (SMK) and Cheongmicheon rice paddy (CFK). The SEBAL input data of Albedo, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) from Terra MODIS products and the meteorological data of wind speed, and solar radiation were prepared for 2 years (2012-2013). For the annual average flux tower ET of 302.8 mm in SMK and 482.0 mm in CFK, the SEBAL ETs were 183.3 mm and 371.5 mm respectively. The determination coefficients ($R^2$) of SEBAL ET versus flux tower ET for total periods were 0.54 in SMK and 0.79 in CFK respectively. The main reason of SEBAL ET underestimation for both sites was from the determination of hot pixel and cold pixel of the day and affected to the overestimation of sensible heat flux.

Estimation of Rice Canopy Leaf Area Index(LAI) by Spectral Reflectance of Solar Radiation in Paddy Field (태양광 반사율을 이용한 벼 군락의 엽면적지수 추정)

  • 이정택;이춘우;주문갑;홍석영
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.42 no.2
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    • pp.173-181
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    • 1997
  • To estimate the leaf area index(LAI) of rice plant by non-destructive method, spectral reflectance from rice plant canopy was measured by using the spectroradiometer (LI-1800, LICOR Inc.) with one week interval during the rice growing season at Suwon paddy field in 1993. LAI of two medium late maturing varieties, Daechungbyeo and Ilpumbyeo, and one early maturing variety, Jinbubyeo, were observed and compared with those estimated by vegetation index. The reflectance(R) of visible wavelength remained less than 0.1 over entire growing season, but that of near infrared wavelength remained from 0.1 to 0.5 with the significant positive correlation with LAI. Vegetation index determined by the reflectance of visible against near infrared wavelength showed high correlation with LAI of rice canopy. Vegetation index derived from wide band ratio, NIR(720~1, 100nm) /Blue(400~500nm), showed the highest correlation coefficient with LAI. Vegetation index derived from narrow band(10nm interval) ratio, R910/R460, from transplanting to heading stage corresponded well to measured values (Y=0.16799X-0.79776 ; $R^2$=0.94). But another vegetation index, NIR(720~1, 100nm) /Red (600~700nm), showed higher correlation with LAI than NIR /Blue did from heading stage to maturity.

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Evaluation of Rededge-M Camera for Water Color Observation after Image Preprocessing (영상 전처리 수행을 통한 Rededge-M 카메라의 수색 관측에의 활용성 검토)

  • Kim, Wonkook;Roh, Sang-Hyun;Moon, Yongseon;Jung, Sunghun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.3
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    • pp.167-175
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    • 2019
  • Water color analysis allows non-destructive estimation of abundance of optically active water constituents in the water body. Recently, there have been increasing needs for light-weighted multispectral cameras that can be integrated with low altitude unmanned platforms such as drones, autonomous vehicles, and heli-kites, for the water color analysis by spectroradiometers. This study performs the preprocessing of the Micasense Rededge-M camera which recently receives a growing attention from the earth observation community for its handiness and applicability for local environment monitoring, and investigates the applicability of Rededge-M data for water color analysis. The Vignette correction and the band alignment were conducted for the radiometric image data from Rededge-M, and the sky, water, and solar radiation essential for the water color analysis, and the resultant remote sensing reflectance were validated with an independent hyperspectral instrument, TriOS RAMSES. The experiment shows that Rededge-M generally satisfies the basic performance criteria for water color analysis, although noticeable differences are observed in the blue (475 nm) and the near-infrared (840 nm) band compared with RAMSES.

The Evaluation of Meteorological Inputs retrieved from MODIS for Estimation of Gross Primary Productivity in the US Corn Belt Region (MODIS 위성 영상 기반의 일차생산성 알고리즘 입력 기상 자료의 신뢰도 평가: 미국 Corn Belt 지역을 중심으로)

  • Lee, Ji-Hye;Kang, Sin-Kyu;Jang, Keun-Chang;Ko, Jong-Han;Hong, Suk-Young
    • Korean Journal of Remote Sensing
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    • v.27 no.4
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    • pp.481-494
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    • 2011
  • Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

Estimation of Reference Crop Evapotranspiration Using Backpropagation Neural Network Model (역전파 신경망 모델을 이용한 기준 작물 증발산량 산정)

  • Kim, Minyoung;Choi, Yonghun;O'Shaughnessy, Susan;Colaizzi, Paul;Kim, Youngjin;Jeon, Jonggil;Lee, Sangbong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.6
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    • pp.111-121
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    • 2019
  • Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

Analysis of Greenhouse Thermal Environment by Model Simulation (시뮬레이션 모형에 의한 온실의 열환경 분석)

  • 서원명;윤용철
    • Journal of Bio-Environment Control
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    • v.5 no.2
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    • pp.215-235
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    • 1996
  • The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad & fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH+7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad & fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

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