• Title/Summary/Keyword: crop coefficient

Search Result 459, Processing Time 0.035 seconds

Probable Evapotranspiration of Paddy Rice using Dry Day Index

  • 장하우;김성준
    • Magazine of the Korean Society of Agricultural Engineers
    • /
    • v.37 no.E
    • /
    • pp.72-78
    • /
    • 1995
  • To support some knowledge in planning irrigation system, short or long-term irrigation scheduling or determining irrigation reservoir capacity, it is necessary to estimate peak irrigation requirements and seasonal distribution of water demands for various return periods. In this paper Dry Day Index and Probable Evapotranspiration were evaluated to decide seasonal consumptive use of paddy rice for a design year using several decades' daily rainfall data and 5 years'('82~'86) actual evapotranspiration data, respectively. To obtain Dry Day Index that is defined as the number of probable dry days for a given period, Slade unsymmetrical distribution function was adopted. Dry Day Index was analysed for 5 and 10-day intervals. Each of them was evaluated with return periods of 1, 3, 5, 10 and 20 year. Their singnificance was tested by X$^2$ method. Based on these values, the Probable Evaportanspiration, that is the average daily ET both in dry days and rainy days during a given period, was estimated. Crop coefficient was also determined by the modified Penman equation proposed by Doorenbos & Pruitt.

  • PDF

영농방식변화에 따른 논용수량 산정 시스템 개발

  • Ju, Uk-Jong;Kim, Jin-Taek;Park, Gi-Uk;Lee, Yong-Jik
    • KCID journal
    • /
    • v.13 no.1
    • /
    • pp.82-90
    • /
    • 2006
  • The practical date of rice growing stages and the date for calculating the water demand in paddy field have differences. The causes are rice planting water requirement, nursery bed area and change of average temperature and so on. Some recent papers have shown the same results. So we have investigated the nursery period, rice transplanting period and mid-summer drainage and developed a system for estimating water demand. And we calculated the water demand by using the system. The result showed that calculation by using the new system is more appropriate than the calculation by using the established period. But because water losses in canals and crop coefficient are not determined appropriately, we can calculate the agricultural water demand more accurately by dstablishing canal losses ratio, crop coefficient and so on.

  • PDF

Change of Weed Community in Paddy - Upland Rotation (답전윤환(畓田輪換)에 따른 잡초(雜草) 발생(發生) 변화(變化))

  • Ku, Y.C.;Seong, K.Y.;Song, D.Y.;Lee, S.B.;Huh, I.P.
    • Korean Journal of Weed Science
    • /
    • v.17 no.2
    • /
    • pp.157-162
    • /
    • 1997
  • This study was conducted to investigate the change of weed community on paddy-upland rotation in 1996. In paddy-upland rotation, dominant weed species in paddy condition were Cyperous amuricus, Echinochloa crus-galli, Rotara indica and Lindernia procumbens. They were E. crusgalli, Digitaria sanguinalis and C. amuricus in upland condition. The number of weed occurrence on paddy and upland rotation reduced about 74-78% as compared with continuous paddy and upland condition. Similarity coefficient and Simpson index on paddy and upland rotation was 8-64, 0.34-0.35, respectively.

  • PDF

Statistical Analysis of Determining Optimal Monitoring Time Schedule for Crop Water Stress Index (CWSI) (작물 수분 스트레스 지수 산정을 위한 최적의 관측 간격과 시간에 대한 통계적 분석)

  • Choi, Yonghun;Kim, Minyoung;Oh, Woohyun;Cho, Junggun;Yun, Seokkyu;Lee, Sangbong;Kim, Youngjin;Jeon, Jonggil
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.61 no.6
    • /
    • pp.73-79
    • /
    • 2019
  • Continuous and tremendous data (canopy temperature and meteorological variables) are necessary to determine Crop Water Stress Index (CWSI). This study investigated the optimal monitoring time and interval of canopy temperature and meteorological variables (air temperature, relative humidity, solar radiation and wind speed) to determine CWSIs. The Nash-Sutcliffe model efficiency coefficient (NSE) was used to quantitatively describe the accuracy of sampling method depending upon various time intervals (t=5, 10, 15, 20, 30 and 60 minutes) and CWSIs per every minute were used as a reference. The NSE coefficient of wind speed was 0.516 at the sampling time of 60 minutes, while the ones of other meteorological variables and canopy temperature were greater than 0.8. The pattern of daily CWSIs increased from 8:00 am, reached the maximum value at 12:00 pm, then decreased after 2:00 pm. The statistical analysis showed that the data collection at 11:40 am produced the closest CWSI value to the daily average of CWSI, which indicates that just one time of measurement could be representative throughout the day. Overall, the findings of this study contributes to the economical and convenient method of quantifying CWSIs and irrigation management.

An Experimental Study on Applying Heat Pump System to Facility Horticulture House (히트펌프 시스템의 시설원예 적용에 관한 실험적 연구)

  • Kim, Jae-Dol
    • Journal of Power System Engineering
    • /
    • v.17 no.6
    • /
    • pp.88-94
    • /
    • 2013
  • As the results of analysis that are applying a heat pump using underground water as heat source of facility horticulture house, temperature change in house, growth of cultivated plants and the crop characteristic, the conclusion can be acquired as follows. It was possible to maintain the chamber temperature through operating heat pump with setting goal temperature at $16^{\circ}C$ and temperature variation at ${\pm}3^{\circ}C$. And cooling and heating coefficient of performance in heat pump system are different from setting room temperature and operation condition of equipment, totally in case that the setting temperature in house is low, the coefficient of performance and the in case that temperature departure is low. In case that the house does not heated, the result of the growth characteristic of cucumber planted last 50days is that cucumber grown in house equipped with heat pump is the most favorable growth characteristic due to maintaining a constant room temperature. After 90 days, the quantity and weight cucumber harvested in each house are averagely 9.8%, 13.1% increase and more heavy weight respectively. So it is researched that crop characteristic is superior.

Establishing a Crop System of Organic Farming for Maximizing Agricultural Income (유기농업의 소득 극대화를 위한 작부체계 수립 전략)

  • Kim, Ho;Kim, Sung-Tae
    • Korean Journal of Organic Agriculture
    • /
    • v.20 no.2
    • /
    • pp.143-159
    • /
    • 2012
  • Agricultural income is calculated with producer price, output and management cost. This study compared organic farming with conventional one for agricultural income, producer price and output by items. And then it proposed the method of item selection and crop system from a diversification point of view. The coefficient of variation to producer prices in organic farming was 4.7%, and conventional one was 30.3% because organic products have been produced in a system of contract farming with consumers' cooperative. This result means the price of organic products is stabler than that of conventional price. And agricultural income of organic farming has been generally known more than that of conventional one. However, agricultural gross income of conventional farming was more than that of organic one by 20.3% in 2010. It was caused by output reduction of a few items(fer example; onion, large green onion, potato and young pumpkin) due to freak weather conditions and constant producer price for several years in organic farming. In order to increase agricultural income, appropriate crop selection and system should be introduced to organic farming. A principal crop is the rice plant and 2 subordinate crops are dry crops at bare field and greenhouse respectively. Thus 5 crop systems that agricultural gross income are relatively increased larger among 15 crop systems estimated are rice+ginger+cucumber, rice+ginger+tomato, rice+large green onion+cucumber, rice+sweet potato+cucumber and rice+onion+ cucumber.

Development of Crop Growth Model under Different Soil Moisture Status

  • Goto, Keita;Yabuta, Shin;Sakagami, Jun-Ichi
    • Proceedings of the Korean Society of Crop Science Conference
    • /
    • 2019.09a
    • /
    • pp.19-19
    • /
    • 2019
  • It is necessary to maintain stable crop productions under the unsuitable environments, because the drought and flood may be frequently caused by the global warming. Therefore, it is agent to improve the crop growth model corresponded to soil moisture status. Chili pepper (Capsicum annuum) is one of the useful crop in Asia, and then it is affected by change of precipitation in consequence drought and flood occur however crop model to evaluate water stresses on chili pepper is not enough yet. In this study, development of crop model under different soil moisture status was attempted. The experiment was conducted on the slope fields in the greenhouse. The water level was kept at 20cm above the bottom of the container. Habanero (C. chinense) was used as material for crop model. Sap bleeding rate, SPAD value, chlorophyll content, stomatal conductance, leaf water potential, plant height, leaf area and shoot dry weight were measured at 10 days after treatment (DAT) and 13 DAT. Moreover, temperature and RH in the greenhouse, soil volume water contents (VWC) and soil water potential were measured. As a result, VWC showed 4.0% at the driest plot and 31.4% at the wettest plot at 13 DAT. The growth model was calculated using WVC and the growth analysis parameters. It was considered available, because its coefficient of determination showed 0.84 and there are significant relationship based on plants physiology among the parameters and the changes over time. Furthermore, we analyzed the important factors for higher accuracy prediction using multiple regression analysis.

  • PDF

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
    • /
    • v.19 no.1
    • /
    • pp.4279-4295
    • /
    • 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.

  • PDF