scholarly journals Encounter probability analysis of irrigation water and reference crop evapotranspiration in irrigation district

2018 ◽  
Vol 66 (3) ◽  
pp. 279-284
Author(s):  
Jinping Zhang ◽  
Jiayi Li ◽  
Xixi Shi
Keyword(s):  
Return Period ◽  
Irrigation Water ◽  
Joint Probability ◽  
Irrigation District ◽  
Joint Probability Distribution ◽  
Data Series ◽  
Crop Evapotranspiration ◽  
Reference Crop Evapotranspiration ◽  
Encounter Probability ◽  
Reference Crop

Abstract Based on the data series of the annual reference crop evapotranspiration (ET0) and the amount of irrigation water (IR) from 1970 to 2013 in the Luhun irrigation district, the joint probability distribution of ET0 and IR is established using the Gumbel-Hougaard copula function. Subsequently, the joint probability, the conditional joint probability, and the conditional return period of rich−poor encounter situations of ET0 and IR are analysed. The results show that: (1) For the joint probabilities of rich−poor encounter situations of ET0 and IR, the asynchronous encounter probability is slightly larger than the synchronous encounter probability. (2) When IR is in rich state or ET0 is in poor state, the conditional joint probability is larger, and the conditional return period is smaller. (3) For a certain design frequency of ET0, if the design frequency decreases, the conditional joint probability of the amount of irrigation water will decrease, therefore the encounter probability of them will decrease. (4) For a certain design frequency of the amount of irrigation water, if the design frequency decreases, the conditional joint probability of ET0 will increase, thus the encounter probability of them will increase.

The joint distribution of reference crop evapotranspiration and irrigation water in the irrigation district

2017 ◽  
Vol 18 (2) ◽  
pp. 567-576 ◽  
Author(s):  
Jinping Zhang ◽  
Xiaomin Lin ◽  
Yong Zhao
Keyword(s):  
Irrigation Water ◽  
Joint Distribution ◽  
Water Shortage ◽  
Irrigation District ◽  
Crop Evapotranspiration ◽  
Archimedean Copulas ◽  
Marginal Distributions ◽  
Reference Crop Evapotranspiration ◽  
Best Fitting ◽  
Reference Crop

Abstract For the irrigation district, irrigation water is the manual water supply for the farmland while reference crop evapotranspiration (ET0) reflects water demand. Thus, the joint distribution of irrigation water and ET0 can reveal water shortage risk under the condition of the manual water supply. In order to understand their relationships and overcome the drawbacks of different marginal distributions of hydrological variables, Archimedean copulas are introduced. Based on the data series of ET0 and irrigation water in the Luhun irrigation district of China, the univariate marginal distributions of ET0 and irrigation water are first selected. Then, with the Gumbel–Hougaard copula in the Archimedean copulas, the joint distribution of ET0 and irrigation water is proposed. The results show that the best-fitting marginal distributions of ET0 and irrigation water are generalized extreme values and normal distributions, respectively, but for their joint distribution, the Gumbel–Hougaard copula is the best-fitting one. The water shortage risks with different encounter situations of ET0 and irrigation water are better revealed using the proposed copula-based joint distribution.

scholarly journals Time series analysis of reference crop evapotranspiration for Bokaro District, Jharkhand, India

2016 ◽  
Vol 30 (1) ◽  
pp. 51-56 ◽  
Author(s):  
Ratnesh Gautam ◽  
Anand K. Sinha
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Moving Average ◽  
Arima Model ◽  
Likelihood Method ◽  
Data Series ◽  
Crop Evapotranspiration ◽  
Reference Crop Evapotranspiration ◽  
Resources Management ◽  
Reference Crop

AbstractEvapotranspiration is the one of the major role playing element in water cycle. More accurate measurement and forecasting of Evapotranspiration would enable more efficient water resources management. This study, is therefore, particularly focused on evapotranspiration modelling and forecasting, since forecasting would provide better information for optimal water resources management. There are numerous techniques of evapotranspiration forecasting that include autoregressive (AR) and moving average (MA), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), Thomas Feiring, etc. Out of these models ARIMA model has been found to be more suitable for analysis and forecasting of hydrological events. Therefore, in this study ARIMA models have been used for forecasting of mean monthly reference crop evapotranspiration by stochastic analysis. The data series of 102 years i.e. 1224 months of Bokaro District were used for analysis and forecasting. Different order of ARIMA model was selected on the basis of autocorrelation function (ACF) and partial autocorrelation (PACF) of data series. Maximum likelihood method was used for determining the parameters of the models. To see the statistical parameter of model, best fitted model is ARIMA (0, 1, 4) (0, 1, 1)12.

scholarly journals Copula-based joint probability distribution of water supply and demand in Luhun irrigation district

2018 ◽  
Vol 19 (3) ◽  
pp. 932-943
Author(s):  
Jinping Zhang ◽  
Xixi Shi ◽  
Jian Li ◽  
Fawen Li
Keyword(s):  
Irrigation Water ◽  
Supply And Demand ◽  
Three Dimensional ◽  
Joint Probability ◽  
Irrigation District ◽  
Joint Probability Distribution ◽  
Joint Distributions ◽  
Best Fitting ◽  
T Copula ◽  
Student’S T

Abstract The potential of the copula method to construct the joint probability distribution of three hydrological variables characterizing water supply and demand (WSD) is explored for the Luhun irrigation district of China. The marginal distributions of rainfall, reference crop evapotranspiration (ET0) and irrigation water are simulated by the corresponding best-fitting cumulative distribution functions. Furthermore, the correlations between every pair of variables are quantified. On this basis, the two-dimensional joint distributions of rainfall and (ET0) (representing natural WSD), and irrigation water and (ET0) (representing man-made WSD), and the three-dimensional joint distribution of rainfall, irrigation water, and (ET0) (representing natural–man-made WSD) are established. The results reveal that the best-fitting marginal distributions for rainfall and (ET0) and irrigation water are the normal distribution and the Weibull distribution. Moreover, for rainfall and (ET0), the Student's t copula is applied to obtain the joint distribution, while the corresponding copula for (ET0) and irrigation water is the Clayton copula. Finally, the three-dimensional Student's t copula is selected to explore the dependence structure among rainfall, irrigation water, and (ET0). Therefore, these joint distributions provide an efficient approach to assess water shortage risks in the irrigation district.

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