Simplified method for estimating the optimal cut‐off time of closed‐end border irrigation<sup>*</sup>

Nie, Wei‐Bo; Li, Yi‐Bo

doi:10.1002/ird.2554

Cited by 3 publications

(8 citation statements)

References 29 publications

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“…The comparison between the Y and Y´ indices acquired from the two methods are indicated in Fig.5. The Y index diagram illustrates that the attained Y index from the proposed method were higher than that from the method presented by(Nie et al 2021). Examination of Y´ values also revealed the better performance of the proposed method in comparison to its counterpart(Nie et al 2021).…”

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confidence: 74%

“…The Y index diagram illustrates that the attained Y index from the proposed method were higher than that from the method presented by(Nie et al 2021). Examination of Y´ values also revealed the better performance of the proposed method in comparison to its counterpart(Nie et al 2021). The average Y´ index for the proposed method and (Nie et al 2021)'s method were 74.5 and 67.8%, respectively.3.2.3.…”

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confidence: 74%

“…To date limited regression equations have been analyzed to estimate the optimal T co based on T a (Nie et al 2021; Smith and Uddin 2020). As mentioned, border irrigation in some area such as Iran is associated with special conditions and is different from areas that studied by previous researchers (the length of the borders is mostly short, the in ow discharge to the borders is high and usually the irrigation depth is less than required due to water shortage crisis).…”

Section: Simulationsmentioning

confidence: 99%

“…Factors affecting the performance of border irrigation can be divided into two categories: physical and management parameters (Nie et al 2021). Physical parameters include soil in ltration characteristics, border slope, roughness coe cient, length and width of 2020) examined the effect of in ow discharge rates on performance of border irrigation.…”

Section: Introductionmentioning

confidence: 99%

“…The empirical equation developed by(Nie et al 2021; Smith and Uddin 2020) was examined and compared with the results of the proposed method. The values of T co obtained by the equation of Smith and Uddin (2020) for experimental borders were negative.…”

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confidence: 99%

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An Approach to Estimate Optimal Cut-off Time under Deficit Irrigation

Ghorbanian

Ojaghlou

Ebrahimian

2022

Preprint

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The use of deficit irrigation technique has become inevitable due to the lack of water resources in many parts of the world. The goal of this study is to improve the performance of border irrigation under deficit strategy by determining the optimal cutoff time (Tco). For this purpose, field experiments and simulation modeling were carried out. The experimental borders were different in terms of inflow discharge, soil texture and length. 1024 combinations included different physical and management factors were analyzed by the WinSRFR software. By determining the optimal Tco for each combination, fifteen regression equations were extracted for three irrigation levels and five advance times (Ta) (times when water advanced to 30 to 70% of the border lengths). Two indexes including Y (combination of efficiency and uniformity indices) and Y′ (combination of efficiency, uniformity, and requirement efficiency) were used to evaluate border irrigation performance. Based on the validation results, the relationship between Tco and Ta at the 70% of the border length was introduced as a suitable option. The performance of the selected equation was evaluated using the field data. The results illustrated that the calculated values of Y and Y′ from the proposed method was in high agreement with theses from the common optimization method. Tco obtained from the proposed relationship improved the Y and Y′ indices by 9.4 and 6.6%, respectively, compared to the field conditions. The proposed relationship will guarantee application efficiency above 60%, uniformity and requirement efficiency above 80%.

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confidence: 74%

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confidence: 74%

Section: Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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