Assessment of Aquacrop Model for Irrigated Cotton under Deficit Irrigation in Semi-Arid Tropics of Maharashtra
Predicting attainable yield under water limiting condition is an important goal in rainfed agriculture. Proper irrigation planning is not only essential for water saving but also for yield enhancement and it is only possible when an accurate and reliable decision-making tool has been adopted. AquaCr...
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Veröffentlicht in: | International journal of current microbiology and applied sciences 2022-01, Vol.11 (1), p.123-135 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Predicting attainable yield under water limiting condition is an important goal in rainfed agriculture. Proper irrigation planning is not only essential for water saving but also for yield enhancement and it is only possible when an accurate and reliable decision-making tool has been adopted. AquaCrop is one of the models extensively used for irrigation planning purposes. To evaluate the performance of the model, the present experiment entitled on “Assessment of AquaCrop model for irrigated cotton under deficit irrigation in semi-arid tropics of Maharashtra’’ was carried out at Department of Irrigation and Drainage Engineering, CAET, Parbhani. The experiment was conducted in such a way that AquaCrop model was calibrated for the year 2009-2010 and it was validated for the year 2010-2011. Part of the obtained field data i.e. data for full irrigation treatment (100% ETc) for the year 2009-2010 was used for calibration of the model, while the data of 2010-2011 was used to validate the model. AquaCrop version 6.1 was used in the study. There was a close match between observed and simulated canopy cover. It was supported by high value of R2NS (0.97). Another statistical parameter CRM having value of -0.045, indicates that the model overestimates the canopy cover. The high value of Nash Sutcliffe coefficient (R2NS) value as 0.81 shows close match between observed and simulated yield. The CRM (Coefficient of Residual Mass) between observed and simulated yield was also as low as -0.060, indicating that the model overestimated the yield. Considering overall acceptability of validation results, it was concluded that the model performs well with relatively high validity. |
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ISSN: | 2319-7692 2319-7706 |
DOI: | 10.20546/ijcmas.2022.1101.015 |