Required Interval of Weather Data for Proper Irrigation Scheduling | ||||
| Egyptian Journal of Agronomy | ||||
| Article 11, Volume 40, The15th International Conference on Crop Science, November 2018, Page 105-114 PDF (810.28 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/agro.2019.5674.1127 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Samiha Ouda  ; Ahmed Taha
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| Water Requirements and Field Irrigation Research Department, Soils, Water and Environment Research Institute, Agricultural Research Center, Giza, Egypt | ||||
| Abstract | ||||
| CLIMATE variability is very common in Egypt recently, therefore studying its effects on irrigation scheduling for crops is important. The objective of this study was to define a number of years of former weather data prerequisite to estimate evapotranspiration (ETo) to schedule irrigation in three sites in Egypt (El-Gharbia, Beni Swief and Sohag). Daily values of weather data were collected for 10 years (2008-2017). Monthly ETo values were calculated by The BISm model. Descriptive statistics (mean, range, R2, CV and SD) were done to determine the temporal and spatial variability between monthly values of weather elements, as well as ETo. Furthermore, assessment of ETo values trend (decreasing or increasing) was done. The results showed that there were increasing temporal and spatial trends in the 10-year weather data, as well as ETo values in the 3 sites. However, it was more pronounced from 2015 to 2017. Furthermore, the results indicated that the range, CV% and SD were lower in the 3-year interval (2015-2017), compared to 10-year interval for all sites. There were stronger relationships between weather elements and ETo values in the 3-year interval, compared to 10-year interval, as represented by R2 values. Thus, it can be concluded that the recent 3-year interval is the most suitable interval for ETo calculation for proper irrigation scheduling to improve water management on field level in Egypt. | ||||
| Keywords | ||||
| Temporal variability; spatial variability; BISm model; 10-year weather data; 3-year weather data | ||||
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