Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Site and Weather Conditions
2.2. Water Needs of Fruit Trees Calculated by Press
2.3. Water Needs of Fruit Trees According to the Method of Rzekanowski and Grabarczyk
2.4. Water Needs of Fruit Trees Calculated Using the Treder Method
- Estimation of the reference evapotranspiration (ETo) that were made according to the formula Equation (3):
- Estimation of the evapotranspiration of a specific species (ETr) that were made according to the formula Equation (5):
- Estimation of the evapotranspiration of a specific planting, taking into account tree sizes (ETr*) that were made according to the formula Equation (6):
3. Results and Discussion
3.1. Water Needs of Fruit Trees Calculated by Press Method
3.2. Water Needs of Fruit Trees According to the Method of Rzekanowski and Grabarczyk
3.3. Water Needs of Fruit Trees Calculated Using the Treders Method
3.4. Comparison of the Methods Used to Calculate the Water Needs of Fruit Trees
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Period | Plant | Water Needs Range (mm) |
---|---|---|
1 April to 30 September | apple | 380–490 |
1 April to 30 September | pear | 325–400 |
1 April to 31 August | cherry | 280–345 |
1 April to 30 September | plum | 400–510 |
Month | Empirically Determined Plant Coefficient α | Plant kc Coefficient | |||
---|---|---|---|---|---|
Apple | Pear | Cherry | Plum | ||
April | 0.28 | 0.50 | 0.45 | 0.45 | 0.50 |
May | 0.21 | 0.75 | 0.75 | 0.75 | 0.75 |
June | 0.19 | 1.10 | 1.05 | 1.00 | 1.10 |
July | 0.18 | 1.20 | 1.15 | 1.10 | 1.20 |
August | 0.17 | 1.20 | 1.15 | 1.10 | 1.20 |
September | 0.16 | 1.15 | 1.10 | 0.90 | 1.15 |
Months | Mean (mm) | Standard Deviation (mm) | Variation Coefficient (%) |
---|---|---|---|
Apple | |||
April | 68 | 7.8 | 11.5 |
May | 78 | 8.1 | 10.3 |
June | 88 | 8.2 | 9.3 |
July | 102 | 11.0 | 10.8 |
August | 94 | 13.2 | 14.1 |
September | 58 | 4.6 | 8.0 |
April–September | 488 | 32.1 | 6.6 |
Pear | |||
April | 55 | 4.6 | 8.4 |
May | 69 | 7.8 | 11.3 |
June | 76 | 4.4 | 5.9 |
July | 81 | 11.1 | 13.7 |
August | 68 | 6.4 | 9.4 |
September | 53 | 5.1 | 9.6 |
April–September | 398 | 26.5 | 6.6 |
Cherry | |||
April | 49 | 5.3 | 10.7 |
May | 60 | 8.0 | 13.4 |
June | 76 | 4.8 | 6.3 |
July | 90 | 10.6 | 11.8 |
August | 73 | 5.8 | 7.9 |
April–August | 347 | 22.1 | 6.3 |
Plum | |||
April | 68 | 8.1 | 11.9 |
May | 84 | 8.6 | 10.3 |
June | 93 | 8.6 | 9.3 |
July | 100 | 10.9 | 10.9 |
August | 103 | 8.3 | 8.0 |
September | 57 | 5.7 | 10.1 |
April–September | 506 | 31.2 | 6.2 |
Months | Mean (mm) | Standard Deviation (mm) | Variation Coefficient (%) |
---|---|---|---|
Apple | |||
April | 31 | 5.6 | 18.2 |
May | 70 | 13.2 | 18.8 |
June | 120 | 19.7 | 16.4 |
July | 151 | 31.8 | 21.0 |
August | 144 | 23.8 | 16.5 |
September | 87 | 18.8 | 21.6 |
April–September | 603 | 65.4 | 10.8 |
Pear | |||
April | 27 | 4.8 | 17.7 |
May | 71 | 13.4 | 19.0 |
June | 115 | 18.3 | 15.9 |
July | 146 | 31.0 | 21.3 |
August | 139 | 25.6 | 18.4 |
September | 83 | 17.7 | 21.3 |
April–September | 580 | 66.4 | 11.5 |
Cherry | |||
April | 27 | 5.0 | 18.1 |
May | 71 | 13.8 | 19.4 |
June | 110 | 17.7 | 16.1 |
July | 139 | 29.1 | 21.0 |
August | 134 | 25.6 | 19.2 |
September | 68 | 14.7 | 21.6 |
April–September | 548 | 61.9 | 11.3 |
Plum | |||
April | 28 | 5.4 | 19.4 |
May | 70 | 13.4 | 19.0 |
June | 120 | 19.5 | 16.3 |
July | 152 | 32.4 | 21.3 |
August | 138 | 22.9 | 16.6 |
September | 87 | 18.7 | 21.5 |
April–September | 595 | 66.7 | 11.2 |
Months | Mean (mm) | Standard Deviation (mm) | Variation Coefficient (%) |
---|---|---|---|
Apple | |||
April | 39 | 6.1 | 17.1 |
May | 71 | 8.4 | 11.8 |
June | 111 | 10.9 | 10.2 |
July | 133 | 13.8 | 10.8 |
August | 123 | 10.4 | 8.8 |
September | 79 | 9.4 | 12.3 |
April–September | 557 | 39.0 | 7.0 |
Pear | |||
April | 36 | 6.1 | 17.1 |
May | 71 | 8.4 | 11.8 |
June | 107 | 10.9 | 10.2 |
July | 128 | 13.8 | 10.8 |
August | 119 | 10.4 | 8.8 |
September | 76 | 9.4 | 12.3 |
April–September | 534 | 37.3 | 7.0 |
Cherry | |||
April | 36 | 6.1 | 17.1 |
May | 71 | 8.4 | 11.8 |
June | 102 | 10.4 | 10.2 |
July | 123 | 13.2 | 10.8 |
August | 113 | 10.0 | 8.8 |
September | 62 | 7.7 | 12.3 |
April–September | 505 | 35.1 | 6.9 |
Plum | |||
April | 36 | 6.1 | 17.1 |
May | 71 | 8.4 | 11.8 |
June | 112 | 11.5 | 10.2 |
July | 134 | 14.4 | 10.8 |
August | 119 | 10.4 | 8.8 |
September | 79 | 9.8 | 12.3 |
April–September | 550 | 38.3 | 7.0 |
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Stachowski, P.; Jagosz, B.; Rolbiecki, S.; Rolbiecki, R. Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas. Atmosphere 2021, 12, 550. https://doi.org/10.3390/atmos12050550
Stachowski P, Jagosz B, Rolbiecki S, Rolbiecki R. Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas. Atmosphere. 2021; 12(5):550. https://doi.org/10.3390/atmos12050550
Chicago/Turabian StyleStachowski, Piotr, Barbara Jagosz, Stanisław Rolbiecki, and Roman Rolbiecki. 2021. "Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas" Atmosphere 12, no. 5: 550. https://doi.org/10.3390/atmos12050550
APA StyleStachowski, P., Jagosz, B., Rolbiecki, S., & Rolbiecki, R. (2021). Predictive Capacity of Rainfall Data to Estimate the Water Needs of Fruit Plants in Water Deficit Areas. Atmosphere, 12(5), 550. https://doi.org/10.3390/atmos12050550