Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model
Remote sensing data of canopy cover and leaf area index are used together with the AquaCrop model to optimize irrigation water use efficiency for tomato and maize fields across Italy, which differ in climate, soil types and irrigation technique. An optimization irrigation strategy, “SIM strategy”, i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Hydrology |
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| Online Access: | https://www.mdpi.com/2306-5338/8/1/39 |
| _version_ | 1797415920855941120 |
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| author | Chiara Corbari Imen Ben Charfi Marco Mancini |
| author_facet | Chiara Corbari Imen Ben Charfi Marco Mancini |
| author_sort | Chiara Corbari |
| collection | DOAJ |
| description | Remote sensing data of canopy cover and leaf area index are used together with the AquaCrop model to optimize irrigation water use efficiency for tomato and maize fields across Italy, which differ in climate, soil types and irrigation technique. An optimization irrigation strategy, “SIM strategy”, is developed based on crop stress thresholds and then applied to all the analyzed fields in different crop seasons, evaluating the effect not only on irrigation volume and number of irrigations but also on crop yield and canopy cover, and on the drainage flux which represents the main water loss. Irrigation volume reduction is found to be between 200 and 1000 mm, mainly depending on the different soil types within the climate, irrigation technique and crop type. This is directly related to the drainage flux reduction which is of a similar entity. The SIM strategy efficiency has then been quantified by different indicators, such as the irrigation water use efficiency (IWUE) which is higher than with the observed irrigations (around 35% for tomato fields in Southern Italy, between 30 and 80% for maize in Northern Italy), and the percolation deficit and irrigation efficiency. The AquaCrop model has been previously calibrated against canopy cover and leaf area index (LAI) data, producing errors between 0.7 and 5%, while absolute mean errors (MAE) between 0.015 and 0.04 are obtained for soil moisture (SM). The validation of the AquaCrop model has been performed against evapotranspiration (ET) ground-measured data and crop yields producing MAE values ranging from 0.3 to 0.9 mm/day, and 0.9 ton/ha for maize and 10 ton/ha for tomatoes, respectively. |
| first_indexed | 2024-03-09T05:56:25Z |
| format | Article |
| id | doaj.art-92dafadd4bdc4d85a055659eed303257 |
| institution | Directory Open Access Journal |
| issn | 2306-5338 |
| language | English |
| last_indexed | 2024-03-09T05:56:25Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Hydrology |
| spelling | doaj.art-92dafadd4bdc4d85a055659eed3032572023-12-03T12:13:20ZengMDPI AGHydrology2306-53382021-03-01813910.3390/hydrology8010039Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop ModelChiara Corbari0Imen Ben Charfi1Marco Mancini2Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, ItalyDepartment of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, ItalyDepartment of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, ItalyRemote sensing data of canopy cover and leaf area index are used together with the AquaCrop model to optimize irrigation water use efficiency for tomato and maize fields across Italy, which differ in climate, soil types and irrigation technique. An optimization irrigation strategy, “SIM strategy”, is developed based on crop stress thresholds and then applied to all the analyzed fields in different crop seasons, evaluating the effect not only on irrigation volume and number of irrigations but also on crop yield and canopy cover, and on the drainage flux which represents the main water loss. Irrigation volume reduction is found to be between 200 and 1000 mm, mainly depending on the different soil types within the climate, irrigation technique and crop type. This is directly related to the drainage flux reduction which is of a similar entity. The SIM strategy efficiency has then been quantified by different indicators, such as the irrigation water use efficiency (IWUE) which is higher than with the observed irrigations (around 35% for tomato fields in Southern Italy, between 30 and 80% for maize in Northern Italy), and the percolation deficit and irrigation efficiency. The AquaCrop model has been previously calibrated against canopy cover and leaf area index (LAI) data, producing errors between 0.7 and 5%, while absolute mean errors (MAE) between 0.015 and 0.04 are obtained for soil moisture (SM). The validation of the AquaCrop model has been performed against evapotranspiration (ET) ground-measured data and crop yields producing MAE values ranging from 0.3 to 0.9 mm/day, and 0.9 ton/ha for maize and 10 ton/ha for tomatoes, respectively.https://www.mdpi.com/2306-5338/8/1/39irrigation water use efficiencyirrigation strategycrop modelremote sensing |
| spellingShingle | Chiara Corbari Imen Ben Charfi Marco Mancini Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model Hydrology irrigation water use efficiency irrigation strategy crop model remote sensing |
| title | Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model |
| title_full | Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model |
| title_fullStr | Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model |
| title_full_unstemmed | Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model |
| title_short | Optimizing Irrigation Water Use Efficiency for Tomato and Maize Fields across Italy Combining Remote Sensing Data and the AquaCrop Model |
| title_sort | optimizing irrigation water use efficiency for tomato and maize fields across italy combining remote sensing data and the aquacrop model |
| topic | irrigation water use efficiency irrigation strategy crop model remote sensing |
| url | https://www.mdpi.com/2306-5338/8/1/39 |
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