Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain
Agricultural droughts cause a great reduction in winter wheat productivity; therefore, timely and precise irrigation recommendations are needed to alleviate the impact. This study aims to assess drought stress in winter wheat with the use of an unmanned aerial system (UAS) with multispectral and the...
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MDPI AG
2023-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/4/1903 |
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| author | Vita Antoniuk Xiying Zhang Mathias Neumann Andersen Kirsten Kørup Kiril Manevski |
| author_facet | Vita Antoniuk Xiying Zhang Mathias Neumann Andersen Kirsten Kørup Kiril Manevski |
| author_sort | Vita Antoniuk |
| collection | DOAJ |
| description | Agricultural droughts cause a great reduction in winter wheat productivity; therefore, timely and precise irrigation recommendations are needed to alleviate the impact. This study aims to assess drought stress in winter wheat with the use of an unmanned aerial system (UAS) with multispectral and thermal sensors. High-resolution Water Deficit Index (WDI) maps were derived to assess crop drought stress and evaluate winter wheat actual evapotranspiration rate (ET<sub>a</sub>). However, the estimation of WDI needs to be improved by using more appropriate vegetation indices as a proximate of the fraction of vegetation cover. The experiments involved six irrigation levels of winter wheat in the harvest years 2019 and 2020 at Luancheng, North China Plain on seasonal and diurnal timescales. Additionally, WDI derived from several vegetation indices (VIs) were compared: near-infrared-, red edge-, and RGB-based. The WDIs derived from different VIs were highly correlated with each other and had similar performances. The WDI had a consistently high correlation to stomatal conductance during the whole season (R<sup>2</sup> between 0.63–0.99) and the correlation was the highest in the middle of the growing season. On the contrary, the correlation between WDI and leaf water potential increased as the season progressed with R<sup>2</sup> up to 0.99. Additionally, WDI and ET<sub>a</sub> had a strong connection to soil water status with R<sup>2</sup> up to 0.93 to the fraction of transpirable soil water and 0.94 to the soil water change at 2 m depth at the hourly rate. The results indicated that WDI derived from multispectral and thermal sensors was a reliable factor in assessing the water status of the crop for irrigation scheduling. |
| first_indexed | 2024-03-11T08:10:40Z |
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| id | doaj.art-41d03c3dc7184579b8d8ae23723035aa |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T08:10:40Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-41d03c3dc7184579b8d8ae23723035aa2023-11-16T23:07:47ZengMDPI AGSensors1424-82202023-02-01234190310.3390/s23041903Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China PlainVita Antoniuk0Xiying Zhang1Mathias Neumann Andersen2Kirsten Kørup3Kiril Manevski4Department of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, DenmarkCenter for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, ChinaDepartment of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, DenmarkDepartment of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, DenmarkDepartment of Agroecology, Aarhus University, Blichers Allé 20, 8830 Tjele, DenmarkAgricultural droughts cause a great reduction in winter wheat productivity; therefore, timely and precise irrigation recommendations are needed to alleviate the impact. This study aims to assess drought stress in winter wheat with the use of an unmanned aerial system (UAS) with multispectral and thermal sensors. High-resolution Water Deficit Index (WDI) maps were derived to assess crop drought stress and evaluate winter wheat actual evapotranspiration rate (ET<sub>a</sub>). However, the estimation of WDI needs to be improved by using more appropriate vegetation indices as a proximate of the fraction of vegetation cover. The experiments involved six irrigation levels of winter wheat in the harvest years 2019 and 2020 at Luancheng, North China Plain on seasonal and diurnal timescales. Additionally, WDI derived from several vegetation indices (VIs) were compared: near-infrared-, red edge-, and RGB-based. The WDIs derived from different VIs were highly correlated with each other and had similar performances. The WDI had a consistently high correlation to stomatal conductance during the whole season (R<sup>2</sup> between 0.63–0.99) and the correlation was the highest in the middle of the growing season. On the contrary, the correlation between WDI and leaf water potential increased as the season progressed with R<sup>2</sup> up to 0.99. Additionally, WDI and ET<sub>a</sub> had a strong connection to soil water status with R<sup>2</sup> up to 0.93 to the fraction of transpirable soil water and 0.94 to the soil water change at 2 m depth at the hourly rate. The results indicated that WDI derived from multispectral and thermal sensors was a reliable factor in assessing the water status of the crop for irrigation scheduling.https://www.mdpi.com/1424-8220/23/4/1903water deficit indexevapotranspirationUAVfraction of transpirable soil waterirrigation requirements |
| spellingShingle | Vita Antoniuk Xiying Zhang Mathias Neumann Andersen Kirsten Kørup Kiril Manevski Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain Sensors water deficit index evapotranspiration UAV fraction of transpirable soil water irrigation requirements |
| title | Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain |
| title_full | Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain |
| title_fullStr | Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain |
| title_full_unstemmed | Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain |
| title_short | Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain |
| title_sort | spatiotemporal winter wheat water status assessment improvement using a water deficit index derived from an unmanned aerial system in the north china plain |
| topic | water deficit index evapotranspiration UAV fraction of transpirable soil water irrigation requirements |
| url | https://www.mdpi.com/1424-8220/23/4/1903 |
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