scholarly journals Integrating Sentinel-2 Imagery with AquaCrop for Dynamic Assessment of Tomato Water Requirements in Southern Italy

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 404 ◽  
Author(s):  
Anna Dalla Marta ◽  
Giovanni Battista Chirico ◽  
Salvatore Falanga Bolognesi ◽  
Marco Mancini ◽  
Guido D’Urso ◽  
...  

A research study was conducted in an open field tomato crop in order to: (i) Evaluate the capability of Sentinel-2 imagery to assess tomato canopy growth and its crop water requirements; and (ii) explore the possibility to predict crop water requirements by assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model. The pilot area was in Campania, a region in the south west of Italy, characterized by a typical Mediterranean climate, where field campaigns were conducted in seasons 2017 and 2018 on processing tomato. Crop water use and irrigation requirement were estimated by means of three different methods: (i) The AquaCrop model; (ii) an irrigation advisory service based on Sentinel-2 imagery known as IRRISAT and (iii) assimilating the canopy cover estimated by Sentinel-2 imagery into AquaCrop model Sentinel-2 imagery proved to be effective for monitoring canopy growth and for predicting irrigation water requirements during mid-season stage of the crop, when the canopy is fully developed. Conversely, the integration of the Sentinel-2 imagery with a crop growth model can contribute to improve the irrigation water requirement predictions in the early and development stage of the crop, when the soil evaporation is not negligible with respect to the total evapotranspiration.

2013 ◽  
Vol 340 ◽  
pp. 961-965
Author(s):  
Xin Hua Wang ◽  
Mei Hua Guo ◽  
Hui Mei Liu

According to Kunming 1980-2010 monthly weather data and CROPWAT software and the corresponding crop data, crop water requirements and irrigation water use are calculated. By frequency analysis, irrigation water requirement was get for different guaranteed rate. The results show that: corn, potatoes, tobacco, and soybeans average crop water requirements were 390.7mm, 447.9mm, 361.8mm and 328.4mm, crop water dispersion coefficient is small, period effective rainfall during crop growth in most of the year can meet the crop water requirements, so irrigation water demand is small. While the multi-year average crop water requirements were 400.8mm, 353.5mm, 394.3mm for small spring crops of wheat, beans, rape. Because the effective rainfall for these crops during growth period is relative less, crop irrigation water requirements for small spring crop is much. Vegetables and flowers are plant around the year, so the crop water and irrigation water requirements are the largest.


2020 ◽  
Author(s):  
maria calera picazo ◽  
Carmen Plaza ◽  
andres cuesta ◽  
vicente bodas ◽  
ramon molina ◽  
...  

<p>In Mediterranean areas, where water scarcity is the main limiting factor, applying good practices in the use of water for irrigation is crucial in order to maximize benefits for farmers and protect the resource. Furthermore, energy costs derived from water pumping from groundwater is one of the most important expenses for farmers in our study area, the South-East of Spain. Variable Rate Irrigation is a promising technique to apply the required water, but VRI faces the challenge to know accurately the crop water requirement distribution in space and time.</p><p>The objective of this work is twofold: Firstly, to demonstrate through a practical case the optimization of the irrigation water in an operativity level managing the variability of the plot using time series of free satellite images currently in orbit. Secondly, to put into practice the technology (SicoP system) developed by ACOEMAN that allows the pivot to apply variable rate at medium cost for farmers.</p><p>The case study was carried out in a commercial wheat plot of 60ha, irrigated by a central pivot endowed with the SicoP technology, during the campaign of 2018-2019.  The SicoP pivot technology allows to implement a variable angular speed for each sector. The pivot circle was divided into 36 sectors of 10 degrees each. Every Thursday during the growing cycle the crop water requirements were estimated per sector by means of remote sensing and meteorological data by the decision support system developed by AgriSat Iberia as consultant company. Thus, the system applied the irrigation water requirement per sector, calculated through a simplified soil water balance.</p><p>The estimation of the actual crop water requirements spatially distributed at 30x30 meter (3x3 pixel) resolution has been based on NDVI-Kc forecasting methodology. The high temporal and spatial resolution provided by free images from satellites Sentinel 2A and Sentinel 2B combined with Landsat 8 images allows the implementation of a remote sensing-based operational approach for this variable rate decision support system.</p><p>This paper includes a comparative analysis of the differences between the water volume applied by homogeneous rate, 1 per plot and week, and the variable rate irrigation, 36 rates per plot and week, using the same EO-based methodology. A yield map was obtained by using a yield-monitoring device implemented into the combine harvester.</p><p>First promising results regarding the optimization of the use of water have been demonstrated going from 1 irrigation decision in 60ha per week, to 36 irrigation decision per week, one per 1.6ha sector. Modest savings in water volumes at the end of the growing cycle have been observed. This map shows no additional increase of yield spatial variability due to the use of VIR.  Some problems were encountered when the climate conditions were not appropriate for irrigation, mainly high wind speed. The system has reached a high operativity level ready for adoption by farmers. </p>


2021 ◽  
Vol 255 ◽  
pp. 107005
Author(s):  
Sara Masia ◽  
Antonio Trabucco ◽  
Donatella Spano ◽  
Richard L. Snyder ◽  
Janez Sušnik ◽  
...  

2013 ◽  
Vol 110 ◽  
pp. 88-98 ◽  
Author(s):  
Christopher Conrad ◽  
Maren Rahmann ◽  
Miriam Machwitz ◽  
Galina Stulina ◽  
Heiko Paeth ◽  
...  

2018 ◽  
Vol 137 (3-4) ◽  
pp. 2203-2215 ◽  
Author(s):  
Xiaoyan Song ◽  
Songbai Song ◽  
Zhi Li ◽  
Wenbin Liu ◽  
Jiuyi Li ◽  
...  

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