Crop water requirements estimation at irrigation district scale from remote sensing: a comparison between MODIS ET product and the analytical approach

Author(s):  
Eufemia Tarantino ◽  
Umberto Fratino ◽  
Giuseppe Peschechera
Author(s):  
Alfonso Calera ◽  
Isidro Campos ◽  
Anna Osann ◽  
Guido D´Urso ◽  
Massimo Menenti

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e. professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies. This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.


2004 ◽  
Author(s):  
Salvatore Barbagallo ◽  
Simona Consoli ◽  
Guido D'Urso ◽  
Rosaria Giorgio Gaggia ◽  
Attilio Toscano

2020 ◽  
Author(s):  
Peejush Pani ◽  
Li Jia ◽  
Massimo Menenti ◽  
Guangcheng Hu ◽  
Chaolei Zheng ◽  
...  

<p>This paper proposes a new approach to estimate and map separately gross and net water requirements and actual crop water use by applying multi–spectral satellite data. Remote sensing information is witnessing a boom in the availability of high-resolution multi-spectral data with frequent revisit time, paving the path for improved assessment of precision agriculture and minimizing the wastage of irrigation water. In this study, we have tried to integrate multi-source remote sensing information with farmer’s irrigation practices to evaluate the water use and losses at farm-scale for center pivot irrigation systems (CPIS) in Inner Mongolia autonomous region of China. The region is practicing modernized irrigation methods to efficiently use groundwater. Crop gross water requirements are estimated by evaluating separately the net crop water requirements (CWR) and the water losses inherently from a CPIS, i.e. droplet evaporation to the air directly before they fell on the crop canopy during irrigation application (<em>E<sub>A</sub></em>) and canopy interception loss (<em>I<sub>c</sub></em>). The crop water requirement is estimated according to the FAO-56 method based on the Penman-Monteith equation. Actual crop water use is evaluated by estimating separately soil evaporation (<em>E<sub>S</sub></em>) and plant transpiration (<em>E<sub>T</sub></em>) by applying the ETMonitor model. High-resolution multi–spectral data acquired by Sentinel-2 MSI and Landsat-8 OLI together with meteorological forcing data and soil moisture retrievals were used to construct daily estimates of crop water requirements and actual use. Finally, the performance of irrigation scenarios was assessed by applying a performance indicator (IP), as the ratio between gross water requirement and the volume of irrigation applied, where values closer to unity referring to optimum utilization and minimum loss. Measurements of actual evapotranspiration by eddy covariance system were applied to evaluate the actual evapotranspiration estimates by the ETMonitor. Field experiments were also carried out to validate the estimated irrigation losses, i.e. <em>E<sub>A</sub></em> and <em>I<sub>C</sub></em>. The estimates were in good agreement with the ground observations, i.e. an R<sup>2</sup> of 0.64 – 0.80 for actual water use and 0.66 – 0.97 for water losses. The RMSE was 0.6 – 1.2 mm/day for actual daily water use and 0.64 – 1.55 mm water losses for each irrigation, respectively. The IP was estimated as 1.6 for the performance of CPIS as per the above definition. Overall, the study shows that CPIS has under-performed in minimizing water losses in the study area with losses of 25.4% per season of the total volume of water applied for wheat, and 23.7% per season for potato. This implies that the amount of water applied was largely insufficient to meet the gross water requirements, i.e. including losses.</p>


2014 ◽  
Vol 03 (02) ◽  
pp. 57-65 ◽  
Author(s):  
Mohammed A. El-Shirbeny ◽  
Abd-Elraouf M. Ali ◽  
Nasser H. Saleh

2021 ◽  
Author(s):  
Jaouad El Hachimi ◽  
Abderrazak El Harti ◽  
Amine Jellouli

<p>In arid and semi-arid regions, agriculture is an important element of the national economy, but this sector is a large consumer of water. In a context of high pressure on water resources (climate change, population growth, desertification, etc.), an appropriate management is required. The development of remote sensing tools: temporal, spatial and spectral resolution offers a better opportunity for hydro-agricultural management. The main objective of this study is to combine climate data with that of optical remote sensing in order to estimate crop water requirements in the irrigated perimeter of Tadla. In semi-arid regions, such as Tadla Plain, a large quantity of water is lost by evapotranspiration (ET). The objective of this study is to use a scientific approach based on the modulation of evaporative demand for the estimation of crop water requirements. This approach is based on the FAO-56 method using image data from the Sentinel-2A and Landsat-8 satellites, and climate data: surface temperature, air humidity, wind speed, global solar radiation and precipitation. It also allowed the spatialization of crop water requirements on a large area of irrigated crops during the 2016–2017 agricultural season. Maps of water requirements have been developed. They show the variability over time of crop development and their estimated water requirements. The results obtained constitute an important indicator of how water should be distributed over the area in order to improve irrigation efficiency and protection of water resources.</p>


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