Automatic extraction of canopy and artificial reference temperatures for determination of crop water stress indices by using thermal imaging technique and a fuzzy-based image-processing algorithm

Author(s):  
Pedram Shoa ◽  
Abbas Hemmat ◽  
Rassoul Amirfattahi ◽  
Mahdi Gheysari
2020 ◽  
Author(s):  
Angela Morales Santos ◽  
Reinhard Nolz

<p>Sustainable irrigation water management is expected to accurately meet crop water requirements in order to avoid stress and, consequently, yield reduction, and at the same time avoid losses of water and nutrients due to deep percolation and leaching. Sensors to monitor soil water status and plant water status (in terms of canopy temperature) can help planning irrigation with respect to time and amounts accordingly. The presented study aimed at quantifying and comparing crop water stress of soybeans irrigated by means of different irrigation systems under subhumid conditions.</p><p>The study site was located in Obersiebenbrunn, Lower Austria, about 30 km east of Vienna. The region is characterized by a mean temperature of 10.5°C with increasing trend due to climate change and mean annual precipitation of 550 mm. The investigations covered the vegetation period of soybean in 2018, from planting in April to harvest in September. Measurement data included precipitation, air temperature, relative humidity and wind velocity. The experimental field of 120x120 m<sup>2</sup> has been divided into four sub-areas: a plot of 14x120 m<sup>2</sup> with drip irrigation (DI), 14x120 m<sup>2</sup> without irrigation (NI), 36x120 m<sup>2</sup> with sprinkler irrigation (SI), and 56x120 m<sup>2</sup> irrigated with a hose reel boom with nozzles (BI). A total of 128, 187 and 114 mm of water were applied in three irrigation events in the plots DI, SI and BI, respectively. Soil water content was monitored in 10 cm depth (HydraProbe, Stevens Water) and matric potential was monitored in 20, 40 and 60 cm depth (Watermark, Irrometer). Canopy temperature was measured every 15 minutes using infrared thermometers (IRT; SI-411, Apogee Instruments). The IRTs were installed with an inclination of 45° at 1.8 m height above ground. Canopy temperature-based water stress indices for irrigation scheduling have been successfully applied in arid environments, but their use is limited in humid areas due to low vapor pressure deficit (VPD). To quantify stress in our study, the Crop Water Stress Index (CWSI) was calculated for each plot and compared to the index resulting from the Degrees Above Canopy Threshold (DACT) method. Unlike the CWSI, the DACT method does not consider VPD to provide a stress index nor requires clear sky conditions. The purpose of the comparison was to revise an alternative method to the CWSI that can be applied in a humid environment.</p><p>CWSI behaved similar for the four sub-areas. As expected, CWSI ≥ 1 during dry periods (representing severe stress) and it decreased considerably after precipitation or irrigation (representing no stress). The plot with overall lower stress was BI, producing the highest yield of the four plots. Results show that DACT may be a more suitable index since all it requires is canopy temperature values and has strong relationship with soil water measurements. Nevertheless, attention must be paid when defining canopy temperature thresholds. Further investigations include the development and test of a decision support system for irrigation scheduling combining both, plant-based and soil water status indicators for water use efficiency analysis.</p>


Due to the overuse of available water resources, it has become very important to define appropriate strategies for planning and management of watershed. The objective for the study is determination of reference evapotranspiration using CROPWAT 8.0 software in GIS environment, which includes a simple water balance model and one of the main component part of the hydrologic cycle, which allows the simulation of crop water stress conditions and estimation of yield reductions based on well-established methodologies. This paper focused on the estimation of reference evapotranspiration using Cowpat 8.0 .


2020 ◽  
Author(s):  
Massimo Tolomio ◽  
Raffaele Casa

<p>Irrigation management decision support systems based on remote sensing and hydrological models need to find a balance between simplicity and accuracy in the definition of crop water stress thresholds when irrigation should be triggered. Among the most widely used crop models, which synthesize current mechanistic knowledge of crop water stress processes, there is a wide range of complexity that is worth exploring in order to improve the formalisms of current hydrological models.</p><p>In the present work, some of the most widely used crop models (chosen among those freely available and well documented) were examined in their description of crop water stress processes and irrigation thresholds definition. They are: APSIM, AQUACROP, CROPSYST, CROPWAT, DAISY, DSSAT, EPIC, STICS and WOFOST. Model manuals and scientific papers were reviewed to identify differences and similarities in the water stress functions related to crop growth.</p><p>A strict categorization of the model features is inappropriate, since the functions utilized are always at least slightly different and the models may focus on different features of the agroecosystem. Nevertheless, major similarities and differences among the models were found:</p><ol><li><em>The function of biomass growth.</em> AQUACROP and CROPWAT (both developed by FAO) are water-driven models (growth is directly related to transpiration). DAISY, DSSAT, EPIC, STICS and WOFOST are radiation-driven models (growth is related to radiation). APSIM and CROPSYST calculate both water- and radiation-driven biomass and keep the most limiting of these.</li> <li><em>The main variable used to calculate water stress indices.</em> AQUACROP, CROPWAT and WOFOST use stress coefficients that depend directly on the depletion status of plant available water (difference between field capacity and wilting point). CROPSYST, DAISY, DSSAT and EPIC calculate water stress on the ratio between actual transpiration (limited by roots and soil characteristics) and potential transpiration (weather-dependent). APSIM uses both approaches, depending on the specific crop and growth process targeted. STICS expresses the transpiration rate as a function of the available water content (in m<sup>3</sup>/m<sup>3</sup> above wilting point), and from this it calculates water stress indices.</li> <li><em>The influence of water stress indices on vegetative growth.</em> Water stress in CROPWAT, DAISY and WOFOST affects biomass growth, whereas in APSIM, AQUACROP, CROPSYST, DSSAT, EPIC and STICS multiple indices affect biomass growth and leaf expansion in different ways. The rationale behind the last approach is that as soil water uptake becomes more difficult, water stress slows down cells division and expansion (reducing the leaf expansion rate) before photosynthesis is reduced by stomatal closure.</li> </ol><p>The models were then calibrated for the maize and tomato crops using field and remote sensing data on crop yield, soil moisture, evapotranspiration (ET) and leaf area index (LAI), for two locations, respectively in Northern and Southern Italy (Calcinato and Capitanata). Simulations were then carried out and compared in terms of the optimal irrigation amounts calculated by the different models and predicted yields.</p>


2017 ◽  
Vol 187 ◽  
pp. 210-221 ◽  
Author(s):  
Gregorio Egea ◽  
Carmen M. Padilla-Díaz ◽  
Jorge Martinez-Guanter ◽  
José E. Fernández ◽  
Manuel Pérez-Ruiz

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