A variable rate irrigation decision support system for corn in the US eastern coastal plain

Author(s):  
K. Stone ◽  
P. Bauer ◽  
S. O’Shaughnessy ◽  
M. Andrade ◽  
S. Evett
2020 ◽  
Vol 63 (5) ◽  
pp. 1295-1303
Author(s):  
Kenneth C. Stone ◽  
Phil J. Bauer ◽  
Susan O’Shaughnessy ◽  
Alejandro Andrade-Rodriguez ◽  
Steven Evett

HighlightsA decision support system using the USDA-ARS Irrigation Scheduling and Supervisory Control and Data Acquisition (ISSCADA) system was evaluated for spatially managing corn irrigation in the U.S. Eastern Coastal Plain.The ISSCADA system was compared to traditional scheduling methods based on measured soil water potentials.The ISSCADA system with feedback on allowable soil water depletion shows potential as a tool for growers for managing variable-rate irrigation systems.Abstract. Variable-rate irrigation (VRI) systems are capable of applying different water depths both in the direction of travel and along the length of the irrigation system. VRI systems maybe useful for improving crop water management and efficiency. Although VRI technology is available and has high grower interest, it has had limited adoption. To address this, researchers have developed a decision support system that uses remote sensing of plant, soil, and microclimate to schedule VRI irrigations. In this research, we evaluated the use of the USDA-ARS Irrigation Scheduling and Supervisory Control and Data Acquisition (ISSCADA) system for spatially managing corn irrigation in the U.S. Eastern Coastal Plain. The ISSCADA system consists of center pivot mounted infrared thermometers (IRT) to measure crop canopy temperatures and in situ soil water sensors. An integrated crop water stress index (iCWSI) was calculated from the canopy temperatures. The ISSCADA system analyzes the iCWSI and soil water measurements to provide an irrigation recommendation. The ISSCADA system was evaluated using (1) iCWSI values and (2) a hybrid ISSCADA system that incorporated both iCWSI values and soil water depletion criteria. These ISSCADA treatments were compared to traditional irrigation management using measured soil water potentials. The ISSCADA system was evaluated for four years. In 2016 and 2017, corn yields and water use efficiency were not significantly different between the irrigation treatments due to adequate rainfall during the growing season. In 2018 and 2019, mid-season drought conditions and sporadic rainfall patterns required frequent irrigations. In both years, the irrigation treatment corn yields were not significantly different from each other but were greater than the rainfed yields. In 2018, the irrigation treatments produced corn yields of 10.7, 10.4, and 10.1 Mg ha-1 for the hybrid, ISSCADA, and SWP treatments, respectively. Over the four-year study, the water use efficiencies of the irrigation treatments were not significantly different from each other or the rainfed treatment and ranged from 16.6 to 22.7 kg ha-1 mm-1. In the two years that the hybrid ISSCADA system was used for managing irrigations, it produced higher corn yields and required less irrigation than the standard ISSCADA treatments. Results from this experiment will help to evaluate and refine the ISSCADA system to provide a tool for growers to use in managing spatial irrigation with VRI systems. Keywords: Crop water stress, Decision support system, Variable rate irrigation.


Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2880 ◽  
Author(s):  
Xiang Shi ◽  
Wenting Han ◽  
Ting Zhao ◽  
Jiandong Tang

Rational utilization of water resources is one of the major methods of water conservation. There are significant differences in the irrigation needs of different agricultural fields because of their spatial variability. Therefore, a decision support system for variable rate irrigation (DSS-VRI) by center pivot was developed. This system can process multi-spectral images taken by unmanned aerial vehicles (UAVs) and obtain the vegetation index (VI). The crop evapotranspiration model (ETc) and crop water stress index (CWSI) were obtained from their established relationships with the VIs. The inputs to the fuzzy inference system were constituted with ETc, CWSI and precipitation. To provide guidance for users, the duty-cycle control map was outputted using ambiguity resolution. The control command contained in the map adjusted the duty cycle of the solenoid valve, and then changed the irrigation amount. A water stress experiment was designed to verify the rationality of the DSS-VRI. The results showed that the more severe water stress is, the more irrigation is obtained, consistent with the expected results. Meanwhile, a user-friendly software interface was developed to implement the DSS-VRI function.


1988 ◽  
Vol 18 (1) ◽  
pp. 57-73 ◽  
Author(s):  
Amir Eiger ◽  
Jonathan M. Jacobs ◽  
Donald B. Chung ◽  
James L. Selsor

2020 ◽  
Vol 63 (5) ◽  
pp. 1507-1519
Author(s):  
Steven R. Evett ◽  
Susan A. O’Shaughnessy ◽  
Manuel A. Andrade ◽  
Paul D. Colaizzi ◽  
Robert C. Schwartz ◽  
...  

HighlightsMulti-faceted research efforts converged to an automated irrigation decision support system (DSS).Low-cost, solar-powered, wireless plant abiotic and biotic stress sensors were developed to aid the DSS.Low-cost, accurate TDR soil water sensors and a wireless node and gateway system were developed for the DSS.Sensor systems and research-based algorithms were integrated into an automated irrigation DSS and control system.Abstract. Variable-rate irrigation (VRI) is now possible with every new center pivot irrigation system sold, either using sector (speed) control or both sector and zone (radial along the pipeline) control. However, decision support systems able to generate a prescription for spatially varying irrigation based on crop water need have lagged far behind VRI equipment. Irrigation based on crop water need has been shown to increase both crop water productivity and nutrient use efficiency, meaning that an effective VRI decision support system (DSS) could improve profitability while conserving resources. In this article, we report separately on a VRI DSS using sensor-based plant and soil water feedback as implemented in four U.S. states. This article describes the genesis and development of the Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system, of the integral plant and soil sensors, and of its wireless sensor network subsystems, as well as the role of multi-location research efforts and cooperative research and development agreements in the development of the needed plant and soil sensors and the ISSCADA and wireless sensor network systems. Keywords: Crop water productivity, Decision support system, Product development, Sensors, Variable-rate irrigation, VRI.


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>


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