scholarly journals Modelling water requirements of greenhouse spinach for irrigation management purposes

2016 ◽  
Vol 48 (3) ◽  
pp. 776-788 ◽  
Author(s):  
Andrea Bianchi ◽  
Daniele Masseroni ◽  
Arianna Facchi
Keyword(s):  
Irrigation Management ◽  
Model Performance ◽  
Crop Coefficient ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Balance Model ◽  
Water Requirements ◽  
Greenhouse Crops ◽  
Using Data ◽  
Nitrogen Treatments

Estimating water requirements of plants cultivated in greenhouse environments is crucial, both for the design of greenhouse irrigation systems and the improvement of irrigation scheduling. Spinach is one of the main vegetables sold as ‘ready-to-eat’ bagged produce; it is very sensitive to water stress and thus requires accurate irrigation. In this work, a water balance model simulating the daily irrigation need for greenhouse crops based on the FAO-56 ‘single crop coefficient’ method was designed and applied (FAO-56-GH). Two experiments were conducted on two spinach varieties grown in pots in different periods. For each experiment, four nitrogen treatments were considered. Irrigation was managed weighing the pots every day, and restoring soil water to field capacity. Crop coefficient (Kc) values were calibrated using data of the first experiment, the model was successively validated using the second dataset. Results showed a good model performance both in the validation and calibration periods (R2 = 0.80 and 0.84, root mean square error (RMSE) = 0.41 and 0.21 mm day−1, Nash–Sutcliffe efficiency (NSE) = 0.78 and 0.83). Analysis of variance (ANOVA) test revealed a scarce dependence of irrigation needs to nitrogen treatments. This study suggests the possibility of adopting the FAO-56-GH model with site-specific Kc to improve irrigation management and planning in greenhouse environments.

scholarly journals Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management

2018 ◽  
Vol 61 (2) ◽  
pp. 533-548 ◽  
Author(s):  
J. Burdette Barker ◽  
Christopher M. U. Neale ◽  
Derek M. Heeren ◽  
Andrew E. Suyker
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Water Balance ◽  
Real Time ◽  
Eddy Covariance ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Irrigation Scheduling ◽  
Balance Model ◽  
Crop Coefficients

Abstract. Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (Kcbrf) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m-2. The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m-2. We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d-1 (RMSE = 1.49 mm d-1) for PM and MBE = 0.04 mm d-1 (RMSE = 1.18 mm d-1) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d-1 (RMSE = 1.37 mm d-1) for the Kcbrf alone to -0.45 mm d-1 (RMSE = 0.98 mm d-1) and -0.39 mm d-1 (RMSE = 0.95 mm d-1) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management. Keywords: Center-pivot irrigation, ET estimation methods, Evapotranspiration, Irrigation scheduling, Irrigation water balance, Model validation, Variable-rate irrigation.

scholarly journals A Smart Irrigation Tool to Determine the Effects of ENSO on Water Requirements for Tomato Production in Mozambique

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1820 ◽  
Author(s):  
Eduardo Gelcer ◽  
Clyde Fraisse ◽  
Lincoln Zotarelli ◽  
Daniel Perondi ◽  
Hipólito Malia ◽  
...  
Keyword(s):  
El Niño ◽  
Water Demand ◽  
El Nino ◽  
Southern Oscillation ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
La Niña ◽  
Water Requirements ◽  
Tomato Production ◽  
La Nina

Irrigation scheduling is used by growers to determine the right amount and timing of water application. In most parts of Mozambique, 90% of the total yearly precipitation occurs from November to March. The El Niño Southern Oscillation (ENSO) phenomenon influences the climate in Mozambique and affects the water demand for crop production. The objectives of this work were to quantify the effects of ENSO phenomenon on tomato crop water requirements, and to create the AgroClimate irrigation tool (http://mz.agroclimate.org/) to assist farmers in improving irrigation management. This study was based on daily grid-based climate information from 1983 to 2016 from the Climate Forecast System Reanalysis. Daily crop evapotranspiration was calculated by Hargreaves equation and crop coefficients. This tool is available online and considers different planting dates, ENSO phases, and crop growing season lengths. Irrigation needs varied from less than 250 mm per growing cycle during winter to 550 mm during spring. Both El Niño and La Niña influenced the irrigation scheduling, especially from November to March. El Niño periods were related to increased water demand due to drier and warmer conditions, while the opposite was observed for La Niña. The ENSO information might be used to understand climate variability and improve tomato irrigation scheduling in Mozambique.

scholarly journals Water requirement and crop coefficients of sorghum in Apodi Plateau

2021 ◽  
Vol 25 (10) ◽  
pp. 684-688
Author(s):  
João G. A. Lima ◽  
José Espínola Sobrinho ◽  
José F. de Medeiros ◽  
Paula C. Viana ◽  
Rudah M. Maniçoba
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Irrigation Management ◽  
High Growth ◽  
Crop Coefficient ◽  
Northeastern Brazil ◽  
Crop Evapotranspiration ◽  
Water Requirements ◽  
Total Crop ◽  
Crop Coefficients

ABSTRACT Sorghum is of significant economic importance for Northeastern Brazil, since it exhibits high growth rates in regions with irregular rainfall distribution and high temperatures, and is an alternative to corn, which has greater water requirements. Despite being a traditional crop in the region, there are few studies on irrigation management in the Apodi plateau. The aim of this study was to determine the evapotranspiration of the crop and the crop coefficient (Kc) for the different stages of sorghum growth in two cycles, and establish the relationship between the Kc and the normalized difference vegetation index (NDVI) obtained by radiometry. Two weighing lysimeters were used to estimate crop evapotranspiration (ETc). Reference evapotranspiration (ETo) was estimated by the Penman-Monteith method (FAO) and the crop coefficient determined using two methodologies: simple Kc and dual Kc. Total crop evapotranspiration in the two cycles was 452 and 557 mm. The ETc value was 23% higher in the second cycle compared to the first. The maximum Kc values for the first and second cycles were 1.21 and 1.35, respectively, using the dual Kc methodology. The linear relationship found between the Kc values and the NDVI allows monitoring and estimating the water requirements of the crop.

scholarly journals Irrigation of Greenhouse Crops

Horticulturae ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. 7 ◽  
Author(s):  
Georgios Nikolaou ◽  
Damianos Neocleous ◽  
Nikolaos Katsoulas ◽  
Constantinos Kittas
Keyword(s):  
Personal Experience ◽  
Management Practices ◽  
Production Systems ◽  
Irrigation Management ◽  
Daily Basis ◽  
Irrigation Scheduling ◽  
Greenhouse Production ◽  
Greenhouse Crops ◽  
Irrigation Control ◽  
Further Development

Precision agricultural greenhouse systems indicate considerable scope for improvement of irrigation management practices, since growers typically irrigate crops based on their personal experience. Soil-based greenhouse crop irrigation management requires estimation on a daily basis, whereas soilless systems must be estimated on an hourly or even shorter interval schedule. Historically, irrigation scheduling methods have been based on soil or substrate monitoring, dependent on climate or time with each having both strengths and weaknesses. Recently, plant-based monitoring or plant reflectance-derived indices have been developed, yet their potential is limited for estimating the irrigation rate in order to apply proper irrigation scheduling. Optimization of irrigation practices imposes different irrigation approaches, based on prevailing greenhouse environments, considering plant-water-soil relationships. This article presents a comprehensive review of the literature, which deals with irrigation scheduling approaches applied for soil and soilless greenhouse production systems. Irrigation decisions are categorized according to whether or not an automatic irrigation control has the ability to support a feedback irrigation decision system. The need for further development of neural networks systems is required.

scholarly journals Crop Coefficients and Transpiration of a Super Intensive Arbequina Olive Orchard using the Dual Kc Approach and the Kcb Computation with the Fraction of Ground Cover and Height

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 383 ◽  
Author(s):  
Teresa Paço ◽  
Paula Paredes ◽  
Luis Pereira ◽  
José Silvestre ◽  
Francisco Santos
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Ground Cover ◽  
Soil Water Balance ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Water Requirements ◽  
Olive Orchard

The SIMDualKc model was used to simulate crop water requirements for a super high density olive orchard in the region of Alentejo, Portugal. This model uses the dual crop coefficient approach to estimate and partitioning the actual crop evapotranspiration (ETc act) and therefore to perform the soil water balance. The model was calibrated with 2011 tree transpiration using trunk sap flow measurements and was validated using similar data from 2012 and tested with 2013 data. Low root mean square errors (RMSE < 0.53 mm·d−1) and acceptable modelling efficiency indicators (EF > 0.25) were obtained. Further validation was performed comparing modelled ETc act with eddy covariance measurements. These indicators support the appropriateness of using SIMDualKc to guide irrigation management. The basal crop coefficient (Kcb) curves obtained with SIMDualKc for those 3 years were compared with the Kcb values computed with the Allen and Pereira approach (A&P approach) where Kcb is estimated from the fraction of ground cover and plant height considering an adjustment factor for crop stomatal control (Fr). Fr values were obtained through a trial and error procedure through comparing the Kcb estimated with this approach and with SIMDualKc. The Kcb curves obtained by both methods resulted highly correlated, which indicates that the A&P approach may be used in the irrigation management practice to estimate crop water requirements. Results of performing the soil water balance with SIMDualKc have shown that soil evaporation is a large fraction of ETc act, varying between 41% and 45% for the 3 years under study. Irrigation, applied with a drip system, represented 39 to 56% of ETc act, which shows the great importance of irrigation to achieve the water requirements of super intensive olive orchards. Nevertheless, the analysis has shown that the irrigation management adopted at the orchard produces a water deficit larger than desirable, with a ratio of ETc act to non-stressed crop evapotranspiration (ETc) varying from 70% to 94% during the mid-season, when that ratio for a eustress irrigation management could be around 90%.

scholarly journals Determining water use of sorghum from two-source energy balance and radiometric temperatures

2011 ◽  
Vol 15 (10) ◽  
pp. 3061-3070 ◽  
Author(s):  
J. M. Sánchez ◽  
R. López-Urrea ◽  
E. Rubio ◽  
V. Caselles
Keyword(s):  
Energy Balance ◽  
Water Use ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Balance Model ◽  
Crop Water ◽  
Phenological Stages ◽  
Crop Water Use ◽  
Promising Tool ◽  
Experimental Campaign

Abstract. Estimates of surface actual evapotranspiration (ET) can assist in predicting crop water requirements. An alternative to the traditional crop-coefficient methods are the energy balance models. The objective of this research was to show how surface temperature observations can be used, together with a two-source energy balance model, to determine crop water use throughout the different phenological stages of a crop grown. Radiometric temperatures were collected in a sorghum (Sorghum bicolor) field as part of an experimental campaign carried out in Barrax, Spain, during the 2010 summer growing season. Performance of the Simplified Two-Source Energy Balance (STSEB) model was evaluated by comparison of estimated ET with values measured on a weighing lysimeter. Errors of ±0.14 mm h−1 and ±1.0 mm d−1 were obtained at hourly and daily scales, respectively. Total accumulated crop water use during the campaign was underestimated by 5%. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management.

scholarly journals A Smart Irrigation Tool to Determine the Effects of ENSO on Water Requirements for Tomato Production in Mozambique

2018 ◽  
Author(s):  
Eduardo Gelcer ◽  
Clyde W. Fraisse ◽  
Lincoln Zotarelli ◽  
Daniel Perondi ◽  
Hipólito A. Malia ◽  
...  
Keyword(s):  
Water Demand ◽  
Crop Production ◽  
Southern Oscillation ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Water Requirements ◽  
Planting Dates ◽  
Tomato Crop ◽  
Tomato Production ◽  
The Right

Irrigation scheduling is used by growers to determine the right amount and timing of water application. In most parts of Mozambique, 90% of the total yearly precipitation occurs from November to March. The El Ni&ntilde;o Southern Oscillation (ENSO) phenomenon influences the climate in Mozambique and affects the water demand for crop production. The objectives of this work were to quantify the effects of ENSO phenomenon on tomato crop water requirements, and to create the AgroClimate irrigation tool (http://mz.agroclimate.org/) to assist farmers in improving irrigation management. This study was based on daily grid-based climate information from 1983 to 2016 from the Climate Forecast System Reanalysis. Daily crop evapotranspiration was calculated by Hargreaves equation and crop coefficients. This tool is available online and considers different planting dates, ENSO phases, and crop growing season lengths. Irrigation needs varied from less than 250 mm per growing cycle during winter to 550 mm during spring. Both El Ni&ntilde;o and La Ni&ntilde;a influenced the irrigation scheduling, especially from November to March. El Ni&ntilde;o periods were related with increased water demand due to drier and warmer conditions while the opposite was observed for La Ni&ntilde;a. The ENSO information might be used to understand climate variability and improve tomato irrigation scheduling in Mozambique.

scholarly journals Performance Assessment of Five Different Soil Moisture Sensors under Irrigated Field Conditions in Oklahoma

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3786 ◽  
Author(s):  
Sumon Datta ◽  
Saleh Taghvaeian ◽  
Tyson Ochsner ◽  
Daniel Moriasi ◽  
Prasanna Gowda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Cropping Systems ◽  
Irrigation Management ◽  
Clay Content ◽  
Field Capacity ◽  
Irrigation Scheduling ◽  
Irrigated Agriculture ◽  
Undisturbed Soil ◽  
Soil Moisture Sensors ◽  
Rosetta Model

Meeting the ever-increasing global food, feed, and fiber demands while conserving the quantity and quality of limited agricultural water resources and maintaining the sustainability of irrigated agriculture requires optimizing irrigation management using advanced technologies such as soil moisture sensors. In this study, the performance of five different soil moisture sensors was evaluated for their accuracy in two irrigated cropping systems, one each in central and southwest Oklahoma, with variable levels of soil salinity and clay content. With factory calibrations, three of the sensors had sufficient accuracies at the site with lower levels of salinity and clay, while none of them performed satisfactorily at the site with higher levels of salinity and clay. The study also investigated the performance of different approaches (laboratory, sensor-based, and the Rosetta model) to determine soil moisture thresholds required for irrigation scheduling, i.e., field capacity (FC) and wilting point (WP). The estimated FC and WP by the Rosetta model were closest to the laboratory-measured data using undisturbed soil cores, regardless of the type and number of input parameters used in the Rosetta model. The sensor-based method of ranking the readings resulted in overestimation of FC and WP. Finally, soil moisture depletion, a critical parameter in effective irrigation scheduling, was calculated by combining sensor readings and FC estimates. Ranking-based FC resulted in overestimation of soil moisture depletion, even for accurate sensors at the site with lower levels of salinity and clay.

scholarly journals Using High-Spatiotemporal Thermal Satellite ET Retrievals for Operational Water Use and Stress Monitoring in a California Vineyard

2019 ◽  
Vol 11 (18) ◽  
pp. 2124 ◽  
Author(s):  
Knipper ◽  
Kustas ◽  
Anderson ◽  
Alsina ◽  
Hain ◽  
...  
Keyword(s):  
Data Fusion ◽  
Water Use ◽  
Deficit Irrigation ◽  
Irrigation Management ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Data Availability ◽  
Sensor Data ◽  
Water Requirements ◽  
Fusion Approach

In viticulture, deficit irrigation strategies are often implemented to control vine canopy growth and to impose stress at critical stages of vine growth to improve wine grape quality. To support deficit irrigation scheduling, remote sensing technologies can be employed in the mapping of evapotranspiration (ET) at the field to sub-field scales, quantifying time-varying vineyard water requirements and actual water use. In the current study, we investigate the utility of ET maps derived from thermal infrared satellite imagery over a vineyard in the Central Valley of California equipped with a variable rate drip irrigation (VRDI) system which enables differential water applications at the 30 × 30 m scale. To support irrigation management at that scale, we utilized a thermal-based multi-sensor data fusion approach to generate weekly total actual ET (ETa) estimates at 30 m spatial resolution, coinciding with the resolution of the Landsat reflectance bands. Crop water requirements (ETc) were defined with a vegetative index (VI)-based approach. To test capacity to capture stress signals, the vineyard was sub-divided into four blocks with different irrigation management strategies and goals, inducing varying degrees of stress during the growing season. Results indicate derived weekly total ET from the thermal-based data fusion approach match well with observations. The thermal-based method was also able to capture the spatial heterogeneity in ET over the vineyard due to a water stress event imposed on two of the four vineyard blocks. This transient stress event was not reflected in the VI-based ETc estimate, highlighting the value of thermal band imaging. While the data fusion system provided valuable information, latency in current satellite data availability, particularly from Landsat, impacts operational applications over the course of a growing season.

scholarly journals Spatial-temporal analysis of water requirements of coffee crop in Minas Gerais State, Brazil

2010 ◽  
Vol 14 (2) ◽  
pp. 165-172 ◽  
Author(s):  
Luis C. de A. Lemos Filho ◽  
Carlos R. de Mello ◽  
Manoel A. de Faria ◽  
Luiz G. de Carvalho
Keyword(s):  
Potential Evapotranspiration ◽  
Crop Coefficient ◽  
Temporal Analysis ◽  
Irrigation Scheduling ◽  
Minas Gerais ◽  
Likelihood Method ◽  
Crop Evapotranspiration ◽  
Water Requirements ◽  
Daily Data ◽  
Minas Gerais State

Scientific investigations about crop water requirements are of fundamental importance to the irrigation process. The main objective of this paper is to analyze and to map water requirements of coffee crop in Minas Gerais State, Brazil. Potential evapotranspiration values (ET0) were estimated by the Penman-Monteith-FAO method, using daily data sets available for 42 National Meteorology Institute (INMET) stations for a period of 17 years. The crop coefficient values (kc) considered were extracted from literature. The results were analyzed by means of geostatistical tools. The theoretical semi-variograms were fitted by the Maximum Likelihood method, considering spherical, exponential and Gaussian models. The maps were created using the ordinary kriging method. In a general way, the results have showed that the coffee crop evapotranspiration (ETc) presents high variability in Minas Gerais State. The largest variations, both spatial and temporal, have been observed in the northern part of the State. January and June, respectively, presented the highest and the smallest water requirements of coffee crop. Based on this, we can conclude that due to the coffee crop evapotranspiration (ETc) data distinction in different regions of Minas Gerais, a good estimate of the ETc values for each locality will bring many benefits to the coffee growers regarding irrigation scheduling.

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