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 Determining irrigation needs of sorghum from two-source energy balance and radiometric temperatures

2011 ◽  
Vol 8 (2) ◽  
pp. 3937-3960 ◽  
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. Accumulated crop water use during the campaign resulted 500 mm versus the total 524 mm measured by the lysimeter. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management.

scholarly journals High-Throughput Phenotyping of Crop Water Use Efficiency via Multispectral Drone Imagery and a Daily Soil Water Balance Model

2018 ◽  
Vol 10 (11) ◽  
pp. 1682 ◽  
Author(s):  
Kelly Thorp ◽  
Alison Thompson ◽  
Sara Harders ◽  
Andrew French ◽  
Richard Ward
Keyword(s):  
Water Balance ◽  
Water Use Efficiency ◽  
Soil Water ◽  
Water Use ◽  
High Throughput ◽  
Soil Water Balance ◽  
Balance Model ◽  
Crop Water ◽  
Crop Water Use ◽  
Use Efficiency

Improvement of crop water use efficiency (CWUE), defined as crop yield per volume of water used, is an important goal for both crop management and breeding. While many technologies have been developed for measuring crop water use in crop management studies, rarely have these techniques been applied at the scale of breeding plots. The objective was to develop a high-throughput methodology for quantifying water use in a cotton breeding trial at Maricopa, AZ, USA in 2016 and 2017, using evapotranspiration (ET) measurements from a co-located irrigation management trial to evaluate the approach. Approximately weekly overflights with an unmanned aerial system provided multispectral imagery from which plot-level fractional vegetation cover ( f c ) was computed. The f c data were used to drive a daily ET-based soil water balance model for seasonal crop water use quantification. A mixed model statistical analysis demonstrated that differences in ET and CWUE could be discriminated among eight cotton varieties ( p < 0 . 05 ), which were sown at two planting dates and managed with four irrigation levels. The results permitted breeders to identify cotton varieties with more favorable water use characteristics and higher CWUE, indicating that the methodology could become a useful tool for breeding selection.

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 Evaluation of Evapotranspiration from Eddy Covariance Using Large Weighing Lysimeters

Agronomy ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 99 ◽  
Author(s):  
Jerry Moorhead ◽  
Gary Marek ◽  
Prasanna Gowda ◽  
Xiaomao Lin ◽  
Paul Colaizzi ◽  
...  
Keyword(s):  
Energy Balance ◽  
Eddy Covariance ◽  
Water Use ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Error Rates ◽  
Energy Balance Closure ◽  
Crop Water ◽  
Crop Water Use ◽  
Hourly Data

Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management.

Thermal time models for estimating wheat phenological development and weather-based relationships to wheat quality

2009 ◽  
Vol 89 (3) ◽  
pp. 429-439 ◽  
Author(s):  
I. M. Saiyed ◽  
P. R. Bullock ◽  
H. D. Sapirstein ◽  
G. J. Finlay ◽  
C. K. Jarvis
Keyword(s):  
Water Use ◽  
Spring Wheat ◽  
Quality Parameters ◽  
Western Canada ◽  
Wheat Quality ◽  
Crop Water ◽  
Bread Making ◽  
Phenological Stages ◽  
Crop Water Use ◽  
Weather Impacts

Accurate prediction of crop phenology is a key requirement for crop development models. The prediction of spring wheat yield and quality from meteorological data can be improved by quantifying heat and moisture conditions during specified phenological phases; therefore, accurate prediction of phenological development is important for estimating weather impacts on wheat quality. The objective of this study was to test the accuracy of biometeorological time (BMT), growing degree days (GDD), and physiological days (Pdays) for prediction of wheat phenological stages and impacts of growing season weather during those stages on wheat bread-making quality. Observed crop phenological stages and detailed weather data across 17 site-years in western Canada for six hard spring wheat varieties were collected to assess BMT, GDD and Pdays. Biometeorological time was most consistent for predicting the length of the seeding to jointing and seeding to anthesis growth stages and second most consistent behind GDD for predicting seeding to soft dough and seeding to maturity. The ability of the BMT and GDD models to predict calendar days to anthesis and maturity were further tested using field data from 166 farms across western Canada. Both GDD and BMT models were effective for predicting time from seeding to anthesis (R2 = 0.84 and 0.90, respectively) and seeding to maturity (R2 = 0.62 and 0.66, respectively). BMT- and GDD-predicted wheat growth phases were used to calculate modeled crop water use by growth period for producer fields. Crop water use is significantly correlated to key bread-making quality parameters of flour protein, farinograph dough development time and farinograph stability. Biometeorological time predicted water use was more highly correlated to these quality parameters than GDD predictions. Accordingly, the BMT scale is recommended for estimation of wheat phenological development especially for modeling weather impacts on wheat end-use quality.Key words: Spring wheat, phenological development, biometeorological time, growing degree day, physiological day, wheat quality

Water extraction by sugarcane on soils of the Ord Irrigation Area

2003 ◽  
Vol 43 (5) ◽  
pp. 487 ◽  
Author(s):  
G. M. Plunkett ◽  
R. C. Muchow
Keyword(s):  
Soil Water ◽  
Water Use ◽  
Best Practice ◽  
Irrigation Management ◽  
Water Extraction ◽  
Soil Types ◽  
Crop Water ◽  
Wet Season ◽  
Irrigation Area ◽  
Crop Water Use

Sugarcane is a new commercial crop in the Ord River Irrigation Area and irrigation management strategies are required for profitable production with minimal environmental consequences such as rising ground water. Knowledge of soil water properties and sugarcane water requirements is a necessary prerequisite for best-practice irrigation. Accordingly, soil water measurements were taken to quantify the amount and depth pattern of water extraction by sugarcane on the Ivanhoe Plain in the Ord River Irrigation Area.The drained upper limit and crop lower limit of extraction were measured on 4 soil types. The amount of soil water available to the sugarcane plant varied between soil types, ranging from 226 to 167 mm in a 2.0 m profile. Sugarcane extracted water down to 1.8 m at the Central and Northern Ivanhoe sites, down to 1.6 m at the Southern Ivanhoe site, but only down to 1.0 m at the Aquitaine site. The pattern of water use over time was determined at 2�sites and showed higher crop water use before the wet season and much lower crop water use after the wet season. There was considerable reduction in the ratio of crop water use to Class A pan evaporation after the wet season. Lower irrigation frequency after the wet season on maturing crops will improve irrigation efficiency and reduce impacts on the environment.This knowledge of the different soil water properties of the 4 soil types can be used with crop growth models to develop recommendations for best-practice irrigation management of sugarcane across the Ord River Irrigation Area. These recommendations need to account for the high soil water extraction capability of sugarcane growing in this environment.

scholarly journals Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Agronomy ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 278 ◽  
Author(s):  
Andrew French ◽  
Douglas Hunsaker ◽  
Lahouari Bounoua ◽  
Arnon Karnieli ◽  
William Luckett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Water Use ◽  
Vegetation Index ◽  
Model Performance ◽  
Remote Sensing Data ◽  
Crop Water ◽  
Crop Water Use ◽  
Model Average ◽  
Central Arizona

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6–8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ∘ ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

scholarly journals Temporal and Spatial Changes in Crop Water Use Efficiency in Central Asia from 1960 to 2016

2020 ◽  
Vol 12 (2) ◽  
pp. 572 ◽  
Author(s):  
Shuang Liu ◽  
Geping Luo ◽  
Hao Wang
Keyword(s):  
Water Use Efficiency ◽  
Central Asia ◽  
Water Use ◽  
Recovery Period ◽  
Crop Coefficient ◽  
State Level ◽  
Crop Water ◽  
Crop Water Use ◽  
Use Efficiency ◽  
Temporal And Spatial

Water resources among five Central Asian countries are distributed unevenly. Since the collapse of the Soviet Union, the conflict between water and land use has become increasingly serious. Due to limited data, the temporal and spatial characteristics and trends of crop water use efficiency in Central Asia over the past 60 years remain unclear. This paper combines state-level agricultural statistics data and cultivated land data (1975, 2005 and 2015) from remote sensing imagery and calculates crop water use efficiency based on the FAO crop coefficient method. The results are as follows: (1) the development of crop cultivation in Central Asia is divided into an expansion period (1960–1990), a reduction period (1990–2000), and a recovery period (2000–2016); (2) the grain yield in Central Asia increased from 0.9 to 1.9 t/ha during 1960–2016, with Uzbekistan having the highest, reaching 4.2 t/ha in 2016. Cotton yield increased during 1960–1990 and decreased from 1990 to 2016. (3) The grain water use efficiency in Central Asia increased from 0.22 kg/m3 to 0.39 kg/m3 during 1960–2016. The cotton water use efficiency increased from 0.23 kg/m3 to 0.30 kg/m3 during 1960–1990, has decreased since 1990, and is currently close to the 1960s level.

scholarly journals Spectral Crop Coefficient Approach for Estimating Daily Crop Water Use

2014 ◽  
Vol 03 (03) ◽  
pp. 197-207 ◽  
Author(s):  
Nithya Rajan ◽  
Stephan J. Maas
Keyword(s):  
Water Use ◽  
Crop Coefficient ◽  
Crop Water ◽  
Crop Water Use
Sign in / Sign up

Export Citation Format

Share Document