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 Optimizing Et-Based Irrigation Scheduling for Wheat and Maize with Water Constraints

2017 ◽  
Vol 60 (6) ◽  
pp. 2053-2065 ◽  
Author(s):  
Liwang Ma ◽  
Zhiming Qi ◽  
Yanjun Shen ◽  
Liang He ◽  
Shouhua Xu ◽  
...  
Keyword(s):  
Grain Yield ◽  
Water Use Efficiency ◽  
Water Use ◽  
Deficit Irrigation ◽  
Irrigation Management ◽  
Irrigation Scheduling ◽  
Weather Data ◽  
Growth Stages ◽  
Area Index ◽  
Use Efficiency

Abstract. Deficit irrigation has been shown to increase crop water use efficiency (WUE) under certain conditions, even though the yield is slightly reduced. In this study, the Root Zone Water Quality Model (RZWQM) was first calibrated with measured data from a large weighing lysimeter from 1998 to 2003 at the Yucheng Experimental Station in the North China Plain for daily evapotranspiration (ET), soil water storage (0-120 cm), leaf area index (LAI), aboveground biomass, and grain yield. The calibrated model was then used to explore crop responses to ET-based irrigation management using weather data from 1958 to 2015 and identify the most suitable ET-based irrigation schedules for the area. Irrigation amount was determined by constraining irrigation to a percentage of potential crop ET (40%, 60%, 80%, and 100% ETc) at the various growth stages of wheat [planting to before winter dormancy (P-D), green up to booting (G-B), booting to flowering (B-F), and flowering to maturity (F-M)] and of maize [planting to silking (P-S) and silking to maturity (S-M)], subject to seasonal water availability limits of 100/50, 200/100, 300/150, and 400/200 mm and no water limit for wheat/maize seasons, respectively. In general, wheat was more responsive to irrigation than maize, while greater influence of weather variation was simulated on maize than on wheat. For wheat with seasonal water limits, the highest average WUE was simulated with the highest targeted ETc levels at both the G-B and B-F stages and lower targeted ETc levels at the P-D and F-M stages. However, the highest average grain yield was simulated with the highest targeted ETc levels at all four growth stages for no water limit and the 400 mm water limit, or at both the G-B and B-F stages for the 300 and 200 mm water limits. For maize, lower targeted ETc levels after silking did not significantly affect maize production due to the high season rainfall, but irrigation of 60% ETc before silking was recommended. These results could be used as guidelines for precision irrigation along with real-time weather information. Keywords: Deficit irrigation, Evapotranspiration, Growth stage, RZWQM, Water use efficiency, Wheat and maize.

Irrigation scheduling and water requirements for cowpea using evaporation pan at middle of Iraq

1970 ◽  
pp. 13-17
Author(s):  
Saifuldeen A. Salim ◽  
Isam Kudhier Hamza ◽  
Laith Farhan Jar
Keyword(s):  
Water Productivity ◽  
Irrigation Treatment ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Water Requirements ◽  
Applied Water ◽  
Fresh Seed ◽  
Irrigation Interval ◽  
Biological Yield ◽  
Evaporation Pan

The present study was conducted to find out the water requirements and most suitable irrigation frequencies for cowpea (Vigna unguiculata L.) var grown under drip irrigation. The treatments were based on the IW:CPE ratio at different empirical pan factors 0.6 , 0.8, 1.0, 1.,1.4 , and 1.6 Ef (where Ef = IW/CPE). It was observed that the irrigation interval was variable values decreased by increasing Ef value and with the progress of the growing season. The 1.2 and 1.0 IW: CPE treatments with approximately 4 days irrigation interval were achieved the best results. The total amount of applied water during Cowpea growing season was varied between 247.7 and 266.5mm with 254.8mm as a mean. Irrigation treatment with Ef1.2 was superior over the rest of other treatments in fresh seed yield (5.13 ton.hec.-1), crop water productivity (2.14 kg.m-3), biological yield (6.88 ton.hec.-1) , fresh pod yield (7.33 ton.hec.-1), weight of 100 seed (31.28gm), number of seed/pod (9.34) and netting percentage (37.1). The lowest values of the most parameters used in this study were obtained by Ef 0.6 irrigation treatment.  

scholarly journals Optimization of irrigation water in South Africa for sustainable and beneficial use

2017 ◽  
Author(s):  
◽  
Akinola Mayowa Ikudayisi
Keyword(s):  
South Africa ◽  
Water Use ◽  
Crop Yield ◽  
Optimization Algorithm ◽  
Irrigation Water ◽  
Irrigation Scheduling ◽  
Crop Water ◽  
Land Area ◽  
Water Requirements ◽  
Irrigation Water Use

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.

scholarly journals Soil moisture heterogeneity regulates water use in Populus nigra L. by altering root and xylem sap phytohormone concentrations

2020 ◽  
Vol 40 (6) ◽  
pp. 762-773 ◽  
Author(s):  
Jaime Puértolas ◽  
Marta Pardos ◽  
Carlos de Ollas ◽  
Alfonso Albacete ◽  
Ian C Dodd
Keyword(s):  
Soil Moisture ◽  
Water Use ◽  
Deficit Irrigation ◽  
Xylem Sap ◽  
Irrigation Scheduling ◽  
Populus Nigra ◽  
Soil Drying ◽  
Plant Water ◽  
Plant Water Use ◽  
Soil Moisture Heterogeneity

Abstract Soil moisture heterogeneity in the root zone is common both during the establishment of tree seedlings and in experiments aiming to impose semi-constant soil moisture deficits, but its effects on regulating plant water use compared with homogenous soil drying are not well known in trees. Pronounced vertical soil moisture heterogeneity was imposed on black poplar (Populus nigra L.) grown in soil columns by altering irrigation frequency, to test whether plant water use, hydraulic responses, root phytohormone concentrations and root xylem sap chemical composition differed between wet (well-watered, WW), and homogeneously (infrequent deficit irrigation, IDI) and heterogeneously dry soil (frequent deficit irrigation, FDI). At the same bulk soil water content, FDI plants had greater water use than IDI plants, probably because root abscisic acid (ABA) concentration was low in the upper wetter layer of FDI plants, which maintained root xylem sap ABA concentration at basal levels in contrast with IDI. Soil drying did not increase root xylem concentration of any other hormone. Nevertheless, plant-to-plant variation in xylem jasmonic acid (JA) concentration was negatively related to leaf stomatal conductance within WW and FDI plants. However, feeding detached leaves with high (1200 nM) JA concentrations via the transpiration stream decreased transpiration only marginally. Xylem pH and sulphate concentration decreased in FDI plants compared with well-watered plants. Frequent deficit irrigation increased root accumulation of the cytokinin trans-zeatin (tZ), especially in the dry lower layer, and of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), in the wet upper soil layer. Root hormone accumulation might explain the maintenance of high root hydraulic conductance and water use in FDI plants (similar to well-watered plants) compared with IDI plants. In irrigated tree crops, growers could vary irrigation scheduling to control water use by altering the hormone balance.

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.

A Decision-Level Data Fusion Approach to Surface Roughness Prediction

2019 ◽  
Author(s):  
Yupeng Wei ◽  
Dazhong Wu ◽  
Janis Terpenny
Keyword(s):  
Surface Roughness ◽  
Data Fusion ◽  
Process Monitoring ◽  
Predictive Models ◽  
Sensor Data ◽  
Fused Deposition ◽  
Decision Level ◽  
Level Data ◽  
Fusion Approach

Abstract To improve the quality of additively manufactured parts, it is crucial to develop real-time process monitoring systems and data-driven predictive models. While various sensor- and image-based process monitoring methods have been developed to improve the quality of additively manufactured parts, very limited research has been conducted to predict surface roughness. To fill this gap, this paper presents a decision-level data fusion approach to predicting surface roughness in the fused deposition modeling (FDM) process. The predictive models are trained by the random forests method using multiple sensor signals. A decision-level data fusion method is introduced to integrate sensor data sources. Experimental results have shown that the decision-level data fusion approach can predict surface roughness in FDM with high accuracy.

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.

scholarly journals Optimized Regulated Deficit Irrigation Management for Watermelon Cultivation in a Semiarid Region

2021 ◽  
Vol 9 (2) ◽  
pp. 113
Author(s):  
Kelly Nascimento Leite ◽  
Daniel Fonseca de Carvalho ◽  
Jose Maria Tarjuelo Martin- Benito ◽  
Geocleber Gomes de Sousa ◽  
Alfonso Dominguez Padilla
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Water Scarcity ◽  
Deficit Irrigation ◽  
Irrigation Management ◽  
Control Treatment ◽  
Water Volume ◽  
Semiarid Region ◽  
Regulated Deficit Irrigation ◽  
Use Efficiency

The present study aimed to validate the MOPECO crop simulation model and to determine a viable irrigation management for watermelon in the semiarid region of Northeast Brazil, using methodologies of optimized regulated deficit irrigation (ORDI) and constant deficit irrigation (CDI). The experiment was carried out during October to December 2013 and the second one from July to August 2014 in plots of land of producers in the Baixo Acaraú Irrigated Perimeter – Ceará, Brazil. Treatments were characterized by ORDI management (70, 80, 90% ETa/ETm ratio) and CDI management along the entire cycle (70, 80 and 90% ETm) and control treatment, irrigated with 100% of the water requirement of the crop (ETm). In terms of saving of water resources, the results showed that management with regulated deficit irrigation leads to favorable and economically viable results for the farmer, of water saving, especially in a situation of severe water scarcity, irrigation management with regulated water deficit (ORDI) can provide favorable and economically viable results for the farmer. The highest value of WUE (41.8 kg m-3) was obtained with the treatment of lowest water volume applied (352.1 L) in the second experiment, decreasing with the increase in the water volume used. The ORDI methodology represents a better water use efficiency for all treatments of deficit applied compared to CDI treatments. The difference of ORDI and CDI methodology provided an increase of up to 200% in the gross margin obtained with the exploration of the watermelon culture which represents a range of R$ 986.00 in profit in a situation of water scarcity, as in the case of the studied region, the strategy with water supply of 70% of ETa/ETm ratio regulated by phenological stage was recommended in order to obtain highest water use efficiency.

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