190 research outputs found

    Proceedings of the 24th annual Central Plains irrigation conference

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    Presented at Proceedings of the 24th annual Central Plains irrigation conference held on February 21-22 in Colby, Kansas.Includes bibliographical references

    Comparison of soil water sensing methods for irrigation management and research

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    Presented at the 2007 Central Plains irrigation conference on February 27-28 in Kearney, Nebraska.Includes bibliographical references.As irrigation water resources decrease and deficit irrigation becomes more common across the Great Plains, greater accuracy in irrigation scheduling will be required. With deficit irrigation a smaller amount of soil water is held in reserve and there is less margin for error. Researchers investigating deficit irrigation practices and developing management practices must also have accurate measures of soil water content - in fact, the two go hand in hand. New management practices for deficit irrigation will require more accurate assessments of soil water content if success is to be ensured. This study compared several commercial soil water sensing systems, four of them based on the electromagnetic (EM) properties of soil as influenced by soil water content, versus the venerable neutron moisture meter (NMM), which is based on the slowing of neutrons by soil water. While performance varied widely, the EM sensors were all less precise and less accurate in the field than was the NMM. Variation in water contents from one measurement location to the next was much greater for the EM sensors and was so large that these sensors are not useful for determining the amount of water to apply. The NMM is still the only sensor that is suitable for irrigation research. However, the NMM is not practical for on-farm irrigation management due to cost and regulatory issues. Unfortunately, our studies indicate that the EM sensors are not useful for irrigation management due to inaccuracy and variability. A new generation of EM sensors should be developed to overcome the problems of those currently available. In the meantime, tensiometers, electrical resistance sensors and soil probes may fill the gap for irrigation management based on soil water sensing. However, many farmers are successfully using irrigation scheduling based on crop water use estimates from weather station networks and reference ET calculations. When used in conjunction with direct field soil water observations to avoid over irrigation, the ET network approach has proved useful in maximizing yields

    Identifying Advantages and Disadvantages of Variable Rate Irrigation – An Updated Review

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    Variable rate irrigation (VRI) sprinklers on mechanical move irrigation systems (center pivot or lateral move) have been commercially available since 2004. Although the number of VRI, zone or individual sprinkler, systems adopted to date is lower than expected there is a continued interest to harness this technology, especially when climate variability, regulatory nutrient management, water conservation policies, and declining water for agriculture compound the challenges involved for irrigated crop production. This article reviews the potential advantages and potential disadvantages of VRI technology for moving sprinklers, provides updated examples on such aspects, suggests a protocol for designing and implementing VRI technology and reports on the recent advancements. The advantages of VRI technology are demonstrated in the areas of agronomic improvement, greater economic returns, environmental protection and risk management, while the main drawbacks to VRI technology include the complexity to successfully implement the technology and the lack of evidence that it assures better performance in net profit or water savings. Although advances have been made in VRI technologies, its penetration into the market will continue to depend on tangible and perceived benefits by producers

    Northern Texas High Plains

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    Presented at the 2002 USCID/EWRI conference, Energy, climate, environment and water - issues and opportunities for irrigation and drainage on July 9-12 in San Luis Obispo, California.Includes bibliographical references.Cotton (Gossypium hirsutum L.) is beginning to be produced on the Northern Texas High Plains as a lower water-requiring crop while producing an acceptable profit. Cotton is a warm season, perennial species produced like an annual yet it requires a delicate balance of water and water deficit controls to most effectively produce high yields in this thermally limited environment. This study measured the water use of cotton in near-fully irrigated, deficiently irrigated, and dryland regimes in a Northern Texas High Plains environment, which has a shortened cotton producing season, using precision weighing lysimeters in 2000 and 2001. The irrigated regimes were irrigated with a lateral-move sprinkler system. The water use data were used to develop crop coefficient data and compared with the FAO-56 method for estimating crop water use. Cotton yield, water use, and water use efficiency was found to be as good in this region as other more noted cotton regions. FAO-56 ET prediction procedures performed better for the more fully irrigated treatments in this environment

    USCID fourth international conference

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    Presented at the Role of irrigation and drainage in a sustainable future: USCID fourth international conference on irrigation and drainage on October 3-6, 2007 in Sacramento, California.Includes bibliographical references.Deficit irrigation commonly is used in regions with reduced or limited irrigation capacity to increase water use efficiency (WUE). This research measured winter wheat (Triticum aestivum L.) and sorghum (Sorghum bicolor L. Moench) water use (ET) and yields so WUE could be determined. Two precision weighing lysimeters were used to accurately measure the crop ET from fully irrigated (FULL) fields and deficit irrigated (DI) fields. The DI wheat was an irrigation cutoff at the jointing growth stage as might be used if available irrigation water was being shifted to summer crops while the sorghum DI used a reduced irrigation rate (~50% FULL irrigation) as might occur with a lower irrigation capacity. Both crops were irrigated by a lateral-move sprinkler system at Bushland, Texas. Wheat ET was decreased by 20% from 849 to 677 mm with a 76% decline in irrigation. Sorghum ET decreased 10% from 621 mm to 560 mm with a 48% decline in irrigation. WUE of sorghum for both grain and dry matter increased slightly with DI but seed mass, and harvest index were unaffected. DI irrigated wheat extracted soil water to a depth of 1.7 m in the Pullman soil with some apparent root extraction to the 2.3-m depth. Sorghum extracted soil water mainly above 1.2 m in the Pullman soil profile if well watered, but DI sorghum extracted soil water to 1.7 m. Sprinkler DI of sorghum beginning with a nearly full soil water content profile permitted the crop to better exploit the soil profile water and minimize soil water deficit effects on crop yield in a year with typical summer rainfall for Bushland (~210 mm) such that yield was not reduced by DI. Cutting off winter wheat irrigation in early spring with a near full soil water profile at jointing, permitted the wheat crop to fully exploit the soil water reservoir when rainfall was normal

    Comparison of stationary and mobile canopy sensing systems for irrigation management of maize and soybean in Nebraska

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    Accurate knowledge of plant and field characteristics is crucial for irrigation management. Irrigation can potentially be better managed by utilizing data collected from various sensors installed on different platforms. The accuracy and repeatability of each data source are important considerations when selecting a sensing system suitable for irrigation management. The objective of this study was to compare data from multispectral (red and near-infrared bands) and thermal (long wave thermal infrared band) sensors mounted on different platforms to investigate their comparative usability and accuracy. The different sensor platforms included stationary posts fixed on the ground, the lateral of a center pivot irrigation system, unmanned aircraft systems (UAS), and Planet (PlanetScope multispectral imager, Planet Labs, Inc., San Francisco, Calif.) satellites. The surface reflectance data from multispectral (MS) sensors were used to compute the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI). The experimental plots were managed with rainfed and irrigated treatments. Irrigation was applied according to a spatial evapotranspiration model informed with Planet satellite imagery. The NDVI and SAVI curves computed from the different sensing systems exhibited similar patterns and were able to capture differences between the rainfed and irrigated treatments when the crops were approaching senescence. Strong correlations were observed for canopy temperature measurements between the stationary and pivot-mounted infrared thermometer (IRT) sensors (p-value of less than 0.01 for the correlations) when canopy were scanned with no irrigation application (dry scans). The best correlation was obtained for the irrigated maize, which yielded r2 of 0.99, RMSE of 0.4°C, and MAE of 0.3°C. The correlation for the canopy temperature data collected during dry scan between UAS and pivot-mounted thermal sensors was weak with r2 = 0.26 to 0.28, larger RMSE values of 3.7°C and MAE values of 3.4°C. Secondary analysis between thermal data from stationary and pivot-mounted IRTs collected during wet scans (during an irrigation event) demonstrated reduced canopy temperature from pivot-mounted IRTs by approximately 2°C for irrigated soybean due to wetting of the canopy by the irrigation. Understanding the performance of these sensor systems is valuable in configuring practical design and operational considerations when using sensor feedback for irrigation management

    Radiometer Footprint Model to Estimate Sunlit and Shaded Components for Row Crops

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    Th is article describes a geometric model for computing the relative proportion of sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil appearing in a circular or elliptical radiometer footprint for row crops, where the crop rows were modeled as continuous ellipses. Th e model was validated using digital photographs of row crops, where each component was determined by supervised classification. Root mean squared errors (RMSE) between modeled and observed components were 35, 49, 29, and 44% of observed means for sunlit vegetation, shaded vegetation, sunlit soil, and shaded soil, respectively. Mean bias errors (MBE) were, respectively, –5.6, 16.6, –4.0, and –0.5% of observed means. Th e continuous ellipse model was compared to the commonly used clumping index model, where the latter estimates total vegetation and total soil, but does not resolve these into their sunlit or shaded components and does not account for radiometer footprint shape dimensions. Th e continuous ellipse model resulted in RMSE for vegetation and soil of 22 and 19%, respectively, whereas the clumping index model resulted in respective RMSE of 37 and 31%. Th e continuous ellipse model had MBE of 3.3 and –2.6% for vegetation and soil, respectively, which was slightly greater than the respective MBE of –1.5 and 1.4% for clumping index model. Given the model sensitivity and uncertainty of leaf area index (LAI), the RMSE and MBE resulting from the continuous ellipse model would not be expected to be less than 20% of the observed means, and model performance was therefore deemed reasonable in this study

    Minimum-Uncertainty Angular Wave Packets and Quantized Mean Values

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    Uncertainty relations between a bounded coordinate operator and a conjugate momentum operator frequently appear in quantum mechanics. We prove that physically reasonable minimum-uncertainty solutions to such relations have quantized expectation values of the conjugate momentum. This implies, for example, that the mean angular momentum is quantized for any minimum-uncertainty state obtained from any uncertainty relation involving the angular-momentum operator and a conjugate coordinate. Experiments specifically seeking to create minimum-uncertainty states localized in angular coordinates therefore must produce packets with integer angular momentum.Comment: accepted for publication in Physical Review

    Evaporative loss from irrigated interrows in a highly advective semi-arid agricultural area

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    Agricultural productivity has increased in the Texas High Plains at the cost of declining water tables, putting at risk the sustainability of the Ogallala Aquifer as a principal source of water for irrigated agriculture. This has led area producers to seek alternative practices that can increase water use efficiency (WUE) through more careful management of water. One potential way of improving WUE is by reducing soil evaporation (E), thus reducing overall evapotranspiration (ET). Before searching for ways to reduce E, it is first important to quantify E and understand the factors that determine its magnitude. The objectives of this study were (1) to quantify E throughout part of the growing season for irrigated cotton in a strongly advective semi-arid region; (2) to study the effects of LAI, days after irrigation, and measurement location within the row on the E/ET fraction; and (3) to study the ability of microlysimeter (ML) measures of E combined with sap flow gage measures of transpiration (T) to accurately estimate ET when compared with weighing lysimeter ET data and to assess the E/T ratio. The research was conducted in an irrigated cotton field at the Conservation & Production Research Laboratory of the USDA-ARS, Bushland, TX. ET was measured by a large weighing lysimeter, and E was measured by 10 microlysimeters that were deployed in two sets of 5 across the interrow. In addition, 10 heat balance sap flow gages were used to determine T. A moderately good agreement was found between the sum E + T and ET (SE = 1 mm or ~10% of ET). It was found that E may account for \u3e50% of ET during early stages of the growing season (LAI \u3c 0.2), significantly decreasing with increase in LAI to values near 20% at peak LAI of three. Measurement location within the north-south interrows had a distinct effect on the diurnal pattern of E, with a shift in time of peak E from west to east, a pattern that was governed by the solar radiation reaching the soil surface. However, total daily E was unaffected by position in the interrow. Under wet soil conditions, wind speed and direction affected soil evaporation. Row orientation interacted with wind direction in this study such that aerodynamic resistance to E usually increased when wind direction was perpendicular to row direction; but this interaction needs further study because it appeared to be lessened under higher wind speeds

    Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset

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    Large sample datasets of in situ evapotranspiration (ET) measurements with well documented data provenance and quality assurance are critical for water management and many fields of earth science research. We present a post-processed ET oriented dataset at daily and monthly timesteps, from 161 stations, including 148 eddy covariance flux towers, that were chosen based on their data quality from nearly 350 stations across the contiguous United States. In addition to ET, the data includes energy and heat fluxes, meteorological measurements, and reference ET downloaded from grid- MET for each flux station. Data processing techniques were conducted in a reproducible manner using open-source soft- ware. Most data initially came from the public AmeriFlux network, however, several different networks (e.g., the USDA- Agricultural Research Service) and university partners pro- vided data that was not yet public. Initial half-hourly energy balance data were gap-filled and aggregated to daily frequency, and turbulent fluxes were corrected for energy balance closure error using the FLUXNET2015/ONEFlux energy balance ratio approach. Metadata, diagnostics of energy balance, and interactive graphs of time series data are included for each station. Although the dataset was developed primarily to benchmark satellite-based remote sensing ET models of the OpenET initiative, there are many other potential uses, such as validation for a range of regional hydrologic and atmospheric models
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