Evaluation of variable rate irrigation using a remote-sensing-based model

Improvements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRINP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as an input. Both 2015 and 2016 had above-average precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 mm, 6 mm, and –12 mm less in separate analyses than for the uniform treatment. Irrigation for the VRIRS was about 40 mm, 50 mm, and –98 mm greater in separate analyses than the uniform at Mead and about 18mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates

Enhancing Production Efficiency and Farm Profitability Through Innovative Extension Programming

Cooperative Extension strives to provide agricultural producers with non-formal educational opportunities designed to positively impact agriculture (NIFA, 2021). Therefore, a team of Extension professionals at the University of Nebraska – Lincoln developed and facilitate an ongoing professional development program designed to enhance the engagement of agricultural producers in farm management, especially in the areas of input use efficiency and profitability. Andragogy was used as the framework to help ensure the Testing Agricultural Performance Solutions (TAPS) program provided agricultural producers with non-formal education that aligned with andragogical principles. Knowles (1980) refers to andragogy as the “art and science of helping adults learn” (p. 45) and his assumptions of andragogy include: 1) Learner’s need to know, 2) Self-Concept of the learner, 3) Prior experience of the learner, 4) Readiness to learn, 5) Orientation to learning, and 6) Motivation to learn (Knowles, 1998, as cited in Knowles et al., 2015, p. 6). The TAPS program uses the assumptions of andragogy (Knowles, 1998, as cited in Knowles et al., 2015) to provide a common platform for experiential and peer-to-peer learning that includes the involvement of university researchers, extension specialists, and industry personnel

Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors

Interreplicate variability—the spread in output values among units of the same sensor subjected to essentially the same condition—can be a major source of uncertainty in sensor data. To investigate the interreplicate variability among eight electromagnetic soil moisture sensors through a field study, eight units of TDR315, CS616, CS655, HydraProbe2, EC5, 5TE, and Teros12 were installed at a depth of 0.30 m within 3 m of each other, whereas three units of AquaSpy Vector Probe were installed within 3 m of each other. The magnitude of interreplicate variability in volumetric water content (θv) was generally similar between a static period near field capacity and a dynamic period of 85 consecutive days in the growing season. However, a wider range of variability was observed during the dynamic period primarily because interreplicate variability in θv increased sharply whenever infiltrated rainfall reached the sensor depth. Interreplicate variability for most sensors was thus smaller if comparing θv changes over several days that excluded this phenomenon than if comparing θv directly. Among the sensors that also reported temperature and/or apparent electrical conductivity, the sensors exhibiting the largest interreplicate variability in these outputs were characterized by units with consistently above or below average readings. Although manufacturers may continue to improve the technology in and the quality control of soil moisture sensors, users would still benefit from paying greater attention to interreplicate variability and adopting strategies to mitigate the consequences of interreplicate variability

Evaluation of selected watershed characteristics to identify best management practices to reduce Nebraskan nitrate loads from Nebraska to the Mississippi/Atchafalaya River basin

Nebraskan streams contribute excess nitrogen to the Mississippi/Atchafalaya River Basin and Gulf of Mexico, which results in major water-quality impairments. Reducing the amount of nitrogen (N) exported in these streams requires the use of best management practices (BMPs) within the landscape. However, proper BMP utilization has rarely been statistically connected to potential controls of N export within watersheds, particularly precipitation and soil characteristics. In this study, 19 watershed variables were evaluated in five categories (hydrological, physiographic, point sources, land use, and soil properties) to determine the characteristics that influenced variable nitrate nitrogen (NO3-N) concentrations in 17 Nebraska watersheds with known high NO3-N export rates. Each characteristic was derived from publicly-available datasets in an effort to develop a multiregional method. Of the 19 variables evaluated, 10 variables (developed, cropland, herbaceous, forest, excessively- drained soils, precipitation, base-flow index, slope, organic matter and point sources) were identified to statistically influence stream NO3-N concentrations. The 17 watersheds were divided into five subset groups using principal component analysis. Distributions of the 10 watershed variables were then used to determine the most applicable BMPs for NO3-N reductions for each stream subset: excessively drained with high baseflow index (Groups 1 and 2), dominantly row crop land usage with well-drained soils, higher precipitation, and an increased tendency for surface runoff concerns (Group 3), highly developed watersheds (Group 4), and single river dominated by wastewater treatment plant discharge (Group 5). Based on the most influential variables a variety of BMPs were recommended, including N fertilizer application management and accounting for N credit from mineralization and NO3-N in irrigation water (Groups 1 and 2), installation of riparian buffers and wetlands (Group 3), urban BMPs such as bioretention cells and permeable pavement (Group 4), and upgrades to the wastewater treatment plant (Group 5). This study provides an improved technique for facilitating watershed management by linking BMPs directly to the characteristics of each watershed to reduce current nitrate export

Performance of Twelve Mass Transfer Based Reference Evapotranspiration Models under Humid Climate

Reference evapotranspiration is very important parameter in the hydrological, agricultural and environmental studies and is accurately estimated by the FAO Penman-Monteith equation (FAO-PM) under different climatic conditions. However, due to data requirement of the FAO-PM equation, there is a need to investigate the applicability of alternative ETo equations under limited data. The objectives of this study were to evaluate twelve mass transfer based reference evapotranspiration equations and determine the impact of ETo equation on long term water management sustainability in Tanzania and Kenya. The results showed that the Albrecht, Brockamp-Wenner, Dalto, Meyer, Rohwer and Oudin ETo equations systematically overestimated the daily ETo at all weather stations with relative errors that varied from 34% to 94% relative to the FAO-PM ETo estimates. The Penman, Mahringer, Trabert, and the Romanenko equations performed best across Tanzania and the South Western Kenya with root mean squared errors ranging from 0.98 to 1.48 mm/day, which are relatively high and mean bias error (MBE) varying from −0.33 to 0.02 mm/day and the absolute mean error (AME) from 0.79 to 1.16 mm/day. For sustainable water management, the Trabert equation could be adopted at Songea, the Mahringer equation at Tabora, the Dalton and/or the Rohwer equations at Eldoret, the Romanenko equation at Dodoma, Songea and Eldoret. However, regional calibration of the most performing equation could improve water management at regional level

Pumping Plant Performance

Irrigation accounts for a large portion of the energy used in Nebraska agriculture. This paper describes a method to estimate the cost of pumping water and compares the amount of energy used by a properly designed and well-maintained pumping plant, represented by the Nebraska Pumping Plant Performance Criteria (NPPPC). The results can help determine the feasibility of repairing the pumping plant. Methods to compare energy sources are also presented. We recommend that you periodically arrange with a well drilling company to test the efficiency of your pump. Worksheets for pumping plant performance are included in the appendix

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska under Full and Deficit Irrigation

Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model performance was promising, as it was executed unaided by measurements of soil water content throughout the season. VRI prescriptions did not correlate well with available water capacity (R2 \u3c 0.4); however, they correlated better with modeled ET in 2018 (R2 = 0. 69, VRI-Full; R2 = 0.55, VRI-Deficit). No significant differences were observed in total intended gross irrigation depth in 2017 (VRI-Full = 351mm, Uniform Full = 344). However, in 2018, VRI resulted in lower mean prescribed gross irrigation than the corresponding uniform treatments (VRI-Full = 265mm, Uniform Full = 282mm, VRI-Deficit = 234mm, and Uniform Deficit = 267mm). Notwithstanding the differences in prescribed irrigation (in 2018), VRI did not affect dry grain yield, with no statistically significant differences being found between any treatments in either year (F = 0.03, p = 0.87 in 2017; F = 0.00, p = 0.96 for VRI/Uniform and F = 0.01, p = 0.93 for Full/Deficit in 2018). Likewise, any reduction in irrigation application apparently did not result in detectable reductions in deep percolation potential or actual evapotranspiration. Additional research is needed to further vet the model as a deficit irrigation management tool. Suggested model improvements include a continuous function for water stress and an optimization routine in computing the basal crop coefficient

Engaging Farmers and the Agriculture Industry Through the Testing Agricultural Performance Solutions Program

The University of Nebraska–Lincoln Testing Agricultural Performance Solutions (TAPS) program involves use of farm management competitions to increase engagement across producers, industry, and universities. Participants make several management decisions throughout the growing season in a controlled field trial held at the university research station. Results are analyzed, and awards are presented for most profitable farm, most efficient farm, and farm with the greatest grain yield. The TAPS program involves several techniques for facilitating participatory assistance, including two-way communication and transformational learning. It has resulted in participants\u27 questioning their past management decisions and realizing that they need to improve their marketing skills to improve profitability

Field Pea Response to Seeding Rate, Depth, and Inoculant in West-Central Nebraska

Increased market demand and larger adoption of field pea (Pisum sativum L.) in semiarid west-central Nebraska has provided opportunities to replace summer fallow and diversify crop rotations. As a relatively new crop, its response to different seeding practices has not been evaluated in this eco-region. Field pea grain yield response to seeding depth (25, 50, and 75 mm), inoculation with Rhizobium leguminosarum bv. viciae (yes and no rhizobia inoculant), and seeding rates (35, 50, 65, 75, 90, 105, and 120 plants m–2) was investigated in 2015 and 2016 at five sites in Perkins County, NE. There were no differences in yield for field pea planted at depths of 25, 50, and 75 mm. Yield differences between inoculated and noninoculated field pea were not observed; however, a lack of nodules on noninoculated field pea plants suggests that carryover of rhizobia in soil with a history of field grown 2 to 3 yr previously was not sufficient to initiate nodulation. Seeding rates resulting in plant populations of 45 to 60 plants m–2 provided the highest economic return; an economic penalty (~$1.05 ha–1) may occur for each additional plant per square meter attained over this plant population. Increasing the seeding rate, however, may help farmers manage risks of hail injury, enhance weed suppression, and increase harvest efficiency. Therefore, field pea grown in semiarid west-central Nebraska should be properly inoculated with rhizobia at every planting, seeded in good moisture at depths ranging from 25 to 75 mm, and have final plant population of at least 60 plants m–2

Water effects on optical canopy sensing for late-season site-specific nitrogen management of maize

The interpretation of optical canopy sensor readings for determining optimal rates of late-season site-specific nitrogen application to corn (Zea mays L.) can be complicated by spatially variable water sufficiency, which can also affect canopy size and/or pigmentation. In 2017 and 2018, corn following corn and corn following soybeans were subjected to irrigation×nitrogen fertilizer treatments in west central Nebraska, USA, to induce variable water sufficiency and variable nitrogen sufficiency. The vegetation index-sensor combinations investigated were the normalized difference vegetation index (NDVI), the normalized difference red edge index (NDRE), and the reflectance ratio of near infrared minus red edge over near infrared minus red (DATT) using ACS-430 active optical sensors; NDVI using SRSNDVI passive optical sensors; and red brightness and a proprietary index using commercial aerial visible imagery. Among these combinations, NDRE and DATT were found to be the most suitable for assessing nitrogen sufficiency within irrigation levels. While DATT was the least sensitive to variable water sufficiency, DATT still tended to decrease with decreasing water sufficiency in high nitrogen treatments, whereas the effect of water sufficiency on DATT was inconsistent in low nitrogen treatments. A new method of quantifying nitrogen sufficiency while accounting for water sufficiency was proposed and generally provided more consistent improvement over the mere averaging of water effects as compared with the canopy chlorophyll content index method. Further elucidation and better handling of water-nitrogen interactions and confounding are expected to become increasingly important as the complexity, automation, and adoption of sensor-based irrigation and nitrogen management increase