Source: UNIVERSITY OF NEBRASKA submitted to NRP
PREDICTABILITY OF WATER DISTRIBUTION AND TRANSPORT ACROSS SPATIAL AND TEMPORAL SCALES: AN APPLICATION ON CROPLAND MANAGEMENT
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
1009760
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Jun 15, 2016
Project End Date
Sep 30, 2020
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
UNIVERSITY OF NEBRASKA
(N/A)
LINCOLN,NE 68583
Performing Department
Biological Systems Engineering
Non Technical Summary
Water resources, both surface water as well as ground water, are vital to Nebraska's agriculture. For example, Nebraska ranks as the fourth state in the nation on ground water use in agriculture and first in the nation on irrigated acreage. In 2012, Nebraska was ranked 3rd and 5th in the nation in corn and soybean production, respectively. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. Unfortunately, in response to irrigation water withdrawals, groundwater levels have declined significantly in several major irrigated areas of the state. Also, groundwater decline can have impacts on streamflow which is important for endangered species and interstate compacts. This factor contributes to the challenge of water, agricultural, and ecosystems sustainability in the state. In consequence, the predictability of productivity of the agro-ecosystem and the consequent preparedness for change in water states is based on our ability to diagnose, forecast, and predict current and future environmental states including water availability and crop production.A key to achieving water and agricultural resources sustainability is to understand the interactions among climate, water availability and water uses in agro-ecosystems. However, human impacts on a natural dynamic equilibrium (or a gradual return to it) of the Earth-life's support system jeopardize efforts to exercise a sustainable development. Rockstrom et al. (2009) identify some of these impacts through eight planetary limits, three of which have exceeded the limits (biodiversity, nitrogen cycle, and climate change) and another three are on their way to do so (land use changes, global freshwater, and ocean acidification). Loss of biodiversity, extensive use of nitrogen, and land-use changes, all are closely related to the expansion and intensification of agricultural activities and reduction of ecosystem services. Also, a changing environment characterized by climate and land-use changes has posed important challenges to identify the pathways to sustain food production and ecosystem services with variable water availability. In the first case, the IPCC attributed climate change to human activities related with fossil fuel combustion at an unprecedented level of confidence (IPCC, 2013), which is leading to more extreme hydrometeorological events (flood and drought), both linked to an increasing global temperature and temporal variability in precipitation. In the second case, land-use changes mainly as a product of agriculture's expansion over large areas has contributed to regional changes in precipitation patterns, which have reached to more than 700,000km2 (3.5 times the size of Nebraska) in less than 25 years in places such as the Amazon (Arima et al 2011). It is expected that an additional 450 million ha will be converted to cropland by 2050 (Rockstrom 2007).All the processes above are interrelated influencing the spatial distribution and temporal variability of water availability, crop production, and ecosystem services across scales. In order to characterize the multi-dimensionality of water-related challenges the Global Water Project (http://thewaterproject.org/) developed a framework where exchanges of water between physical, biological/biogeochemical, and socioeconomic components of the Global Water System (GWS) contribute to regulate the dynamics of the water cycle. Under this framework, understanding the relationships between components of the GWS and the inherent effect of local processes on the global water-cycle dynamics (and vice versa) advances the science and technologic development toward providing more food at higher levels of water productivity.Sustainability is defined by Griggs et al. (2013) as "Economy serving society within Earth-life's support system". In water- and crop-management this definition can be interpreted as a reduction in poverty while environment and economic wealth are maintained. Thus water sustainable development is engineered to anticipate change and facilitate the achievement of water sustainability through improvements in planning, designing, and management of water resources (Loucks, 2000). In this context, sustainable development can be seen as a pathway that tracks how water (or other environmental) states can be prolonged to ultimately achieve sustainability of water and agricultural resources. These pathways, sinuous or straight, are the result of integrating processes that drive the GWS and ultimately define an spatial and temporal representation of sustainability achievement.The multi-dimensionality of the relationships defining sustainable development of water and agricultural resources can be seen as mass and energy fluxes forced by climate and regulated by human activities along the water continuum from the atmosphere to the aquifer. The water continuum from field to global scales integrates processes that regulate water supply/demand. We aim to better understand how these processes (naturally driven or anthropogenically affected) may change over time influencing future water availability and crop production.At field-scale (producers, land/water managers) a diagnostic research on water management includes irrigation scheduling, deficit irrigation (Martin et al., 2010), tillage practices, and drainage. In Nebraska conservation tillage has enjoyed significant adoption rates, and a growing number of producers are using soil water sensors and ET-gages through the influence of the Nebraska Agricultural Water Management Network (NAWMN), UNL Extension, and in some cases industry. However, due to the high spatial variability of soil water, there is a need for meso-scale soil water measurement to provide field average soil water. Despite research and extension efforts, very few producers take the time to calculate their own soil water balance. An online tool that utilizes a soil water balance and a crop growth model is available for soybeans (SoySim), but an equivalent tool needs to be developed for corn.At the sub-field scale, precision agriculture has provided producers the opportunity to manage inputs spatially, including fertilizer, plant population, hybrid, and water. Variable rate irrigation (VRI) technology provides an opportunity to prevent over-application and/or under-application of water, but best management practices are not yet well defined and the benefits of VRI are not well quantified. Previous research has included development of the technology (Kranz et al., 2012), correlating spatial variability in soil water extraction with soil electrical conductivity (EC) (Rudnick & Irmak, 2014), soil water sensor location determined by ET and elevation (Pan et al., 2013) potential energy and water savings (Hillyer and Higins, 2014), and modeling and decision support (McCarthy et al., 2014). Industry service providers for VRI management include CropMetrics and HydroBio.
Animal Health Component
33%
Research Effort Categories
Basic
33%
Applied
33%
Developmental
34%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1110210310030%
1210310205010%
1320430207010%
4050210202010%
2050199209010%
1021820303010%
1117310208010%
4020210310010%
Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships; 111 - Conservation and Efficient Use of Water; 205 - Plant Management Systems; 132 - Weather and Climate; 405 - Drainage and Irrigation Systems and Facilities; 121 - Management of Range Resources; 402 - Engineering Systems and Equipment;

Subject Of Investigation
0310 - River basins; 7310 - Experimental design and statistical methods; 0430 - Climate; 0210 - Water resources; 1820 - Soybean; 0199 - Soil and land, general;

Field Of Science
2070 - Meteorology and climatology; 2090 - Statistics, econometrics, and biometrics; 2020 - Engineering; 2050 - Hydrology; 2080 - Mathematics and computer sciences; 3030 - Information and communication; 3100 - Management;
Goals / Objectives
GoalGeneral objective Particular Objectives Objective 1. Develop and/or improve agriculturally relevant soil moisture observational strategies at two distinct spatial scales, i.e., the sprinkler and center-pivot, using state-of- the-art hydrogeophysical measurement techniques. Objective 2. Increase the productivity of water used for irrigation and protect the quality of water resources through spatial management of irrigation systems. Objective 3 part 1. At the field scale, develop irrigation decision support tools to improve irrigation timing and reduce overall field irrigation water consumption in corn-soybean systems and increase crop water productivity by using corn and soybean simulation models, including the Hybrid-Maize (Yang et al, 2005, 2013), SoySim (Setiyono et al, 2010), and producer specified crop management information and real-time weather data. Objective 3 part 2. Couple crop simulation model with variable rate irrigation technologies to improve timing and amount of irrigation using sub-field scale soil water status and crop growth. Objective 3 part 3. At the regional scale, using crop models to guide assessment of regional irrigation water requirement and rational allocation for high water use efficiency based on crop management practices (crop maturity, planting time, plant population, rotation), soil properties (texture, rooting depth, drainage class), landscape attributes (slope, soil cover), tillage and residue management, and long-term weather pattern. Objective 4. Improve the accuracy of spatial and temporal crop input data acquisition and develop tools for data analysis and producer decision support systems in their crop production systems. Objective 5 part 1. Estimate the contribution of climate forcings (e.g. precipitation) to the spatial distribution and temporal variability of soil moisture and evapotranspiration (ET) across scales. Objective 5 part 2. Develop hydroinformatics techniques to improve process understanding and model integration.
Project Methods
Sprinkler scale soil moisture monitoringBetter characterization of two- and three-dimensional distributions of soil moisture at the spatial scale achievable by variable rate irrigation (i.e., the wetted diameter of a sprinkler) is needed. To overcome this limitation we will collect a series (5-7 surveys) of in-season soil moisture maps using cosmic-ray neutron probes mounted to farm equipment. The recently developed cosmic-ray neutron probe has a horizontal footprint of ~28 ha and vertical penetration depth of ~10 to 50 cm depending on hydrogen content (Desilets and Zreda, 2013; Franz et al., 2012a; Zreda et al., 2008). The spatial soil moisture training datasets will complement the efforts of ECa mapping for soil texture distribution as well as calibration and validation of continuously recording distributed sensor networks. The combination of efforts will be critical in establishing realtime three-dimensional estimates of soil moisture for optimal management of variable rate irrigation technologies.Center pivot scale soil moisture monitoringIn current practice, producers will likely operate a center pivot irrigation system using 1 to 3 profiles of soil moisture sensors to make management decisions about when to run the center-pivot and how much to water. All to often irrigation managers rely on the "hand feel wetness method" by themselves or a hired crop consultant on a weekly basis. In order to provide representative area-average soil moisture data at the center pivot scale we will install a cosmic-ray neutron probe (CRNP) at the center of each field after planting (April). To correspond with the sensitivity of the CRNP (Franz et al., 2012b), we will install up to 12 profiles of Watermark soil moisture sensors from the center point. The sensors will be located at different depths for each profile. In addition we will perform bi-monthly cosmic-ray rover surveys over a 12x12 km grid (Chrisman and Zreda 2013).Quantification of potential benefits of VRIWhile VRI has many potential benefits, producers could make more informed decisions about whether to invest in VRI technology if the benefits were quantified (Evans et al., 2012). One benefit is that VRI can allow crops to utilize stored rain in soils with a high water holding capacity (WHC) before initiating irrigation, while irrigating soils that have limited WHC.Also, the hydrological impact of topography on lateral soil water redistribution will be investigated. Soil water content will be monitored across two hillslopes in an irrigated corn field with a neutron probe, Watermark sensors, and Campbell Scientific 616 sensors. Textural analysis of soil samples will also be considered to account for spatial variability in soil properties. The amount of water that could be saved by using VRI will be estimated.Best management practices for VRIUniform irrigation will be compared to two strategies for VRI management. The first VRI strategy will divide the field into management zones (based on EC, soil type, topography, and yield) and determine irrigation prescriptions based on the mean WHC and the mean available water (measured with a neutron probe) for each management zone.The second VRI strategy will develop dynamic irrigation prescription maps utilizing remote sensing data from unmanned aircraft systems and a spatial soil water balance. Spatial ET will be determined within the Spatial Evapo-Transpiration Modeling Interface (SETMI; Neale et al., 2012).Accurate as-applied irrigation maps will be critical for the analysis. Yield, irrigation applied, ET, and water use efficiency will be compared for the uniform irrigation and the two VRI strategies. Physiological data will also be collected in order to be able to run CornSoyWater for each management zone.Decision support tool development An online irrigation support tool that includes corn and soybean will be developed to help irrigators reduce irrigation water consumption, increase crop yield and water use efficiency and profitability, save energy and reduce leaching losses of nutrients. This technological development will also include the development of a smartphone app for irrigation management for mobile access to the online tool system. The project includes field experiments to monitor corn growth and development (biomass and LAI at key stages, and final yield), as well as continuous monitoring of soil water status at different depths under different irrigation levels.Crop Modeling Simulations of crop growth and development, water consumption and soil water dynamics will be developed. At the irrigated fields indicated in Fig. 1, soil properties of the 6~10 subfield zones derived from cluster analysis of VARI map, along with real-time weather data and crop information (hybrid maturity, planting date, plant population, etc.). Measured soil water data will be used to calibrate model functions and/or parameters. Models will be used to predict when to irrigate for the whole field and how much water is required for each individual zone. During the first two to three seasons, the effect of variable rate irrigation on yield, water consumption and water use efficiency will be evaluated and compared with regular irrigation strategy, and model functions for irrigation timing and amount will be tuned for optimal results.Use of corn production and crop management data farmers reported to NRDs in combination with survey data conducted in selected regions, as well as the data collected in NAWMN. Irrigation technologies will be analyzed to quantify crop yield gap, water productivity, and water productivity gap in different regions across Nebraska.Precision AgricultureGeographic Information System tools will be used to create as-applied maps with higher detail and resolution to more accurately represent crop input distribution (Fulton et al., 2013; Luck et al., 2011). Geospatial analyses will include data from sources other than field equipment including soil properties, field topography for terrain analysis, soil water status, and crop canopy reflectance measurements.).Studies will be conducted at UNL research farms and with cooperating producers (when possible) by instrumenting field machinery (e.g., center pivot irrigation systems and mobile field application equipment) and recording georeferenced field application data. Current research projects will be leveraged to increase data collection information including the SENSE project which focuses on in-season N management (Ferguson, Luck, et al.) and the WEAI phase II project (Luck, Heeren, et al.) which combines center pivot monitoring with geospatial data analysis techniques.Integrated HydrologyThree models will be used: (a) Variable Infiltration Capacity model (VIC; Liang et al. 1994), which is a land surface model aimed to provide lower boundary conditions and upper boundary conditions to an atmospheric and groundwater-farming process model, respectively; (b) Ocean-Land-Atmospheric Model (Walko and Avissar, 2008a and 2008b) is a multi-scale climate model that runs globally and can simulate at high resolution water and energy, as well as the atmosphere dynamics; (c) MODFLOW-Farming Process (Hanson et al. 2010) is an integrated model composed by a channel distribution surface model, vadose zone, and groundwater modelsHydroinformaticsSources of data and user needs vary across the state. The development of the Water for Food Interoperability/Information System (WaFIS) uses an interoperation interface to cope with diversity and management of data to pursue a wider and more open accessibility of information. WaFIS will collect data to produce: 1) Standardized and multi-source water-related variables; 2) user-friendly access to historical water-related data (for academics or farmers); and ultimately 3) meaningful representations of integrated climate-, water- and agriculture-related information for stakeholders.

Progress 06/15/16 to 09/30/20

Outputs
Target Audience:Water resources, both surface water, as well as groundwater, are vital to Nebraska agriculture. For example, Nebraska ranks as the fourth state in the nation on groundwater use in agriculture and first in the country on irrigated acreage. In 2012, Nebraska was ranked 3rd and 5th in corn and soybean production, respectively. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. Unfortunately, in response to irrigation water withdrawals, groundwater levels have declined significantly in several major irrigated areas of the state. Also, groundwater decline can impact streamflow, which is essential for endangered species and interstate compacts. This factor contributes to the challenge of water, agricultural, and ecosystem sustainability in the state. Consequently, the predictability of productivity of the agro-ecosystem and the consequent preparedness for change in future environmental states is subject to our ability to diagnose, forecast, and predict current and water availability and crop production. A key to achieving water and agricultural resources sustainability is understanding the interactions among climate, water availability, and water uses in agro-ecosystems. The multi-dimensionality of the relationships defining sustainable development of water and agricultural resources can be seen as mass and energy fluxes forced by climate and regulated by human activities along the water continuum from the aquifer's atmosphere. In this project, we improved our understanding of how these processes (naturally driven or anthropogenically affected) change over time, influencing our ability to diagnose and predict water availability and crop production. At the field-scale, the PIs Luck and Heeren developed analytics that helped producers, land/water managers improve water and fertilizers. The PIs Franz, Wang, and Munoz-Arriola integrated observations and models, creating cross-scale water and agriculture management tools. Irrigation scheduling and nutrient transport became accessible to farmers and researchers as par to PIs Luck-Heeren, and Yang efforts, which later allowed Franz to apply novel geophysical technologies. All PIs embarked in the development of information technologies. Such technologies became online tools used to balance soil water balance and crop growth based on observations and statistical, numerical, and data-driven models. For example, Yang's SoySim 9and corn-based), Heeren's VIR-remote sensing tool, Franz's Cosmic Ray-based analytics, Lucks geospatial techniques, and Munoz-Arriola data-driven groundwater predictions. These tools were developed as part of this project and other projects funded by local to federal agencies. Between 2016 and 2020, the project fostered 101 peer-reviewed publications, 11 book chapters, 56 extension publications, 129 conference presentations, 69 extension presentations, 49 undergraduate projects, 68 MS projects, 37 Ph.D. projects, and 12 post-doctoral projects. Changes/Problems:COVID-19 affected all the activities, specifically, those research activities with a field components, and consequently those in the intersection of research, extension and in-person teaching. What opportunities for training and professional development has the project provided?PI-Franz has taught formal courses at the university focused on Freshman non-science majors, Sophomores in Natural Resources, and the Seniors and Graduate students in Natural Resources. In addition PI-Franz co-developed the Freshman level course intended for non-science majors as part of an NSF grant in Science Literacy (2 peer reviewed pub). In addition, PI-Franz has taught 3-day long online courses on the cosmic-ray neutron sensor technique focused on scientists in the Andes and Himalayan region. The classs consisted of 15 to 25 government scientists from countries around the world. Also, this objective resulted in 29 of peer reviewed publications, 3 book chapters; 3 extension publications, 6 undergraduate projects, 9 MS projects, and 6 PhD projects. The results of the research have led to 12 grant applications PI-Heeren has taught or co-taught undergraduate course (i.e., MSYM 462 Equipment Systems, 20 students/semester) and graduate course (i.e., MSYM 855 Irrigation Systems Management, ~10-20 students/semester). Objective 2 of the Hatch project provided scholarly material for irrigation courses. Objective 2 also resulted in 24 of peer reviewed publications, 3 book chapters; 16 extension publications, 13 undergraduate projects, 10 MS projects, and 6 PhD projects. The results of the research have led to 20 grant applications. PI-Yang taught crop modeling (AGRO/NRES 906, 3 credits, 7 students). This objective resulted in 8 of peer reviewed publications, 6 extension publications, 1 undergraduate projects, 3 MS projects, and 2 PhD projects. The results of the research have led to 2 grant applications. PI-Luck provided recorded lectures for one undergraduate course (AGEN/AGRO/MSYM 431: Site-Specific Crop Management) in support of Objective 4 of the Hatch project. Objective 4 also resulted in 22 of peer reviewed publications, 27 extension publications, 5 undergraduate projects, 21 MS projects, and 5 PhD projects. The results of the research have led to 11 grant applications. PI- Munoz-Arriola taught one formal courses (Attribution Science and Decision-Making is Socio(agro)ecological Systems, 4 graduate students at UNL and 7 graduate students at the University of Sao Paulo). The project funded by National Science Foundation (a 3-million-dollar grant) has 10 master and 6 PhD students on Resilient Complex Agricultural Landscapes (expecting to fund additional 3 graduate students in Natural Resources, Biological and Computational Engineering, Agronomy, and Political Sciences, among other areas, in the following four years). The activities above are cmplemented by PI Munoz-Arriola's lab activities resulting in 18 of peer reviewed publications, 2 book chapters; 4 extension publications, 24 undergraduate projects, 24 MS projects, and 17 PhD projects (quantified individually per year). The results of the research have led to 18 grant applications. How have the results been disseminated to communities of interest?The PIs have disseminated their contributions to this project to farmers and communities in Nebraska through extension talks and publications. The topics encompas emerging sensing and information technologies, as well as improved and novel analytics to traditional water and crop management. The team of PIs has had the oportunity to communicate their findings in multiple national and international conferences, highliging the role of collective thinking and development and the support of USDA to such research, extension and teaching endeavors. PI-Franz was presenter 11 conference presentationsand 8 extension presentation, including keynote talks and international workshops. PI-Heeren was presenter or coauthor on 9 conference presentations in 2020. PI-Heeren also has given multiple guest lectures for courses at UNL. His work has been presented at multiple local venues and national and international conferences (35 conference presentations, 3 extension presentation). PI-Yang has taught at UNL Soil School classes to about attendees and multiple invited keynote presentations in the US and China (i.e., the Plant Nutrition and Fertilizer Association annual conference). His communications reach 3 conference presentations, 4 extension presentation. PI-Luck was presenter or coauthor on 17 conference presentations and 42 extension presentations. He has also lead the NE Extension Digital Ag Workshops, hosted on the Teachable.com web platform. TheNE Extension Digital Ag Workshops are online learning opportunities to interested agricultural professionals (over 100 registered as of the end of this year). PI-Munoz-Arriola was presenter or coauthor on 63 conference presentations and 6 extension presentation. His talks and teaching include countries such as the Netherlands, Brazil, India, and Mexico. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? MA= Major Activities; DA=Data Collected; SM=Summary Statistics; KO=Key Outcomes Objective 1. MA: Installation and monitoring of 10 cosmic-ray neutron probes across Nebraska. DA: Hourly soil moisture data at 10 sites and multiple geophysical spatial maps collected during the span of the project. KO: Point-scale soil moisture monitoring is challenging as irrigation decisions are made on areas. The disconnect and gap between the point scale and area-average values desired by producers can be addressed through the use of geophysical methods and scaling approaches. In addition, the description of soil properties like field capacity and wilting point over areas can be better approximated using geophysical approaches. Research aimed to improve the cosmic-ray neutron probe method and applications to irrigation agriculture, including improvements in the algorithm. The cosmic-ray neutron probe technology is a cutting-edge technology with potential to be included in advanced irrigation management and other precision ag applications in the future. PI-Franz has consolidated a global leadership in developing this technology via active projects and collaborations across the USA, Europe, Africa, Asia, and Australia. Of particular note is PI-Franz's role in a 5-yr United Nations Coordinated Research Project which includes participants from 10 developing countries. Objective 2. MA: Remote sensing imagery from satellites and unmanned aircraft were used along with the SETMI model in order to quantify spatial variability in ET and to develop variable rate irrigation (VRI) prescription maps. Research was implemented at a sub-humid field site (Mead, NE). This project led to the establishment of a new irrigation technology project in east-central NE with sensors mounted on the center pivot, in partnership with USDA-ARS and Valmont Industries. KO: VRI is a technology that may improve irrigation water productivity, reducing pumping and nitrate leaching. There is a need to quantify the benefits of VRI and to develop a decision support system for VRI. Our research program in VRI is establishing UNL and the DWFI as national and international leaders in field-scale research in VRI management. Field implementation of prescription maps demonstrated that effective management of VRI will likely require a combination of both remote sensing and soil water monitoring. Objective 3 part 1. MA: developed SoySim and CornAid. Both are simulation models that combines decision makings of nitrogen rate and real-time irrigation scheduling for soybean and corn. They have the capability of unlimited number of zones in a field to aid variable rate management Objective 3 part 2. MA: conducted field experiment in farmer's production fields to test the online app CornSoyWater DA: collected crop, soil, and weather data from six experimental fields for testing the CornSoyWater online app Objective 3 part 3. MA: used the Hybrid-Maize to make in-season corn yield predictions for major states in the US Corn Belt. KO: seven CropWatch extension publications on corn yield forecast Objective 4. MA: Sixteen study sites were conducted with grower/cooperators or on UNL research farms which were directed at in-season nitrogen (N) management using crop canopy sensors and algorithms. Four sites utilized center pivot-based fertigation, while the remaining eight sites utilized active sensors on a high clearance applicator in irrigated and rainfed production systems. An additional two sites studied starter-N rates across a research field site sponsored by an industry cooperator. Two field studies were conducted with grower/cooperators across NE focused on studying the effect of soybean seeding population on yield and profitability. These studies utilized the growers' precision agriculture technology to deploy and assess these field studies. DA: Weekly aerial and proximal multi-spectral crop reflectance data were collected for each field site along with as-applied data (planting or N application) and georeferenced yield monitor datasets. Georeferenced in-season crop scouting datasets were also documented for the majority of field sites. KO: Key outcomes for work accomplished under objective 4 were: 1) N applications using sensor-based management continued to show the potential for reducing the amount of N required for corn production in irrigated sites with little negative impact on crop yields. Rainfed sites were more challenging and yield losses were noted. . Yield and profitability may not always be improved, however the corresponding reductions in N introduced into the environment are largely unknown, but likely significant. A significant output from the project has been the development of IP in the form of an automated N prescription tool for Fertigated N management (via center pivots) that will likely be protected by the University commercialization office. Producers are continually looking for ways to reduce input costs on their farms and reducing soybean seeding rates can likely improve on-farm economics by an average of $15/ac (up to $47/ac) based on two studies sites completed in 2019). SM: Preliminary analyses have indicated that using sensor-based systems and algorithms for N management improved N-use efficiency in over 90% of field sites compared to current grower/cooperator methods. In rainfed sites, yield losses were common as we were not able to approach economic optimum N rates. Results indicated that soybean seeding rates could be reduced by 30 to 60 ksds/ac without a significant penalty towards yield or profitability in 100% of field sites compared to current grower rates which reinforced previous years' studies. Objective 5 parts 1 and 2. MA: (i) Development of the Genetic-by-Environment (GEEN) phenotype prediction tool; (ii) development of two algorithms coupling a covariance matrix approach and an artificial neural network -both-- to a global sensitivity analysis algorithm for uncertainty's characterization and propagation of hydroclimate variables ; (iii) development of an algorithm for geospatial point to field-scale upscaling of atrazine; (iv) construction of algorithms to simulte tethered drone flying trajectories. DC: Developed four algorithms; one architecture of software; characterization and propagation of uncertainty in groundwater well-level databases; and consolidation and uncertainty assessment algorithms and databases for large-scale, high throughput phenotyping in the US. KO: To date the greatest impact has been (i) the development of software that simulates phenotypes and the identification of uncertainties driven by hydroclimate variables; (ii) the characterization and propagation of uncertainties in input variables to simulate groundwater well-levels using data-driven models and global sensitivity analyses; and (iii) three proposals submitted as PI (USDA-NIFA FACT, USGS 104G, and BAYER), one rejected two pending.

Publications

  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Vather, T., C. S. Everson, and T. E. Franz (2020), The Applicability of the Cosmic Ray Neutron Sensor to Simultaneously Monitor Soil Water Content and Biomass in an Acacia mearnsii Forest, Hydrology, 7(3), 48.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Li, Y., K. Y. Guan, B. Peng, T. E. Franz, B. Wardlow, and M. Pan (2020), Quantifying irrigation cooling benefits to maize yield in the US Midwest, Global Change Biology, 26(5), 3065-3078. doi:10.1111/gcb.15002.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Franz, T. E., S. Pokal, J. P. Gibson, Y. Z. Zhou, H. Gholizadeh, F. A. Tenorio, D. Rudnick, D. Heeren, M. McCabe, M. Ziliani, Z. Jin, K. Y. Guan, M. Pan, J. Gates, and B. Wardlow (2020), The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield, Field Crop. Res., 252, 17. doi:10.1016/j.fcr.2020.107788.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Lo, T. H., D. R. Rudnick, K. C. DeJonge, G. Bai, H. N. Nakabuye, A. Katimbo, Y. Ge, T. E. Franz, X. Qiao, and D. M. Heeren (2020), Differences in soil water changes and canopy temperature under varying water� nitrogen sufficiency for maize, Irrigation Science, 1-16.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Shearer, C.A., J.D. Luck, J.T. Evans3, J.P. Fulton, and A. Sharda. Pesticide application coverage training (PACT) tool: development and evaluation of a sprayer performance diagnostic tool. Precision Agric. DOI: 10.1007/s11119-020-09761-z
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Sivakumar, A.N.V., J.T. Li, S. Scott, E. Psota, A. Jhala, J.D. Luck, and Y. Shi. 2020. Comparison of object detection and patch-based classification deep learning models on mid to late season weed detection in UAV imagery. Remote Sensing. 12(3). DOI: 10.3390/rs12132136
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Vieira, B.C., J.D. Luck, K.L. Amundsen, R. Werle, T.A. Gaines, and G.R. Kruger. 2020. Herbicide drift exposure leads to reduced herbicide sensitivity in Amaranthus spp. Sci. Reports. 10(1). DOI: 10.1038/s41598-020-59126-9
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Evans, J.T.3, S.K. Pitla, J.D. Luck, and M.F. Kocher. 2020. Row crop grain harvester path optimization in headland patterns. Computers Electronics Agric. 171: https://doi.org/10.1016/j.compag.2020.105295
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Singh, J., D.M. Heeren, D. Rudnick, W. Woldt, Y. Ge, and J.D. Luck. 2020. Soil structure and texture effects on the precision of soil water content measurements by a capacitance-based electromagnetic sensor. Trans. ASABE. 63(1): 141-152.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Bullock, D.S., M. Boerngen, H. Tao, B. Maxwell , J.D. Luck, L.S. Shiratsuchi, L. Puntel, and N.F. Martin. 2019. The data-intensive farm management project: changing agronomic research through on-farm precision experimentation. Agronomy J. 111(6): 2736-2746.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Evett, S. R., P. D. Colaizzi, F. R. Lamm, S. A. OShaughnessy, D. M. Heeren, T. J. Trout, W. L. Kranz, and X. Lin. 2020. Past, present and future of irrigation on the U.S. Great Plains. Transactions of the ASABE 63(3): 703-729, doi: 10.13031/trans.13620.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Chavez, J. L., A. F. Torres-Rua, W. E. Woldt, H. Zhang, C. Robertson, G. W. Marek, D. Wang, D. M. Heeren, S. Taghvaeian, and C. M. U. Neale 2020. A decade of unmanned aerial systems in irrigated agriculture in the Western U.S. Applied Engineering in Agriculture 36(4): 423-436, doi: 10.13031/aea.13941.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Barker, J. B., W. E. Woldt, B. D. Wardlow, M. S. Maguire, B. C. Leavitt, C. M. U. Neale, and D. M. Heeren. 2020. Calibration of a common shortwave multispectral camera system for quantitative agricultural applications. Precision Agriculture 21: 922-935, doi: 10.1007/s11119-019-09701-6.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Bhatti, S., D. M. Heeren, J. B. Barker, C. M. U. Neale, W. E. Woldt, M. S. Maguire, and D. R. Rudnick. 2020. Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery. Agricultural Water Management 230, doi: 10.1016/j.agwat.2019.105950.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Lo, T., D. R. Rudnick, J. Singh, H. N. Nakabuye, A. Katimbo, D. M. Heeren, and Y. Ge. 2020. Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors. Agricultural Water Management 231, doi: 10.1016/j.agwat.2019.105984.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Koehler-Cole, K., R. W. Elmore, H. Blanco-Canqui, C. A. Francis, C. A. Shapiro, C. A. Proctor, S. Ruis, D. M. Heeren, S. Irmak, and R. B. Ferguson. 2020. Cover crop productivity and subsequent soybean yield in the Western Corn Belt. Agronomy Journal 112: 26492663, doi: 10.1002/agj2.20232.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Pandey, V., P. K. Srivastava, R. K. Mall, F. Munoz-Arriola, and D. Han (2020). Multi-Satellite Precipitation Products for Meteorological Drought Assessment and Forecasting in Bundelkhand region of Central India. Geocarto Internacional. https://doi.org/10.1080/10106049.2020.1801862.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Amaranto, A., F. Pianosi, D. Solomatine, G. Corzo-Perez, and F. Munoz-Arriola (2020). Sensitivity Analysis of Hydroclimatic Controls of Data-driven Groundwater Forecast in Irrigated Croplands. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2020.124957.
  • Type: Books Status: Published Year Published: 2020 Citation: Kumar, M., F. Munoz-Arriola, H. Furumai, and T Chaminda (2020) RESILIENCE, RESPONSE, AND RISK IN WATER SYSTEMS: SHIFTS IN NATURAL FORCINGS AND MANAGEMENT PARADIGMS. Springer Transactions in Civil and Environmental Engineering. ISBN#978-981-15-4667-9: 395pp.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Rico, D.A., Carrick Detweiler, and Francisco Mu�oz-Arriola (2020). Power-over-Tether UAS Leveraged for Nearly-Indefinite Meteorological Data Acquisition. 2020 ASABE Annual International Meeting, Paper No. 1345. DOI: https://doi.org/10.13031/aim.202001345.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Sarzaeim, P., D. Jarquin, and F. Mu�oz-Arriola (2020). Analytics for climate-uncertainty estimation and propagation in maize-phenotype predictions. 2020 ASABE Annual International Meeting, Paper No. 1165. DOI: https://doi.org/10.13031/aim. 202020884.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Garret Williams, Parisa Sarzaeim, and Francisco Mu�oz-Arriola (2020). Simplification of Complex Environmental Variations on Maize-Phenotype Predictability. 2020 ASABE Annual International Meeting, Paper No. 1291. DOI: https://doi.org/10.13031/aim.201291.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Luciano Alves de Oliveira, Bryan L Woodbury, Jarbas Honorio de Miranda, and Francisco Munoz-Arriola (2020). Geospatial upscaling of atrazines transport using electromagnetic induction across point to field scale (2020). ASABE Annual International Meeting, Paper No. 884. DOI: https://doi.org/10.13031/aim.202001165.
  • Type: Book Chapters Status: Accepted Year Published: 2021 Citation: Janin1, J., F. Munoz-Arriola, and Deepak Khare (Accepted). Short-Term Resilience and Transformation of Urban Socio-environmental Systems to COVID-19 Lockdowns in India using Air Quality as Proxy. In ENVIRONMENTAL RESILIENCE AND TRANSFORMATION IN TIMES OF COVID-19 (Eds. Ramanathan et al). Elsevier
  • Type: Books Status: Awaiting Publication Year Published: 2021 Citation: Ramanathan, A.L.R., S. Chidambaram, M.P. Jonathan, M.V. Prasana, P. Kumar, and F. Munoz-Arriola (Accepted). ENVIRONMENTAL RESILIENCE AND TRANSFORMATION IN TIMES OF COVID-19: CLIMATE CHANGE EFFECTS ON ENVIRONMENTAL FUNCTIONALITY. Elsevier.


Progress 10/01/18 to 09/30/19

Outputs
Target Audience: Nothing Reported Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?PI-Heeren taught or co-taught two undergraduate courses (MSYM 452 Irrigation Systems Management, 44 students; MSYM 462 Equipment Systems, 37 students) and one graduate course (MSYM 855 Irrigation Systems Management, 9 students) in 2019. Objective 2 of the Hatch project provided scholarly material for irrigation courses. Objective 2 also supported 1.5 PhD students, 0.5 MS students, and 5 undergraduate research assistants. PI- Munoz-Arriola taught two formal courses (Soil and Water Resources Engineering, 17 undergraduate students;Hydroclimatology 3 undergraduate and 9 graduate students) and co-taught two formal Courses (Complexity Science in Food, Energy, Water, and Ecosystem Services Systems; 17 graduate students; and Hydraulic Systems in Europe, 9 graduate students). The project funded by National Science Foundation (a 3-million dollar grant) has 10 master and 5 PhD students on Resilient Complex Agricultural Landscapes (expecting to fund additional 9 graduate students in Natural Resources, Biological and Computational Engineering, Agronomy, and Political Sciences, among other areas, in the following four years). I received funding for two internal projects to study the sustainability of irrigation in Nebraska and the use of data-driven models to explore the integration of water quality and quantity in irrigated landscapes. Supported research experiences for (i) three undergraduates (66% students of minority and underrepresented groups in science and engineering); (ii) 1.5 master's and 3.5 Ph.D. students; (iii) one postdoc and 0.25 Research Assistant Professor; and (iv) one visiting scholar. PI-Yang taught crop modeling (AGRO/NRES 906, 3 credits, 7 students). PI-Luck co-instructed one undergraduate course (AGEN/AGRO/MSYM 431: Site-Specific Crop Management) with 65 students in support of Objective 4 of the Hatch project. Objective 4 also supported 2 PhD students, 3 MS students, and 2 undergraduate research assistants. How have the results been disseminated to communities of interest?PI-Heeren was presenter or coauthor on 10 conference presentations and 2 invited presentations in 2018. PI-Heeren also gave 2 guest lectures for courses at UNL. PI-Munoz-Arriola was presenter or coauthor on 16 conference presentations and 1 invited presentation. Also, was guest lecturer in one course. PI-Yang gave one UNL Soil School class to about attendees and one invited keynote presentation to China's Plant Nutrition and Fertilizer Association annual conference. PI-Luck was presenter or coauthor on 8 research conference presentations and 20 extension presentations in 2019. The NE Extension Digital Ag Workshops were hosted on the Teachable.com web platform to offer online learning opportunities to interested agricultural professionals (over 40 registered as of the end of this year). What do you plan to do during the next reporting period to accomplish the goals?PI-Heeren will continue to lead field research in variable rate irrigation and other technology for center pivot management. Team members in 2019 will include 1.5 Ph-D students and 0.5 MS students. PI-Luck will continue to lead field research activities directed at sensor-based nitrogen management practices in 2020. Team members in 2020 will include 2 PhD students, 3 MS students, and 2 research technicians. PI-Yang will continue testing the CornSoyWater irrigation app and the CornAid model using field data. Will also promote their uses by farmers, crop advisors and other professionals.

Impacts
What was accomplished under these goals? Objective 1. MA: Installation and monitoring of 10 cosmic-ray neutron probes across Nebraska DA: Hourly soil moisture data at 10 sites and 70 geophysical spatial maps. KO: Point-scale soil moisture monitoring is challenging as irrigation decisions are made on areas. The disconnect and gap between the point scale and area-average values desired by producers can be addressed through the use of geophysical methods and scaling approaches. In addition, the description of soil properties like field capacity and wilting point over areas can be better approximated using geophysical approaches. Research aimed to improve the cosmic-ray neutron probe method and applications to irrigation agriculture, including improvements in the algorithm. The cosmic-ray neutron probe technology is a cutting edge technology that has the potential to be included in advanced irrigation management and other precision ag applications in the future. PI-Franz continues to be a global leader in developing this technology via active projects and collaborations across the USA, Europe, Africa, Asia, and Australia. Of particular note is PI-Franz's role in a 5-yr United Nations Coordinated Research Project which includes participants from 10 developing countries. Objective 2. MA: Remote sensing imagery from satellites and unmanned aircraft were used along with the SETMI model in order to quantify spatial variability in ET and to develop variable rate irrigation (VRI) prescription maps. Research was implement at a sub-humid field site (Mead, NE). KO: VRI is a technology that may improve irrigation water productivity, reducing pumping and nitrate leaching. There is a need to quantify the benefits of VRI and to develop a decision support system for VRI. Our research program in VRI is establishing UNL and the DWFI as national and international leaders in field-scale research in VRI management. Field implementation of prescription maps demonstrated that effective management of VRI will likely require a combination of both remote sensing and soil water monitoring. Objective 3 part 1. MA: developed CornAid: a simulation model that combines decision makings of nitrogen rate and real-time irrigation scheduling for corn. It has the capability of unlimited number of zones in a field to aid variable rate management Objective 3 part 2. MA: conducted field experiment in farmer's production fields to test the online app CornSoyWater DA: collected crop, soil, and weather data from six experimental fields for testing the CornSoyWater online app Objective 3 part 3. MA: used the Hybrid-Maize to make in-season corn yield predictions for major states in the US Corn Belt. KO: seven CropWatch extension publications on corn yield forecast Objective 4. MA: Fourteen study sites were conducted with grower/cooperators which were directed at in-season nitrogen (N) management using crop canopy sensors and algorithms. Six sites utilized center pivot-based fertigation, while the remaining eight sites utilized active sensors on a high clearance applicator in irrigated and rainfed production systems. An additional site studied N rates across a grower/cooperator field using their preferred N management system. Seven field studies were conducted with grower/cooperators across NE focused on studying the effect of soybean seeding population on yield and profitability. These studies utilized the growers' precision agriculture technology to deploy and assess these field studies. DA: Aerial and proximal crop reflectance data were collected for each field site along with as-applied data (planting or N application) and georeferenced yield monitor datasets. SS: Preliminary analyses have indicated that using sensor-based systems and algorithms for N management improved N-use efficiency in 100% of field sites compared to current grower/cooperator methods. Results indicated that soybean seeding rates could be reduced by 30 to 60 ksds/ac without a significant penalty towards yield or profitability in 100% of field sites compared to current grower rates. KO: Key outcomes for work accomplished under objective 4 are: 1) N applications using sensor-based management can reduce the amount of N required for corn production in rainfed and irrigated sites. Yield and profitability may not always be improved, however the corresponding reductions in N introduced into the environment are largely unknown, but likely significant. Producers are continually looking for ways to reduce input costs on their farms and reducing soybean seeding rates can likely improve on-farm economics by an average of $15/ac (up to $47/ac) based on six studies sites completed in 2019). Objective 5 parts 1 and 2. MA: (i) Development of two algorithms (Constrained Variable Selection and Multi Model Combination) used to select input variables' lag-times and expand the selection in the geospacer; (ii) development of the software NEO-SAT, An information support system for flood-disaster management; (iii) implementation of data-driven models to improve sub-seasonal predictability of groundwater well level changes in irrigated landscapes across the High Plains Aquifer; (iv) construction of a tethered drone used to launch proximal sensing capabilities that enables long-term, high frequency, high spatial resolution and wide monitoring; (v) implementation of nonlinear support vector machine-based regression (SVR) model to fuse soil moisture (remote sensing) and precipitation data (field-based observations) for near-real time precipitation now casts; and (vi) identification of regime shifts in large-scale areas dominated by agriculture. DC: Developed two algorithms; one architecture of software; improvement of groundwater well-level databases; and development of algorithms and databases for large-scale, high throughput phenotyping in the US. KO: To date the greatest impact has been (i) the development of software to assess EHCEs and their impact on small rural communities in Nebraska and large-scale agricultural areas in India; (ii) the geospatial expansion of input variables for improvements of data-driven models; and (iii) three proposals submitted as PI (USDA-NIFA FACT, NSF Coupled Natural Human Systems, and Nebraska Environmental Trust Fund), one rejected two pending.

Publications

  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Vather, T., C. Everson, and T. E. Franz (2019), Calibration and Validation of the Cosmic Ray Neutron Rover for Soil Water Mapping within Two South African Land Classes, Hydrology 6(3). doi:10.3390/hydrology6030065.
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Barker, J. B., S. Bhatti, D. M. Heeren, C. M. U. Neale, and D. R. Rudnick. 2019. Variable rate irrigation of maize and soybean in West-Central Nebraska under full and deficit irrigation. Frontiers in Big Data 2(34), doi: 10.3389/fdata.2019.00034. (Hatch acknowledged? Yes)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Halihan, T., R. B. Miller, D. Correll, D. M. Heeren, and G. A. Fox. 2019. Field evidence of a natural capillary barrier in a gravel alluvial aquifer. Vadose Zone Journal 18:180008, doi:10.2136/vzj2018.01.0008. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: OShaughnessy, S. A., S. R. Evett, P. D. Colaizzi, M. A. Andrade, T. H. Marek, D. M. Heeren, F. R. Lamm, and J. L. LaRue. 2019. Identifying advantages and disadvantages of variable rate irrigation  an updated review. Applied Engineering in Agriculture 35(6): 837-852, doi: 10.13031/aea.13128. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: OShaughnessy, S. A., S. R. Evett, P. D. Colaizzi, M. A. Andrade, T. H. Marek, D. M. Heeren, F. R. Lamm, and J. L. LaRue. 2019. Identifying advantages and disadvantages of variable rate irrigation  an updated review. Applied Engineering in Agriculture 35(6): 837-852, doi: 10.13031/aea.13128.
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Lo, T., D. R. Rudnick, B. T. Krienke, D. M. Heeren, Y. Ge, and T. M. Shaver. 2019. Water effects on optical canopy sensing for late-season site-specific nitrogen management of maize. Computers and Electronics in Agriculture 162: 154-164, doi: 10.1016/j.compag.2019.04.006. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Mendes, W. R., F. M. U. Ara�jo, R. Dutta, and D. M. Heeren. 2019. Fuzzy control system for variable rate irrigation using remote sensing. Expert Systems with Applications 124: 13-24, doi: 10.1016/j.eswa.2019.01.043. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Ashish Kumar, RAAJ Ramsankaran, Luca Brocca, Francisco Munoz-Arriola (2019). A Machine learning approach for improving near-real-time satellite-based rainfall estimates by integrating soil moisture. Remote Sensing. doi:10.3390/rs11192221 (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Amaranto, A., F. Munoz-Arriola, G. Corzo-Perez, and D. Solomatine (2019). A Spatially enhanced data-driven multi-model to improve semi-seasonal groundwater forecasts in the High Plains aquifer, USA. Water Resources Research. DOI:10.1029/2018WR024301 (Hatch acknowledged? Yes)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Khan, M., F. Munoz-Arriola, R. Shaik3, and P. Greer1 (2019). Spatial heterogeneity of temporal shifts in extreme precipitation across India. Journal of Climate Change. DOI: 10.3233/JCC190003. (Hatch acknowledged? Yes)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Shaik R., F. Munoz-Arriola, D. A. Rico, and S. L. Bartelt-Hunt (2019). Modelling Water Temperatures Sensitivity to Atmospheric Warming and River Flow. In Environmental Biotechnology: for sustainable future (Eds. R. B. Sobti, N. Arora, and R. Kothari) ISBN 978-981-10-7283-3. (Hatch acknowledged? Yes)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Vieira, B.C., J.D. Luck, K.L. Amundsen, T.A. Gaines, R. Werle, and G.R. Kruger. 2019. Response of Amaranthus spp. Following exposure to sublethal herbicide rates via spray particle drift. PLoS ONE 14(7): e0220014. https://doi.org/10.1371/journal.pone.0220014 (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Rohrer, R.A.3, S.K. Pitla, and J.D. Luck. 2019. Tractor can bus interface tools and application development for real-time data analysis. Computers Electronics Agric. DOI: https://doi.org/10.1016/j.compag.2019.06.002 (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Butts, T.R., C.A. Samples, L.X. Franca, D.M. Dodds, D.B. Reynolds, J.W. Adams, R.K. Zollinger, K.A. Howatt, B.K. Fritz, W.C. Hoffmann, J.D. Luck, and G.R. Kruger. 2019. Optimum droplet size using a pulse-width modulation sprayer for applications of 2,4-D choline plus glyphosate. Agron J. 111(3):1425-1432. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Butts, T.R., C.A. Samples, L.X. Franca, D.M. Dodds, D.B. Reynolds, J.W. Adams, R.K. Zollinger, K.A. Howatt, B.K. Fritz, W.C. Hoffmann, J.D. Luck, and G.R. Kruger. 2019. Droplet size impact on dicamba plus glyphosate tank-mixture efficacy. Weed Tech. 33(1):66-74. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Luck, J.D., S.A. Shearer, and M.P. Sama. 2019. Development and preliminary evaluation of an integrated individual nozzle direct injection/carrier flow rate control system for pesticide applications. Trans. ASABE. 62(2): 505-514 (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Butts, T.R., J.D. Luck, B.K. Fritz, W.C. Hoffmann, and G.R. Kruger. 2019. Evaluation of spray pattern uniformity using three unique analyses as impacted by nozzle, pressure, and pulse-width modulation duty cycle. Pest Mgmt. Sci. 75(7): 1875-1886. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Butts, T.R., L.E. Butts, J.D. Luck, B.K. Fritz, W.C. Hoffmann, and G.R. Kruger. 2019. Droplet size and nozzle tip pressure from a pulse-width modulation sprayer. Biosys. Eng. 178(2019) 52-69. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Butts, T.R., W.C. Hoffmann, J.D. Luck, and G.R. Kruger. 2019. Droplet velocity from broadcast agricultural nozzles as influenced by pulse-width modulation. Pesticide Formulation and Delivery Systems: 38th Volume, Innovative Application, Formulation and Adjuvant Technologies. ASTM STP 1610, B.K. Fritz and T.R. Butts, Eds. ASTM International, West Conshohocken, PA, pp. 24-52, DOI: 10.1520/STP161020170192. (Hatch acknowledged? No)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Michel Rocha da Silva, Nereu Augusto Streck, Haishun Yang, Claudio Ogoshi, Alencar Junior Zanon, Ioran Guedes Rossato, Geter Alves Machado, Lorenzo Dalcin Meus, Tuira Barcellos, Francisco Tonetto, Vladison Fogliato, Pablo Mazzuco de Souza, Luciano Alegre, Isabela Bulegon Pilecco, Mois�s de Freitas do Nascimento, Ary Jose Duarte Jr, Giovana Ghisleni Ribas, Isadora Hubner Brondani, Lucas Adilio Sari, Anderson Haas Poersch, Lorenzo Sartori. 2019. Classifying Irrigated Rice Regions in Brazil According the Favorability for Blast Disease. ASA, CSSA and SSSA International Annual Meetings. (Hatch acknowledged? No)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Sabrina Ruis, Humberto Blanco, Haishun Yang, Katja Koehler-Cole, Roger W Elmore, Cody Creech, Paul Jasa, Charles A Francis. Predicting Cover Crop Biomass Production for Expanded Uses in the Great Plains. 2019. ASA, CSSA and SSSA International Annual Meetings. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: Nanyan Deng, Patricio Grassini, Haishun Yang, Jianliang Huang, Kenneth G Cassman, Shaobing Peng. 2019. Closing yield gaps for rice self-sufficiency in China. Nature communications. (Hatch acknowledged? No)
  • Type: Journal Articles Status: Published Year Published: 2019 Citation: M Zhan, AJ Liska, AL Nguy-Robertson, AE Suyker, MP Pelton, H Yang. 2019. Modeled and Measured Ecosystem Respiration in MaizeSoybean Systems Over 10 Years. Agronomy Journal 111 (1), 49-58. (Hatch acknowledged? No)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Banda, M. M., D. M. Heeren, D. L. Martin, F. Munoz-Arriola, and L. G. Hayde. 2019. Economic analysis of deficit irrigation in sugarcane farming: Nchalo Estate, Chikwawa District, Malawi. ASABE Annual International Meeting, Paper No. 1900852, Boston, Mass. 19 pages. (Hatch acknowledged? No)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Martin, D. L, D. M. Heeren, S. R. Melvin, and T. Ingram. 2019. Effect of limited water supplies on center pivot performance. Central Plains Irrigation Association (CPIA) Central Plains Irrigation Conference, Kearney, Nebr. 27 pages. (Hatch acknowledged? No)
  • Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Isaak Arslan4, Jake Field4, Cale Harms4, Hallie Hohbein4, Miracle Modey4, B. Ramamurthy, D. Benet. Y-C Chen, and F. Munoz-Arriola (2019). NEO-SAT: An information support system for flood-disaster management. (Hatch acknowledged? No)
  • Type: Other Status: Submitted Year Published: 2019 Citation: Sensing System and Method for Direct Injection Systems on Agricultural Sprayers. Inventors: J.D. Luck and C.C. Folkerts. United States Patent Office #62/744,446 (provisional status-in review) (Hatch acknowledged? No)
  • Type: Websites Status: Published Year Published: 2019 Citation: Haishun Yang, Saeideh Samani, Babak Samani, and Suraj Samal. 2019. Nitrogen Leaching App (https://hprcc-agron1.unl.edu/).


Progress 10/01/17 to 09/30/18

Outputs
Target Audience:Water resources, both surface water as well as ground water, are vital to Nebraska agriculture. For example, Nebraska ranks as the fourth state in the nation on ground water use in agriculture and first in the nation on irrigated acreage. In 2012, Nebraska was ranked 3rd and 5th in the nation in corn and soybean production, respectively. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. Unfortunately, in response to irrigation water withdrawals, groundwater levels have declined significantly in several major irrigated areas of the state. Also, groundwater decline can have impacts on streamflow which is important for endangered species and interstate compacts. This factor contributes to the challenge of water, agricultural, and ecosystems sustainability in the state. In consequence, the predictability of productivity of the agro-ecosystem and the consequent preparedness for change in water states is based on our ability to diagnose, forecast, and predict current and future environmental states including water availability and crop production. A key to achieving water and agricultural resources sustainability is to understand the interactions among climate, water availability and water uses in agro-ecosystems. The multi-dimensionality of the relationships defining sustainable development of water and agricultural resources can be seen as mass and energy fluxes forced by climate and regulated by human activities along the water continuum from the atmosphere to the aquifer. In this project we aim to better understand how these processes (naturally driven or anthropogenically affected) may change over time influencing future water availability and crop production. At the field-scale (producers, land/water managers), diagnostic research on water management includes irrigation scheduling and nutrient transport. However, due to the high spatial variability of soil water, there is a need for large-scale soil water measurement to provide field average soil water. As part of this project new geophysical technologies are being deployed across the state and being evaluated by producers and water managers. Despite research and extension efforts, very few producers take the time to calculate their own soil water balance. An online tool that utilizes a soil water balance and a crop growth model is available for soybeans (SoySim), but an equivalent tool needed to be developed for corn. This tool has been developed as part of this project. At the sub-field scale, precision agriculture has provided producers the opportunity to manage inputs spatially, including fertilizer, plant population, hybrid, and water. Variable rate irrigation (VRI) technology provides an opportunity to prevent over-application and/or under-application of water. Best management practices are not yet well defined and the benefits of VRI are not well quantified and will be assessed in the current project by multiple PIs in collaboration. A well-defined set of best management practices and technology transfer to local industries (center-pivot manufacturers, crop consultants, cooperative units, etc.) will no doubt continue to fuel the agricultural-based economy of Nebraska and other state and national economies that seek to emulate its success. In 2018, the project resulted in 21 peer-reviewed publications, 3 extension publications, 42 conference presentations, 20 extension presentations, 9 undergraduate projects, 9 MS projects, 9 PhD projects, and 2 post-doctoral projects. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?PI-Franz has taught 3 formal courses at the university: 1 focused at Freshman non-science majors, 1 focused at Sophomores in Natural Resources, and the other 1 focused at Seniors and Graduate students in Natural Resources. In addition PI-Franz co-developed the Freshman level course intended for non-science majors as part of an NSF grant in Science Literacy (1 peer reviewed pub). In addition, PI-Franz taught a 1 week long course in Kuwait on the cosmic-ray neutron sensor technique. The class consisted of 16 government scientists from the surrounding Gulf States. PI-Heeren taught or co-taught two undergraduate courses (Irrigation Systems Management, 43 students; Equipment Systems, 28 students) and two graduate course (Irrigation Lab and Field Course, 15 students; Modeling Vadose Zone Hydrology, 8 students) in 2018. Objective 2 of the Hatch project provided scholarly material for irrigation courses. Objective 2 also supported 0.5 post-doc, 2.5 MS students, and 3 undergraduate research assistants. PI-Luck taught one undergraduate course in 2018 focused on site-specific crop management. This lecture and computer laboratory-based course had 82 students registered in 2017; majors included agricultural engineering, agronomy and horticulture, mechanized systems management, and agricultural economics. Seven graduate and undergraduate students were significantly associated with project activities under objective 4 during 2018. PI- Munoz-Arriola taught two formal courses (Soil and Water Resources Engineering, Extreme Events and Water Resources, and Hydroclimatology). Undergraduate and graduate students, evidencing the need of non-stationary approaches to address water, food, and energy security through the presentation of sixteen final projects. Also, a strong support for undergraduate research experience is evidenced in the projects developed in Munoz-Arriola research lab with 5 undergraduate projects (and 10 undergraduates involved) working on independent and team research projects (half of them women in science and engineering); 80% of the undergraduates in this lab have received funding in response to competitive grants solicitations. The project funded by National Science Foundation (a 3-million dollar grant) has launched its curricular activities training 5 master and 3 PhD students on Resilient Complex Agricultural Landscapes (expecting to fund additional 14 graduate students in Natural Resources, Biological and Computational Engineering, Agronomy, and Political Sciences, among other areas, in the following four years). The project "Gene-to-Global Hydroclimatic Controls on Hybrid Performance Forecast" was funded early this year by the United States Department of Agriculture-NIFA Foundational's Plant Breeding for Agricultural Production. How have the results been disseminated to communities of interest?PI-Franz was the main organizer and host for the 2018 MOISST conference on soil moisture. The conference was attended by 100+ people from federal, state, university and private industry. In addition PI-Franz and his MS student presented his work at 1 extension meeting attended by local producers and water managers. PI-Franz also had 3 invited talks at conferences/workshops. PI-Franz also taught a 1 week course on the cosmic-ray neutron probe sensor in Kuwait as part of the United Nations joint programme with the Food and Agriculture Organization and International Atomic Energy Agency. The course was attended by 18 participates from developing countries in the Gulf State region. PI-Heeren and his graduate students gave 11 conference presentations and 7 invited presentations in 2018. PI-Heeren also gave 3 guest lectures for courses at UNL. PI-Luck and his graduate students gave 12 research conference presentations at the American Society of Agricultural and Biological Engineers Annual Meeting, the International Conference on Precision Agriculture, and the American Society of Agronomy Annual Meeting. During 2018, 15 extension presentations/webinars resulting from project activities were also conducted including ten day-long data management workshops. Over 1,000individuals have attended extension presentations, workshops, or other sessions in 2017 resulting from activities conducted under objective 4. PI-Yang (1) Invited to give a presentation in a symposium of 2016 ASA-CSSA-SSSA International Annual Meetings. (2) Invited to visit two research institutions in China and to give presentations on crop modeling and their application. PI- Munoz-Arriola:Is member of the American Meteorological Society Water Resources Committee. Mohr Lecturer in the Department of Earth and Atmospheric Sciences and Invited lectured at the Ohio State University. Additionally, Francisco and his group gave 16 conference presentations and developed an assessment on Irrigation Sustainability base on questionnaire approved by the IRB and applied to decision and policy makers in Nebraska. Consolidated the international research collaborative programs on Hydroinformatics and Integrated Hydrology with the Delft Institute for Water Education (The Netherlands); and software design and construction with Universidad Autonoma de Baja California (Mexico); progress have been made toward strengthen activities with India. What do you plan to do during the next reporting period to accomplish the goals?PI-Franz will teach a CRNS training course in Qatar and Oman as part of his work with the United Nations. PI-Heeren will continue to lead field research in variable rate irrigation. Team members in 2018 will include 1 Ph-D student and 1 MS student. PI-Luck will be recruiting two graduate students in 2019 to continue activities related to geospatial applications of precision agriculture technologies and pesticide application systems (to be funded by a successful USDA Foundational Program proposal through 2020). Two MS students will graduate in 2019 and will submit multiple journal articles and extension publications prior to graduation. PI-Yang Nothing to report PI- Munoz-Arriola expects to consolidate the software developed in the past two cycles and publish findings in scientific journals, addressing the complexity of extreme precipitation and drought in agricultural and urban areas. PI-Munoz-Arriola expects to continue strengthen communication and collaboration with irrigation district administrators as well as private companies, exploring new synergies with such sectors. Graduate 1 PhDs and 1 Ph D student will be recruited as part of the National Science Foundation Research Training program on Resilient Complex Landscapes.

Impacts
What was accomplished under these goals? MA= Major Activities; DA=Data Collected; SM=Summary Statistics; KO=Key Outcomes Objective 1. MA: Installation and monitoring of 10 cosmic-ray neutron probes across Nebraska DA: Hourly soil moisture data at 10 sites and 70 geophysical spatial maps. KO: Point-scale soil moisture monitoring is challenging as irrigation decisions are made on areas. The disconnect and gap between the point scale and area-average values desired by producers can be addressed through the use of geophysical methods (soil properties like field capacity and wilting point over areas can be better approximated) and scaling approaches. Research aimed to improve the cosmic-ray neutron probe (CRNP) method and applications to irrigation agriculture, including improvements in the algorithm. The CRNP technology is a cutting edge technology that has the potential to be included in advanced irrigation management and other precision ag applications in the future. PI-Franz continues to be a global leader in developing this technology via active projects and collaborations across the USA, Europe, Africa, Asia, and Australia. Of particular note is PI-Franz's role in a 5-yr United Nations Coordinated Research Project which includes participants from 10 developing countries. Objective 2. MA: Remote sensing imagery from satellites and unmanned aircraft were used along with the SETMI model in order to quantify spatial variability in ET and to develop variable rate irrigation (VRI) prescription maps. Research was implement at a sub-humid field site (Mead, NE) and a semi-arid field site (Brule, NE). KO: VRI is a technology that may improve irrigation water productivity, reducing pumping and nitrate leaching. There is a need to quantify the benefits of VRI and develop a decision support system for VRI. Our research program in VRI is establishing UNL and the WFI as national and international leaders in field-scale VRI management research. A method was developed for making irrigation prescription maps based on soil properties, including an evaluation of control scenarios for prescription maps. Field implementation of prescription maps demonstrated that effective management of VRI will likely require a combination of both remote sensing and soil water monitoring. VRI based on soil water sensors reduced irrigation by 0.5 in for soybeans and by 0.1 in for corn. Objective 3 part 1. MA: We added a function for users to correct or add local rainfall records to the current online irrigation decision making tool 'CornSoyWater'. This makes the program more robust and easily adapted to local conditions. KO: The first version of CornAid software (version 2019.1) will be released to the public in early 2019. Objective 3 part 2. MA: (1) As a result of collaboration with industry, we have developed 'CornAid', a corn management decision making support software. It features integrated functions of N fertilizer rate estimation, real-time predictions of corn development, soil water availability, and irrigation requirement for an unlimited number of management zones. This program will not only advance the capability of corn management by producers and ag-industry professional, but also provides a solid foundation for incorporation into hardware control of precision field equipment and center pivots. It will be further tested and validated in the following year. (2) The Chinese tech company, Beijing ICAN Technology Co. Ltd (ICAN) has licensed our three decision support software programs, including Hybrid-Maize, Maize-N, and CornSoyWater to adopt them in China. SM/KO: Model-based crop management decision support tools have started to attract attention not only from farmers but also ag-industry for value-added products and services. Objective 3 part 3. MA: we have developed the online 'N Leaching Calculator' (https://hprcc-agron1.unl.edu/). The program estimates N leaching across crop lands of the state of Nebraska. It uses the automated weather stations across the state, USDA SSURGO database for soil properties, and generic county level cropping information to estimate in real-time N leaching in crop lands. The program is based on simulation of crop growth, soil N mineralization, crop N uptake, soil water dynamics, and N leaching. DC: More experimental data at multiple sites have been collected on soil nitrate at multiple depths at different times of the season. The data will be used for model testing and validation. SM: N leaching is important but difficult to predict. Our effort is the first of its kind and we expect widespread interest from producers, environmentalists, rural communities, and governmental agencies. KO: Hybrid-Maize and Maize-N models can apply the fundamental and quantitative scientific principles to help answer questions. Objective 4. MA: Multiple field-based research projects continued across eastern NE crop canopy sensor-based fertilizer application in corn for increasing N-use efficiencyband on-farm research studies to optimize seeding and N application rates;. DC: Multiple geospatial datasets were collected for these projects including machine field operation status, agronomic as-applied (seeding and nitrogen) application and harvest data from field equipment, crop status from active canopy sensors, aerial imagery, sub-field-level terrain, soil texture, and other soil properties. SM: A three year project on nitrogen application showed that N could be reduced by almost 30 lb-N/ac without a significant loss to marginal net return (MNR; $/ac). Multi-hybrid planter study using seed treatment for Sudden Death Syndrome in soybeans (a persistent issue), a MNR of almost $80/ac was noted. Variable rate application studies showed that producers can reduce N application without significant losses in MNR; in addition soybean seeding rates could be lowered to increase MNR in those fields. KO: Significant project impacts include increased awareness of improved N management strategies and maximizing N-use efficiency, resulting in some cooperators reducing the amount of N applied, which will benefit the environment. Objective 5 parts 1 and 2. MA: (i) Design and implementation of machine learning techniques (ramdom forests, support vector machines, artificial neural networks, extreme learning machines, and genetic programing) to predict groundwater yields in wells for crop irrigation. (ii) Development of software to collect, standardize, integrate and store, station (punctual data) and remote sensing (rainfall, NDVI, LAI, and soil moisture); the modular architecture was designed and constructed as plugins (each represents a specific data source); the storage architecture was built to retrieve and store data from multiple sources, standardizing the access to the data though the use of different APIs (selected by the client). (iii) Predict future changes in groundwater availability for irrigation purposes in geopolitical conflicted areas (the lower Republican River basin in the limits between NE, CO and KS) was also published this year. (iv) design of a tethered drone used to launch proximal sensing capabilities that enables long-term, high frequency, high spatial resolution and wide monitoring. DC: Groundwater-well levels, precipitation, temperature, and soil moisture at various timespans and frequencies from field and remote sensing were collected and transformed to characterize future changes in water availability. The lead-times explored were from months (for semi-seasonal forecast) to decades (for assessment of climate change). Development of a software (in R) aimed to test geospatial representations of groundwater well levels and hydrometeorological and climate variables at multiple resolutions. KO: To date the greatest impact has been the continuous development of software to assess EHCEs, develop datasets, and geospatial integrations. Further, implemented models are used to test climate indices for agricultural and urban areas in the US, Mexico and India.

Publications

  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Miller, K. A., J. D. Luck, D. M. Heeren, T. Lo, D. L. Martin, and J. B. Barker. 2018. A geospatial variable rate irrigation control scenario evaluation methodology based on mining root zone available water capacity. Precision Agriculture.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Barker, J. B., C. M. U. Neale, D. M. Heeren, and A. E. Suyker. 2018. Evaluation of a hybrid reflectance-based crop coefficient and energy balance evapotranspiration model for irrigation management. Transactions of the ASABE 61(2): 533-548, doi: 10.13031/trans.12311.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Freiberger, R. P., D. M. Heeren, D. E. Eisenhauer, A. R. Mittelstet, and G. A. Baigorria. 2018. Tradeoffs in model performance and effort for long-term phosphorus leaching based on in situ field data. Vadose Zone Journal 17:170216, doi: 10.2136/vzj2017.12.0216.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: (2018), Cosmic Ray Neutron Sensing: Estimation of Agricultural Crop Biomass Water Equivalent. Joint FAO/IAEA Programme Nuclear Techniques in Food and Agriculture. 37 pg. Springer Open. Online at https://link.springer.com/book/10.1007/978-3-319-69539-6.
  • Type: Book Chapters Status: Published Year Published: 2018 Citation: (2018), Soil Moisture Mapping with a Portable Cosmic Ray Neutron Sensor. IAEA- TECDOC-1845. Joint FAO/IAEA Programme Nuclear Techniques in Food and Agriculture. 43 pg. Vienna, Austria. Online at https://www-pub.iaea.org/books/IAEABooks/12357/Soil-Moisture-Mapping-with-a-Portable-Cosmic-Ray-Neutron-Sensor
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Wieder, W., S. Shoop, L. Barna, T. Franz, and C. Finkenbiner (2018), Comparison of soil strength measurements of agricultural soils in Nebraska, J. Terramech., 77, 31-48.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Vather, T., C. Everson, M. Mengistu, and T. Franz (2018), Cosmic ray neutrons provide an innovative technique for estimating intermediate scale soil moisture, S. Afr. J. Sci., 114(7-8), 79-87. doi:10.17159/sajs.2018/20170422.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Smyth, A. R., T. Loecke, T. E. Franz, and A. Burgin (2018 accepted), Using high-frequency soil oxygen sensors to predict greenhouse gas emissions from wetlands, Soil Biology and Biochemistry.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Gibson, K. E. B., H. S. Yang, T. Franz, D. Eisenhauer, J. B. Gates, P. Nasta, B. S. Farmaha, and P. Grassini (2018), Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems, Agric. Water Manage., 197, 34-40.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Forbes, C. T., N. Brozovic, T. E. Franz, D. E. Lally, and D. N. Petitt (2018), Water in Society: An Interdisciplinary Course to Support Undergraduate Students⿿ Water Literacy, Journal of College Science Teaching, 48(1), 36-42.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Babaeian, E., M. Sadeghi, T. E. Franz, S. Jones, and M. Tuller (2018), Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations, Remote Sens. Environ., 211, 425-440.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Gibson, J., and T. E. Franz (2018), Spatial prediction of near surface soil water retention functions using hydrogeophysics and empirical orthogonal functions, Journal of Hydrology, 561, 372-383.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Finkenbiner, C., T. E. Franz, J. Gibson, D. M. Heeren, and J. D. Luck (2018), Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management, Precis. Agric.
  • Type: Book Chapters Status: Published Year Published: 2018 Citation: Sharda, A., A. Franzen, D.E. Clay, and J.D. Luck. 2018. Precision Variable Equipment, In Precision Agriculture Basics. K. Shannon, D.E. Clay, and N. Kitchen, Chapter 11. ASA/CSSA/SSSA, Madison, WI.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Thompson, L.J., B.R. Krienke, R.B. Ferguson, and J.D. Luck. 360-degree Video for Immersive Learner Engagement. J. Extension [On-line], 53(4) Article 5TOT2. Available at: https://joe.org/joe/2018september/pdf/JOE_v56_5tt2.pdf
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Rohrer, R.A., S.K. Pitla, J.D. Luck, and R.M. Hoy. 2018. Evaluation of the accuracy of machine reported CAN data for engine torque and speed. Trans. ASABE 61(5): 1547-1557
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Yang, L, Yang, HS, Li, J, Li, Y, and Yan, H. 2018. Estimation of irrigation requirements for drip-irrigated maize in a sub-humid climate. Journal of Integrative Agriculture. 17, 677-692.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Meng, Qingfeng, Cui, Zhenling, Yang, Haishun, Zhang, Fusuo, and Chen, Xinping. Sparks, Donald L. 2018. Establishing High-Yielding Maize System for Sustainable Intensification in China. Advances in Agronomy. 148, 85-109. Academic Press.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Gibson, Katherine E. B., Yang, Haishun S., Franz, Trenton, Eisenhauer, Dean, Gates, John B., Nasta, Paolo, Farmaha, Bhupinder S., and Grassini, Patricio. 2018. Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems. Agricultural Water Management. 197, 34-40.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Tollenaar, M, Dzotsi, K. A., Kumudini, S, Boone, KE., Chen, Keru, Hatfield, J. L., Jones, J. W., Lizaso, J. I., Nielsen, R. L., Thomison, P, Timlin, D., Valentinuz, O. R., Vyn, T, and Haishun, Yang. Jerry L.Hatfield, Mannava V. K. Sivakumar John H. Prueger editors. 2018. Modeling the Effects of Genotypic and Environmental Variation on Maize Phenology: The Phenology Subroutine of the AgMaize Crop Model. Agroclimatology: Linking Agriculture to Climate, Agronomy Monograph 60.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Rizzo, Gonzalo, Edreira, Juan Ignacio Rattalino, Archontoulis, Sotirios V., Yang, Haishun S., and Grassini, Patricio. 2018. Do shallow water tables contribute to high and stable maize yields in the US Corn Belt? Global Food Security. 18, 27-34.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Zhan, Ming, Liska, Adam J., Nguy-Robertson, Anthony L., Suyker, Andrew E., Pelton, Matthew P., and Yang, Haishun. 2018. Modeled and Measured Ecosystem Respiration in Maize?ÿôSoybean Systems Over 10 Years. Agro J. 1-10.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Anderson, Ryan, Keshwani, Deepak, Guru, Ashu, Yang, Haishun, Irmak, Suat, and Subbiah, Jeyamkondan. 2018. An integrated modeling framework for crop and biofuel systems using the DSSAT and GREET models. Environmental Modelling & Software. 108, 40-50.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Liben, F. M., Wortmann, C. S., Yang, H., Lindquist, J. L., Tadesse, T., and Wegary, D. 2018. Crop model and weather data generation evaluation for conservation agriculture in Ethiopia. Field Crops Research. 228, 122-134.
  • Type: Journal Articles Status: Published Year Published: 2108 Citation: Singh1, J., T. Lo, D.R. Rudnick, T.J. Dorr, C.A. Burr, R. Werle, T.M. Shaver, and F. Muñoz-Arriola (2018). Performance Assessment of Factory and Field Calibrations for Electromagnetic Sensors in a Loam Soil. Agricultural Water Management.196: 87-98.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Rudnick, D.R., T. Lo, J. Singh1, R. Werle, F. Muñoz-Arriola, T.M. Shaver, C.A. Burr, and T.J. Dorr (2018). Reply to comments on "Performance assessment of factory and field calibrations for electromagnetic sensors in a loam soil". 203:272-276. DOI:10.1016/j.agwat.2018.02.036.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Uden2, D.R., C.R. Allen, F. Munoz-Arriola, G. Ou2, and N. Shank (2018). A Framework for Tracing Social⿿Ecological Trajectories and Traps in Intensive Agricultural Landscapes. Sustainability. doi:10.3390/su10051646.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Amaranto1, A., F. Munoz-Arriola, G. Meyer, D. Solomatine, and G. Corzo (2018). Semi-seasonal Predictability of Water-table Changes Using Machine Learning Methods in Response to Integrated Hydroclimatic and Management Controls. Journal of Hydroinformatics. doi: 10.2166/hydro.2018.002.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Ou2, G., F. Munoz-Arriola, D. Uden2, D. Martin and C. Allen (2018). Groundwater Availability in a Changing Climate: The case of Irrigated Landscapes in Geopolitically Contentious Areas. Climatic Change. https://doi.org/10.1007/s10584-018-2278-z.
  • Type: Other Status: Published Year Published: 2108 Citation: Lo, T., D. R. Rudnick, Y. Ge, D. M. Heeren, S. Irmak, J. B. Barker, X. Qiao, T. M. Shaver. 2018. Ground-based thermal sensing of field crops and its relevance to irrigation management. NebGuide G2301, Nebraska Extension, peer-reviewed.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Barker, J. B., D. M. Heeren, C. M. U. Neale, and D. R. Rudnick. 2018. Evaluation of variable rate irrigation using a remote-sensing-based model. Agricultural Water Management 203: 63-74, doi: 10.1016/j.agwat.2018.02.022.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Barker, J. B., D. M. Heeren, K. Koehler-Cole, C. A. Shapiro, H. Blanco-Canqui, R. W. Elmore, C. A. Proctor, S. Irmak, C. A. Francis, T. M. Shaver, and A. T. Mohammed. 2018. Cover crops have negligible impact on soil water in Nebraska maize-soybean rotation. Agronomy Journal 110: 1-13, doi: 10.2134/agronj2017.12.0739.


Progress 10/01/16 to 09/30/17

Outputs
Target Audience:Water resources, both surface water as well as ground water, are vital to Nebraska agriculture. For example, Nebraska ranks as the fourth state in the nation on ground water use in agriculture and first in the nation on irrigated acreage. In 2012, Nebraska was ranked 3rd and 5th in the nation in corn and soybean production, respectively. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. Unfortunately, in response to irrigation water withdrawals, groundwater levels have declined significantly in several major irrigated areas of the state. Also, groundwater decline can have impacts on streamflow which is important for endangered species and interstate compacts. This factor contributes to the challenge of water, agricultural, and ecosystems sustainability in the state. In consequence, the predictability of productivity of the agro-ecosystem and the consequent preparedness for change in water states is based on our ability to diagnose, forecast, and predict current and future environmental states including water availability and crop production. A key to achieving water and agricultural resources sustainability is to understand the interactions among climate, water availability and water uses in agro-ecosystems. The multi-dimensionality of the relationships defining sustainable development of water and agricultural resources can be seen as mass and energy fluxes forced by climate and regulated by human activities along the water continuum from the atmosphere to the aquifer. In this project we aim to better understand how these processes (naturally driven or anthropogenically affected) may change over time influencing future water availability and crop production. At the field-scale (producers, land/water managers), diagnostic research on water management includes irrigation scheduling and nutrient transport. However, due to the high spatial variability of soil water, there is a need for large-scale soil water measurement to provide field average soil water. As part of this project new geophysical technologies are being deployed across the state and being evaluated by producers and water managers. Despite research and extension efforts, very few producers take the time to calculate their own soil water balance. An online tool that utilizes a soil water balance and a crop growth model is available for soybeans (SoySim), but an equivalent tool needed to be developed for corn. This tool has been developed as part of this project. At the sub-field scale, precision agriculture has provided producers the opportunity to manage inputs spatially, including fertilizer, plant population, hybrid, and water. Variable rate irrigation (VRI) technology provides an opportunity to prevent over-application and/or under-application of water. Best management practices are not yet well defined and the benefits of VRI are not well quantified and will be assessed in the current project by multiple PIs in collaboration. A well-defined set of best management practices and technology transfer to local industries (center-pivot manufacturers, crop consultants, cooperative units, etc.) will no doubt continue to fuel the agricultural-based economy of Nebraska and other state and national economies that seek to emulate its success. In 2017, the project resulted in 21 peer-reviewed publications, 5 extension publications, 37 conference presentations, 22 extension presentations, 12 undergraduate projects, 15 MS projects, 9 PhD projects, and 5 post-doctoral projects. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?PI-Franz has taught 3 formal courses at the university and co-developed the Freshman level course intended for non-science majors as part of an NSF grant in Science Literacy. The course will be expanded to an online format in the coming years to reach all 4 University of Nebraska campuses. PI-Heeren taught one undergraduate course (Irrigation Systems Management, 36 students) and one graduate course (Advanced Irrigation Management, 7 students) in 2017. Objective 2 of the Hatch project provided scholarly material for both courses. Objective 2 also supported 1 post-doc, 1 PhD student, 2 MS students, and 3 undergraduate research assistants. PI-Luck taught one undergraduate course in 2017 focused on site-specific crop management. Seven graduate and undergraduate students were significantly associated with project activities under objective 4 during 2017. PI-Yang Developed an online distance format for Crop Modeling, a 900 level course for graduate students. PI- Munoz-Arriola taught two formal courses (Soil and Water Resources Engineering, Extreme Events and Water Resources, and Hydroclimatology). Also, a strong support for undergraduate research experience is evidenced in the projects developed in Munoz-Arriola research lab with 10 undergraduates working on independent research projects (half of them women in science and engineering). How have the results been disseminated to communities of interest?PI-Franz participated in the 2017 Water for Food Global Conference. The conference was attended by 400+ people from 40+ countries. In addition PI-Franz and his MS student presented his work at 2 extension meetings attended by local producers and water managers. PI-Franz also had 2 invited talks at conferences. PI-Franz also taught a 1 week course on the cosmic-ray neutron probe technology in Austria as part of the United Nations joint programme with the Food and Agriculture Organization and International Atomic Energy Agency. The course was attended by 19 participants from developing countries in Africa and Asia. PI-Heeren and his graduate students gave 9 conference presentations and 7 invited presentations in 2017. The peer-reviewed extension website which was launched in 2016 (http://heeren.unl.edu/map) has had 1,479 pageviews. PI-Luck and his graduate students gave 10 research conference presentations at the American Society of Agricultural and Biological Engineers Annual Meeting, the International Conference on Precision Agriculture, and the American Society of Agronomy Annual Meeting. During 2017, 14 extension presentations resulting from project activities were also conducted . Over 600 individuals have attended extension presentations in 2017 resulting from activities conducted under objective 4. PI-Yang (1) Invited to give a presentation in a symposium of 2016 ASA-CSSA-SSSA International Annual Meetings. (2) Invited to visit two research institutions in China and to give presentations on crop modeling and their application. PI- Munoz-Arriola: Invited by the Computing Community Consortium (CCC) biannual conference to present on "Toward a Resilient Food-Energy-Water-Ecosytem Services Nexus: Analytics and Synthesis". What do you plan to do during the next reporting period to accomplish the goals?PI-Heeren will continue to lead field research in variable rate irrigation. PI-Luck will be recruiting two graduate students in 2016 to continue activities related to geospatial applications of precision agriculture technologies and pesticide application systems (to be funded by a successful USDA Foundational Program proposal through 2020). Three MS students will graduate in 2016 and will submit multiple journal articles and extension publications prior to graduation. PI- Munoz-Arriola expects to consolidate the software developed in the past two cycles and publish findings in scientific journals, addressing the complexity of extreme precipitation and drought in agricultural and urban areas. PI-Munoz-Arriola expects to continue strengthen communication and collaboration with irrigation district administrators as well as private companies, exploring new synergies with such sectors. Two PhDs and an MS student will be recruited as part of collaborative funds obtained this year.

Impacts
What was accomplished under these goals? Water resources are vital to Nebraska agriculture. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. In response to irrigation water withdrawals, groundwater levels have declined. Also, groundwater decline impacts streamflow which is important for endangered species and interstate compacts. A key to achieving water and agricultural resources sustainability is to understand the interactions among climate, water availability and water uses in agro-ecosystems. In this project we aim to better understand how these processes (naturally driven or anthropogenically affected) may change over time influencing future water availability and crop production. MA= Major Activities; DA=Data Collected; SM=Summary Statistics; KO=Key Outcomes Objective 1. MA: Installation and monitoring of 10 cosmic-ray neutron probes across Nebraska DA: Hourly soil moisture data at 10 sites and 70 geophysical spatial maps. KO: Point-scale soil moisture monitoring is challenging as irrigation decisions are made on areas. The disconnect and gap between the point scale and area-average values desired by producers can be addressed through the use of geophysical methods and scaling approaches. The description of soil properties like field capacity and wilting point over areas can be better approximated using geophysical approaches. Research aimed to improve the cosmic-ray neutron probe method and applications to irrigation agriculture, including improvements in the algorithm. The cosmic-ray neutron probe technology is a cutting edge technology that has the potential to be included in advanced irrigation management and other precision ag applications in the future. Objective 2. MA: We adapted a remote sensing model (SEMI) for use in conventional irrigation and variable rate irrigation (VRI) management. Dynamic prescription maps applied water at two field sites based on three treatments: uniform irrigation, VRI based on the SETMI model (using satellite data), and rainfed. KO: VRI is a technology that may improve irrigation water productivity, reducing pumping and nitrate leaching. There is a need to quantify the benefits of VRI and develop a decision support system for VRI. A method was developed for soil maps for VRI management (Lo et al., 2017). A statewide analysis estimated that pumping reductions from VRI could exceed two inches per year for 2% and one inch per year for 13% of the fields in Nebraska (Lo et al., 2016). This data (49,224 fields) was made available for producers and industry through a peer-reviewed extension website (http://heeren.unl.edu/map; 1,479 pageviews). The Nebraska NRCS expressed interest in using this online map tool to evaluate VRI cost-share applications. In comparing potential benefits, increasing yield is more likely to economically justify an investment in VRI than reducing pumping. An analysis of the number of soil water monitoring locations required for VRI management zones was performed and indicated that effective VRI management will likely require a combination of both soil water monitoring and remote sensing (Barker et al., 2017). Objective 3 part 1. MA: Both SoyWater and CornSoyWater programs were enhanced (user interface and internal routines) and moved to a long-term sever location. A NSF proposal based on this program was funded. SM: It was concluded that soils have insufficient rooting depth in many cropping systems in Africa, which limits yield unless irrigation is provided. Hybrid-Maize was also used to quantify the effects of plastic film on water saving, soil temperature, and faster crop development in North East China. KO: Applications of the Hybrid-Maize models lead to new insights to the limitation of food production in Africa under rainfed conditions and suggests the importance of irrigation. Objective 3 part 2. MA: An ag-company in Nebraska is investing and collaborating with us to develop computerized integrated decision support system for irrigation and fertilization, and to incorporate it into the control panel of center pivot to automate VRI control. Another tech company in China is in the process of licensing the program. SM/KO: Model-based crop management decision support tools have started to attract attention not only from farmers but also ag-industry for value-added products and services. Objective 3 part 3. MA: We are developing N leaching Calculator, a web-based program for estimating N leaching from crop field in Nebraska. The program is based on simulation of crop growth, soil N mineralization, crop N uptake, soil water dynamics, and N leaching. DC: Experimental data at multiple sites are collected on soil nitrate at multiple depths at different times of the season. SM: N leaching is important but difficult to predict. Our effort is the first of its kind and we expect widespread interest from producers, environmentalists, rural communities, and governmental agencies. KO: Hybrid-Maize and Maize-N models can apply the fundamental and quantitative scientific principles to help answer questions. Objective 4. MA: Multiple field-based research projects across eastern NE including 1) multi-hybrid planter applications in corn and soybeans for improved seed variety or seed treatment placement; 2) crop canopy sensor-based fertilizer application in corn for increasing N-use efficiency; 3) on-farm research studies to optimize seeding and N application rates; 4) enhanced pesticide application mapping to improve operator behavior and modeling harvest system logistics for improved equipment selection and utilization. DC: Multiple geospatial datasets were collected for these projects including machine field operation status, agronomic as-applied (seeding and nitrogen) application and harvest data from field equipment, crop status from active canopy sensors, aerial imagery, sub-field-level terrain, soil texture, and other soil properties. SM: In most cases, nitrogen application could be reduced without a significant loss to marginal net return (MNR; $/ac). Multi-hybrid planter applications in corn and soybeans can greatly improve MNR in some but not all fields. Sensor-based nitrogen application can improve nitrogen use efficiency (averaging 0.06 lb-N/bu-corn), though MNR may be slightly penalized (-$5/ac on average). KO: Significant project impacts include increased awareness of improved N management strategies and maximizing N-use efficiency, resulting in some cooperators reducing the amount of N applied, which will eventually benefit the environment. In 2017, over 600 individuals received research-based information from different projects covered under this objective via extension presentations, workshops, and media. Objective 5 parts 1 and 2. MA: (i) Implementation of multiple indices of Extreme Hydrometeorological and Climate Events (EHCEs) to assess geospatial distributions in agricultural and urban areas; use of numerical and data-driven models to simulate water quality and groundwater changes in response to EHCEs in Nebraska's catchments; and implementation of a multiscale climate model to simulate EHCEs. (ii) Development of software to estimate indices EHCEs from publically available weather and climate data and seasonally forecast groundwater changes. DC: Groundwater-well levels, precipitation, temperature, and soil moisture at various timespans and frequencies from field and remote sensing. Development of a software (in python) aimed to test geospatial representations of hydrometeorological and climate variables at multiple resolutions from station data. KO: To date the greatest impact has been the development of software to assess EHCEs, develop datasets, and geospatial integrations. Further, implemented models are used to test climate indices for agricultural and urban areas in the US, Mexico and India.

Publications

  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Luck, J.D., S.A. Shearer, B.D. Luck, and M.P. Sama. 2016. Recalibration methodology to compensate for changing fluid properties in an individual nozzle direct injection system. Trans. ASABE. 59(3): 847-859.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Roeber, J.BW., S.K. Pitla, M.F. Kocher, J.D. Luck, and R.M. Hoy. 2016. Tractor hydraulic power data acquisition system. Computers Electronics Agric. 127: 1-14.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Creech, C.F., J.G. Moraes, R.S. Henry, J.D. Luck, and G.R. Kruger. 2016. The impact of spray droplet size on the efficacy of 2,4-D, Atrazine, Chromium-methyl, Dicamba, Glufosinate, and Saflufenacil. Weed Tech. 30(2): 573-586.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Luck, J.D., W.A. Schaardt, S.H. Forney1, and A. Sharda. 2016. Development and evaluation of an automated spray patternator using digital liquid level sensors. Appl. Eng. Agric. 32(1): 47-52.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Pitla, S.K., J.D. Luck, N. Lin, J.P. Werner, and S.A. Shearer. 2016. In-field fuel use and load states of agricultural machinery. Computers Electronics Agric. 121: 290-300.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Espe MB; Cassman KG; Yang HS; Guilpart N; Grassini P; van Wart J; Anders M; Beighley D; Harrell D; Linscombe S; McKenzie K; Mutters R; Wilson LT; and Linquist BA. 2016. Yield gap analysis of US rice production systems shows opportunities for improvement. Field Crops Research. 196, 276-283
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Espe MB; Yang HS; Cassman KG; Guilpart N; Sharifi H; and Linquist BA. 2016. Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems. Field Crops Research. 193, 123-132.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Carr T; Yang H; and Ray C. 2016. Temporal Variations of Water Productivity in Irrigated Corn: An Analysis of Factors Influencing Yield and Water Use across Central Nebraska. PLOS One. 11, e0161944-DOI:10.1371/journal.pone.0161944.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Meng Q; Chen X; Lobell D; Cui Z; Zhang Y; Yang HS; and Zhang F. 2016. Growing sensitivity of maize to water scarcity under climate change. Nature - Scientific Reports, 6, 19605.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Farmaha BS; Lobell DB; Boone KE; Cassman KG; Yang HS; and Grassini P. Contribution of persistent factors to yield gaps in high-yield irrigated maize. 2016. Field Crops Research. 186, 124-132
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Farmaha BS; Eskridge KM; Cassman KG; Specht JE; Yang HS; and Grassini P. 2016. Rotation Impact on On-Farm Yield and Input-Use Efficiency in High-Yield Irrigated Maize-Soybean Systems. Agron.J. 108, 1-9.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Morell FJ; Yang HS; Cassman KG; van Wart J; Elmore RW; Licht M; Coulter JA; Ciampitti IA; Pittelkow CM; and Brouder SM. 2016. Can crop simulation models be used to predict local to regional maize yields and total production in the US Corn Belt? Field Crops Research. 192, 1-12.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Barker, J. B., T. E. Franz, D. M. Heeren, C. M. Neale, and J. D. Luck (2017), Soil Water Content Monitoring for Irrigation Management: A Geostatistical Analysis, Agric. Water Manage, 188, 36-49.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Gibson, J., T. E. Franz, Wang, T., J. Gates, P. Grassini, H. Yang, and D. E. Eisenhauer (2017), A case study of field-scale maize irrigation patterns in Western Nebraska: Implications to water managers and recommendations for hyper-resolution land surface modelling, HESS, 21, 1051-1062.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Forney, S.H.1, J.D. Luck, M.F. Kocher, and S.K. Pitla (2017). Laboratory and full boom-based investigation of nozzle setup error effects on flow, pressure, and spray pattern distribution. Appl. Eng. Agric. 33(5): 641-653.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Franz, T. E., T. Loecke, A. Burgin, Y. Zhou, T. Le, and D. Moscicki (2017), Spatio-temporal predictions of soil properties and states in variably saturated landscapes, Journal of Geophysical Research  Biogeosciences, 122.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Heeren, D. M., G. A. Fox, C. J. Penn, T. Halihan, D. E. Storm, and B. E. Haggard. 2017. Impact of macropores and gravel outcrops on phosphorus leaching at the plot scale in silt loam soils. Transactions of the ASABE 60(3): 823-835, doi: 10.13031/trans.12015.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Lo, T.H., D.M. Heeren, L. Mateos, J.D. Luck, D.L. Martin, K.A. Miller1, J.B. Barker, and T.M. Shaver (2017). Field characterization of root zone available water holding capacity for variable rate irrigation. Appl. Eng. Agric. 33(4): 559-572.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Lo, T., D. M. Heeren, D. L. Martin, L. Mateos, J. D. Luck, and D. E. Eisenhauer. 2016. Pumpage reduction by using variable rate irrigation to mine undepleted soil water. Transactions of the ASABE 59(5): 1285-1298, doi: 10.13031/trans.59.11773.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Magnus, D.L., A. Sharda, A.Engelhardt, D. Flippo, R. Strasser, J.D. Luck, and T. Griffin (2017). Analyzing the nozzle spray fan pattern of an agricultural sprayer using pulse width modulation technology to generate an on-ground coverage map. Trans. ASABE. 60(2): 315-325.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Roeber, J.BW., S.K. Pitla, R.M. Hoy, J.D. Luck, and M.F. Kocher (2017). Tractor power take-off torque measurement and data acquisition system. Appl. Eng. Agric. 33(5): 679-686.
  • Type: Other Status: Published Year Published: 2017 Citation: Shekhar, S., J. Colleti, F. Munoz-Arriola, L. Ramaswamy, C. Krinz, L. Varshney, D. Richardson (2017). Intelligent Infrastructure for Smart Agriculture: An Integrated Food, Energy and Water System. eprint arXiv:1705.01993. 2017arXiv170501993S. A Computing Community Consortium (CCC) white paper, 8 pp.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: Singh, J., T. Lo, D.R. Rudnick, T.J. Dorr, C.A. Burr, R. Werle, T.M. Shaver, and F. Mu�oz-Arriola (2018). Performance Assessment of Factory and Field Calibrations for Electromagnetic Sensors in a Loam Soil. Agricultural Water Management.196: 87-98.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2017 Citation: Wang, T., Q. Liu, T. E. Franz, R. Li, and Y. Lang, C.A. Fiebrich (2017 In Press), Spatial patterns of soil moisture from two regional monitoring networks in the United States, Journal of Hydrology.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Wang, T., T. E. Franz, R. Li, M. D. Shulski, and C. Ray (2017), Evaluating climate and soil effects on regional soil moisture spatial variability using EOFs, Water Resources Research, 53, 4022-4035.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Wang, T., T. E. Franz, J. You, M. D. Shulski, and C. Ray (2017), Evaluating controls of soil properties and climatic conditions on the use of an exponential filter for converting near surface to root zone soil moisture contents, Journal of Hydrology, 548, 683-696.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Das, A., F. Munoz-Arriola, S. Singh, and M. Kumar (2017). Nutrient Dynamics of Brahmaputra (Tropical River) during Monsoon Period. Desalinization and Water Treatment.doi:10.5004/dwt.2017.20788.
  • Type: Websites Status: Published Year Published: 2016 Citation: Lo, T., D. M. Heeren, J. D. Luck, D. L. Martin, L. Mateos, and D. E. Eisenhauer. 2016. Map for VRI pumping reduction: Potential pumping reductions by using VRI to mine undepleted soil water. Peer-reviewed extension website, available at http://heeren.unl.edu/map.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Marx, S.E.1, J.D. Luck, R.M. Hoy, and S.K. Pitla. 2016. Comparing various hardware/software solutions and conversion methods for Controller Area Network (CAN) bus data collection. Computers Electronics Agric. 128: 141-148.


Progress 06/15/16 to 09/30/16

Outputs
Target Audience: Water resources, both surface water as well as ground water, are vital to Nebraska agriculture. For example, Nebraska ranks as the fourth state in the nation on ground water use in agriculture and first in the nation on irrigated acreage. In 2012, Nebraska was ranked 3rd and 5th in the nation in corn and soybean production, respectively. Considering that one of three Nebraskans work in ag-related jobs, water and agricultural activities are closely tied from a socioeconomic perspective. Unfortunately, in response to irrigation water withdrawals, groundwater levels have declined significantly in several major irrigated areas of the state. Also, groundwater decline can have impacts on streamflow which is important for endangered species and interstate compacts. This factor contributes to the challenge of water, agricultural, and ecosystems sustainability in the state. In consequence, the predictability of productivity of the agro-ecosystem and the consequent preparedness for change in water states is based on our ability to diagnose, forecast, and predict current and future environmental states including water availability and crop production. A key to achieving water and agricultural resources sustainability is to understand the interactions among climate, water availability and water uses in agro-ecosystems. The multi-dimensionality of the relationships defining sustainable development of water and agricultural resources can be seen as mass and energy fluxes forced by climate and regulated by human activities along the water continuum from the atmosphere to the aquifer. In this project we aim to better understand how these processes (naturally driven or anthropogenically affected) may change over time influencing future water availability and crop production. At the field-scale (producers, land/water managers), diagnostic research on water management includes irrigation scheduling, deficit irrigation, tillage practices, and drainage. However, due to the high spatial variability of soil water, there is a need for large-scale soil water measurement to provide field average soil water. As part of this project new geophysical technologies are being deployed across the state and being evaluated by producers and water managers. Despite research and extension efforts, very few producers take the time to calculate their own soil water balance. An online tool that utilizes a soil water balance and a crop growth model is available for soybeans (SoySim), but an equivalent tool needs to be developed for corn. This tool is actively under development as part of this project. At the sub-field scale, precision agriculture has provided producers the opportunity to manage inputs spatially, including fertilizer, plant population, hybrid, and water. Variable rate irrigation (VRI) technology provides an opportunity to prevent over-application and/or under-application of water. Best management practices are not yet well defined and the benefits of VRI are not well quantified and will be assessed in the current project by multiple PIs in collaboration. A well defined set of best management practices and technology transfer to local industries (center-pivot manufacturers, crop consultants, cooperative units, etc.) will no doubt continue to fuel the agricultural based economy of Nebraska and other state and national economies that seek to emulate its success. Given that this is the first year of the project, most research objectives are just underway. To date the project has resulted in 10 of peer reviewed publications, 2 extension publications, 34 conference presentations, 25 extension presentations, 17 undergraduate projects, 10 MS projects, and 7 of PhD projects. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?PI-Franz has taught 2 formal courses at the university, 1 focused at Sophomores in Natural Resources, and the other 1 focused at Seniors and Graduate students in Natural Resources. In additional PI-Franz is co-developing a Freshman level course intended for non-science majors as part of an NSF grant in Science Literacy. The course will be expanded to an online format in the coming years to reach all 4 University of Nebraska campuses. PI-Heeren taught two undergraduate courses and one graduate course in 2016. Objective 2 of the project supported 1 PhD student and provided undergraduate research experiences for three students. VRI was incorporated into MSYM 452 Irrigation Systems Management as a lecture and lab. PI-Luck taught one undergraduate course in 2016 focused on site-specific crop management. This lecture and computer laboratory-based course had 88 students registered in 2016; majors included agricultural engineering, agronomy and horticulture, mechanized systems management, and agricultural economics. Seven graduate and undergraduate students were significantly associated with project activities under objective 4 during 2016. PI-Yang Developed an online distance format for Crop Modeling, a 900 level course for graduate students. PI- Munoz-Arriola taught two formal courses (Soil and Water Resources Engineering, Extreme Events and Water Resources, and Hydroclimatology), introducing data science and engineering as well as non-stationary assessments of water resources. Undergraduate and graduate students, evidencing the need of non-stationary approaches to address water, food, and energy security through the presentation of sixteen Final projects. Also, a strong support for undergraduate research experience is evidenced in the projects developed in Munoz-Arriola research lab with 10 undergraduates working on independent research projects (half of them women in science and engineering); 80% of the undergraduates in this lab have received funding in response to competitive grants solicitations. How have the results been disseminated to communities of interest?PI-Franz organized and lead a panel discussion on Information Technology at the 2016 Water for Food Global Conference. The conference was attended by 400+ people from 40+ countries. In addition PI-Franz presented his work at 1 extension meeting attended by local producers and water managers. PI-Heeren and his graduate students gave seven extension presentations on VRI, including groups of international visitors, the Central Plains Irrigation Conference, a seminar to the NRCS, a training event for extension educators, and an extension field day. PI-Heeren also gave guest lectures on VRI for courses at UNL and one course at Purdue University. Findings were also shared through six conference presentations, including the World Irrigation Forum in Thailand. A peer-reviewed extension website was launched (http://heeren.unl.edu/map) and has had 910 page views in the first few months. Based on his analysis of 49,000 center pivot irrigated fields in Nebraska, Himmy Lo (graduate student) developed this online map tool where a producer can navigate through a Google Maps interface to find his field and get an estimate of potential pumping reductions from adopting variable rate irrigation. The website has been promoted through WFI, IANR News, a blog on irrigation education, and has been shared directly with industry. A CropWatch article is planned for early 2017 which will promote the website to the Nebraska Extension community. PI-Luck and his graduate students gave 11 research conference presentations and 13 extension presentations resulting from project activities. Over 800 individuals have attended extension presentations, workshops, or other sessions in 2016 resulting from activities conducted under objective 4. PI-Yang (1) Invited to give a presentation in a symposium of 2016 ASA-CSSA-SSSA International Annual Meetings. (2) Invited to visit two research institutions in China and to give presentations on crop modeling and their application. PI- Munoz-Arriola is member of the American Meteorological Society' Water Resources Committee. Munoz-Arriola co-authored current policy statement of such committee. I have developed three international research collaborative programs on Hydroinformatics and Integrated Hydrology with UNESCO-IHE's Hydroinformatics research group (The Netherlands); Hydrologic Modeling and Remote Sensing with the Indian Institute of Technology-Guwahati and Banaras Hindu University, and Multi-scale climate and water-cycle modeling with Universidad Autonoma de Queretaro and Baja California (Mexico) What do you plan to do during the next reporting period to accomplish the goals?PI-Franz Nothing to report PI-Heeren has an MS student who will start in January, funded by WFI student support, who will continue the VRI field research at both field sites. The current PhD student plans to graduate in May and will submit three journal manuscripts. A USDA Foundational Program grant (led by Christopher Neale and includes Wayne Woldt, Joe Luck, and others) was recently awarded which will provide funding to support the VRI field research. A 104(b) proposal has been pre-selected for funding; this project, in collaboration with PI-Munoz-Arriola, Daran Rudnick, and Burdette Barker, will focus on quantifying the impact of VRI on consumptive use of water resources. PI-Luck will be recruiting two graduate students in 2016 to continue activities related to geospatial applications of precision agriculture technologies and pesticide application systems (to be funded by a successful USDA Foundational Program proposal through 2020). Three MS students will graduate in 2016 and will submit multiple journal articles and extension publications prior to graduation. PI-Yang Nothing to report PI- Munoz-Arriola expects to communicate findings on Hydroinformatics and integrated hydrology in scientific journals, addressing the complexity of extreme precipitation and drought in agricultural working environments. Technologic developments (prototypes) will be launched this year as part of the under-development Water for Food Interoperability/Information System (WaFIS). PI-Munoz-Arriola expects to strength communication and collaboration with irrigation district administrators as well as private companies, exploring new synergies with such sectors. Six papers will be submitted in the following two months and three postdocs have been recruited as part of collaborative funds obtained this year.

Impacts
What was accomplished under these goals? MA= Major Activities; DA=Data Collected; SM=Summary Statistics; KO=Key Outcomes Objective 1. MA: Installation of 10 cosmic-ray neutron probes across Nebraska DC: Hourly soil moisture data at 10 sites and 50 geophysical spatial maps. SM: This objective has resulted in 3 of peer reviewed publications, 0 extension publications, 5 conference presentations, 1 extension presentation, 2 undergraduate projects, 3 MS projects, and 2 PhD projects. The results of the research have led to 4 additional grant applications. KO: To date the greatest impact has been a change in knowledge with the publication of peer reviewed papers and conference presentations. We anticipate a change of action in the coming years as we interact with more producers and water managers across Nebraska. Objective 2. MA: Variable rate irrigation (VRI) field research at ARDC near Mead, NE (sub-humid). A second field site at the BWL near Brule, NE (semi-arid) was added to the project. Dynamic prescription maps applied water based on four treatments: uniform irrigation based on neutron probe data, VRI based on neutron probe data, VRI based on remote sensing data and modeling, and dryland. At the ARDC site, cosmic-ray neutron probe rover data were collected and analyzed along with the neutron probe data. DC: Weekly neutron probe soil water content readings, crop height, crop stage, irrigation applied, and yield for 138 management zones. SM: In 2016, this objective resulted in 1 peer reviewed publication, 1 extension publications, 6 conference presentations, 7 extension presentations, 3 undergraduate projects, 0 MS projects, and 1 PhD project. The results of the research have led to 3 additional grant applications. KO: To date the greatest impact has been a change in knowledge with the publication of a peer reviewed paper, conference proceedings, several presentations, and a peer reviewed extension website. Objective 3 part 1. MA: developed online app CornSoyWater, an irrigation decision support tool for irrigation of corn and soybean fields. Comparisons were made between predictions of the program and field observation/measurements. DC: measurements were collected from production scale fields as well as small plots for testing and validating the CornSoyWater app SM: Three manuscripts out of the activities have been submitted to peer-reviewed journals. One PhD student has completed his degree study. Received a two-year research grant for developing online, real-time N leaching and mapping for Nebraska. KO: (1) The CornSoyWater app has more than one thousand registered users. An ag-company in Nebraska is investing and collaborating with us to further develop the model based farming decision tools. Objective 3 part 2. MA: An ag-company in Nebraska is investing and collaborating with us to develop computerized integrated decision support system for irrigation and fertilization for corn and soybean, and to incorporate it into the control panel of center pivot to automate the variable rate irrigation control. DC: one season field data from producers' fields have been collected to test the prototype of the grogram. SM: A new proposal has been submitted to the Nebraska Department of Economic Development for the collaboration between UNL and the ag-company mentioned above. KO: a prototype has been developed for the computerized integrated decision support system for irrigation and fertilization for corn and soybean. Objective 3 part 3. MA: conducted two studies using multiple year-field farmers' reported data for several natural resource districts of Nebraska DC: no new data collected. SM: published one paper in peer reviewed journal, submitted another manuscript for publication, and a MSc student completed her study. KO: The studies found that many farmers over-irrigated corn and soybean crops by more than 20% of the necessary amount. This could be due to combination of risk aversion consideration and not knowing the correct amount of water requirement. Objective 4. MA: PI-Luck led or significantly contributed to multiple field-based research projects across eastern NE for improving crop input control including: multi-hybrid planter applications in corn and soybeans (MS student Rachel Stevens), crop canopy sensor-based N application in corn, improved harvest operation logistics , data intensive seed rate and fertilizer management (MS student Greg Frenzel), and enhanced pesticide application mapping for improving operator behavior. DC: Multiple geospatial datasets were collected for these projects including machine field operation status, as-applied data from field equipment, crop status from active canopy sensors, and field-level agronomic data including terrain, soil texture, and other soil properties. SM: In 2016, outputs from this objective led to publication of 4 peer reviewed journal articles, 11 conference presentations, and 13 extension presentations. The objective was supported by 4 MS graduate student projects and 1PhD graduate student project. Project objective activities led to the submittal of 9 additional grant proposals in 2016. KO: Project research activities led to significant outreach through extension programs to clientele across NE and other states. In 2016, over 800 individuals received research-based information from this project objective via different extension presentations, workshops, and media. Objective 5 part 1. MA: Development of a multi-distribution-function statistical model to assess Extreme Hydrometeorological and Climate Events (EHCEs); implementation of two land surface hydrologic models to simulate hydrologic responses to EHCEs in agroecosystems and ecosystems in the Northern High Plains at basin- and catchment-scales; and implementation of a multi-scale climate model to simulate EHCEs. (ii) Development of hydroclimatological data collection and seasonal forecast systems. DC: Groundwater-well levels, precipitation, remote sensing Leaf Area Index and Soil Moisture at various timespans and frequencies. Co-developed a precipitation, minimum and maximum temperatures, and wind speed 1/16th resolution database for the US, Canada, and Mexico. SM: This objective has resulted in 1 peer reviewed publication, 0 extension publications, 2 conference presentations, 1 extension presentation, 7 undergraduate projects, 2 MS projects, and 2 PhD projects. The results of the research have lead to 4 additional grant applications. KO: To date the greatest impact has been the development of a hydroclimatological dataset . Further, implemented models are used to test climate indices for crop, livestock and community decision-making. Objective 5 part 2. MA: (i) Development of two platforms coded in Java and Python, aimed to collect data from publically available sources and individuals; (ii) A seasonal forecast platform has been created using "C" programing to operate forecasts of water availability; (iii) Analytics on extreme weather and climate; and (iv) Analytics to improve short- to seasonal forecast of Groundwater-use. DC: We collected groundwater data via web services from the USGS; other sources of climatological data are collected from High Plains Regional Climate Center and the Nebraska Geological Survey. SM: This objective has resulted in 0 of peer reviewed publications, 0 extension publications, 6 conference presentations, 1 extension presentation, 3 undergraduate projects, 2 MS projects, and 2 Postdoc. The results of the research have lead to 6 additional grant applications. KO: To date the greatest impact has been a change in the development of analytics and synthesis techniques specific to address stakeholders' demands of water resources data under changing weather and climate conditions. We have made progress toward better understanding the role of data and information technologies on decision-making.

Publications