Looking at the manure-management technologies that currently exist and the new and emerging technologies, Newtrient provides a reliable, third-party technology evaluation tool for the dairy industry. Three years of time and effort has been put into evaluating almost 300 technologies that are included in the catalog, over half of which are related to biogas production or digestate management. Newtrient launched an open-source, technology catalog in 2017 that provides a comprehensive listing of relevant and readily available dairy manure management technologies in the U. S.
What we do?
The U.S. dairy industry is voluntarily playing a critical role in working “towards sustainability” (Scott & Gooch, 2017). As a result of industry consolidation, manure treatment technologies are being developed and marketed that target larger operations. The goal is to help farms work on continuous improvement on sustainability issues while operating at larger scale. Unfortunately, the efficacy and economics of the treatment technologies are not always well established. As a result, the relative costs and impacts are often difficult to compare, although its importance is realized.
Newtrient, on behalf of the U.S. dairy industry, formed a Technology Assessment Team (TAT) in 2016, comprised of a cross section of academic and industry professionals with in-depth expertise in dairy manure management. One of the first tasks assigned to the TAT was to conduct systematic verification and catalog available dairy manure treatment technologies in the United States. The ongoing effort by Newtrient is to identify and evaluate available dairy manure treatment technologies which has resulted in the Newtrient online Technology Catalog (Catalog)with over 240 entries (Newtrient, 2019).
Lessons Learned?
Many lessons have been learned during the development of the Newtrient Technology Catalog. One of the most important is that it is necessary to develop a standard, easy to use way of presenting the information on many differing technologies and companies, the Newtrient TAT does this in a variety of ways including:
Company description – We work with each vendor to provide a brief description of the company, its mission and its history.
Technology description – A succinct and informative overview of the technology and how it works is the goal and this, combined with an image or flow chart, is often enough for the average visitor.
Business information – A vendor-completed Newtrient Business Information Request (BIR) form can be viewed or downloaded when additional information is desired.
Technology information – A vendor-completed Newtrient Technology Information Request (TIR) is also available on line providing additional technical details including what it takes to install and make the technology work.
Expert reviews – Expert opinion and evaluation of technologies from the Newtrient TAT provide insight and perspective that is not available anywhere else.
Newtrient 9-Point Score – A quick and intuitive visual reference that provides answers to 9 specific questions in three categories, chosen to help set a standard for technologies and a basis for comparison. The nine points include the following:
COMMERCIAL VIABILITY
OPERATIONAL HISTORY – Is this technology currently operational on at least three North American dairy farms?
OPERATIONAL RELIABILITY – Does this technology have record of reliable performance of more than 12 months at each of at least three farms?
MARKET PENETRATION – Has this technology been installed on at least 10 North American dairy farms?
ECONOMICS & INDUSTRY VALUE
CAPITAL COST – Has information on the installed capital costs been clearly defined and communicated to the Newtrient TAT?
OPERATIONS AND MAINTENANCE COST – Are the actual operations and maintenance costs clearly defined and communicated to the Newtrient TAT?
VALUE PROPOSITION – Does this technology or the products it makes, deliver to the farm identifiable economic, environmental, or community value (e.g. reduced cost, increased income, reduced odor, improved nutrient use, etc.)?
TRANSPARENCY & INTERACTION
VENDOR INFORMATION SHARING – Has the company provided complete and verified Newtrient BIR and TIR documents to Newtrient?
CASE STUDY – Has a case study demonstrating the performance claimed by the vendor been completed by the Newtrient TAT?
CUSTOMER REVIEWS – When asked how likely is it they would recommend this technology to a colleague; have at least three customers scored the technology at least a 7 out of 10?
Highlighting Technologies – Newtrient reviews technologies and provides recognition for those that have proven themselves, show potential or have not engaged with Newtrient but are actively marketing to dairymen. The three categories are:
Newtrient Recognized: for technologies that are proven in the field.
Emerging Technology: for technologies that show significant promise.
Not Vendor Verified: for vendors who have not worked with Newtrient to verify and validated the information regarding their business or technology.
Newtrient Evaluation & Assessment of Technologies (NEAT) – After the catalog was first introduced it became obvious that there was additional work that was needed regarding the impact of each technology on key environmental areas. In response, the TAT developed the NEAT process for evaluating technologies and their impacts on six key areas (see accompanying paper presented at this conference on the NEAT process).
Future Plans
The Newtrient Technology Catalog is ever changing and being updated; new technologies are added regularly, BIRs and TIRs are updated, new case studies are written, and new functionality is added regularly. The catalog was recently updated to accommodate outcomes of applying the NEAT process to select technology types. Additionally, the TAT is evaluating inclusion of the following:
NRCS Conservation Practice Standards and guide to USDA grant programs
Feed and manure additives with a system for comparing their efficacy and economics
Directories of resources for help in nutrient management planning, engineering, and other professional services related to manure treatment/nutrient management
Expanding and updating the Newtrient TIR to include all of the information needed to qualify a technology for USDA grant and cost share programs
Author
Mark Stoermann, Chief Operating Officer, Newtrient LLC.
mstoerm@newtrient.com
Other authors
Curt Gooch, Environmental Systems Engineer, PRO-DAIRY Dairy Environmental System Program, Dept. of Animal Science, Cornell University.
Additional information
Additional information, including business information, technical information and case studies on technologies, is available on the catalog page of the Newtrient website: https://www.newtrient.com
Acknowledgements
Newtrient, LCC and the papers authors thank the following supporters of Newtrient: Agri-Mark, Inc.; Dairy Farmers of America, Inc.; Dairy Management Inc.; Foremost Farms USA; Land O’Lakes, Inc.; Maryland Virginia Milk Producers Cooperative Association, Inc.; Michigan Milk Producers, National Milk Producers Federation; Prairie Farms Dairy, Inc.; Prairie Farms Dairy, Inc.; Select Milk Producers, Inc.; Southeast Milk, Inc.; St. Albans Cooperative Creamery; Tillamook County Creamery Association; and United Dairymen of Arizona.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
Recently there have been significant effort put into promoting soil health, emphasizing management practices such as low or no tillage, cover crop, and increasing soil organic matter content. A state-wide effort in Missouri has been taken to encourage adoption of cover crops, to improve water quality and soil health. The program presents a unique opportunity for systematic evaluation of soil health indicators, crop rotation and yield, and manure application. Participants are required to submit soil samples to University of Missouri Soil Health Assessment Center (https://cafnr.missouri.edu/soil-health/), on an annual basis, along with critical crop, soil, and manure nutrient management information. The objective of this effort is to assemble and analyze soil health indicators and manure application data.
What did we do?
A team of agricultural engineers and soil scientists in Missouri correlated data of soil health variables and manure land application details, for state-wide and research plot data. For the first dataset (2016-17) collected, the team examined the overall effects of manure land application on soil characteristics, especially those that have more implication in soil health. In addition to the typical soil nutrient (nitrogen and phosphorus) variables, many key soil health indicators that were included in the program are total organic carbon, active carbon, exchangeable cations, bulk density, and water stable aggregates. Some of the important management information collected from the program included field location, crop rotation, tillage use, and if there was previous cover crop use, etc. Manure land application information included manure type, application rate, and method applied.
In order to better examine the effects of manure land application on soil characteristics, another set of data from research plots was examined. The controlled, experimental field plots had consistent tillage and repeated crop and fertilizer treatments. Some of the plot management considered included full fertilizer, no fertilizer, manure application (6 tons manure/acre), and green manure (red clover). A wide range of cropping systems were conducted, ranging from continuous corn, continuous soybean, continuous wheat, continuous Timothy, to three-year rotation of corn-wheat-red clover, and four-year rotation of corn-soybean-wheat-red clover.
What we have learned?
A significant difference was found only for phosphorus for the state-wide samples. The lack of correlation is mostly likely because of relatively few samples were associated with manure application, and the samples were highly variable in tillage, soil type, crop, and manure type, application rate and methods. However, when the effects of manure land application was compared within the counties, the manure applications increased the active carbon contents (p<0.01) for two of the top three counties where manure application data was collected. The manure application also significantly increased (p <0.05) organic carbon, phosphorus, potentially mineralizable nitrogen, and water stable aggregate values for Stoddard county.
For the central Missouri research plot data, the manure land application clearly affected several key variables. The manure application has resulted in higher soil organic carbon, active carbon, phosphorus, and water stable aggregates, and lower bulk density, Figures 1 and 2.
Include impacts/implications of the project or research.
These findings confirm that the benefits of manure application in increasing soil organic materials and improving soil aggregate ability can be seen at least from fields that were consistently treated. While considering measurable economic and environmental impacts of nutrient and manure management, especially for increasing the carbon content in the crop fields, manure land application can be one of the recommended practices.
What should people remember as take-home messages from your presentation?
Manure application can be considered an effective management to increase soil organic carbon, active carbon, and water stable aggregates, and decrease soil bulk density, although the results have also shown to increase soil phosphorus content. The findings regarding manure use and important soil health indicators are important to management of the soil and can be contributing to many factors need to be considered for increasing food production on a limited land base.
Future plans
Continue analyzing the growing management and soil analysis dataset, and cross examining the correlation between the different variables. The team will promote the findings and encourage management that can result in better soil health and resource preservation.
Authors
Lim, Teng (Associate Professor and Extension Agricultural Engineer, Agricultural Systems Management, University of Missouri, limt@missouri.edu)
Wang, Allen Haipeng (Heilongjiang Bayi Agricultural University); Brandt, Donna, (University of Missouri); Norkaew, Saranya, (University of Missouri); Miles, Randy (University of Missouri); and Rick Koelsch, (University of Nebraska, Lincoln).
Additional information
Please visit https://soilhealthnexus.org/can-manure-improve-soil-health/to find more information and download the data brief and final report.
Acknowledgements
Funding for this data analysis and report were provided by the North Central Region Water Network – a 12-state collaboration between Extension water resource professionals and university, federal, state, NGO and industry partners; and Soil Health Institute (http://soilhealthinstitute.org/).
Figure 1. Comparisons of organic carbon contents for the state-wide and research field plot soil samples, the plots depict median (solid line), mean (x), quartile box, and minimum/maximum values. The state-wide samples (Top figure) were state-wide average (overall), fields treated with manure (Soil+manure), and fields did not have manure application (Soil-manure). The field plot treatments (Bottom figure) were full fertility (FF), manure (M), and no fertility (NF).Figure 2. Water stable aggregates of state-wide and researcy field soil samples, the plots depict median (solid line), mean (x), quartile box, and minimum/maximum values. The state-wide samples (Top figure) were state-wide average (overall), fields treated with manure (Soil+manure), and fields did not have manure application (Soil-manure). The field plot treatments (Bottom figure) were full fertility (FF), manure (M), and no fertility (NF).
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
NRCS has started a pilot project to test existing animal waste storage facilities for seepage using the DeltaProbeTM Seepage meter. The DeltaProbeTMseepage meter is the result of an NRCS Conservation Innovation Grant (CIG) to develop a device to quickly and directly measure seepage rates from waste storage ponds or lagoons. The pilot project will assess the use of the equipment under a variety of regional, environmental and climatic conditions.
What did we do?
The DeltaProbeTM Seepage meter was developed in Michigan through an NRCS Conservation Innovation grant (CIG) with Nth Consultants, Ltd. and Abletech Industries, LLC.
NRCS purchased two seepage meters and trained six individuals to operate the device. The device is used in conjunction with a weather station on site to collect data.
Standard Testing procedure has been developed.
Initial testing under the CIG was performed in Michigan. A pilot test was performed in Washington state on an HDPE lined waste storage facility during 2018. Further testing was planned for the winter months of 2018, but the extremely high rainfall has precluded testing.
What we have learned?
The equipment has the potential to provide “whole pond” testing of a waste storage facility overnight under suitable conditions. The device can measure the change in the depth of water surface with a 95% confidence interval to the nearest 0.035 mm over a 25.4 mm range in 8 hours overnight.
Testing results in a snapshot of seepage rate under the conditions during the timeframe which the test is performed.
The equipment requires training for proper setup, use and to review the results of testing.
Future plans
Further testing will take place on waste storage facilities in North Carolina and Kansas in 2019.
Agricultural Research Service (USDA, ARS) will be providing a test of the equipment.
Authors
Sandra L. Means, Environmental Engineer, USDA-NRCS, National Animal Manure Nutrient Management Team, Greensboro, North Carolina. Sandy.Means@gnb.usda.gov
Bill Reck, National Environmental Engineer, USDA, NRCS.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
Provide leaders with information to develop a well-planned crowd-sourced data application that improves communication and speed response times in disasters. Recognize the potential benefits of crowd-sourced and employee-sourced real-time geospatial data during emergency response. Present steps taken by United States Department of Agriculture – Natural Resources Conservation Service (NRCS) Texas State Office for the deployment of the “dead cow tool” and share lessons learned. Provide a framework of questions and items that need to be addressed for the successful deployment of a real-time data collection tool.
What Did We Do?
In response to Hurricane Harvey in the fall of 2017, the Texas NRCS GIS staff developed on-line reporting tools to collect real-time data related to damages and animal mortalities that could be used by employees and the public. ESRI’s ArcGIS Collector Application was selected for its ease of use, ability to be used when off-line, and staff familiarity with the tool’s programming language. In this case, NRCS already had the necessary licensing for ArcGIS Online accounts.
The “dead cow tool” is a near real-time reporting tool for the public to identify locations, types and magnitude of agricultural losses. This provides NRCS and other agencies with data to request funding for emergency response and recovery funds to assist the local agricultural producers. However, significant concerns were raised relative to releasing the application for public use, so the data collection applications were then limited to a handful of NRCS employees within the disaster areas.
The Dead Cow Tool (displayed as Hurricane Harvey Data Collector Map) was designed to collect the following parameters: Damage Type; Livestock Type; Number of Livestock Lost; Number of Livestock in Need; Accessibility; and Comments. There was also an option to add or take images and add the location from a map previously downloaded onto a user’s mobile device (if network connectivity was lacking). Here are a few screenshots to serve as an example from an iPhone (Figures 1 – 6):
Figure 1. Data collection maps developed in response to Hurricane Harvey
Figure 2. Main data collection screen for the “Dead Cow Tool” aka Hurricane Harvey Collector Map
Figure 3. Options for damage types in the “dead cow tool”
Figure 4. Completed Livestock Damage Assessment ready to be submitted. There is includes the option to add a photo.
Texas NRCS developed and deployed another tool for employees to complete Damage Survey Reports while in the field. “In Hurricanes Ike and Rita, staff went out in the field, took handwritten notes about the damage, wrote down the location, took pictures and then had to return to the office, to download and enter the information on their computer. They had to look up the latitude and longitude points from their notes to document the exact location and then save all that information in several different locations. It was a long process for our staff,” says NRCS State Soil Scientist Alan Stahnke. “I knew there had to be a way to make it more efficient for them.” Stahnke had been working with Steven Diehl, GIS technician, and others on his staff for several months on an ArcGIS application, ArcCollector, based on ESRI map data. They had the basics down and when Hurricane Harvey showed up on the radar, they knew they had to work fast to get the application ready for staff in the wake of Harvey’s wrath. The resulting smart phone device field tool – the Hurricane Harvey Damage Reporter – is a method to record the damage and collect information on all the points into a central database. (Littlefield, 2017)
The Damage Survey Report tool reduced the time needed by field engineers by approximately 50% from the previous method. The data was available to others with access as it was entered – thereby providing timely data to managers and leadership. Additionally, it allowed the final reports to be developed by state office personnel further reducing the time required by the field – allowing them to take care of other pressing matters.
Figure 5. Screenshot of Data Collected and viewed through ESRI’s ArcGISOnline Portal
Figure 6. Screenshot of visual map of data collected through ESRI’s ArcGIS Online Portal
What Have We Learned?
Several lessons were learned: First, approve policies on data collection prior to the disaster – these need buy-in and flexibility. Second, decide how data will be released and identify typical reports. Third, develop Data Collection Applications in advance – allowing testing, training, familiarity, and formatting needed for user-friendliness. Fourth, select the correct Data Collection Tool. Fifth, identify data collection alternatives if the application cannot be realistically utilized – power outages, lack of network connection, closed roads, flooded areas, etc.
It is important to prepare, plan, and train prior to a disaster to allow time to adjust and/or develop policies and reduce knee-jerk reactions.
Data collection can have negative impacts if not properly administered and protected. Several identified concerns during Hurricane Harvey were protecting the data collected, preventing submittal of inappropriate language and/or photos, potential for someone submitting the data to believe that they had applied or requested assistance, and data distribution. Our NRCS GIS specialists (Texas and across the US) worked with ESRI developers to overcome some of the data protection and prevention of inappropriate material. However, obtaining clearance from leadership for public-use of the application was not obtainable in a timely matter.
Real-time data collection is a useful tool for both internal customers and the public when faced with a disaster and allows the timely coordination of resources for rapid response and recovery.
Disasters such as Hurricane Harvey require significant resources for response and recovery. Real-time data collection can aid in allocating resources. With animal mortalities, it is important that animals in sensitive environmental areas are properly disposed of in a timely manner. NRCS has provided technical and financial assistance for proper carcass disposal following natural disasters to reduce the associated environmental risk.
Generating Reports and Maps with Information Collected — Recognize the market impacts of sharing reported losses. NRCS must follow applicable federal rules and regulations to related to personally identifiable information. Generally, a report could be published with information grouped by county based on collected data provided there is more than one producer in the county with that type of livestock or commodity. For example, if there is only one farm in a county with emus, and the producer reported their losses of 50% of their emus, USDA Agencies could not share that data, as the producer could then be identified.
Policies are needed to address data collection with public interfaces. Consider modifications to existing policies or creating new policies to allow the use of crowd-source data.
The intent of the app and intended use of the data must be clearly conveyed to users. USDA Agencies raised concerns the public would believe that the tool indicated that they were applying for assistance, not simply reporting. (Stahnke, Jannise, & Northcut, 2018)
Prior to collecting data, appropriate policies should be written that address, how, when, where and why the information is needed and how it will be used in accordance with federal data collection requirements. The policies should be reviewed internally by a variety of users to ensure that the policy is clear and provides adequate accountability. Buy-in from all levels is needed prior to launching a data collection system to the public. Depending upon the type of organization that is collecting the data – a variety of controls may need to be established to protect the data.
How the data will be collected and shared– this area should allow flexibility. Allowing public to enter data using their own devices may be necessary to obtain the data in a timely manner. What will public users gain by sharing their information?
Will the data be shared with other agencies, non-governmental organizations (NGOs), etc.?
If employees are allowed to use their own device, is there a possibility of a litigation hold on the personal device? (USDA – Forest Service, Mobile Geospatial Advisory Group, 2015)
When does the data need to be collected? This may vary – for example, the number and type of livestock lost in a sensitive area may need to be reported as soon as the livestock are found; flooded fields and associated losses, road closures, or areas with downed power lines may have some lag-time in reporting over a period of several weeks as roads and properties become available for inspection
Where does the data that has been submitted get collected?
Who is going to oversee the data collection and create needed reports?
Will the data be adequately protected? As mentioned, some of the data collected, particularly with potential images and audio embedded with file attributes, will likely include personal or sensitive data that must be protected.
Why is the data being collected?
Will it serve a purpose and be used?
Can the data be potentially abused?
What level of data integrity is required?
Will certification or training be required for various users?
Will additional weight be placed on data from “authenticated” or “certified” users?
Who will be required to review of the proposed data collection system?
Should these vary based on the scope of the project? Setting the review levels and identifying who is authorized for deployment of the tool in advance is helpful to know what rules need to be followed. Some flexibility should be provided to allow modifications and adaptations as needed during an emergency.
Selecting the appropriate data collection tool and platform is critical to success. There is an organization “Principles for Data Collection” that has created a guidance document for mobile data collection (MDC). Additionally, they host a “Digital Principles Forum — an online meeting place for peer learning, connection building, and debate on the Principles for Digital Development. Together with you, we aim to build a community that connects ICT4D, information technology, and international aid and humanitarian development practitioners with thoughtful curated content, relevant conversation and quality opportunities to improve their work.”
“How to Choose a Mobile Data Collection Platform” is a guidance document prepared by the Principal for Data Collection group. Below are some of the considerations that they have identified:
Consider data and security needs including personal or sensitive data.
Consider the ecosystem – following a disaster, internet and wireless connections may be intermittent or non-existent.
Identify and prioritize selection criteria
Short-term and long-term costs
Number of users, surveys, and items
Devices and data requirements for enumerators
Security and privacy compliance
Integration with other technology
Offline collection
Short Message Service (SMS) integration
Unstructured Supplementary Service Data Integration
Authentication and user roles
Skip logic and data parameters
Data analysis
GIS and mapping
Language
Photos, audio and video
Ease of setup and use
Research MDC platform options
Rank options
Consider whether to customize an MDC platform
Select and test your platform.
TIP: Be sure to test several devices in your context before making a final selection.
(Principles for Digital Development, 2018)
When developing and testing applications, consider the following:
Users accessibility to AGOL, i.e., do they need a login in their company’s Enterprise ESRI platform or is the application in the public domain on AGOL.
Amount of training required for user to input
Ease of navigation and number of clicks required to complete form
Varying size of screens on user devices (small screens vs. tablets)
Test with a variety of different levels of users
Types of reports and training required for the administrator
Duration of the application and availability
Creating sample reports and identifying who can see specific data in advance will aid when a disaster does occur. In Texas, this type of data might be useful to the Texas Animal Health Commission, and other agencies involved in Emergency Support Function #11 – Agriculture and Natural Resources Annex (ESF-11).
The following items should be further investigated for disaster related activities:
FEMA’s National Incident Management System
How to share some information with users that have input data – allows them to know that their data is being utilized for a worthy cause
Identifying other agencies that are working on recovery efforts with the same groups
Setting up mechanisms to share data automatically rather than relying on an individual to send out reports
Methodologies for ground-truthing and screening data quickly
Explore the possibilities of utilizing ESRI’s WorkForce application to track locations of employees for safety and workflow coordination.
It is important to consider that even with the best tools developed and ready for deployment – they might not be able to be used in the field if there is no power to charge the mobile data collection device or ability to transmit the data back to the database. Considerations of solar chargers for the mobile devices for employees might be helpful. Establishing alternate methods of communication such as, but not limited to, land lines, postal mail, drop off locations, leaving surveys at the gates, and 800 phone numbers should be implemented.
Future Plans
There are infinite possibilities for the collection and use of real-time data in a disaster. It is the opinion of the authors that the potential benefits greatly outweigh the risks of not obtaining and utilizing the data. We will continue to share the lessons learned to help others implement solid data collection tools.
Authors
Cherie LaFleur, P.E., Environmental Engineer, USDA – Natural Resources Conservation Service, Central National Technical Service Center, Fort Worth, Texas. Cherie.lafleur@usda.gov
Collins, C. (2017, October 27). Retrieved from Texas Observer: https://www.texasobserver.org/agriculture-losses-estimated-200-million-harvey/
Fannin, B. (2017, October 27). Texas agricultural losses from Hurricane Harvey estimated at more than $200 million. Retrieved from AgriLife Today — Texas Agrilife Extension: https://today.agrilife.org/2017/10/27/texas-agricultural-losses-hurricane-harvey-estimated-200-million/
Littlefield, D. A. (2017, September). NRCS Develops New Web App to Expedite Agency Response to Harvey. Retrieved from USDA-NRCS: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/tx/newsroom/stories/?cid=nrcseprd1351676
Principles for Digital Development. (2018, May 8). How to Choose a Mobile Data Collection Platform. Retrieved from Digital Principles: https://digitalprinciples.org/wp-content/uploads/PDD_HowTo_ChooseMDC-v3.pdf
Stahnke, A., Jannise, P., & Northcut, M. (2018, 05 15). USDA NRCS Texas Personnel. (C. Stanley, Interviewer)
The Weather Company. (2017, September 2). Historic Hurricane Harvey’s Recap. Retrieved from The Weather Company: https://weather.com/storms/hurricane/news/tropical-storm-harvey-forecast-texas-louisiana-arkansas
USDA – Forest Service, Mobile Geospatial Advisory Group. (2015, August). Internal Document: Collector for ArcGIS Field Data Collection Pilot for Enterprise GIS Using ArcGIS Online.
Acknowledgements
Alan Stahnke, State Soil Scientist, NRCS, Temple, TX.
Pam Jannise, State GIS Specialist, NRCS, Temple, TX.
Steven Diehl, Cartographic Technician, NRCS, Temple, TX.
Mark Northcut, Landscape and Planning Staff Leader, NRCS, Temple, TX.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
Soluble nutrients are believed to be contributing to the recent high-profile impacts in the Great Lakes including excessive cyanobacteria growth (Ohio 2010; Baker et al. 2014). Retaining nutrients, and especially phosphorus in the Great Lakes region, on crop land is also important to the producer as it is non-renewable, scarce, expensive, exhibits high price variability, and can cause adverse environmental impacts when discharged into fresh water systems.
This research program was designed to quantitatively investigate preferential flow pathways caused by macropores by conducting field analyses using the mobile macropore characterization unit. Such pathways enable soluble nutrients, such as phosphorous, to rapidly migrate through soil, into tile drains, and then to surface water (Geohring et al. 2001; Heathwaite and Dils 2000). Results, along with site characteristics such as farm-management practices, topography, soil texture, depth to water table, depth and spacing of subsurface drains, if applicable, topography, and proximity to surface water, enable the qualitative selection of the best management practice to retain nutrients. This approach recognizes that all farm fields are unique and best practices to maximize nutrient uptake and minimize its transport off site are not equally applicable
What did we do?
Forrer et al., 2000, developed a visual technique to assess liquid flow through microporous soil. The technique entails adding dye to small plots of saturated soil and excavating trenches in each area. This method was expanded by photographing the soil profiles, processing the image to convert pixels with dye to white and soil without dye to black, and quantifying each with depth using MATLAB (Figure 1). The result is an estimate of the amount and extent of the macropores.
Figure 1. Assessment of Soil Macropores
This technique was packaged into the mobile macropore characterization unit to allow for efficient measurements (Figures 2 and 3).
Figure 2. Mobile Macropore Characterization Unit
Figure 3. Dye and Water Distribution Unit using Sprinklers
What we have learned?
Five sites across Michigan with varied management practices and soil structure were tested using the newly developed protocol as shown in Figure 4.
Figure 4. Representative Images from Five Sites using Dye Tracer Study
What are the next steps?
The mobile micropore characterization unit will be used extensively at an ongoing edge-of-field monitoring research site in Michigan to develop correlations between soluble pollutants in the tile drain water and quantitative macropore characterization. Thereafter, the unit will be used by extension educators for field-specific measurements to help producers decide on the most appropriate best management practices.
Authors
Steven I. Safferman1, Jason S. Smith2, Thiramet Sothiyapai3, Ehsan Ghane4
1 Associate Professor; Michigan State University, Biosystems and Agricultural Engineering; Corresponding Author: SteveS@msu.edu
2 Teaching Specialist, Michigan State University, Engineering CoRe
3 Undergraduate Research Assistant, Michigan State University, Biosystems and Agricultural Engineering
4 Assistant Professor and Extension Specialist, Michigan State University, Biosystems and Agricultural Engineering
Additional Information
Baker, D. B., R. Confesor, D. E. Ewing, L. T. Johnson, J. W. Kramer, and B. J. Merryfield. 2014. “Phosphorus Loading to Lake Erie from the Maumee, Sandusky and Cuyahoga Rivers: The Importance of Bioavailability.” Journal of Great Lakes Research 40 (3): 502–17. https://doi.org/10.1016/j.jglr.2014.05.001.
Forrer, I., A. Papritz, R. Kasteel, H. Flühler, and D. Luca. 2000. “Quantifying Dye Tracers in Soil Profiles by Image Processing.” European Journal of Soil Science 51 (2): 313–22. https://doi.org/10.1046/j.1365-2389.2000.00315.x.
Geohring, Larry D, Oloro V Mchugh, M Todd Walter, Tammo S Steenhuis, M Saleem Akhtar, and Michael F Walter. 2001. “Phosphorus Transport Into Subsurface Drains By Macropores After Manure Applications :” Soil Science 166 (12): 896–909.
Heathwaite, A. L., and R. M. Dils. 2000. “Characterising Phosphorus Loss in Surface and Subsurface Hydrological Pathways.” Science of the Total Environment 251–252: 523–38. https://doi.org/10.1016/S0048-9697(00)00393-4.
Ohio, E P A. 2010. “Ohio Lake Erie Phosphorus Task Force Final Report.” Ohio EPA OH Task Force.
Acknowledgements
This project was funded by the Michigan Soybean Promotion Committee, Corn Marketing Program of Michigan, and Michigan Wheat Program. The author wish to acknowledge contributions from Brendon Kelly, Lyndon Kelly, Steve Miller, and the MSU Soil and Plant Nutrient Laboratory.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
Livestock farming practices and technologies, like many aspects of agriculture and industry, continue to evolve. As technology and attitudes change regarding livestock farming, public response changes as well; this is reflected in the way that people talk and write about the subject. This change and growth is a common topic of both public and technical debate and scrutiny. Databases on the internet collect public articles and documents related to livestock farming dating back to the early 1980’s. The information in these articles can be evaluated using a number of computer science based approaches. These data can help to highlight how significant past events and their impacts were perceived, and possibly predict how future trends within the industry will be described in popular press/media.
What Did We Do?
We gathered popular press articles from an online database, Factiva, with the search terms “livestock and odor,” from the year 2000 to the present. A computer program developed using machine learning processes: (1) cleans and structures the individual articles into text files; and (2) quantifies the importance and frequency of words in individual and groups of articles, by year. The program assigns two measures of importance to each word. Words that frequently occur in many articles per year provide broad overarching ideas and subjects. Words that are deemed important to each individual article provide more nuanced data including companies, people, and equipment discussed in livestock farming. To demonstrate the results, this data is visualized in tables and graphs to show patterns in subjects as they develop and change over time.
What Have We Learned?
This analysis method gives us a quantitative basis for reviewing the change in importance of words over time. All analysis after choosing the subject and search terms is done by a computer program, protecting the outcomes from reader bias. Changes in word importance or frequency can be supported with numerical data and easily visualized from year to year. The different approaches also allow for inferences between long-term subjects and ideas (Table 1), and shorter term players in the industry (Table 2).
This analysis method does not pull out the context that any of the words are used. Manure and waste are two means of describing the same material, with different connotations. Manure and waste appeared at similar frequencies in many, but not all years. Dairy was more prominent in 2011 and 2013, but hogs (or synonyms) appeared in most years. Refinements to the article search protocol could limit the articles to those of opinion (i.e. editorials) or regional perspectives. There are opportunities for this method to inform historical reviews of livestock and the environment, and inform future communication efforts.
Future Plans
There are a number of opportunities to extend this project in the future. One would be to experiment with different search terms and databases to see how outcomes depend on the data source. Another opportunity would be to apply the quantitative method to other applications. The computer program could be applied to any database and so the method has utility to topics other than livestock farming.
Authors
Ryan Felton, Undergraduate Research Assistant, University of Minnesota
Erin Cortus, Assistant Professor and Extension Engineer, University of Minnesota
ecortus@umn.edu
Additional Information
Project support provided by the University of Minnesota UROP program.
Table 1. The top twenty words by year that most frequently appeared in a popular press article database search based on the keywords “livestock and odor”, by year. The relative frequency of some livestock types (cattle, hog, dairy) and manure-related words (manure, waste) are highlighted.
Table 2. The top twenty words by year that were the important focus of articles in a popular press article database search based on the keywords “livestock and odor”.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
In the Twin Cities, sewage sludge is incinerated and in the process 5 MW of power is generated per day. Incineration produces significant amounts of ash (38 tons/day) which contains nearly 30% total phosphate (P2O5). Currently, sewage sludge incinerator ash (SSA) is landfilled at a cost to taxpayers, but previous studies have shown that the ash has the potential to be a source of phosphorus (P) for crop production. Additionally, P is a limited and difficult-to-renew resource.
What did we do?
To determine the viability of SSA as a P fertilizer, we are in the middle of conducting a 3-year corn and soybean field study comparing this ash to other P sources including conventional P fertilizer (triple super phosphate), dried pelletized biosolids, and struvite. Each P source was applied in the spring at 40, 80, 120, and 160 lb P2O5/ha, with a zero-P control included. Soil and plant samples were taken throughout the season and after harvest and then were analyzed for available P and EPA 503 metals (elements monitored by the EPA in biosolids land application). In-situ probes that act as a proxy for ions in soil solution were also analyzed.
What we have learned?
After two years of field studies, there is evidence to show that SSA can be a viable phosphorus fertilizer as well as a source of copper (Cu) and zinc (Zn), although additional years of study on a more P-responsive soil are required to draw definitive conclusions. While soils amended with biosolids or SSA have higher levels of DTPA-Cu and DTPA-Zn compared with TSP- or struvite-amended soils, only grain concentrations of zinc reflected this difference in source.
While Cu and Zn are both elevated in biosolids and SSA soils, in-situ probes show that these elements are significantly more available in the biosolids-amended soils. This may be due to the difference in matrices and requires more study. However, our results demonstrate that land-application of ash and biosolids for crop production are two potential options for resolving sewage solids disposal and beneficial reuse of nutrients that go through our food systems. While land-applying biosolids is a good source of carbon and nitrogen where SSA is not, SSA has the benefit of having minimal organic contaminants (pathogens, pharmaceuticals) due to the incineration process. Additionally, biosolids are applied to meet a crop’s nitrogen requirements whereas SSA is applied to meet a crop’s phosphorus requirements. Because of this, the total amount of SSA-amendment added is significantly less than biosolids and thus results in lower or equal amounts of EPA 503 metals.
Future plans:
We will continue our study through a third field season (2019) and will continue to monitor P and 503 metals concentrations in soils and uptake by plants. We are also analyzing soil samples for changes in microbial populations due to SSA application. However, an early proof-of-concept incubation showed no significant effects of SSA when applied at agronomic P-rates.
1Department of Soil, Water, and Climate, University of Minnesota, Twin Cities
Additional information:
Bierman P, Rosen C. 1994a. Phosphate and trace-metal availability from SSA. JEQ. 23(4):822-830. Bierman P, Rosen C. 1994b. SSA effects on soil chem-prop and growth of lettuce and corn. Comm in SS and Plant Analysis. 25(13-14):2409-2437. Crants, J., C. Rosen, C. Blake, and M. McNearney. “Is SSAa Safe and Effective Phosphate Fertilizer?” U of Minn, 2015. Abs. Syn in Sci: Partn .for Sol. ASA, CSSA, SSSA, 16 Nov. 2015. Jasinski, S. “Phosphate Rock Statistics and Information.”Phosphate Rock Stat. and Info., USGS, 2017. Walker, J., et al. A Plain English Guide to the EPA Part 503 Biosolids Rule , USEPA, Off. of Ww. Mgmt, 1994.
Acknowledgements:
Metropolitan Council, Rosen Lab field crew, Rosemount Research and Outreach Center field crew, Department of Soil, Water, and Climate field crew
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
An Anaerobic Sequencing Batch Reactor (ASBR) is a high-rate liquid digestion system that retains microflora in the reactor by sequentially feeding influent, mixing the reactor, settling solids, and decanting effluent from the top of the reactor (Figure 1). All operations take place in a single reactor vessel. Since solids are retained in the reactor vessel, Solids Retention Time (SRT) can be managed separately from Hydraulic Retention Time (HRT). Although ASBR digesters are highly efficient at conversion of low-solids high-energy organic liquids to biogas, very few designs have made it out of the laboratory and onto the farm. Two problems have hindered ASBR development: detachment of roofs from reactor vessels and poor settling and retention of solids.
Figure 1. Four phases of an Anaerobic Sequencing Batch Reactor cycle
What did we do?
Improvements to ASBR design at Oklahoma State University have led to a patent pending invention that solves both settling roof detachment problems (Figure 2). Roof detachment is alleviated by employing a floating cover. The new design uses a partial mixing system — suspended solids are lifted below the mixing withdrawal point during the react phase of the ASBR cycle. The decanting point is fixed relative to the floating cover, so effluent is decanted from the clear liquid above the cloud of settling solids.
Figure 2. Next generation ASBR design developed at Oklahoma State University (from OSU provisional patent disclosure 2016-040)
What did we learn?
A battery of six, 30L reactors were operated under full and then partial mixing schemes with an HRT of 15 days and an Organic Loading Rate (OLR) of 0.31 g COD L-1 day-1. Partial mixing greatly improved reactor performance as measured in effluent quality and solids retention. Effluent from the reactors operated under the partial mixing scheme had significantly (p = 0.05) lower Total Suspended Solids (TSS) compared to the fully mixed reactors – 129 versus 452 mg L-1. Average SRT of the partially mixed reactors was 760 days versus 72 days for the fully mixed reactors. Biogas production was largely unaffected by switching from fully mixed to partially mixed operation. Average volumetric reactor efficiency (VRE) was 0.23 L biogas L1 reactor day-1 under full mixing and 0.28 L biogas L1 reactor day-1 under partial mixing.
When OLR was increased on the partially mixed reactors to 0.62 g COD L-1 day-1 with an HRT of 7.5 days, TSS concentration of effluent remained below 200 mg L-1 with an average of 183 mg L-1. Average SRT was 440 days, and VRE rose to 0.70 L biogas L1 .reactor day-1. Organic matter removal efficiency measured as Chemical Oxygen Demand (COD) averaged 0.91%.
Future Plans
Prototype testing of reactor at HRT < 5 days and OLR > 1.0 g g COD L-1day-1 is currently underway. After that we plan to construct a 1,000 L mobile reactor for on-farm testing.
Author
Douglas W. Hamilton
Associate Professor and Extension Waste Management Specialist
Biosystems and Agricultural Engineering
Oklahoma State University
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
Much of the antimicrobials (AM) used therapeutically and prophylactically pass through the animal and enter the environment through irrigation with beef runoff wastewater (WW). There are concerns repeated low-level AM loading of soils through irrigation will alter the natural biota resulting in increased resistance; thereby, making AM critical for human and animal health less effective.
What Did We Do?
Several studies are summarized describing a cost-effective removal process of AM from beef wastewater before being applied as irrigation. Study 1 investigated three radiolabeled AM, ([14C]-erythromycin (ERY), [3H]-chlortetracycline (CTC), and [3H]-monensin (MON)) to quantify their partitioningin the aqueous and solids fractions of a beef wastewater (WW) containing suspended solids (SS). Following this, several flocculants were evaluated for removing SS with sorbed AM from WW. Study 2 evaluated the sorption properties of tylosin (TYL) with diatomaceous earth (DE) added to WW as a binding agent. Study 3 evaluated the proposed treatment process using pre-treatment of WW with flocculants then adding a binding agent to remove aqueous phase AM before being used an irrigation water.
What Have We Learned?
Study 1) After 48 hours, more ERY sorbed to the SS fraction than the aqueous. CTC partitioning occurred in three phases: a rapid sorption to the SS fraction between 0.5 and 8 hours with desorption into the aqueous fraction at 24 hours followed by short steady state at 48 hours with further desorption at 96 hours. The most lipophilic antibiotic, MON, quickly sorbed into the SS fraction and remained in equilibrium with the aqueous fraction after 48 hours. Calculated partitioning coefficients, Kd, for WW were very different from published soil-water values illustrating wastewater uniqueness. A follow up study determined alum and ferric chloride removed some ceftiofur (CEF) and chlorotetracycline (CTC); however, they were ineffective for removing TYL. Therefore, a process was needed to remove aqueous phase AM (figure 1). Study 2 evaluated three DE sources for binding aqueous TYL in WW. Raw (DER) contained organic carbon (OC) (3% g g-1), clays (20%) and amorphous silica (65%). Kieselguhr (DEK) had no OC (<1% g g-1), no clay (2%) and amorphous silica (96%). had nearly 3.5 times greater maximum sorption capacity when compared to DEK. Sorption of TYL to DEK and DER at different pH values showed cationic and hydrogen bonding interactions are important. Higher sorption of TYL to DER compared to DEK suggested clays-DE matrix was important for TYL sorption. Removing OC improved TYL sorption and decreased the separation time for DE/AM removal to complete treatment. Study 3 found CEF and CTC would bind to DE in controlled, neutral aqueous solution. When AMs were spiked into WW collected from a beef feedlot runoff pond, DE successfully removed TYL and CTC, but not CEF. Wastewater treated with excess alum to remove SS followed by DE treatment showed similar removal rates for TYL. Pretreatment of water with alum also resulted in CEF removal if larger amounts of DE are needed. The reason for change in CEF binding when pretreated WW with alum is still under investigation. Alum treatment appeared to remove most of the CTC spiked into WW and therefore no assessment of how CTC binding to DE after treatment.
Future Plans
Future work will include: evaluating the proposed treatment process on other AM and their metabolites. Development of modified DE matrices specific for non-polar AM and metabolites. These matrices could be combined to remove both polar and non-polar contaminants. Finally, the process needs to be evaluated for effectiveness of contaminant removal with municipal wastewater treatment systems.
Authors
Bryan L. Woodbury, Agricultural Engineer, USDA-U.S. Meat Animal Research Center, Clay Center, NE
Bobbi S. Stromer, Chemist Post Doc., USDA-U.S. Meat Animal Research Center, Clay Center, NE
Clinton. F. Williams, Lead Soil Scientist, USDA-US Arid-Land Agric. Research Center, Maricopa, AZ.
Katherine A. Woodward, Ph.D. Candidate, Tufts University, Civil & Environmental Eng., Medford, MA
Heldur Hakk, Research Chemist, USDA-Edward T. Schafer Agricultural Research Center, Fargo, ND.
Sara Lupton, Research Chemist, USDA-Edward T. Schafer Agricultural Research Center, Fargo, ND.
Additional Information
Stromer, B.S., B.L. Woodbury and C.F. Williams. 2018. Tylosin sorption to diatomaceous earth described by Langmuir isotherm and Freundlich isotherm models. Chemosphere. 193:912-920.
Figure 1. Illustration of a wastewater treatment process to reduce the antimicrobials load applied through irrigation of agricultural wastewater. Loading soils with antimicrobials may cause increased antimicrobial resistance. This resistance may make antimicrobials less effective to treat humans.
Acknowledgements
USDA is an equal opportunity provider and employer.
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
The Runoff Risk project was started in Wisconsin in 2011, with the realization at that time, there was no real-time runoff risk guidance available for manure applicators. The project has grown, with four states (Michigan, Minnesota, Ohio and Wisconsin) now operating real-time runoff risk forecast websites.
Figure 1. Minnesota Runoff Risk Advisory Forecast from July 1, 2018.
The Minnesota Runoff Risk Advisory Forecast (RRAF) system is a tool developed by the Minnesota Department of Agriculture (MDA) and the National Weather Service (NWS). It is designed to help farmers and commercial applicators determine the best time to apply manure to reduce the runoff risk of valuable nutrients and protect water resources. It is part of a regional risk advisory forecast project that utilizes existing NWS weather and watershed models in a water quality application. Figure 1 shows a screenshot of the website from July 1, 2018, indicating the runoff risk forecast in the central part of the state.
Runoff Risk Analysis
The NWS models continuously simulate soil moisture and temperature conditions as well as incorporating future precipitation and temperature forecasts and current and future snowpack. An algorithm that looks at chosen model state values is evaluated for a variety of risk conditions, such as runoff and soil saturation. Based on over 20 years of simulations, basin specific thresholds were created. Finally, there was post–processing of that data that is run on the output to produce risk events. This information is provided daily to the project partners through data servers. The data is processed and the website is updated twice daily. The graphic displays the different risk events predicting the likelihood of today (Day 1), tomorrow (Day 2), and Day 3 or multi-day (Day 1 through Day 3 combined) runoff events. Farmers and commercial applicators use an interactive map to locate their field and find their forecasted risk. Users can also sign up for email or text messages for their county that alert them to a severe runoff risk for that day.
Figure 2. Tabular 5 day forecast from June 24, 2019 in Bandon Township, Renville County, Minnesota.
Runoff risk is grouped into four categories: No event, Low, Moderate and Severe. When the risk is Moderate or Severe, it is recommended that the applicator evaluate the situation to determine if there are other locations or later dates when the application could take place. Figure 2 shows results for a specific location in Bandon Township in Renville County, Minnesota. For the first three days, the risk of runoff at that specific location was Severe, which indicated that a producer should wait to apply.
Daily Mapping Information
Figure 3. Daily soil temperature forecast at 6 inch depth for Minnesota.
The RRAF website also provides statewide forecasted daily average two inch soil depth temperatures which can be useful at planting time, daily average six inch soil depth temperatures which are helpful when determining fall fertilizer application in appropriate areas and daily precipitation forecasts. Figure 3 shows the daily soil temperature forecast at the six inch depth for the state of Minnesota. The colored dots are real time soil temperature gauges that can be interactively clicked on to reveal current soil temperature. The color of the dot is not reflective of the temperature at the gauge. It simply notes what entity is in charge of the gauge.
Potential of RRAF
This is a relatively new application that has been implemented in Minnesota since March 2018. The potential impacts of usage on this could be quite large. Any time movement of manure to water resources can be minimized is a success for the farmer and the environment. The overall goal of the presentation is to make people aware of this tool, share information on the performance, and encourage potential users to add this tool to their “toolbox”. The main message is to check conditions, delay if necessary, and spread on the day when there is least potential impact to the environment.
Further partnerships are desired to continue to get the word out on this application. Yearly multi-state coordination meetings occur, with the next meeting coming up in Ohio in August 2019. Version 3 of the RRAF will be derived from the National Weather Service National Water Model. Development on this version will start in Spring 2019 and should take four years for it to be merged into the National Water Model system. For MDA, we continue to promote RRAF website and monitor the output, comparing it to real time data to make sure that the model is working correctly.
Heather Johnson, Hydrologist 3, Minnesota Department of Agriculture
The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.
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