Assessing BMP Effectiveness for Water Quality Outcomes with Remote Sensing
Virtually everyone in Minnesota and bordering states whose profession has a direct stake in Water Conservation assembled in Downtown St. Paul’s RiverCentre October 17-18 for the annual Water Resources Conference. I had the honor of chairing a Special Session at the conference titled “Assessing BMP Effectiveness for Water Quality Outcomes with Remote Sensing.” The session featured two very foundational efforts that we are attempting to bridge together in partnered research at GEMS: (1) The Minnesota Department of Agriculture’s (MDA) Minnesota Agricultural Water Quality Certification Program (MAWQCP), directed by Brad Jordahl Redlin, and (2) the Department of Forest Resources’ remote-sensed Water Quality assessment for our 10,000+ lakes, led by Leif Olmanson.
The 90-minute session was organized so that each of the three speakers (one had dropped out last minute for logistical reasons) had 20 minutes to speak plus two minutes for burning questions. At the end the audience had 15 minutes for questions with the entire panel of speakers. There were about 30 very inquisitive people in the audience, who peppered the speakers with questions throughout.
Updates on the MDA’s certification program
Brad Jordahl Redlin kicked off the session with an outstanding talk that outlined the principles on which the certification program he founded and directs was created, and highlighted the progress that has been made. Literally over a million acres have now been certified, spread across over 1400 producers. In exchange for regulatory certainty for a period of time, these producers allow his government agency to (1) assess their farm practices, (2) suggest new management practices (sometimes with additional incentives such as subsidized equipment from a grant), and (3) carry out audits of their new practices. The program, which has been operational for nearly a decade, is well beyond the stage of corralling early-adopters. New participants span the spectrum of producer demographics in age, farm size, and more.
Scaling lake quality measurement
Leif Olmanson stepped up to review an activity that he first spearheaded twenty years ago – using remote sensing to measure the water quality of Minnesota lakes. In the interim, he has overseen steady progress using new generations of satellites (from Landsat to Sentinel), multiple metrics (clarity, chlorophyll, organic matter), and the frequency of data reporting (from once every 5 years to ~weekly lake snapshot and monthly pixel-level composites of all 10,000+ lakes). Data is made available to the casual user via a friendly Lake Browser interface, and in numeric form pixel-by-pixel for data wizards on GEMS Exchange.
GEMS bridging the two programs
David Porter rounded out the session discussing the improvements he has made in creating algorithms that properly remove clouds and aerosols from the satellite images. This is a prerequisite for feeding all of the regularly spaced (~5 day) images of a field through a growing season into a sophisticated Recurrent Neural Network (RNN, a type of Machine Learning algorithm) that his colleague Anubha Agrawal has been preparing. As described in this case study, David, Anubha, and I intend to use the RNN trained on known, certified management practices (e.g., strip till / no till, cover crops) from the MAWQCP to make a prediction of what practices growers are making on uncertified farmland. We then will trace these producer fields to the downstream lakes in each watershed, and see what covariates (e.g., slope, soil type, distance to waterway) affect the correlation of % farm practice adoption vs. downstream lake quality in a watershed.
Making Sense of Agriculture from Minnesota to Malawi
GEMS Sensing has coupled world-class engineering design and build expertise with first-rate agricultural science smarts to realize a robust, extensible sensing system for agri-food research anywhere in the world.
Since early 2020, GEMS Sensing has partnered with the Centre for Agricultural Transformation(CAT) in Malawi to pilot the local deployment of GEMS research-grade weather stations and its associated data visualization and sharing tool. Piloting a network of weather stations across Malawi involves much more than working through the logistics of manufacturing, delivering and deploying the necessary hardware and software. It also involves identifying partners willing to trial the weather stations on their research stations/farms and training local CAT personnel to enable the deployment, particularly in remote rural areas with uncertain cellular connectivity. Working through the CAT provides a unique opportunity to engage with private and public agribusiness throughout Malawi to test GEMS Sensing technologies in a low-income, smallholder farmer, tropical environment.
GEMS weather stations across Malawi
Over the past five years, the GEMS Sensing team has used feedback from our field partners to develop ever-improving scientific-grade, plug-and-play sensing devices coupled with a secure web-based informatics service. Weather stations aren’t new, but GEMS Sensing has created a highly customizable system that is built specifically for the varied sensing needs of researchers and their collaborators. The system's core logger box can be used for scientists with vastly different sensing requirements, from a full-stack meteorological station supporting a host of on-station or in-field crop performance studies to more specialized applications aimed at monitoring the below ground conditions that affect plant growth and health. The system's configurable and easy-to-use dashboard enables the integration, exploration, and sharing of real-time sensor data from multiple, perhaps distant, sites through a single portal.
Tracking the real-time, micro-level weather and edaphic patterns impacting agricultural production is crucial for a whole host of reasons, including advancements in breeding, agronomy, and extension efforts and the livelihoods of the farmers responsible for this production. These types of data are used for modeling weather events over large areas (e.g., rainfall and temperature) or informing management decisions like when and how much to irrigate a crop. However, being able to collect, store, clean, explore, share, and analyze these data from multiple sites, isn’t always straightforward. With this motivation in mind, the team has coupled world-class engineering design and build expertise with first-rate agricultural science smarts to realize a robust, extensible sensing system for agri-food research anywhere in the world.
GEMS Sensing in sub-Saharan Africa
For the Malawi pilot project, we worked with a South African-based manufacturer to produce the GEMS Sensing stations. The full-stack weather stations are configured to collect eight parameters every 15 minutes: air temperature, humidity, barometric pressure, rainfall, soil moisture, soil temperature, wind speed, and solar radiation. Data are sent via cellular network to a cloud-based database, processed for quality, and made accessible to partners via a user-friendly, web-based portal.
The primary objectives of the pilot exercise were to better understand:
Tropical environmental impacts on the sensing hardware;
Total cost of ownership from a user perspective (i.e., costs of acquisition, installation, and maintenance) involved in deploying digital ag weather sensors in a low-income context with limited infrastructure support; and
Malawian agribusiness’ demand, willingness to pay and potential use cases for networked weather stations (or related real-time sensing needs).
To date, the CAT team has deployed nearly 40 solar-powered weather stations across the spatially and temporally variable agro-ecologies that affect agricultural outcomes throughout the country. The stations continue to stream real-time data from experimental research stations, commercial farms, and smallholder farms. The pilot project is set to wrap-up in December 2023, though the CAT may continue to operate some of the weather stations beyond that time.
Learnings and Lessons
Scaling up a pilot project in Malawi from our operations based in Minnesota during the height of the global pandemic was not without its challenges. The original game plan was to travel with a handful of sensors to Malawi so that our technical team could work closely with CAT personnel and deployment partners to scope out the entire constellation of technical, human capital, cell connectivity, local logistics, device assembly and deployment partner protocols and other factors that could likely affect the odds of a successful outcome. Based on this test deployment we had envisaged tweaking the technical specs, revising our training and related deployment protocols before scaling up deployment throughout the country.
COVID-19 had other plans. It shut down all travel to Malawi, disrupted supply chains for computer chips that were critical to fabricating the GEMS designed sensors, and complicated shipping logistics. Undeterred, we pivoted our whole operation to enable a remote deployment, which, despite our best efforts, was not without its own complications.
Persistence ultimately paid. As we began scaling field deployment in April 2022, our technical team became adept at diagnosing issues long distance, ably supported by a great ground team in Malawi. Fluky cell connectivity issues seemed to be associated with variable soil properties that were vastly improved by simply raising the logger box further off the ground. Unexpected down-time issues were eventually tracked to battery depletion problems that arose from locally assembled devices that sat turned on for lengthy time before travel resumption enabled field deployment to proceed. The fix, change out the run-down batteries.
All told, our GEMS Sensing devices exceeded our expectations, even withstanding Tropical Cyclone Freddy that hit Malawi in February 2023!
Our team visited Malawi in May and traveled with the local CAT sensing team throughout the Southern and Central regions to get first-hand feedback from a host of public and private partners who participated in the GEMS Sensing pilot project. We made site visits with DARS research scientists, commercial agrifood businesses such as Bayer, Pxyus and Global Seeds, and One Acre Fund which services smallholder farmers directly. These partners were uniformly enthusiastic about the ready access to automatically streamed and easily accessible localized weather data. They also highlighted numerous opportunities for leveraging the streaming weather data streams with various backend analytics to tailor informatics solutions to the particular and varied agri-food production problems they faced.
GEMS sensors are currently being deployed with success across four continents. However, this represented our first widespread test of the system in a logistically challenged, low-income African agricultural setting. Prior to the pilot we had all sorts of questions as to whether or not the system would even work, and if so, how reliably and securely. Importantly, would anyone find practical value in such a sophisticated, real-time sensing system in a country dealing with many infrastructure and technological constraints.
Weather matters a lot for agriculture, whether you are farming in Minnesota or Malawi. While Minnesota farmers have access to all sorts of weather related data products, locally accurate, real-time data is still relatively scarce. In Malawi, rurally-relevant weather data of any sort is largely absent. The last time we checked, NOAA (National Oceanic and Atmospheric Administration) live stream weather data from just one site in Malawi, the Blantyre International airport! This pilot demonstrated the potential for changing this reality for Malawian farmers and the numerous public and private agencies that support their operations.
Even with its many hurdles and holdups, this pilot exercise revealed the feasibility and the latent demand for access to locally sensed weather data. With the lessons learned from our pilot deployment we are excited about the possibility of using GEMS Sensing’s data generation and analytical capabilities to support data-driven decisions that strengthen existing and emerging value chains in Malawi, as well as unlock new agri-food value-chains throughout the world.
This posting was produced as part of the Centre for Agricultural Transformation, an effort led by Land O’Lakes Venture37 and funded with a grant from the Foundation for a Smoke-Free World, Inc. (“FSFW”), a US nonprofit 501(c)(3) private foundation. The contents, selection and presentation of facts, as well as any opinions expressed herein, are the sole responsibility of the authors and under no circumstances should they be regarded as reflecting the positions of FSFW.
A Cross-Border Research Partnership with the University of Saskatchewan
Wheat Varietal Change in the US and Canada
The United States and Canada are both major wheat producers, with total harvested areas in 2021 respectively ranked 4th and 7th globally (FAOSTAT, 2023). Advancements in crop breeding and agricultural practices have led to steady productivity gains in the production of high-quality wheat varieties in both countries, positioning North America as a leading force in the world’s wheat market. Facing the challenges of climate change, increasing land and water scarcity, and emerging pest and disease threats, the resilience and productivity of wheat crops are of paramount importance in ensuring a stable and secure food supply for the continent and the world.
Using a century of data on commercial wheat crops in the United States, a recent paperpublished by researchers from the University's GEMS Informatics Center finds that the solution to sustainable wheat productivity growth lies in modern, scientifically-bred crop varieties. The study authors found that the increasingly intensive use of scientifically-selected crop varieties resulted in more biodiverse wheat production throughout the U.S., accompanied by a fourfold increase in average wheat yields over the past century.
Our Partnership with the University of Saskatchewan
To undertake a complementary, in-depth study of wheat varietal diversity and genetic improvements throughout Canada, the GEMS Informatics Center is partnering with Dr. Richard Gray’s team from the University of Saskatchewan to undertake joint research in support of the “4DWheat: Diversity, Discovery, Design and Delivery” project. The specific focus of this new study is to estimate the economic gains attributable to wheat varietal improvement in Canada and to identify the respective roles of landraces (farmer-bred varieties) along with Canadian and rest-of-world breeders in realizing these gains. In so doing, the study will quantify and characterize the shifting structure of varietal spill-ins to Canadian agriculture over the past half a century.
The first research objective of the GEMS-U Sask partnership is to evaluate the overall Genetic Gain (so-called G-gains) attributable to varietal improvement in Canadian wheat during the period 1970-2019. The study compiled comprehensive data on the areas planted to improved varieties coupled with detailed experimental data on the comparative yield performance of these varieties to assess the yield gains stemming from improved varieties relative to a chained counterfactual baseline of check varieties. To delve deeper into the different dimensions of the gains resulting from varietal improvement, we are dissecting the geography of genetic gains among the three major wheat-producing provinces (Alberta, Manitoba and Saskatchewan) and two specific classes of wheat (spring and durum).
Second, using a purpose-built data set developed by this project, we are also investigating the changing varietal diversity of Canadian wheat over the period 1970 to 2019, and partitioning the sources of yield/value gains into their various genetic parts using both phylogenetically-blind and phylogenetically-informed approaches. Our phylogenetically-informed approach utilizes the GEMS PedTools to map the lineage and evaluate the genetic relatedness among varieties when partitioning these gains. This analysis is designed to evaluate the economic value of the Canadian wheat crop that arises from various genetic sources, be that landraces, Canadian breeding programs, US breeding programs, and other international (e.g., CIMMYT/Mexico) research efforts. An additional feature of our approach is to identify the contributions coming from "dominant" varieties based on their prevalence and pedigree connections. Taken together, our findings will contribute to a better understanding of the dynamics and implications of varietal improvement in Canadian wheat crops.
Data-driven insights on the biodiversity and sustainability of wheat crops in Canada
Beginning in early 2020 our joint efforts have successfully compiled a novel Canadian wheat variety database that includes breeding passport information (both pedigree and phenotyping data) for over 310 commercial wheat varieties grown by Canadian farmers since 1970. Our initial results reveal that genetic improvements through breeding new wheat varieties are a dominant source of the overall yield gains achieved by commercial wheat farmers across the major wheat producing provinces in Canada. Furthermore, our new phylogenetically-informed partitioning procedures will help better align the costs and benefits associated with local R&D vis a vis research conducted elsewhere in the world. This work is also laying the quantitative foundations for practical, data-informed approaches to sharing the benefits arising from crop varietal change, a still often contentious aspect of the international agreements (e.g., the Nagoya Protocolembodied in the Convention on Biological Diversity) that shapes the access to and use of farmer versus scientifically bred crop varieties.
The key to sustainable agricultural productivity growth lies in embracing modern, scientifically-bred crop varieties that have demonstrated their ability to enhance biodiverse cropping practices and boost crop yields. Leveraging their respective expertise and data resources, the on-going partnership between the GEMS Informatics Center and the University of Saskatchewan is addressing the increasing challenges faced by cropping agriculture by providing data-driven insights on the biodiversity and sustainable productivity consequences of investments in modern crop breeding endeavors.
