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Here you can soon find links to all information and videos of the 2023 DSOS/AEMON-J Virtual Workshop and Summit. All recordings are available on our OSF archive The organisers of this event were:
| Day 1: Remote Sensing -- Monday 24 July 2023 15:00-19:00 UTC |
| AquaSat: A unified dataset of in situ water quality data with Landsat matchups |
| Matthew RV Ross (@MagicalSystems; Colorado State University) |
| Remote sensing models of water quality can be improved by training and validation on larger data sets of coincident field and satellite observations, here called matchups. To facilitate model development and deeper integration of remote sensing into inland water science, we have built AquaSat, the largest such matchup data set ever assembled. AquaSat contains more than 600,000 matchups, covering 1984–2019, of ground-based total suspended sediment, dissolved organic carbon, chlorophyll a, and Secchi disk depth measurements paired with spectral reflectance from Landsat 5, 7, and 8 collected within ±1 day of each other. To build AquaSat, we developed open source tools in R and Python and applied them to existing public data sets covering the contiguous United States, including the Water Quality Portal, LAGOS-NE, and the Landsat archive. In addition to publishing the data set, we are also publishing our full code architecture to facilitate expanding and improving AquaSat. |
| 15:00-15:45 UTC - Keynote: Earth Observations to detect mixing anomalies |
| Elisa Calamita (@e_calamita; Swiss Federal Institute of Aquatic Science and Technology (EAWAG)) |
| Satellite Earth Observations provide only surface water properties in lakes without resolving vertical gradients, however, the horizontal gradients of such data could help develop a better understanding of lake internal processes. In this keynote, I will present how the spatial component of remotely sensed lake surface water temperature can reveal information about lake mixing and mixing anomalies and I will present a global-scale assessment of lake mixing anomalies occurrence in the last 20 years in dimictic lakes |
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A live stream of the pre-recorded keynote will begin at 15:00 UTC, followed immediately by a live Question and Answer session with Matt and Elisa. |
| 15:45-16:00 UTC - Break |
| 16:00-18:00 UTC - Workshop: Water quality retrieval using remote sensing and machine learning methods (So, we don’t need to be stuck into one component/method/sensor) |
| Daniel Maciel (Instituto Nacional de Pesquisas Espaciais) |
| Remote sensing provides a practical solution to monitor water quality at large spatiotemporal scales. This workshop aims to introduce participants to remote sensing, machine learning, and big data to develop water quality algorithms using the R programming language and open-source datasets. By the end of the workshop, attendees will have gained valuable skills and knowledge that will enable them to apply these techniques in their research or work effectively. |
| This workshop will be live. |
| The material for this workshop can be found on this Github repo |
| 18:00-19:00 UTC Breakout/Working Groups Sessions |
| A traditional part of AEMON-J meetings in the past has been to openly discuss ideas for new, joint projects. This time in the schedule is to bring up such ideas, perhaps inspired by the workshops earlier that day, and discuss. If no such ideas are pitched, this time can also be used for small talk, networking, and other social activities. |
| Day 2: Ecological Forecasting -- Tuesday 25 July 2023 15:00-19:00 UTC |
| Introductory Talk: Progress and opportunities in near-term forecasting of freshwater quality |
| Mary Lofton (@me_lofton; Virginia Tech), Dexter Howard (@DexterHoward77; Virginia Tech), and Cayelan Carey (@CareyLab; Virginia Tech) |
| Ecological forecasting, a growing field in ecology and aquatic sciences, makes predictions of the future state of ecosystem variables with quantified uncertainty. Near-term freshwater forecasts are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Freshwater forecasting is currently dominated by near-term forecasts of water quantity and near-term water quality forecasts are fewer in number and in the early stages of development (i.e., non-operational) despite their potential as important preemptive decision support tools. Nonetheless, near-term water quality forecasting is poised to make substantial advances with recent progress in forecasting methodology, workflows, and end-user engagement. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management. |
| 15:00-15:45 UTC - Keynote: Democratized automated iterative ecological forecasting |
| R Quinn Thomas (@rquinnthomas; Virginia Tech) |
| This keynote will articulate a vision for the future of ecological forecasting cyberinfrastructure that empowers anyone with an internet connection to automatically generate ecological forecasts that are executed daily, making ecological forecasting more accessible than ever. First, I will describe the key components of an ecological forecasting flow from downloading data to forecast dissemination. I will then introduce how this workflow can be launched for free using cloud computing and describe work that allows these democratized forecasts to be discoverable through a simple web search. The cutting edge software that has been developed to achieve these goals and lower the barrier of entry will be highlighted throughout. |
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A live stream of the pre-recorded keynote will begin at 15:00 UTC, followed immediately by a live Question and Answer session with the speaker. |
| 15:45-16:00 UTC - Break |
| 16:00-18:00 UTC - Workshop: Can you predict the future? An introduction to the EFI-NEON Forecast Challenge |
| Freya Olsson (@FreyaOlsson; Virginia Tech) |
| This workshop will get you forecasting by introducing the Ecological Forecasting Initiative Research Coordination Network’s (EFI-RCN) National Ecological Observatory Network (NEON) Ecological Forecast Challenge, a national-scale effort of generating real-time forecasts for ecosystems across the U.S. The workshop will focus on the Challenge’s Aquatics theme to make predictions, with associated uncertainty, of water temperature, dissolved oxygen and chlorophyll a concentration for 30 days into the future at 34 freshwater sites across the continental USA. This workshop will move through an example forecasting workflow: accessing the historical NEON observations, past and future driving data, forecast generation, and workflow automation using Github Actions. Using an R programming workflow we hope that you can go away from the workshop with a fully formed forecasting workflow that will allow you to submit a brand new 30 day forecast every single day! |
| For the Ecological Forecasting workshop we will be using R and RStudio as well as Github. You will need R version 4.2 to run some of the packages and a Github account to make the most of the materials. Detailed instructions about package installation and set up can be found at the main Github repo. Please email freyao@vt.edu with any questions about the workshop preparation before Tuesday's workshop. |
| This workshop will be live. |
| 18:00-19:00 UTC - Breakout/Working Groups Sessions |
| A traditional part of AEMON-J meetings in the past has been to openly discuss ideas for new, joint projects. This time in the schedule is to bring up such ideas, perhaps inspired by the workshops earlier that day, and discuss. If no such ideas are pitched, this time can also be used for small talk, networking, and other social activities. |
| Day 3: Catchment Modeling -- Wednesday 26 July 2023 15:00-19:00 UTC |
| Introductory Talk: Challenges in Synthesis Catchment Science: An Introduction to MacroSheds |
| Nicholas Gubbins (@ecogub; Colorado State University) |
| Macrosystem-scale watershed science is the search for general principles that describe functional capacity and behavior across watersheds. Collectively, government-funded hydrology labs and experimental forests support hundreds of small watershed studies that collect very similar data. However, data harmonization challenges have limited attempts to collate these datasets in a way that would facilitate watershed science at the macrosystem scale. The MacroSheds project has developed a flexible, future-friendly system for continually harmonizing daily time series of streamflow, precipitation, and solute chemistry from 168+ watershed studies, and supplementing each with a comprehensive set of predictive watershed attributes. |
| 15:00-15:45 UTC - Keynote: "MacroSheds: a synthesis of long-term biogeochemical, hydroclimatic, and geospatial data from small watershed ecosystem studies" |
| Nick Marzolf (@NickMarzolf;Duke University) & Audrey Thellman (@AudreyThellman;Duke University) |
| The small watershed approach has been used to understand biogeochemical cycling in ecosystems since the 1960s, however little effort has been made to compare and synthesize watersheds at broad spatial scales. The MacroSheds project is an on-going data harmonization and synthesis of small watershed studies that enables cross-site comparison of watershed chemical fluxes, weathering rates, and responses to climate change. With this newly synthesized data, we can evaluate spatial variability in nitrogen cycling and export in small watersheds across North America. The same dataset allows us to identify responses to anthropogenic change, for example, recovery from acidification in Northeastern forested watersheds. These represent two analyses that are made possible by a large data harmonization effort like MacroSheds and should accelerate evaluation of ecosystem processes in small catchment. |
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A live stream of the pre-recorded keynote will begin at 15:00 UTC, followed immediately by a live Question and Answer session with the speakers. |
| 15:45-16:00 UTC - Break |
| 16:00-18:00 UTC - Workshop: MacroSheds: long-term, continental-scale watershed ecosystem science |
| Mike Vlah (Duke University) and Nicholas Gubbins (@ecogub; Colorado State University) |
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The MacroSheds dataset harmonizes chemistry and hydrology data from 169 watershed ecosystem monitoring efforts (and counting).
In this workshop, we tour the MacroSheds platform, which includes a web portal and an R package. Participants will calculate
watershed fluxes for a subset of sites and solutes, then perform ordination and classification of sites based on fluxes and
watershed attributes. We will also demonstrate how to link MacroSheds data with complementary datasets like CAMELS/Caravan. You can access the GitHub repo for the workshop materials here. Please note that there is a rendered HTML document on GitHub that contains all workshop materials, but the file is too large to be rendered. You can access the rendered HTML file here. If you intend to follow along during the workshop, you will need to install several packages. Please refer to the "before_the_workshop.R" file for more information. |
| This workshop will be live. |
| 18:00-19:00 UTC - Breakout/Working Groups Sessions |
| A traditional part of AEMON-J meetings in the past has been to openly discuss ideas for new, joint projects. This time in the schedule is to bring up such ideas, perhaps inspired by the workshops earlier that day, and discuss. If no such ideas are pitched, this time can also be used for small talk, networking, and other social activities. |
| 27 July 2023 | |||||||||
| 13:00-13:15 EDT Introduction, Welcome, and Ground Rules | |||||||||
| 13:15-14:15 EDT Big Data | |||||||||
| 13:15-13:25 EDT |
Linnea Rock @RockLinnea A broad-scale shift away from single nutrient limitation in United States Lakes |
| 13:25-13:35 EDT |
Robin Rohwer @RobinRohwer Computational barriers to realistic reproducibility: examples from metagenomic sequencing |
| 13:35-13:45 EDT |
Ruchi Bhattacharya @LimnoRuchi Unraveling drivers and trends of centennial scale lake Phosphorus accumulation trajectories across global scales |
| 13:45-13:55 EDT |
Chris Hay @IISD_ELA The flow and future of IISD Experimental Lakes Area data, presenting the bathymetry data pipeline and open data package as a case study |
| 13:55-14:15 EDT | Live Q&A with the speakers |
| 14:15-14:35 EDT Break | |||||||||
| 14:35-15:35 EDT Data Intensive Models | |||||||||
| 14:35-14:45 EDT |
Ames Fowler @FowlerAmes Muddy Waters: Investigating the Spatial Distribution of Runoff Driven Soil Erosion "Hot Spots" in an Agricultural Watershed to Improve Water Quality |
| 14:45-14:55 EDT |
Sofia La Fuente @LFSofi8 Ensemble modeling of global lake evaporation under climate change |
| 14:55-15:05 EDT |
Fred Cheng @pHred_cheng Leveraging a densely monitored watershed to disentangle catchment controls on whole-network streamflow to develop optimal stream gage placement strategies |
| 15:05-15:15 EDT |
Shuqi Lin @shuqilin0820 Lake dissolved oxygen and hypolimnetic hypoxia predictions via multi-model machine learning approach |
| 15:15-15:35 EDT | Live Q&A with the speakers |
| 15:35-15:55 EDT Break |
| 15:55-16:55 EDT Community Listening Session: How can we grow DSOS & AEMON-J? |
| Looking to the future, the organizational teams of DSOS and AEMON-J are keen to find funding mechanisms and opportunities to expand these communities. As we feel strongly that these communities should be both of and for early career researchers, we'd like to get your your thoughts and feedback on how best we can grow these communities. This time will be an open, hour-long conversation, where you can share your thoughts directly with the org team. |
| 16:55-17:00 EDT Closing Remarks |
| 28 July 2023 | |||||||||||
| 13:00-13:15 EDT Introduction, Welcome, and Ground Rules | |||||||||||
| 13:15-14:25 EDT Remote Sensing of Aquatic Environments | |||||||||||
| 13:15-13:25 EDT |
Maartje Korver Assembling and quality controlling high resolution, global scale data from remote sensing: examples from a lake water temperature dataset |
| 13:25-13:35 EDT |
Camille Minaudo @CamilleMinaudo High resolution profiles of hyperspectral water optical properties to better understand the functioning of lake ecosystems |
| 13:35-13:45 EDT |
Merritt Harlan @MerrittEHarlan Data-driven approaches for satellite-based discharge estimation in Alaskan rivers |
| 13:45-13:55 EDT |
Md Mamun @MdMamun31237853 Quantification of Algal Chlorophyll, Water Clarity and Suspended Solids Across Korea Using Sentinel -2 MSI and Landsat -8 OLI Imagery with Machine Learning Algorithm |
| 13:55-14:05 EDT |
Daniel Maciel Remote sensing of water transparency in global waters based on Landsat long-term data |
| 14:05-14:25 EDT | Live Q&A with the speakers |
| 14:25-14:45 EDT Break | |||||||||
| 14:45-15:45 EDT Applications of Open Science | |||||||||
| 14:45-14:55 EDT |
Lorena Silva @lorena_biouni Using community science to enhance Earth Observation data |
| 14:55-15:05 EDT |
Keyvan Malek @keyvan_malek Opportunities and challenges in providing water and agricultural customers with data-driven services |
| 15:05-15:15 EDT |
Leon Katona Modeling river ecosystem responses to environmental change using long-term water quality monitoring data from the Truckee River, Nevada, USA |
| 15:15-15:25 EDT |
Riley Hale @riley_hale8 Phytoplankton community structure predicts interannual patterns in net trophic status of dynamic near-shore ecosystem at the Scripps Ecological Observatory |
| 15:25-15:45 EDT | Live Q&A with the speakers |
| 15:45-16:00 EDT Break |
| 16:00-16:55 EDT Panel: Careers in Data Science and Open Science |
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Joshua Fisher @jawzsh - Hydrosat & Chapman University Stephen Kennedy @oh_sk - UrbanFootprint Roxane Maranger @Water_Rox - University of Montreal Anika Pyle @anikasneaka - Colorado State University Emily Read - U.S. Geological Survey |
| 16:55-17:00 EDT Closing Remarks |
| 17:00-18:00 EDT Virtual Social Hour |
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