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            <h1>Dynamic Earth Simulation Laboratory</h1>
            <h2 class="ua-crimson">University of Alabama</h2>
            <h3 class="ua-grey">Department of Geological Sciences</h3>
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        <h1>Publications</h1>
        <section id="papers">
            <h2>Hot Off The Press!!!</h2>
            <div class="paper">
                <img src="fig/papers/loof_frame_2026_markets.png" alt="Figure from loof_frame_2026_markets" class="paper-image">
                <p><a href="https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2026.1923411/full" target="_blank">Frontiers Link to paper</a> | <a href="papers/loof_frame_2026_markets.pdf" target="_blank">PDF alternate link | Prediction markets for hydrology (2026)</a></p>
                <p class="paper-description">
                    Travis Loof and <b>Jonathan M. Frame</b><br>
                    <br>This paper explores the ethical and operational risks that follow when AI-accelerated hydrologic forecasting becomes the settlement basis for prediction markets.</p>
            </div>
 
            <!-- Frame Papers -->
            <h2>First-Author Publications</h2>

            <div class="paper">
                <img src="fig/papers/frame_2025_ml_nextgen.png" alt="Figure from frame_2025_ml_nextgen" class="paper-image">
                <p><a href="https://onlinelibrary.wiley.com/doi/10.1111/1752-1688.70000" target="_blank">Wiley Link to paper</a> | <a href="papers/frame_2025_ml_nextgen.pdf" target="_blank">PDF alternate link | ML for Nextgen (2025)</a></p>
                <p class="paper-description">
                    <b>Jonathan M. Frame</b>, Ryoko Araki, Soelem Aafnan Bhuiyan, Tadd Bindas, Jeremy Rapp, Lauren Bolotin, Emily Deardorff, Qiyue Liu, Francisco Haces-Garcia, Mochi Liao, Nels Frazier, Fred L. Ogden<br>
                    <br>This paper explores potential machine learning methods most suitable for the Next Generation Water Resources Modeling Framework.</p>
            </div>

            <div class="paper">
                <img src="fig/papers/frame_2024_fim.png" alt="Figure from frame_2024_fim" class="paper-image">
                <p><a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2024GL109424" target="_blank">AGU Link to paper</a> | <a href="papers/frame_2024_fim.pdf" target="_blank">PDF alternate link | Flood Inundation Mapping (2024)</a></p>
                <p class="paper-description">
                    <b>Jonathan M. Frame</b>, Tanya Nair, Veda Sunkara, Philip Popien, Subit Chakrabarti, Tyler Anderson, Nicholas R. Leach, Colin Doyle, Mitchell Thomas, Beth Tellman<br>
                    <br>This paper proposes a method of generating flood inundation maps based on large-domain hydrologic simulations. Demonstrating predictive performance during the most damaging flood season in California history. Highlighting the need to go beyond simple streamflow-based flood predictions which fail to capture pluvial flooding.</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/frame_2023_mass_balance.png" alt="Figure from frame_2023_mass_balance" class="paper-image">
                <p><a href="https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.14847" target="_blank">Wiley Link to paper</a> | <a href="papers/frame_2023_mass_balance.pdf" target="_blank">PDF alternate link | Mass Balance Modeling (2023)</a></p>
                <p class="paper-description">
                    <b>Jonathan M. Frame</b>, Frederik Kratzert, Hoshin V. Gupta, Paul Ullrich, Grey S. Nearing<br>
                    <br>This paper explores the watershed boundary as a control volume of mass conservation, and the potential for machine learning with mass balance constraints to learn volumetric biases in data.</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/frame_2022_extreme.png" alt="Figure from frame_2022_extreme" class="paper-image">
                <p><a href="https://hess.copernicus.org/articles/26/3377/2022/hess-26-3377-2022.html" target="_blank">HESS Link to paper</a> | <a href="papers/frame_2022_extreme.pdf" target="_blank">PDF alternate link | Extreme Event Modeling (2022)</a></p>
                <p class="paper-description">
                    <b>Jonathan M. Frame</b>, Frederik Kratzert, Daniel Klotz, Martin Gauch, Guy Shalev, Oren Gilon, Logan M. Qualls, Hoshin V. Gupta, and Grey S. Nearing<br>
                    <br>This paper explores the ability of machine learning models to make predictions of extremely large, and rare, runoff events, particularly when those events are not included in training data.</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/frame_2021_post_processing.png" alt="Figure from frame_2021_post_processing" class="paper-image">
                <p><a href="https://onlinelibrary.wiley.com/doi/10.1111/1752-1688.12964" target="_blank">Wiley Link to paper</a> | <a href="papers/frame_2021_post_processing.pdf" target="_blank">PDF alternate link | Post-Processing NWM (2021)</a></p>
                <p class="paper-description">
                    <b>Jonathan M. Frame</b>, Frederik Kratzert, Austin Raney II, Mashrekur Rahman, Fernando R. Salas, Grey S. Nearing<br>
                    <br>This paper explores a trivial method of combining hydrologic process-based modeling with machine learning. This approach for hybrid modeling is useful for understanding hydrology across large domains, and for identifying weaknesses in hydrological modeling approaches.</p>
            </div>
    
            <!-- Co-authored and Other Papers -->
            <h2>Co-authored Publications</h2>

            <div class="paper">
                <img src="fig/papers/ogden2026nextgen.png" alt="Figure from ogden2026nextgen" class="paper-image">
                <p><a href="https://onlinelibrary.wiley.com/doi/10.1111/1752-1688.70089" target="_blank">Wiley Link to paper</a> | <a href="papers/ogden2026nextgen.pdf" target="_blank">PDF alternate link | Nextgen National Water Model (2026)</a></p>
                <p class="paper-description">
                    Fred L. Ogden, Keith Jennings, Edward P. Clark, Ethan Coon, Brian Cosgrove, Luciana Kindl da Cunha, Matthew W. Farthing, Trey Flowers, <b>Jonathan M. Frame</b>, Nels J. Frazier, Jessica L. Garrett, Thomas M. Graziano, Joseph D. Hughes, J. Michael Johnson, Rachel McDaniel, J. David Moulton, Scott D. Peckham, Fernando R. Salas, Gaurav Savant, Roland Viger, Andy Wood<br>
                    <br>Finally, a paper describing the philosophy behind the Next Generation Water Resources Modeling Framework. We've worked on several models that make up the initial formulations for this Framework, which is slated to makeup the computational ecosystem of the next version of the operational U.S. National Water Model. The idea behind this frameowkork is that it allows a "plug and play" environment for adding new models and testing new formulations, conceptualization and combinations of hydrologic modules.</p>
            </div>

            <div class="paper">
                <img src="fig/papers/song2026extreme.png" alt="Figure from song2026extreme" class="paper-image">
                <p><a href="https://doi.org/10.1029/2025WR040414" target="_blank">AGU Link to paper</a> | <a href="song2026extreme.pdf" target="_blank">PDF alternate link | Differentiable Extreme Events (2026)</a></p>
                <p class="paper-description">
                    Yalan Song, Kamlesh Sawadekar, <b>Jonathan M. Frame</b>, Ming Pan, Martyn P. Clark, Wouter J. M. Knoben, Andrew W. Wood, Kathryn E. Lawson, Trupesh Patel, and Chaopeng Shen<br>
                    <br>This is a similar experiment to the <a href="https://hess.copernicus.org/articles/26/3377/2022/hess-26-3377-2022.html" target="_blank">2022 Extreme Events Paper</a>, but using differentiable HBV.</p>
            </div>

            <div class="paper">
                <img src="fig/papers/wei2025sve.png" alt="Figure from Wei2025" class="paper-image">
                <p><a href="https://doi.org/10.1038/s41598-025-23061-4" target="_blank">Nature Link to paper</a></p>
                <p><a href="papers/wei2025sve.pdf" target="_blank">PDF alternate link</a></p>
                <p class="paper-description">Time fractional Saint Venant equations. We developed an LSTM benchmark for river routing.</p>
            </div>

            <div class="paper">
                <img src="fig/papers/arefin2025swat.png" alt="Figure from arefin2025swat" class="paper-image">
                <p><a href="https://doi.org/10.3390/environments12100395" target="_blank">MDPI Link to paper</a></p>
                <p><a href="papers/arefin2025swat.pdf" target="_blank">PDF alternate link</a></p>
                <p class="paper-description">SWAT Machine Learning-Integrated Modeling</p>
            </div>
            
            <div class="paper">
                <img src="fig/papers/thapa_2025_riverplanform.png" alt="Figure from Thapa" class="paper-image">
                <p><a href="https://onlinelibrary.wiley.com/doi/10.1002/esp.70158" target="_blank">Wiley Link to paper</a></p>
                <p><a href="papers/thapa_2025_riverplanform.pdf" target="_blank">PDF alternate link</a></p>
                <p class="paper-description">Detecting river centrelines and estimating river water surface widths</p>
            </div>

            <div class="paper">
                <img src="fig/papers/RamirezMolina_2025_lstm.png" alt="Figure from RamírezMolina" class="paper-image">
                <p><a href="papers/RamirezMolina_2025_lstm.pdf" target="_blank">Ramírez Molina et al., 2024, Synthetic experiment for spatially paired sites for data assimilation.</a></p>
                <p class="paper-description">We contributed a software environment (<a href="https://github.com/NWC-CUAHSI-Summer-Institute/deep_bucket_lab.git" target="_blank">Deep Bucket Lab</a>) for prototyping deep learning modeling techniques with hydrologically realistic synthetic data.</p>
            </div>

            <div class="paper">
                <img src="fig/papers/Abramowitz_2024_plumber2.png" alt="Figure from Abramowitz" class="paper-image">
                <p><a href="papers/Abramowitz_2024_plumber2.pdf" target="_blank">Abramowitz et al., 2024, LSTM as a benchmark for land surface energy fluxes</a></p>
                <p class="paper-description">We developed an LSTM model as the benchmark for evaluating land surface models’ predictions of turbulent carbon, water, and heat fluxes using flux tower data from 170 sites.</p>
            </div>


            <div class="paper">
                <img src="fig/papers/gholizadeh_2023_lstm_gw.png" alt="Figure from gholizadeh_2023_lstm_gw" class="paper-image">
                <p><a href="papers/gholizadeh_2023_lstm_gw.pdf" target="_blank">Gholizadeh et al., 2023, LSTM for Groundwater</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/nair_2022_deephydro.png" alt="Figure from nair_2022_deephydro" class="paper-image">
                <p><a href="papers/nair_2022_deephydro.pdf" target="_blank">Nair et al., 2022, DeepHydro</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/wei_2022_hydro_exchange.png" alt="Figure from wei_2022_hydro_exchange" class="paper-image">
                <p><a href="papers/wei_2022_hydro_exchange.pdf" target="_blank">Wei et al., 2021, A distributed domain model coupling open channel flow and groundwater</a></p>
                <p><a href="https://www.sciencedirect.com/science/article/abs/pii/S0022169422005856" target="_blank">Science Direct Link to paper</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
            
	    <div class="paper">
                <img src="fig/papers/zhang_2021_fade.png" alt="Figure from zhang_2021_fade" class="paper-image">
                <p><a href="papers/zhang_2021_fade.pdf" target="_blank">Zhang et al., 2021, Fractional Advection-Dispersion</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/brenner_2021_deep_learning_evapotranspiration.png" alt="Figure from brenner_2021_deep_learning_evapotranspiration" class="paper-image">
                <p><a href="papers/brenner_2021_deep_learning_evapotranspiration.pdf" target="_blank">Brenner et al., 2021, Deep Learning for Evapotranspiration</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/nearing_2020_hydro_role_age_ml_wrr.png" alt="Figure from nearing_2020_hydro_role_age_ml_wrr" class="paper-image">
                <p><a href="papers/nearing_2020_hydro_role_age_ml_wrr.pdf" target="_blank">Nearing et al., 2020, Hydrological Role in ML</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/nearing_2019_nonstationary.png" alt="Figure from nearing_2019_nonstationary" class="paper-image">
                <p><a href="papers/nearing_2019_nonstationary.pdf" target="_blank">Nearing et al., 2019, Nonstationary Climate</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
    
            <div class="paper">
                <img src="fig/papers/pelissier_2019_GPR.png" alt="Figure from pelissier_2019_GPR" class="paper-image">
                <p><a href="papers/pelissier_2019_GPR.pdf" target="_blank">Pelissier et al., 2019, Gaussian Process Regression</a></p>
                <p class="paper-description">[Description coming soon]</p>
            </div>
        </section>
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