DualEarth.github.io/papers.html at main · majid828/DualEarth.github.io · GitHub

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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">
            <!-- 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/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/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>
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