| Sources of hydrological model uncertainties and advances in their analysis E Moges, Y Demissie, L Larsen, F Yassin Water 13 (1), 28, 2020 | 159 | 2020 |
| Historical and future drought in Bangladesh using copula-based bivariate regional frequency analysis MR Mortuza, E Moges, Y Demissie, HY Li Theoretical and Applied Climatology 135, 855-871, 2019 | 52 | 2019 |
| The utility of information flow in formulating discharge forecast models: A case study from an arid snow‐dominated catchment C Tennant, L Larsen, D Bellugi, E Moges, L Zhang, H Ma Water Resources Research 56 (8), e2019WR024908, 2020 | 35 | 2020 |
| Uncertainty propagation in coupled hydrological models using winding stairs and null-space Monte Carlo methods E Moges, Y Demissie, H Li Journal of Hydrology 589, 125341, 2020 | 19 | 2020 |
| Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty E Moges, Y Demissie, HY Li Water Resources Research 52 (4), 2551-2570, 2016 | 14 | 2016 |
| Evaluation of sediment transport equations and parameter sensitivity analysis using the SRH-2D model EM Moges Universität Stuttgart, 2010 | 14 | 2010 |
| Strength and memory of precipitation’s control over streamflow across the conterminous United States E Moges, BL Ruddell, L Zhang, JM Driscoll, LG Larsen Water Resources Research, e2021WR030186, 2022 | 6 | 2022 |
| HydroBench: Jupyter supported reproducible hydrological model benchmarking and diagnostic tool E Moges, BL Ruddell, L Zhang, JM Driscoll, P Norton, F Perez, LG Larsen Frontiers in Earth Science, 1469, 2022 | 5 | 2022 |
| CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments and comparative analysis of hydrologic extremes L Zhang, E Moges, J Kirchner, E Coda, T Liu, AS Wymore, Z Xu, ... Hydrological Processes, e14429, 2021 | 5 | 2021 |
| Bayesian Augmented L-Moment Approach for Regional Frequency Analysis E Moges, A Jared, Y Demissie, E Yan, R Mortuza, V Mahat Proceedings of the EWRI Congress, 165 - 180, 2018 | 5 | 2018 |
| A physics-informed machine learning model for streamflow prediction L Zhang, DG Bellugi, S Li, A Kamat, J Kadi, E Moges, G Gorski, O Wani, ... AGU Fall Meeting Abstracts 2022, H31E-01, 2022 | 1 | 2022 |
| CHOSEN: A synthesis of hydrometeorological data from 30 intensively monitored watersheds across the US L Zhang, E Moges, E Coda, T Liu, Z Xu, J Kirchner, L Larsen Authorea Preprints, 2020 | 1 | 2020 |
| Extreme Precipitation and Runoff under Changing Climate in Southern Maine E Yan, A Jared, V Mahat, M Picel, D Verner, T Wall, EM Moges, ... Argonne National Lab.(ANL), Argonne, IL (United States), 2016 | 1 | 2016 |
| How appropriate is the alternating block method to represent flooding from extreme precipitation events? S Jankowfsky, M Sharifian, E Moges, L Nicotina, S Li, A Hilberts EGU24, 2024 | | 2024 |
| Towards the application of a semi-distributed LSTM model E Moges, S Zanardo, S Li, L Nicotina, A Hilberts AGU, 2023 | | 2023 |
| Synchrony of nitrogen wet deposition inputs and watershed nitrogen outputs using information theory DS Murray, E Moges, L Larsen, MD Shattuck, WH McDowell, AS Wymore Water Resources Research 59 (10), e2023WR034794, 2023 | | 2023 |
| Design Rainfall controls on Pluvial Flood Risk at different spatial and temporal scales-a US case study L Nicotina, E Moges, M Sharifian, S Jankowfsky, S Li, A Hilberts EGU General Assembly Conference Abstracts, EGU-13498, 2023 | | 2023 |
| Calling for a National Model Benchmarking Facility BL Ruddell, M Clark, JM Driscoll, D Gochis, H Gupta, D Huntzinger, ... EarthArXiv, 2023 | | 2023 |
| Quantifying the synchrony of wet deposition N inputs and watershed N exports using information theory D Murray, E Moges, L Larsen, MD Shattuck, WH McDowell, AS Wymore AGU Fall Meeting Abstracts 2022, B16G-08, 2022 | | 2022 |
| Diagnostics and postprocessing of the National Hydrological Model product E Moges, JM Driscoll, L Zhang, BL Ruddell, L Larsen AGU Fall Meeting Abstracts 2022, H12M-0847, 2022 | | 2022 |
Laurel G. LarsenAssociate Professor, Depts. of Geography and Civil & Environmental Engineering, UC Berkeley在 berkeley.edu 的电子邮件经过验证
