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Edom Moges
Edom Moges
Подтвержден адрес электронной почты в домене berkeley.edu
Название
Процитировано
Процитировано
Год
Sources of hydrological model uncertainties and advances in their analysis
E Moges, Y Demissie, L Larsen, F Yassin
Water 13 (1), 28, 2020
1672020
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
552019
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
362020
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
192020
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
142016
Evaluation of sediment transport equations and parameter sensitivity analysis using the SRH-2D model
EM Moges
Universität Stuttgart, 2010
142010
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
92022
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
62022
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
62021
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
52018
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
12022
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
12020
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
12016
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
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Статьи 1–20