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Nooshin Mehrnegar
Nooshin Mehrnegar
Postdoctoral researcher at Aalborg university
Verified email at plan.aau.dk
Title
Cited by
Cited by
Year
Understanding the global hydrological droughts of 2003–2016 and their relationships with teleconnections
E Forootan, M Khaki, M Schumacher, V Wulfmeyer, N Mehrnegar, ...
Science of the Total Environment 650, 2587-2604, 2019
1602019
Bayesian convolutional neural networks for predicting the terrestrial water storage anomalies during GRACE and GRACE-FO gap
S Mo, Y Zhong, E Forootan, N Mehrnegar, X Yin, J Wu, W Feng, X Shi
Journal of Hydrology 604, 127244, 2022
592022
An iterative ICA-based reconstruction method to produce consistent time-variable total water storage fields using GRACE and Swarm satellite data
E Forootan, M Schumacher, N Mehrnegar, A Bezděk, MJ Talpe, ...
Remote Sensing 12 (10), 1639, 2020
502020
Exploring groundwater and soil water storage changes across the CONUS at 12.5 km resolution by a Bayesian integration of GRACE data into W3RA
N Mehrnegar, O Jones, MB Singer, M Schumacher, T Jagdhuber, ...
Science of the Total Environment 758, 143579, 2021
262021
Comparing global hydrological models and combining them with GRACE by dynamic model data averaging (DMDA)
N Mehrnegar, O Jones, MB Singer, M Schumacher, P Bates, E Forootan
Advances in Water Resources 138, 103528, 2020
252020
Sustained water storage in Horn of Africa drylands dominated by seasonal rainfall extremes
M Adloff, MB Singer, DA MacLeod, K Michaelides, N Mehrnegar, ...
Geophysical Research Letters 49 (21), e2022GL099299, 2022
172022
Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance …
E Forootan, N Mehrnegar, M Schumacher, LAR Schiettekatte, ...
Science of the Total Environment 912, 169476, 2024
42024
Making the best use of GRACE, GRACE‐FO and SMAP data through a constrained Bayesian data‐model integration
N Mehrnegar, M Schumacher, T Jagdhuber, E Forootan
Water Resources Research 59 (9), e2023WR034544, 2023
42023
A hierarchical Constrained Bayesian (ConBay) approach to jointly estimate water storage and Post-Glacial Rebound from GRACE (-FO) and GNSS data
E Forootan, N Mehrnegar
All Earth 34 (1), 120-146, 2022
42022
AssimEO-Berechnung des Gesamtwasserdargebots für die Pflanzenproduktion durch Assimilation von Erdbeobachtungsdaten
C Montzka, A Fluhrer, T Jagdhuber, S Moradi, H Zhao, D Mengen, ...
2023
Two decades (2003-2021) of storage changes in the soil water and groundwater of CONUS
N Mehrnegar, M Schumacher, T Jagdhuber, E Forootan
2023
How can the contribution of water storage changes and post glacier rebound be jointly estimated from GRACE (-FO) and GNSS measurements?
N Mehrnegar, E Forootan
Fall Meeting 2022, 2022
2022
A hierarchical Constrained Bayesian (ConBay) approach to jointly estimate water storage and post glacier rebound from GRACE (-FO) and GNSS data
N Mehrnegar, E Forootan
EGU22, 2022
2022
Groundwater storage in the Horn of Africa drylands dominated by seasonal rainfall extremes
M Adloff, M Bliss Singer, D McLeod, K Michaelides, N Mehrnegar, ...
EGU General Assembly Conference Abstracts, EGU21-15470, 2021
2021
Bayesian integration of satellite geodetic data with models to separate land hydrology and surface deformation signals
N Mehrnegar
Cardiff University, 2021
2021
Exploring meso-scale soil water and groundwater storage changes within the USA through a Bayesian combination of GRACE data with monthly 12.5 km model simulations
N Mehrnegar, O Jones, MB Singer, M Schumacher, T Jagdhuber, ...
EGU General Assembly Conference Abstracts, 19070, 2020
2020
Comparing Global Hydrological Models and Combining them with GRACE Data by Dynamic Bayesian Averaging (DBA).
N Mehrnegar, O Jones, MB Singer, M Shumacher, P Bates, E Forootan
Geophysical Research Abstracts 21, 2019
2019
A comprehensive assessment of a Bayesian-based and a statistical decomposition-based framework for separating GRACE signals
N Mehrnegar, E Forootan, O Jones, M Singer, M Shumacher, P Bates
EGU General Assembly Conference Abstracts, 6913, 2018
2018
Global Droughts are More Severe than They Appear in Hydrological Models: An Investigation Through a Bayesian Merging of Grace and Grace-Fo Data into a Water Balance Model
E Forootan, N Mehrnegar, M Schumacher, LA Retegui Schiettekatte, ...
Available at SSRN 4482334, 0
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Articles 1–19