| Why continuous simulation? The role of antecedent moisture in design flood estimation S Pathiraja, S Westra, A Sharma Water Resources Research 48 (6), 2012 | 175 | 2012 |
| Hydrologic modeling in dynamic catchments: A data assimilation approach S Pathiraja, L Marshall, A Sharma, H Moradkhani Water Resources Research 52 (5), 3350-3372, 2016 | 100 | 2016 |
| Data‐driven model uncertainty estimation in hydrologic data assimilation S Pathiraja, H Moradkhani, L Marshall, A Sharma, G Geenens Water resources research 54 (2), 1252-1280, 2018 | 72 | 2018 |
| Detecting non-stationary hydrologic model parameters in a paired catchment system using data assimilation S Pathiraja, L Marshall, A Sharma, H Moradkhani Advances in water resources 94, 103-119, 2016 | 69 | 2016 |
| Fundamentals of data assimilation and theoretical advances H Moradkhani, GS Nearing, P Abbaszadeh, S Pathiraja Handbook of hydrometeorological ensemble forecasting, 1-26, 2018 | 54 | 2018 |
| Time-varying parameter models for catchments with land use change: the importance of model structure S Pathiraja, D Anghileri, P Burlando, A Sharma, L Marshall, H Moradkhani Hydrology and Earth System Sciences 22 (5), 2903-2919, 2018 | 45 | 2018 |
| McKean--Vlasov SDEs in nonlinear filtering S Pathiraja, S Reich, W Stannat SIAM Journal on Control and Optimization 59 (6), 4188-4215, 2021 | 21 | 2021 |
| Discrete gradients for computational Bayesian inference S Pathiraja, S Reich Journal of Computational Dynamics 6 (2), 2019 | 17 | 2019 |
| Hemodynamic data assimilation in a subject-specific circle of willis geometry F Gaidzik, S Pathiraja, S Saalfeld, D Stucht, O Speck, D Thévenin, ... Clinical Neuroradiology 31, 643-651, 2021 | 16 | 2021 |
| Insights on the impact of systematic model errors on data assimilation performance in changing catchments S Pathiraja, D Anghileri, P Burlando, A Sharma, L Marshall, H Moradkhani Advances in water resources 113, 202-222, 2018 | 13 | 2018 |
| Perturbations and projections of Kalman–Bucy semigroups AN Bishop, P Del Moral, SD Pathiraja Stochastic Processes and their Applications 128 (9), 2857-2904, 2018 | 11 | 2018 |
| DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling A Kapoor, S Pathiraja, L Marshall, R Chandra Environmental Modelling & Software 169, 105831, 2023 | 8 | 2023 |
| L2 convergence of smooth approximations of stochastic differential equations with unbounded coefficients S Pathiraja Stochastic Analysis and Applications, 2023 | 7 | 2023 |
| Ensemble transform algorithms for nonlinear smoothing problems J de Wiljes, S Pathiraja, S Reich SIAM Journal on Scientific Computing 42 (1), A87-A114, 2020 | 7 | 2020 |
| Why continuous simulation S Pathiraja, S Westra, A Sharma The role of antecedent moisture in design flood 5, 0 | 5 | |
| Analysis of the feedback particle filter with diffusion map based approximation of the gain S Pathiraja, W Stannat Foundations of Data Science 3 (3), 615-645, 2021 | 4 | 2021 |
| Multiplicative non-Gaussian model error estimation in data assimilation S Pathiraja, PJ van Leeuwen Journal of Advances in Modeling Earth Systems 14, 2022 | 2 | 2022 |
| Multiplicative non-Gaussian model error estimation in data assimilation S Pathiraja, PJ van Leeuwen arXiv preprint arXiv:1807.09621, 2021 | 2 | 2021 |
| Model Uncertainty Quantification Methods For Data Assimilation In Partially Observed Multi-Scale Systems SD Pathiraja, PJ van Leeuwen AGU Fall Meeting Abstracts 2017, NG31A-0154, 2017 | 1 | 2017 |
| Model Uncertainty Quantification Methods In Data Assimilation SD Pathiraja, LA Marshall, A Sharma, H Moradkhani AGU Fall Meeting Abstracts 2017, U13B-34, 2017 | 1 | 2017 |
Ashish SharmaProfessor, Civil and Environmental Engineering, UNSWVerified email at unsw.edu.au
