| The potential of knowing more: A review of data-driven urban water management S Eggimann, L Mutzner, O Wani, MY Schneider, D Spuhler, ... Environmental science & technology 51 (5), 2538-2553, 2017 | 179 | 2017 |
| Parameter estimation of hydrologic models using a likelihood function for censored and binary observations O Wani, A Scheidegger, JP Carbajal, J Rieckermann, F Blumensaat Water Research, 2017 | 31 | 2017 |
| Comparing approaches to deal with non‐gaussianity of rainfall data in kriging‐based radar‐gauge rainfall merging F Cecinati, O Wani, MA Rico‐Ramirez Water Resources Research 53 (11), 8999-9018, 2017 | 29 | 2017 |
| Smart urban water systems: what could possibly go wrong? M Moy de Vitry, MY Schneider, OF Wani, L Manny, JP Leitão, S Eggimann Environmental Research Letters 14 (8), 081001, 2019 | 27 | 2019 |
| Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O Wani, JVL Beckers, AH Weerts, DP Solomatine Hydrology and Earth System Sciences 21 (8), 4021, 2017 | 26 | 2017 |
| Using a simple post-processor to predict residual uncertainty for multiple hydrological model outputs LB Ehlers, O Wani, J Koch, TO Sonnenborg, JC Refsgaard Advances in Water Resources 129, 16-30, 2019 | 8 | 2019 |
| Exploring a copula-based alternative to additive error models—for non-negative and autocorrelated time series in hydrology O Wani, A Scheidegger, F Cecinati, G Espadas, J Rieckermann Journal of Hydrology 575, 1031-1040, 2019 | 7 | 2019 |
| Accounting for variation in rainfall intensity and surface slope in wash-off model calibration and prediction within the Bayesian framework M Muthusamy, O Wani, A Schellart, S Tait Water research 143, 561-569, 2018 | 3 | 2018 |
| Parameter estimation of urban drainage models using binary observations from low-cost sensors O Wani, F Blumensaat, A Scheidegger, T Doppler, J Rieckermann 10th International Urban Drainage Modelling Conference, 2015 | 2 | 2015 |
| Evaluation and correction of uncertainty due to Gaussian approximation in radar-rain gauge merging using kriging with external drift F Cecinati, O Wani, MA Rico-Ramirez AGU Fall Meeting Abstracts 2016, H11G-06, 2016 | 1 | 2016 |
| Does distributed monitoring improve the calibration of urban drainage models? O Wani, M Maurer, J Rieckermann, F Blumensaat International Urban Drainage Modeling Conference, 2022, Costa Mesa, USA, 2021 | | 2021 |
| Is flow control in a space-constrained drainage network effective? A performance assessment for combined sewer overflow reduction W Wang, JP Leitão, O Wani Environmental Research 202, 111688, 2021 | | 2021 |
| Climate emergency: It is time to prepare for severe floods that will hit South Asia O Wani Down to Earth, Aug 2021, URL: https://tinyurl.com/35hteaur, 2021 | | 2021 |
| Voices of Eawag Researchers J Hering, AS Narayan, F Balk, OF Wani, C Lüthi, JP Leitao, R Blackman | | 2020 |
| Impact of different sources of precipitation data on urban rainfall-runoff predictions: A comparison of rain gauges, commercial microwave links and radar A Disch, A Scheidegger, OF Wani, J Rieckermann Rainfall Monitoring, Modelling and Forecasting in Urban Environment …, 2019 | | 2019 |
| Statistical Methods for Better Hydrologic Predictions—Improving Parameter and Uncertainty Estimation O Wani ETH Zurich, 2018 | | 2018 |
| Towards a more robust sediment wash-off model M Muthusamy, O Wani, A Schellart, S Tait AGU Fall Meeting Abstracts 2017, H13A-1346, 2017 | | 2017 |
| Gaussian copula as a likelihood function for environmental models O Wani, G Espadas, F Cecinati, J Rieckermann AGU Fall Meeting Abstracts 2017, H23C-1670, 2017 | | 2017 |
| Implications of risk perception on flood management and warning: 2014 Kashmir floods as a case study R Ghani | | 2015 |
| Predictive uncertainty in streamflows: quantification using instance-based learning O Wani UNESCO-IHE, 2014 | | 2014 |
Jörg RieckermannEawagVerified email at eawag.ch
