| Assessing the significance of wet‐canopy evaporation from forests during extreme rainfall events for flood mitigation in mountainous regions of the United Kingdom T Page, NA Chappell, KJ Beven, B Hankin, A Kretzschmar Hydrological Processes 34 (24), 4740-4754, 2020 | 35 | 2020 |
| A risk-based network analysis of distributed in-stream leaky barriers for flood risk management B Hankin, I Hewitt, G Sander, F Danieli, G Formetta, A Kamilova, ... Natural Hazards and Earth System Sciences 20 (10), 2567-2584, 2020 | 24 | 2020 |
| Reversing hydrology: Estimation of sub-hourly rainfall time-series from streamflow A Kretzschmar, W Tych, NA Chappell Environmental modelling & software 60, 290-301, 2014 | 21 | 2014 |
| On (in) validating environmental models. 2. Implementation of a Turing‐like test to modelling hydrological processes K Beven, S Lane, T Page, A Kretzschmar, B Hankin, P Smith, N Chappell Hydrological processes 36 (10), e14703, 2022 | 17 | 2022 |
| The effect of hedgerow wild‐margins on topsoil hydraulic properties, and overland‐flow incidence, magnitude and water‐quality EE Wallace, G McShane, W Tych, A Kretzschmar, T McCann, ... Hydrological Processes 35 (3), e14098, 2021 | 17 | 2021 |
| Deciding on fitness‐for‐purpose‐of models and of natural flood management K Beven, T Page, B Hankin, P Smith, A Kretzschmar, D Mindham, ... Hydrological Processes 36 (11), e14752, 2022 | 10 | 2022 |
| JBA trust challenge: A risk-based analysis of small scale, distributed,“nature-based” flood risk management measures deployed on river networks S Cabaneros, F Danieli, G Formetta, R Gonzalez, M Grinfield, B Hankin, ... Maths Foresees, Leeds, 2018 | 10* | 2018 |
| Using micro‐catchment experiments for multi‐local scale modelling of nature‐based solutions B Hankin, TJC Page, NA Chappell, KJ Beven, PJ Smith, A Kretzschmar, ... Hydrological Processes 35 (11), e14418, 2021 | 8 | 2021 |
| Reversing hydrology: quantifying the temporal aggregation effect of catchment rainfall estimation using sub-hourly data A Kretzschmar, W Tych, NA Chappell, KJ Beven Hydrology Research 47 (3), 630-645, 2016 | 7 | 2016 |
| What really happens at the end of the rainbow?–paying the price for reducing uncertainty (using reverse hydrology models) A Kretzschmar, W Tych, N Chappell, K Beven Procedia Engineering 154, 1333-1340, 2016 | 6 | 2016 |
| Efficient cascade modelling of nature-based solutions scaled to larger catchments to model extremes taking account of uncertainties. B Hankin, A Kretzschmar, T Page, N Chappell, R Lamb, K Beven, ... Geophysical Research Abstracts 21, 2019 | 1 | 2019 |
| Utilising Reverse Hydrology to quantify and improve the spatio-temporal information content of catchment rainfall estimates for flood modelling A Kretzschmar PQDT-Global, 2017 | 1 | 2017 |
| UPH Problem 20–reducing uncertainty in model prediction: a model invalidation approach based on a Turing-like test K Beven, T Page, P Smith, A Kretzschmar, B Hankin, N Chappell Proceedings of IAHS 385, 129-134, 2024 | | 2024 |
| Problem 20. Reducing uncertainty in model prediction: The role of model invalidation K Beven, A Kretzschmar, P Smith, N Chappell IAHS2022, 2022 | | 2022 |
| Developing and documenting a Hydrological Model for reproducible research: A new version of Dynamic TOPMODEL P Smith, K Beven, A Kretzschmar, N Chappell EGU General Assembly Conference Abstracts, 20790, 2020 | | 2020 |
| System Performance of networks of NFM B Hankin, R Lamb, I Hewitt, G Sander, S Cabaneros, F Danieli, ... EGU General Assembly Conference Abstracts, 7088, 2018 | | 2018 |
| How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology A Kretzschmar, W Tych, K Beven, N Chappell EGU General Assembly Conference Abstracts, 11724, 2017 | | 2017 |
| Flood forecasting using non-stationarity in a river with tidal influence–a feasibility study R Killick, A Kretzschmar, S Ilic, W Tych EGU General Assembly Conference Abstracts, 13799, 2017 | | 2017 |
| Filling the Gap A Kretzschmar | | |
