Keirnan Fowler


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Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
Luca Trotter, Wouter Knoben, Keirnan Fowler, Margarita Saft, Murray C. Peel
Geoscientific Model Development, Volume 15, Issue 16

Abstract. The Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) is a flexible modelling framework reproducing the behaviour of 47 established hydrological models. This toolbox can be used to calibrate and run models in a user-friendly and consistent way and is designed to facilitate the sharing of model code for reproducibility and to support intercomparison between hydrological models. Additionally, it allows users to create or modify models using components of existing ones. We present a new MARRMoT release (v2.1) designed for improved speed and ease of use. While improved computational efficiency was the main driver for this redevelopment, MARRMoT v2.1 also succeeds in drastically reducing the verbosity and repetitiveness of the code, which improves readability and facilitates debugging. The process to create new models or modify existing ones within the toolbox is also simplified in this version, making MARRMoT v2.1 accessible for researchers and practitioners at all levels of expertise. These improvements were achieved by implementing an object-oriented structure and aggregating all common model operations into a single class definition from which all models inherit. The new modelling framework maintains and improves on several good practices built into the original MARRMoT and includes a number of new features such as the possibility of retrieving more output in different formats that simplifies troubleshooting, and a new functionality that simplifies the calibration process. We compare outputs of 36 of the models in the framework to an earlier published analysis and demonstrate that MARRMoT v2.1 is highly consistent with the previous version of MARRMoT (v1.4), while achieving a 3.6-fold improvement in runtime on average. The new version of the toolbox and user manual, including several workflow examples for common application, are available from GitHub (, last access: 12 May 2022;, Trotter and Knoben, 2022b).


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Towards more realistic runoff projections by removing limits on simulated soil moisture deficit
Keirnan Fowler, Gemma Coxon, Jim Freer, Wouter Knoben, Murray C. Peel, Thorsten Wagener, Andrew W. Western, Ross Woods, Zhiqu Lu
Journal of Hydrology, Volume 600

• Most conceptual bucket models have an upper limit on simulated soil moisture deficit. • Problems arise when the bucket “empties” because ET drops to unrealistic (low) levels. • Alternatives include bottomless buckets or deficit-based soil moisture accounting. • Here, we switch to a deficit-based scheme while keeping everything else constant. • Tested over historic drought, model performance and realism are enhanced. Rainfall-runoff models based on conceptual “buckets” are frequently used in climate change impact studies to provide runoff projections. When these buckets approach empty, the simulated evapotranspiration approaches zero, which places an implicit limit on the soil moisture deficit that can accrue within the model. Such models may cease to properly track the moisture deficit accumulating in reality as dry conditions continue, leading to overestimation of subsequent runoff and possible long-term bias under drying climate. Here, we suggest that model realism may be improved through alternatives which remove the upper limit on simulated soil moisture deficit, such as “bottomless” buckets or deficit-based soil moisture accounting. While some existing models incorporate such measures, no study until now has systematically assessed their impact on model realism under drying climate. Here, we alter a common bucket model by changing the soil moisture storage to a deficit accounting system in such a way as to remove the upper limit on simulated soil moisture deficit. Tested on 38 Australian catchments, the altered model is better able to track the decline in soil moisture at the end of seasonal dry periods, which leads to superior performance over varied historic climate, including the 13-year “Millennium” drought. However, groundwater and GRACE data reveal long-term trends that are not matched in simulations, indicating that further changes may be required. Nonetheless, the results suggest that a broader adoption of bottomless buckets and/or deficit accounting within conceptual rainfall runoff models may improve the realism of runoff projections under drying climate.


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Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections
Keirnan Fowler, Wouter Knoben, Murray C. Peel, Tim Peterson, Dongryeol Ryu, Margarita Saft, Ki‐Weon Seo, Andrew W. Western
Water Resources Research, Volume 56, Issue 5

Evidence suggests that catchment state variables such as groundwater can exhibit multiyear trends. This means that their state may reflect not only recent climatic conditions but also climatic conditions in past years or even decades. Here we demonstrate that five commonly used conceptual “bucket” rainfall‐runoff models are unable to replicate multiyear trends exhibited by natural systems during the “Millennium Drought” in south‐east Australia. This causes an inability to extrapolate to different climatic conditions, leading to poor performance in split sample tests. Simulations are examined from five models applied in 38 catchments, then compared with groundwater data from 19 bores and Gravity Recovery and Climate Experiment data for two geographic regions. Whereas the groundwater and Gravity Recovery and Climate Experiment data decrease from high to low values gradually over the duration of the 13‐year drought, the model storages go from high to low values in a typical seasonal cycle. This is particularly the case in the drier, flatter catchments. Once the drought begins, there is little room for decline in the simulated storage, because the model “buckets” are already “emptying” on a seasonal basis. Since the effects of sustained dry conditions cannot accumulate within these models, we argue that they should not be used for runoff projections in a drying climate. Further research is required to (a) improve conceptual rainfall‐runoff models, (b) better understand circumstances in which multiyear trends in state variables occur, and (c) investigate links between these multiyear trends and changes in rainfall‐runoff relationships in the context of a changing climate.

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A Brief Analysis of Conceptual Model Structure Uncertainty Using 36 Models and 559 Catchments
Wouter Knoben, Jim Freer, Murray C. Peel, Keirnan Fowler, Ross Woods
Water Resources Research, Volume 56, Issue 9

The choice of hydrological model structure, that is, a model's selection of states and fluxes and the equations used to describe them, strongly controls model performance and realism. This work investigates differences in performance of 36 lumped conceptual model structures calibrated to and evaluated on daily streamflow data in 559 catchments across the United States. Model performance is compared against a benchmark that accounts for the seasonality of flows in each catchment. We find that our model ensemble struggles to beat the benchmark in snow-dominated catchments. In most other catchments model structure equifinality (i.e., cases where different models achieve similar high efficiency scores) can be very high. We find no relation between the number of model parameters and performance during either calibration or evaluation periods nor evidence of increased risk of overfitting for models with more parameters. Instead, the choice of model parametrization (i.e., which equations are used and how parameters are used within them) dictates the model's strengths and weaknesses. Results suggest that certain model structures are inherently better suited for certain objective functions and thus for certain study purposes. We find no clear relationships between the catchments where any model performs well and descriptors of those catchments' geology, topography, soil, and vegetation characteristics. Instead, model suitability seems to relate strongest to the streamflow regime each catchment generates, and we have formulated several tentative hypotheses that relate commonalities in model structure to similarities in model performance. Modeling results are made publicly available for further investigation.


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Twenty-three unsolved problems in hydrology (UPH) – a community perspective
Günter Blöschl, M. F. Bierkens, António Chambel, Christophe Cudennec, Georgia Destouni, Aldo Fiori, J. W. Kirchner, Jeffrey J. McDonnell, H. H. G. Savenije, Murugesu Sivapalan, Christine Stumpp, Elena Toth, Elena Volpi, Gemma Carr, Claire Lupton, José Luis Salinas, Borbála Széles, Alberto Viglione, Hafzullah Aksoy, Scott T. Allen, Anam Amin, Vazken Andréassian, Berit Arheimer, Santosh Aryal, Victor R. Baker, Earl Bardsley, Marlies Barendrecht, Alena Bartošová, Okke Batelaan, Wouter Berghuijs, Keith Beven, Theresa Blume, Thom Bogaard, Pablo Borges de Amorim, Michael E. Böttcher, Gilles Boulet, Korbinian Breinl, Mitja Brilly, Luca Brocca, Wouter Buytaert, Attilio Castellarin, Andrea Castelletti, Xiaohong Chen, Yangbo Chen, Yuanfang Chen, Peter Chifflard, Pierluigi Claps, Martyn P. Clark, Adrian L. Collins, Barry Croke, Annette Dathe, Paula Cunha David, Felipe P. J. de Barros, Gerrit de Rooij, Giuliano Di Baldassarre, Jessica M. Driscoll, Doris Duethmann, Ravindra Dwivedi, Ebru Eriş, William Farmer, James Feiccabrino, Grant Ferguson, Ennio Ferrari, Stefano Ferraris, Benjamin Fersch, David C. Finger, Laura Foglia, Keirnan Fowler, Б. И. Гарцман, Simon Gascoin, Éric Gaumé, Alexander Gelfan, Josie Geris, Shervan Gharari, Tom Gleeson, Miriam Glendell, Alena Gonzalez Bevacqua, M. P. González‐Dugo, Salvatore Grimaldi, A.B. Gupta, Björn Guse, Dawei Han, David M. Hannah, A. A. Harpold, Stefan Haun, Kate Heal, Kay Helfricht, Mathew Herrnegger, Matthew R. Hipsey, Hana Hlaváčiková, Clara Hohmann, Ladislav Holko, C. Hopkinson, Markus Hrachowitz, Tissa H. Illangasekare, Azhar Inam, Camyla Innocente, Erkan Istanbulluoglu, Ben Jarihani, Zahra Kalantari, Andis Kalvāns, Sonu Khanal, Sina Khatami, Jens Kiesel, M. J. Kirkby, Wouter Knoben, Krzysztof Kochanek, Silvia Kohnová, Alla Kolechkina, Stefan Krause, David K. Kreamer, Heidi Kreibich, Harald Kunstmann, Holger Lange, Margarida L. R. Liberato, Eric Lindquist, Timothy E. Link, Junguo Liu, Daniel P. Loucks, Charles H. Luce, Gil Mahé, Olga Makarieva, Julien Malard, Shamshagul Mashtayeva, Shreedhar Maskey, Josep Mas‐Pla, Maria Mavrova-Guirguinova, Maurizio Mazzoleni, Sebastian H. Mernild, Bruce Misstear, Alberto Montanari, Hannes Müller-Thomy, Alireza Nabizadeh, Fernando Nardi, Christopher M. U. Neale, Nataliia Nesterova, Bakhram Nurtaev, V.O. Odongo, Subhabrata Panda, Saket Pande, Zhonghe Pang, Georgia Papacharalampous, Charles Perrin, Laurent Pfister, Rafael Pimentel, María José Polo, David Post, Cristina Prieto, Maria‐Helena Ramos, Maik Renner, José Eduardo Reynolds, Elena Ridolfi, Riccardo Rigon, Mònica Riva, David Robertson, Renzo Rosso, Tirthankar Roy, João Henrique Macedo Sá, Gianfausto Salvadori, Melody Sandells, Bettina Schaefli, Andreas Schumann, Anna Scolobig, Jan Seibert, Éric Servat, Mojtaba Shafiei, Ashish Sharma, Moussa Sidibé, Roy C. Sidle, Thomas Skaugen, Hugh G. Smith, Sabine M. Spiessl, Lina Stein, Ingelin Steinsland, Ulrich Strasser, Bob Su, Ján Szolgay, David G. Tarboton, Flavia Tauro, Guillaume Thirel, Fuqiang Tian, Rui Tong, Kamshat Tussupova, Hristos Tyralis, R. Uijlenhoet, Rens van Beek, Ruud van der Ent, Martine van der Ploeg, Anne F. Van Loon, Ilja van Meerveld, Ronald van Nooijen, Pieter van Oel, Jean‐Philippe Vidal, Jana von Freyberg, Sergiy Vorogushyn, Przemysław Wachniew, Andrew J. Wade, Philip J. Ward, Ida Westerberg, Christopher White, Eric F. Wood, Ross Woods, Zongxue Xu, Koray K. Yılmaz, Yongqiang Zhang
Hydrological Sciences Journal, Volume 64, Issue 10

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.