Runoff prediction in ungauged basins: Synthesis across processes, places and scales
01 Jan 2013-pp 1-465
TL;DR: In this article, the authors present a data acquisition framework for predictions of runoff in ungauged basins, including a synthesis framework for runoff predictions in un-gauging basins.
Abstract: List of contributors Foreword Thomas Dunne Preface Gunter Bloeschl, Murugesu Sivapalan, Thorsten Wagener, Alberto Viglione and Hubert Savenije 1. Introduction Gunter Bloeschl, Murugesu Sivapalan, Thorsten Wagener, Alberto Viglione and Hubert Savenije 2. A synthesis framework for runoff predictions in ungauged basins Thorsten Wagener, Gunter Bloeschl, David Goodrich, Hoshin V. Gupta, Murugesu Sivapalan, Yasuto Tachikawa, Peter Troch and Markus Weiler 3. A data acquisition framework for predictions of runoff in ungauged basins Brian McGlynn, Gunter Bloeschl, Marco Borga, Helge Bormann, Ruud Hurkmans, Jurgen Komma, Lakshman Nandagiri, Remko Uijlenhoet and Thorsten Wagener 4. Process realism: flow paths and storage Doerthe Tetzlaff, Ghazi Al-Rawas, Gunter Bloeschl, Sean K. Carey, Ying Fan, Markus Hrachowitz, Robert Kirnbauer, Graham Jewitt, Hjalmar Laudon, Kevin J. McGuire, Takahiro Sayama, Chris Soulsby, Erwin Zehe and Thorsten Wagener 5. Prediction of annual runoff in ungauged basins Thomas McMahon, Gregor Laaha, Juraj Parajka, Murray C. Peel, Hubert Savenije, Murugesu Sivapalan, Jan Szolgay, Sally Thompson, Alberto Viglione, Ross Woods and Dawen Yang 6. Prediction of seasonal runoff in ungauged basins R. Weingartner, Gunter Bloeschl, David Hannah, Danny Marks, Juraj Parajka, Charles Pearson, Magdalena Rogger, Jose Luis. Salinas, Eric Sauquet, Sri Srikanthan, Sally Thompson and Alberto Viglione 7. Prediction of flow duration curves in ungauged basins Attilio Castellarin, Gianluca Botter, Denis A. Hughes, Suxia Liu, Taha B. M. J. Ouarda, Juraj Parajka, David Post, Murugesu Sivapalan, Christopher Spence, Alberto Viglione and Richard Vogel 8. Prediction of low flows in ungauged basins Gregor Laaha, Siegfried Demuth, Hege Hisdal, Charles N. Kroll, Henny A. J. van Lanen, Thomas Nester, Magdalena Rogger, Eric Sauquet, Lena M. Tallaksen, Ross Woods and Andy Young 9. Prediction of floods in ungauged basins Dan Rosbjerg, Gunter Bloeschl, Donald H. Burn, Attilio Castellarin, Barry Croke, Guliano Di Baldassarre, Vito Iacobellis, Thomas Kjeldsen, George Kuczera, Ralf Merz, Alberto Montanari, David Morris, Taha B. M. J. Ouarda, Liliang Ren, Magdalena Rogger, Jose Luis Salinas, Elena Toth and Alberto Viglione 10. Predictions of runoff hydrographs in ungauged basins Juraj Parajka, Vazken Andreassian, Stacey Archfield, Andras Bardossy, Francis Chiew, Qingyun Duan, Alexander Gelfan, Kamila Hlavcova, Ralf Merz, Neil McIntyre, Ludovic Oudin, Charles Perrin, Magdalena Rogger, Jose Luis Salinas, Hubert Savenije, Jon Olav Skoien, Thorsten Wagener, Erwin Zehe and Yongqiang Zhang 11. Case studies Hubert Savenije, Murugesu Sivapalan, Trent Biggs, Shaofeng Jia, Leonid M. Korytny, E.A.Ilyichyova, Boris Gartsman, John W. Pomeroy, Kevin Shook, Xing Fang, Tom Brown, Denis A. Hughes, Stacey Archfield, Jos Samuel, Paulin Coulibaly, Robert A. Metcalfe, Attilio Castellarin, Ralf Merz, Gunter Humer, Ataur Rahman, Khaled Haddad, Erwin Weinmann, George Kuczera, Theresa Blume, Armand Crabit, Francois Colin, Roger Moussa, Hessel Winsemius, Hubert Savenije, Jens Liebe, Nick van de Giesen, M. Todd Walter, Tammo S. Steenhuis, Jeffrey R. Kennedy, David Goodrich, Carl L. Unkrich, Dominic Mazvimavi, Neil R. Viney, Kuniyoshi Takeuchi, H. A. P. Hapuarachchi, Anthony S. Kiem, Hiroshi Ishidaira, Tianqi Ao, Jun Magome, Maichun C. Zhou, Mikhail Georgievski, Guoqiang Wang, Chihiro Yoshimura, Berit Arheimer, Goeran Lindstroem and Shijun Lin 12. Synthesis across processes, places and scales Hoshin V. Gupta, Gunter Bloeschl, Jeffrey McDonnell, Hubert Savenije, Murugesu Sivapalan, Alberto Viglione and Thorsten Wagener 13. Recommendations Kuniyoshi Takeuchi, Gunter. Bloeschl, Hubert Savenije, John Schaake, Murugesu Sivapalan, Alberto Viglione, Thorsten Wagener and Gordon Young Appendix: summary of studies used in the comparative assessments References Index.
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Delft University of Technology1, UNESCO-IHE Institute for Water Education2, Vienna University of Technology3, University of Saskatchewan4, University of Illinois at Urbana–Champaign5, Swedish Meteorological and Hydrological Institute6, National Center for Atmospheric Research7, Karlsruhe Institute of Technology8, University of Bristol9, Russian Academy of Sciences10, University of Arizona11, Rhodes University12, University of Bologna13, University of Aberdeen14, Agrocampus Ouest15
TL;DR: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS) launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23-25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power as discussed by the authors.
Abstract: The Prediction in Ungauged Basins (PUB) initiative of the International Association of Hydrological Sciences (IAHS), launched in 2003 and concluded by the PUB Symposium 2012 held in Delft (23–25 October 2012), set out to shift the scientific culture of hydrology towards improved scientific understanding of hydrological processes, as well as associated uncertainties and the development of models with increasing realism and predictive power. This paper reviews the work that has been done under the six science themes of the PUB Decade and outlines the challenges ahead for the hydrological sciences community.Editor D. KoutsoyiannisCitation Hrachowitz, M., Savenije, H.H.G., Bloschl, G., McDonnell, J.J., Sivapalan, M., Pomeroy, J.W., Arheimer, B., Blume, T., Clark, M.P., Ehret, U., Fenicia, F., Freer, J.E., Gelfan, A., Gupta, H.V., Hughes, D.A., Hut, R.W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P.A., Uhlenbrook, S., Wagener, T., Winsemius, H.C., Woods, R.A., Zehe, E., and Cudennec, C., 2013. A d...
848 citations
TL;DR: A review of the current state of scientific knowledge of definitions, processes, and quantification of hydrological drought is given in this paper, where the influence of climate and terrestrial properties (geology, land use) on hydrologic drought characteristics and the role of storage is discussed.
Abstract: Drought is a complex natural hazard that impacts ecosystems and society in many ways. Many of these impacts are associated with hydrological drought (drought in rivers, lakes, and groundwater). It is, therefore, crucial to understand the development and recovery of hydrological drought. In this review an overview is given of the current state of scientific knowledge of definitions, processes, and quantification of hydrological drought. Special attention is given to the influence of climate and terrestrial properties (geology, land use) on hydrological drought characteristics and the role of storage. Furthermore, the current debate about the use and usefulness of different drought indicators is highlighted and recent advances in drought monitoring and prediction are mentioned. Research on projections of hydrological drought for the future is summarized. This review also briefly touches upon the link of hydrological drought characteristics with impacts and the issues related to drought management. Finally, four challenges for future research on hydrological drought are defined that relate international initiatives such as the Intergovernmental Panel on Climate Change (IPCC) and the ‘Panta Rhei’ decade of the International Association of Hydrological Sciences (IAHS). WIREs Water 2015, 2:359–392. doi: 10.1002/wat2.1085
For further resources related to this article, please visit the WIREs website.
805 citations
TL;DR: In this paper, a novel data-driven approach, using the Long Short-Term Memory (LSTM) network, a special type of recurrent neural network, was proposed for modeling storage effects in e.g. catchments with snow influence.
Abstract: . Rainfall–runoff modelling is one of the key
challenges in the field of hydrology. Various approaches exist, ranging from
physically based over conceptual to fully data-driven models. In this paper,
we propose a novel data-driven approach, using the Long Short-Term Memory
(LSTM) network, a special type of recurrent neural network. The advantage of
the LSTM is its ability to learn long-term dependencies between the provided
input and output of the network, which are essential for modelling storage
effects in e.g. catchments with snow influence. We use 241 catchments of the
freely available CAMELS data set to test our approach and also compare the
results to the well-known Sacramento Soil Moisture Accounting Model (SAC-SMA)
coupled with the Snow-17 snow routine. We also show the potential of the LSTM
as a regional hydrological model in which one model predicts the discharge
for a variety of catchments. In our last experiment, we show the possibility
to transfer process understanding, learned at regional scale, to individual
catchments and thereby increasing model performance when compared to a LSTM
trained only on the data of single catchments. Using this approach, we were
able to achieve better model performance as the SAC-SMA + Snow-17, which
underlines the potential of the LSTM for hydrological modelling applications.
569 citations
TL;DR: The impact of climate change on karst aquifers has been studied in this article, where the authors explore different conceptual models and how they can be translated into numerical models of varying complexity and therefore varying data requirements.
Abstract: Karst regions represent 7–12% of the Earth's continental area, and about one quarter of the global population is completely or partially dependent on drinking water from karst aquifers. Climate simulations project a strong increase in temperature and a decrease of precipitation in many karst regions in the world over the next decades. Despite this potentially bleak future, few studies specifically quantify the impact of climate change on karst water resources. This review provides an introduction to karst, its evolution, and its particular hydrological processes. We explore different conceptual models of karst systems and how they can be translated into numerical models of varying complexity and therefore varying data requirements and depths of process representation. We discuss limitations of current karst models and show that at the present state, we face a challenge in terms of data availability and information content of the available data. We conclude by providing new research directions to develop and evaluate better prediction models to address the most challenging problems of karst water resources management, including opportunities for data collection and for karst model applications at so far unprecedented scales.
556 citations
University of Bologna1, Wilfrid Laurier University2, Delft University of Technology3, Rhodes University4, University of Bristol5, Hohai University6, National Technical University of Athens7, Agrocampus Ouest8, Tuscia University9, Vienna University of Technology10, University of Illinois at Urbana–Champaign11, Lancaster University12, Uppsala University13, University of Arizona14, University of Western Australia15, École Polytechnique Fédérale de Lausanne16, École nationale de l'aviation civile17, Swedish Meteorological and Hydrological Institute18, Roskilde University19, UNESCO-IHE Institute for Water Education20, Griffith University21, Pierre-and-Marie-Curie University22, Ruhr University Bochum23, Commonwealth Scientific and Industrial Research Organisation24, Johns Hopkins University25, University of California, Berkeley26, National Institute of Water and Atmospheric Research27, University of North Carolina at Chapel Hill28, Chinese Academy of Sciences29, University of the West Indies30, Moscow State University31
TL;DR: The Panta Rhei Everything Flows project as mentioned in this paper is dedicated to research activities on change in hydrology and society, which aims to reach an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems.
Abstract: The new Scientific Decade 2013-2022 of IAHS, entitled Panta RheiEverything Flows, is dedicated to research activities on change in hydrology and society. The purpose of Panta Rhei is to reach an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems. The practical aim is to improve our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment. The concept implies a focus on hydrological systems as a changing interface between environment and society, whose dynamics are essential to determine water security, human safety and development, and to set priorities for environmental management. The Scientific Decade 2013-2022 will devise innovative theoretical blueprints for the representation of processes including change and will focus on advanced monitoring and data analysis techniques. Interdisciplinarity will be sought by increased efforts to connect with the socio-economic sciences and geosciences in general. This paper presents a summary of the Science Plan of Panta Rhei, its targets, research questions and expected outcomes.
550 citations
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TL;DR: The IAHS Decade on Predictions in Ungauged Basins (PUB) as discussed by the authors is an initiative of the International Association of Hydrological Sciences (IAHS) to advance our ability to make reliable predictions in ungauged basins.
Abstract: The face of hydrologic science is changing rapidly, on national as well as on international scales.The increasing complexity of the problems hydrology is asked to investigate in research and practice today often requires solutions that can no longer be obtained by a single hydrologist, but require a multidisciplinary team. One consequence of this trend is the establishment of initiatives that help formulate and implement science programs to engage and energize the scientific community toward achieving major advances.
The IAHS Decade on Predictions in Ungauged Basins (PUB) is an initiative of the International Association of Hydrological Sciences (IAHS) [Sivapalan et al., 2003] to advance our ability to make reliable predictions in ungauged basins. Within PUB, the drainage basin (at various scales) is seen as the element that integrates all aspects of the hydrological cycle within a defined area that can be studied, quantified, and acted upon.
59 citations
"Runoff prediction in ungauged basin..." refers background in this paper
...The International Association of Hydrological Sciences Prediction in Ungauged Basins initiative [Wagener et al., 2004] has focused researchers and meetings on the topic, culminating in this book, which assembles the thoughts gathered over the last decade....
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