Articles | Volume 19, issue 1
https://doi.org/10.5194/hess-19-631-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-631-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Jan 2015
Research article |
| 30 Jan 2015
Assessing the impact of different sources of topographic data on 1-D hydraulic modelling of floods
A. Md Ali
CORRESPONDING AUTHOR
Department of Integrated Water System and Knowledge Management, UNESCO-IHE Institute for Water Education, Delft, the Netherlands
Department of Irrigation and Drainage, Kuala Lumpur, Malaysia
D. P. Solomatine
Department of Integrated Water System and Knowledge Management, UNESCO-IHE Institute for Water Education, Delft, the Netherlands
Water Resource Section, Delft University of Technology, the Netherlands
G. Di Baldassarre
Department of Earth Sciences, Uppsala University, Sweden
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Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Augusto Corzo, Dimitri Solomatine, and Emmanouil Varouchakis
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-98, https://doi.org/10.5194/hess-2023-98, 2023
Preprint under review for HESS
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In this research, we explored the use of machine learning (ML) to improve the S2S ensemble precipitation forecast, different approaches were used as exploratory experiments to see which approach is better addressing the improvement of the ensemble probabilistic forecast, as a conclusion of our research, we found that the concept of committee model (CM) is a promising approach that can be further studied and evaluated using a different combination of the state of the art ML techniques.
Ana Paez-Trujilo, Jeffer Cañon, Beatriz Hernandez, Gerald Corzo, and Dimitri Solomatine
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-50, https://doi.org/10.5194/nhess-2023-50, 2023
Revised manuscript accepted for NHESS
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This study uses a machine learning technique, the multivariate regression tree approach to asses the hydroclimatic characteristics that govern agricultural and hydrological drought severity. The results show that the employed technique successfully identified the primary drivers of droughts and their critical thresholds. In addition, it provides relevant information to identify the areas most vulnerable to droughts and design strategies and interventions for drought management.
Mohamed Elneel Elshaikh Eltayeb Elbasheer, Gerald Augusto Corzo, Dimitri Solomatine, and Emmanouil Varouchakis
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-348, https://doi.org/10.5194/hess-2022-348, 2022
Manuscript not accepted for further review
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In this research, we explored the use of machine learning (ML) to improve the ECMWF S2S ensemble precipitation forecast, different approaches were used as exploratory experiments to see which approach is better addressing the improvement of the ensemble probabilistic forecast, as a conclusion of our research, we found that the concept of committee model (CM) is a promising approach that can be further studied and evaluated using a different combination of the state of the art ML techniques.
Vitali Diaz, Ahmed A. A. Osman, Gerald A. Corzo Perez, Henny A. J. Van Lanen, Shreedhar Maskey, and Dimitri Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-252, https://doi.org/10.5194/hess-2022-252, 2022
Preprint withdrawn
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Drought impacts on crops can be assessed in terms of crop yield (CY) variation. The hypothesis is that the spatiotemporal change of drought area is a good input to predict CY. A step-by-step approach for predicting CY is built based on two types of machine learning models. Drought area was found suitable for predicting CY. Since it is currently possible to calculate drought areas within drought monitoring systems, the prediction of drought impacts can be integrated directly into them.
Vitali Diaz, Ahmed A. A. Osman, Gerald A. Corzo Perez, Henny A. J. Van Lanen, Shreedhar Maskey, and Dimitri Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-600, https://doi.org/10.5194/hess-2021-600, 2021
Preprint withdrawn
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Drought effects on crops are usually evaluated through crop yield (CY). The hypothesis is that the drought spatial extent is a good input to predict CY. A machine learning approach to predict crop yield is introduced. The use of drought area was found suitable. Since it is currently possible to calculate drought areas within drought monitoring systems, the direct application to predict drought effects can be integrated into them by following approaches such as the one presented or similar.
Giuliano Di Baldassarre, Elena Mondino, Maria Rusca, Emanuele Del Giudice, Johanna Mård, Elena Ridolfi, Anna Scolobig, and Elena Raffetti
Nat. Hazards Earth Syst. Sci., 21, 3439–3447, https://doi.org/10.5194/nhess-21-3439-2021, https://doi.org/10.5194/nhess-21-3439-2021, 2021
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COVID-19 has affected humankind in an unprecedented way, and it has changed how people perceive multiple risks. In this paper, we compare public risk perceptions in Italy and Sweden in two different phases of the pandemic. We found that people are more worried about risks related to recently experienced events. This finding is in line with the availability heuristic: individuals assess the risk associated with a given hazard based on how easily it comes to their mind.
Sara Lindersson, Luigia Brandimarte, Johanna Mård, and Giuliano Di Baldassarre
Nat. Hazards Earth Syst. Sci., 21, 2921–2948, https://doi.org/10.5194/nhess-21-2921-2021, https://doi.org/10.5194/nhess-21-2921-2021, 2021
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Riverine flood risk assessments require the identification of areas prone to potential flooding. We find that (topography-based) hydrogeomorphic floodplain maps can in many cases be useful for riverine flood risk assessments, particularly where hydrologic data are scarce. For 26 countries across the global south, we also demonstrate how dataset choice influences the estimated number of people living within flood-prone zones.
Elena Mondino, Anna Scolobig, Marco Borga, and Giuliano Di Baldassarre
Nat. Hazards Earth Syst. Sci., 21, 2811–2828, https://doi.org/10.5194/nhess-21-2811-2021, https://doi.org/10.5194/nhess-21-2811-2021, 2021
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Survey data collected over time can provide new insights on how different people respond to floods and can be used in models to study the complex coevolution of human–water systems. We present two methods to collect such data, and we compare the respective results. Risk awareness decreases only for women, while preparedness takes different trajectories depending on the damage suffered. These results support a more diverse representation of society in flood risk modelling and risk management.
Giuliano Di Baldassarre, Fernando Nardi, Antonio Annis, Vincent Odongo, Maria Rusca, and Salvatore Grimaldi
Nat. Hazards Earth Syst. Sci., 20, 1415–1419, https://doi.org/10.5194/nhess-20-1415-2020, https://doi.org/10.5194/nhess-20-1415-2020, 2020
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Global floodplain mapping has rapidly progressed over the past few years. Different methods have been proposed to identify areas prone to river flooding, resulting in a plethora of available products. Here we assess the potential and limitations of two main paradigms and provide guidance on the use of these global products in assessing flood risk in data-poor regions.
Shaokun He, Shenglian Guo, Chong-Yu Xu, Kebing Chen, Zhen Liao, Lele Deng, Huanhuan Ba, and Dimitri Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-586, https://doi.org/10.5194/hess-2019-586, 2020
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Aiming at cascade impoundment operation, we develop a classification-aggregation-decomposition method to overcome the
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Paolo De Luca, Gabriele Messori, Robert L. Wilby, Maurizio Mazzoleni, and Giuliano Di Baldassarre
Earth Syst. Dynam., 11, 251–266, https://doi.org/10.5194/esd-11-251-2020, https://doi.org/10.5194/esd-11-251-2020, 2020
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We show that floods and droughts can co-occur in time across remote regions on the globe and introduce metrics that can help in quantifying concurrent wet and dry hydrological extremes. We then link wet–dry extremes to major modes of climate variability (i.e. ENSO, PDO, and AMO) and provide their spatial patterns. Such concurrent extreme hydrological events may pose risks to regional hydropower production and agricultural yields.
Philippe Weyrich, Elena Mondino, Marco Borga, Giuliano Di Baldassarre, Anthony Patt, and Anna Scolobig
Nat. Hazards Earth Syst. Sci., 20, 287–298, https://doi.org/10.5194/nhess-20-287-2020, https://doi.org/10.5194/nhess-20-287-2020, 2020
Giuliano Di Baldassarre, Heidi Kreibich, Sergiy Vorogushyn, Jeroen Aerts, Karsten Arnbjerg-Nielsen, Marlies Barendrecht, Paul Bates, Marco Borga, Wouter Botzen, Philip Bubeck, Bruna De Marchi, Carmen Llasat, Maurizio Mazzoleni, Daniela Molinari, Elena Mondino, Johanna Mård, Olga Petrucci, Anna Scolobig, Alberto Viglione, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 5629–5637, https://doi.org/10.5194/hess-22-5629-2018, https://doi.org/10.5194/hess-22-5629-2018, 2018
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One common approach to cope with floods is the implementation of structural flood protection measures, such as levees. Numerous scholars have problematized this approach and shown that increasing levels of flood protection can generate a false sense of security and attract more people to the risky areas. We briefly review the literature on this topic and then propose a research agenda to explore the unintended consequences of structural flood protection.
Md Ruknul Ferdous, Anna Wesselink, Luigia Brandimarte, Kymo Slager, Margreet Zwarteveen, and Giuliano Di Baldassarre
Hydrol. Earth Syst. Sci., 22, 5159–5173, https://doi.org/10.5194/hess-22-5159-2018, https://doi.org/10.5194/hess-22-5159-2018, 2018
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Socio-hydrological space (SHS) is a concept that enriches the study of socio-hydrology because it helps understand the detailed human–water interactions in a specific location. The concept suggests that the interactions between society and water are place-bound because of differences in social processes and river dynamics. This would be useful for developing interventions under disaster management, but also other development goals. SHS provides a new way of looking at socio-hydrological systems.
David R. Casson, Micha Werner, Albrecht Weerts, and Dimitri Solomatine
Hydrol. Earth Syst. Sci., 22, 4685–4697, https://doi.org/10.5194/hess-22-4685-2018, https://doi.org/10.5194/hess-22-4685-2018, 2018
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In high-latitude (> 60° N) watersheds, measuring the snowpack and predicting of snowmelt runoff are uncertain due to the lack of data and complex physical processes. This provides challenges for hydrological assessment and operational water management. Global re-analysis datasets have great potential to aid in snowpack representation and snowmelt prediction when combined with a distributed hydrological model, though they still have clear limitations in remote boreal forest and tundra environments.
Alexander Gelfan, Vsevolod Moreydo, Yury Motovilov, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 22, 2073–2089, https://doi.org/10.5194/hess-22-2073-2018, https://doi.org/10.5194/hess-22-2073-2018, 2018
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We describe a forecasting procedure that is based on a semi-distributed hydrological model using two types of weather ensembles for the lead time period: observed weather data, constructed on the basis of the ESP methodology, and synthetic weather data, simulated by a weather generator. We compare the described methodology with the regression-based operational forecasts that are currently in practice and show the increased informational content of the ensemble-based forecasts.
Thaine H. Assumpção, Ioana Popescu, Andreja Jonoski, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 22, 1473–1489, https://doi.org/10.5194/hess-22-1473-2018, https://doi.org/10.5194/hess-22-1473-2018, 2018
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Citizens can contribute to science by providing data, analysing them and as such contributing to decision-making processes. For example, citizens have collected water levels from gauges, which are important when simulating/forecasting floods, where data are usually scarce. This study reviewed such contributions and concluded that integration of citizen data may not be easy due to their spatio-temporal characteristics but that citizen data still proved valuable and can be used in flood modelling.
Anqi Wang and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-78, https://doi.org/10.5194/hess-2018-78, 2018
Manuscript not accepted for further review
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This paper presents a brief review and classification of sensitivity analysis (SA) methods. Six different global SA methods: Sobol, FAST, Morris, LH-OAT, RSA and PAWN are tested on the three conceptual rainfall-runoff models with varying complexity: (GR4J, Hymod and HBV), with respect to effectiveness, efficiency and convergence. Practical framework of selecting and using the SA methods is presented, which may be of assistance for practitioners assessing reliability of their models.
Maurizio Mazzoleni, Vivian Juliette Cortes Arevalo, Uta Wehn, Leonardo Alfonso, Daniele Norbiato, Martina Monego, Michele Ferri, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 22, 391–416, https://doi.org/10.5194/hess-22-391-2018, https://doi.org/10.5194/hess-22-391-2018, 2018
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We investigate the usefulness of assimilating crowdsourced observations from a heterogeneous network of sensors for different scenarios of citizen involvement levels during the flood event occurred in the Bacchiglione catchment in May 2013. We achieve high model performance by integrating crowdsourced data, in particular from citizens motivated by their feeling of belonging to a community. Satisfactory model performance can still be obtained even for decreasing citizen involvement over time.
Omar Wani, Joost V. L. Beckers, Albrecht H. Weerts, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 4021–4036, https://doi.org/10.5194/hess-21-4021-2017, https://doi.org/10.5194/hess-21-4021-2017, 2017
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We generate uncertainty intervals for hydrologic model predictions using a simple instance-based learning scheme. Errors made by the model in some specific hydrometeorological conditions in the past are used to predict the probability distribution of its errors during forecasting. We test it for two different case studies in England. We find that this technique, even though conceptually simple and easy to implement, performs as well as some other sophisticated uncertainty estimation methods.
Diana Fuentes-Andino, Keith Beven, Sven Halldin, Chong-Yu Xu, José Eduardo Reynolds, and Giuliano Di Baldassarre
Hydrol. Earth Syst. Sci., 21, 3597–3618, https://doi.org/10.5194/hess-21-3597-2017, https://doi.org/10.5194/hess-21-3597-2017, 2017
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Reproduction of past floods requires information on discharge and flood extent, commonly unavailable or uncertain during extreme events. We explored the possibility of reproducing an extreme flood disaster using rainfall and post-event hydrometric information by combining a rainfall-runoff and hydraulic modelling tool within an uncertainty analysis framework. Considering the uncertainty in post–event data, it was possible to reasonably reproduce the extreme event.
Juan C. Chacon-Hurtado, Leonardo Alfonso, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 3071–3091, https://doi.org/10.5194/hess-21-3071-2017, https://doi.org/10.5194/hess-21-3071-2017, 2017
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This paper compiles most of the studies (as far as the authors are aware) on the design of sensor networks for measurement of precipitation and streamflow. The literature shows that there is no overall consensus on the methods for the evaluation of sensor networks, as different design criteria often lead to different solutions. This paper proposes a methodology for the classification of methods, and a general framework for the design of sensor networks.
Giuliano Di Baldassarre, Fabian Martinez, Zahra Kalantari, and Alberto Viglione
Earth Syst. Dynam., 8, 225–233, https://doi.org/10.5194/esd-8-225-2017, https://doi.org/10.5194/esd-8-225-2017, 2017
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There is still little understanding about the dynamics emerging from human–water interactions. As a result, policies and measures to reduce the impacts of floods and droughts often lead to unintended consequences. This paper proposes a research agenda to improve our understanding of human–water interactions, and presents an initial attempt to model the reciprocal effects between water management, droughts, and floods.
Maurizio Mazzoleni, Martin Verlaan, Leonardo Alfonso, Martina Monego, Daniele Norbiato, Miche Ferri, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 839–861, https://doi.org/10.5194/hess-21-839-2017, https://doi.org/10.5194/hess-21-839-2017, 2017
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This study assesses the potential use of crowdsourced data in hydrological modeling, which are characterized by irregular availability and variable accuracy. We show that even data with these characteristics can improve flood prediction if properly integrated into hydrological models. This study provides technological support to citizen observatories of water, in which citizens can play an active role in capturing information, leading to improved model forecasts and better flood management.
Giuliano Di Baldassarre, Smeralda Saccà, Giuseppe Tito Aronica, Salvatore Grimaldi, Alessio Ciullo, and Massimiliano Crisci
Adv. Geosci., 44, 9–13, https://doi.org/10.5194/adgeo-44-9-2017, https://doi.org/10.5194/adgeo-44-9-2017, 2017
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Throughout history, the city of Rome has experienced numerous flooding events from the Tiber river. Ancient Rome mostly developed on the hills, while the Tiber’s floodplain was mainly used for agricultural purposes. Instead, many people live nowadays in modern districts in the Tiber’s floodplain, often unaware of their exposure to potentially flooding. This research work aims to explore the dynamics of changing flood risk between these two opposite pictures of ancient and contemporary Rome.
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
N. Dogulu, P. López López, D. P. Solomatine, A. H. Weerts, and D. L. Shrestha
Hydrol. Earth Syst. Sci., 19, 3181–3201, https://doi.org/10.5194/hess-19-3181-2015, https://doi.org/10.5194/hess-19-3181-2015, 2015
P. López López, J. S. Verkade, A. H. Weerts, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 18, 3411–3428, https://doi.org/10.5194/hess-18-3411-2014, https://doi.org/10.5194/hess-18-3411-2014, 2014
U. Ehret, H. V. Gupta, M. Sivapalan, S. V. Weijs, S. J. Schymanski, G. Blöschl, A. N. Gelfan, C. Harman, A. Kleidon, T. A. Bogaard, D. Wang, T. Wagener, U. Scherer, E. Zehe, M. F. P. Bierkens, G. Di Baldassarre, J. Parajka, L. P. H. van Beek, A. van Griensven, M. C. Westhoff, and H. C. Winsemius
Hydrol. Earth Syst. Sci., 18, 649–671, https://doi.org/10.5194/hess-18-649-2014, https://doi.org/10.5194/hess-18-649-2014, 2014
N. Kayastha, J. Ye, F. Fenicia, V. Kuzmin, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 17, 4441–4451, https://doi.org/10.5194/hess-17-4441-2013, https://doi.org/10.5194/hess-17-4441-2013, 2013
G. Di Baldassarre, A. Viglione, G. Carr, L. Kuil, J. L. Salinas, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 3295–3303, https://doi.org/10.5194/hess-17-3295-2013, https://doi.org/10.5194/hess-17-3295-2013, 2013
M. B. Mabrouk, A. Jonoski, D. Solomatine, and S. Uhlenbrook
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-10873-2013, https://doi.org/10.5194/hessd-10-10873-2013, 2013
Revised manuscript not accepted
G. Di Baldassarre, M. Kooy, J. S. Kemerink, and L. Brandimarte
Hydrol. Earth Syst. Sci., 17, 3235–3244, https://doi.org/10.5194/hess-17-3235-2013, https://doi.org/10.5194/hess-17-3235-2013, 2013
Related subject area
Subject: Engineering Hydrology | Techniques and Approaches: Remote Sensing and GIS
Inundation analysis of metro systems with the storm water management model incorporated into a geographical information system: a case study in Shanghai
A method for parameterising roughness and topographic sub-grid scale effects in hydraulic modelling from LiDAR data
Hai-Min Lyu, Shui-Long Shen, Jun Yang, and Zhen-Yu Yin
Hydrol. Earth Syst. Sci., 23, 4293–4307, https://doi.org/10.5194/hess-23-4293-2019, https://doi.org/10.5194/hess-23-4293-2019, 2019
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This study presents an integrated approach to evaluate inundation risks, in which an algorithm is proposed to integrate the storm water management model (SWMM) into a geographical information system (GIS). The proposed algorithm simulates the flood inundation of overland flows and in metro stations for each designed scenario. It involves the following stages: (i) determination of the grid location and spreading coefficient and (ii) an iterative calculation of the spreading process.
A. Casas, S. N. Lane, D. Yu, and G. Benito
Hydrol. Earth Syst. Sci., 14, 1567–1579, https://doi.org/10.5194/hess-14-1567-2010, https://doi.org/10.5194/hess-14-1567-2010, 2010
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