Articles | Volume 386
https://doi.org/10.5194/piahs-386-41-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/piahs-386-41-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Performance analysis of physically-based (HEC-RAS, CADDIES) and AI-based (LSTM) flood models for two case studies
Marina Batalini de Macedo
CORRESPONDING AUTHOR
Natural Resources Institute, Federal University of Itajuba, Itajubá, Brazil
Nikunj K. Mangukiya
Department of Hydrology, Indian Institute of Technology Roorkee, Roorke, India
Maria Clara Fava
Institute of Exact and Technological Sciences, Federal University of Viçosa, Rio Paranaíba, Brazil
Ashutosh Sharma
CORRESPONDING AUTHOR
Department of Hydrology, Indian Institute of Technology Roorkee, Roorke, India
Roberto Fray da Silva
Institute of Advanced Studies, University of Sao Paulo, São Carlos, Brazil
Ankit Agarwal
Department of Hydrology, Indian Institute of Technology Roorkee, Roorke, India
Maria Tereza Razzolini
School of Public Health, University of Sao Paulo, São Paulo, Brazil
Eduardo Mario Mendiondo
Sao Carlos School of Engineering, Department of Hydraulics and Sanitation, University of Sao Paulo, São Carlos, Brazil
Narendra K. Goel
Department of Hydrology, Indian Institute of Technology Roorkee, Roorke, India
Mathew Kurian
Water-Energy-Food Nexus, Pennsylvania State University, State College, USA
Adelaide Cássia Nardocci
School of Public Health, University of Sao Paulo, São Paulo, Brazil
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Nat. Hazards Earth Syst. Sci., 24, 2165–2173, https://doi.org/10.5194/nhess-24-2165-2024, https://doi.org/10.5194/nhess-24-2165-2024, 2024
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With climate change, societies increasingly need to adapt to deal with more severe droughts and the impacts they can have on food production. To make better adaptation decisions, drought resilience indicators can be used. To build these indicators, surveys with experts can be done. However, designing surveys is a costly process that can influence how experts respond. In this communication, we aim to deal with the challenges encountered in the development of surveys to help further research.
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The Himalayan landscape is particularly susceptible to extreme events, which interfere with increasing populations and the expansion of settlements and infrastructure. This preface introduces and summarizes the nine papers that are part of the special issue,
Estimating and predicting natural hazards and vulnerabilities in the Himalayan region.
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey, Shailza Sharma, Vijaykumar Bejagam, Pradeep P. Mujumdar, and Ashutosh Sharma
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-379, https://doi.org/10.5194/essd-2024-379, 2024
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We introduce CAMELS-INDIA (Catchment Attributes and MEteorology for Large-sample Studies – India), which provides daily hydrometeorological time series and static catchment attributes representing location, topography, climate, hydrological signatures, land-use, land cover, soil, geology, and anthropogenic influences for 472 catchments in peninsular India, to foster large-sample hydrological studies in India and promote the inclusion of Indian catchments in global hydrological research.
Marina Batalini de Macedo, Marcos Roberto Benso, Karina Simone Sass, Eduardo Mario Mendiondo, Greicelene Jesus da Silva, Pedro Gustavo Câmara da Silva, Elisabeth Shrimpton, Tanaya Sarmah, Da Huo, Michael Jacobson, Abdullah Konak, Nazmiye Balta-Ozkan, and Adelaide Cassia Nardocci
Nat. Hazards Earth Syst. Sci., 24, 2165–2173, https://doi.org/10.5194/nhess-24-2165-2024, https://doi.org/10.5194/nhess-24-2165-2024, 2024
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With climate change, societies increasingly need to adapt to deal with more severe droughts and the impacts they can have on food production. To make better adaptation decisions, drought resilience indicators can be used. To build these indicators, surveys with experts can be done. However, designing surveys is a costly process that can influence how experts respond. In this communication, we aim to deal with the challenges encountered in the development of surveys to help further research.
Abderraman R. A. Brandão, Frederico C. M. de Menezes Filho, Paulo T. S. Oliveira, and Maria C. Fava
Proc. IAHS, 386, 81–86, https://doi.org/10.5194/piahs-386-81-2024, https://doi.org/10.5194/piahs-386-81-2024, 2024
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Flow simulation using artificial neural networks is widely used in modeling, particularly in data-scarce areas. Our study utilized MLP neural networks to predict urban runoff in flood-prone basin. Motivated by the vulnerability to floods, we input rainfall and previous runoff data. The model effectively captured basin dynamics, highlighting the impact of urbanization. This research supports urban river basin planning and aids in flood mitigation and adaptation strategies.
Gabriela C. Gesualdo, Marcos R. Benso, Fabrício A. R. Navarro, Luis M. Castillo, and Eduardo M. Mendiondo
Proc. IAHS, 385, 117–120, https://doi.org/10.5194/piahs-385-117-2024, https://doi.org/10.5194/piahs-385-117-2024, 2024
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We simulated indexed insurance for a water utility responsible for providing water to 7.2 million people in a metropolitan region. According to our findings, an annual amount (premium) of USD 0.43, 0.87, and 1.73 should be charged per person to obtain drought coverage for three, six, and twelve months. The premium fee can be implemented in the water bills as a new strategy to pool the risk between the supplied users and the utility, to prevent them from being exposed to surcharge fluctuations.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Gesualdo Chiquito, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, and Eduardo Mario Mendiondo
EGUsphere, https://doi.org/10.5194/egusphere-2023-3002, https://doi.org/10.5194/egusphere-2023-3002, 2024
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The production of food is susceptible to several climate hazards such as droughts, excessive rainfall, and heat waves. In this paper, we present a methodology that uses artificial intelligence for assessing the impact of climate risks on food production. Our methodology helps us to automatically select the most relevant indices and critical thresholds of these indices that when surpassed can increase the danger of crop yield loss.
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.
Marcos Roberto Benso, Gabriela Chiquito Gesualdo, Roberto Fray Silva, Greicelene Jesus Silva, Luis Miguel Castillo Rápalo, Fabricio Alonso Richmond Navarro, Patricia Angélica Alves Marques, José Antônio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 23, 1335–1354, https://doi.org/10.5194/nhess-23-1335-2023, https://doi.org/10.5194/nhess-23-1335-2023, 2023
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Ashish Shrestha, Felipe Augusto Arguello Souza, Samuel Park, Charlotte Cherry, Margaret Garcia, David J. Yu, and Eduardo Mario Mendiondo
Hydrol. Earth Syst. Sci., 26, 4893–4917, https://doi.org/10.5194/hess-26-4893-2022, https://doi.org/10.5194/hess-26-4893-2022, 2022
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Equitable sharing of benefits is key to successful cooperation in transboundary water resource management. However, external changes can shift the split of benefits and shifts in the preferences regarding how an actor’s benefits compare to the other’s benefits. To understand how these changes can impact the robustness of cooperative agreements, we develop a socio-hydrological system dynamics model of the benefit sharing provision of the Columbia River Treaty and assess a series of scenarios.
Abhishek Kashyap, Mukunda Dev Behera, Anand Kumar Pandey, and Ankit Agarwal
EGUsphere, https://doi.org/10.5194/egusphere-2022-533, https://doi.org/10.5194/egusphere-2022-533, 2022
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Bedrock landslides are currently spatially dispersed over a process of landscape evolution in the NW Himalayan river catchments. Our analysis indicates that the zones with slope range between 24–32°, topographic relief ranges between 800–1200 m, and elevation range between 1200–2400 m, are compatible with precipitation intensity ranges between 1500–3000 mm/year in the NW Himalayan river catchments, have the highest probability of frequently occurring landslides.
Pankaj R. Dhote, Joshal K. Bansal, Vaibhav Garg, Praveen K. Thakur, and Ankit Agarwal
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-101, https://doi.org/10.5194/nhess-2022-101, 2022
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In the present paper, we have developed framework to establish virtual stage-discharge gauging network in sparsely gauged basin using hydrodynamic modelling and satellite altimetry data. The publication of the work will provide more insights to hydraulic community dealing with flood hazard in sparsely gauged basins, on how to monitor extreme river flow events using remote sensing data at ungauged locations.
Ankit Agarwal, Norbert Marwan, Rathinasamy Maheswaran, Ugur Ozturk, Jürgen Kurths, and Bruno Merz
Hydrol. Earth Syst. Sci., 24, 2235–2251, https://doi.org/10.5194/hess-24-2235-2020, https://doi.org/10.5194/hess-24-2235-2020, 2020
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In the climate/hydrology network, each node represents a geographical location of climatological data, and links between nodes are set up based on their interaction or similar variability. Here, using network theory, we first generate a node-ranking measure and then prioritize the rain gauges to identify influential and expandable stations across Germany. To show the applicability of the proposed approach, we also compared the results with existing traditional and contemporary network measures.
Jürgen Kurths, Ankit Agarwal, Roopam Shukla, Norbert Marwan, Maheswaran Rathinasamy, Levke Caesar, Raghavan Krishnan, and Bruno Merz
Nonlin. Processes Geophys., 26, 251–266, https://doi.org/10.5194/npg-26-251-2019, https://doi.org/10.5194/npg-26-251-2019, 2019
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We examined the spatial diversity of Indian rainfall teleconnection at different timescales, first by identifying homogeneous communities and later by computing non-linear linkages between the identified communities (spatial regions) and dominant climatic patterns, represented by climatic indices such as El Nino–Southern Oscillation, Indian Ocean Dipole, North Atlantic Oscillation, Pacific Decadal Oscillation and Atlantic Multi-Decadal Oscillation.
Denise Taffarello, Raghavan Srinivasan, Guilherme Samprogna Mohor, João Luis Bittencourt Guimarães, Maria do Carmo Calijuri, and Eduardo Mario Mendiondo
Hydrol. Earth Syst. Sci., 22, 4699–4723, https://doi.org/10.5194/hess-22-4699-2018, https://doi.org/10.5194/hess-22-4699-2018, 2018
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This paper aims to compare freshwater quality scenarios under different land uses, related to ecosystem-based adaptation in subtropical headwaters. Using a spatially semi-distributed model, nitrate, total phosphorous loads and sediments yield were modeled in Brazilian catchments ranging from 7 to 1037 km2. In short, we proposed the new hydrologic services index as a composite metric comparing water pollution levels for reference catchments related to the grey water footprint and water yield.
Diego A. Guzmám, Guilherme S. Mohor, Denise Taffarello, and Eduardo M. Mendiondo
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-615, https://doi.org/10.5194/hess-2017-615, 2017
Manuscript not accepted for further review
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Climate variability and increasing water demands prioritize the need to implement planning strategies for urban water security. Within the context of managing the financial resilience, we have explored how to evaluate the water utility company economic profit losses to face the hydrological drought impacts. Thus, the main objective of this work is propose a methodology to integrate the coevolution of anthropogenic factors and climate, which directly influence water availability.
Cited articles
Barros, M. T., Conde, F., Andrioli, C. P., and Zambon, R. C.: Flood Forecasting System in a Mega City: Challenges and Results for the São Paulo Metropolitan Region, in: World Environmental and Water Resources Congress 2016, 10–19, https://doi.org/10.1061/9780784479889.002, 2016.
Batalini de Macedo, M., Fray da Silva, R., Fava, M. C., Sharma, A., K. Mangukiya, N., Sarmento Buarque, A. C., Razzolini, M. T., Mendiondo, E. M., Goel, N. K., Kurian, M., and Nardocci, A. C.: Modelling urban floods in megacities: a comparative bibliometric review of traditional physically based and artificial intelligence models, IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 June 2022, IAHS2022-687, https://doi.org/10.5194/iahs2022-687, 2022.
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Guidolin, M., Chen, A. S., Ghimire, B., Keedwell, E. C., Djordjević, S., and Savić, D. A.: A weighted cellular automata 2D inundation model for rapid flood analysis, Environ. Model. Softw., 84, 378–394, https://doi.org/10.1016/j.envsoft.2016.07.008, 2016.
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Mangukiya, N. K., Sharma, A., and Shen, C.: How to enhance hydrological predictions in hydrologically distinct watersheds of the Indian subcontinent?, Hydrol. Process., 37, e14936, https://doi.org/10.1002/hyp.14936, 2023.
Paulino, E.: Alagamento interdita trechos da Avenida Aricanduva, Mobilidade Sampa: Brazil, https://mobilidadesampa.com.br/2020/03/alagamento-interdita-trechos-da-avenida-aricanduva/ (last access: 1 January 2024), 2020.
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Short summary
More and more extreme rainfall causes flooding problems in cities and communities, affecting the health and well-being of the population, as well as causing damage to the economy. To help design actions aiming at reducing the impacts of these floods, computational models can be used to simulate their extent. However, there are different types of models currently available. In this study, we evaluated three different models, for a city in Brazil and a region in India, to guide the best use of it.
More and more extreme rainfall causes flooding problems in cities and communities, affecting the...