Articles | Volume 15, issue 9
https://doi.org/10.5194/hess-15-2979-2011
© Author(s) 2011. 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-15-2979-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Sep 2011
Research article |
| 26 Sep 2011
Discharge estimation combining flow routing and occasional measurements of velocity
G. Corato
Research Institute for Geo-hydrological Protection, National Research Council, via della Madonna Alta 126, 06128 Perugia, Italy
T. Moramarco
Research Institute for Geo-hydrological Protection, National Research Council, via della Madonna Alta 126, 06128 Perugia, Italy
T. Tucciarelli
Department of Civil, Environmental and Aerospace Engineering, University of Palermo, Italy, Viale delle Scienze, 90128 Palermo, Italy
Related subject area
Subject: Engineering Hydrology | Techniques and Approaches: Modelling approaches
Deep learning methods for flood mapping: a review of existing applications and future research directions
Extreme floods in Europe: going beyond observations using reforecast ensemble pooling
Hydroinformatics education – the Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training
Wetropolis extreme rainfall and flood demonstrator: from mathematical design to outreach
Technical note: The beneficial role of a natural permeable layer in slope stabilization by drainage trenches
Assessing the impacts of reservoirs on downstream flood frequency by coupling the effect of scheduling-related multivariate rainfall with an indicator of reservoir effects
Observation operators for assimilation of satellite observations in fluvial inundation forecasting
Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River
Inundation mapping based on reach-scale effective geometry
Effects of variability in probable maximum precipitation patterns on flood losses
The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data
A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction
Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset
Technical note: Design flood under hydrological uncertainty
Topography- and nightlight-based national flood risk assessment in Canada
Regime shifts in annual maximum rainfall across Australia – implications for intensity–frequency–duration (IFD) relationships
Performance evaluation of groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs
A continuous rainfall model based on vine copulas
Estimates of global dew collection potential on artificial surfaces
Climate changes of hydrometeorological and hydrological extremes in the Paute basin, Ecuadorean Andes
An assessment of the ability of Bartlett–Lewis type of rainfall models to reproduce drought statistics
Modeling root reinforcement using a root-failure Weibull survival function
Socio-hydrology: conceptualising human-flood interactions
Application of a model-based rainfall-runoff database as efficient tool for flood risk management
Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis
HydroViz: design and evaluation of a Web-based tool for improving hydrology education
Web 2.0 collaboration tool to support student research in hydrology – an opinion
SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach
Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application
Comment on "A praxis-oriented perspective of streamflow inference from stage observations – the method of Dottori et al. (2009) and the alternative of the Jones Formula, with the kinematic wave celerity computed on the looped rating curve" by Koussis (2009)
An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 26, 4345–4378, https://doi.org/10.5194/hess-26-4345-2022, https://doi.org/10.5194/hess-26-4345-2022, 2022
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Deep learning methods have been increasingly used in flood management to improve traditional techniques. While promising results have been obtained, our review shows significant challenges in building deep learning models that can (i) generalize across multiple scenarios, (ii) account for complex interactions, and (iii) perform probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in deep learning to flood mapping.
Manuela I. Brunner and Louise J. Slater
Hydrol. Earth Syst. Sci., 26, 469–482, https://doi.org/10.5194/hess-26-469-2022, https://doi.org/10.5194/hess-26-469-2022, 2022
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Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System to increase the sample size available to estimate the frequency of extreme flood events. We demonstrate that such ensemble pooling produces more robust estimates than observation-based estimates.
Thorsten Wagener, Dragan Savic, David Butler, Reza Ahmadian, Tom Arnot, Jonathan Dawes, Slobodan Djordjevic, Roger Falconer, Raziyeh Farmani, Debbie Ford, Jan Hofman, Zoran Kapelan, Shunqi Pan, and Ross Woods
Hydrol. Earth Syst. Sci., 25, 2721–2738, https://doi.org/10.5194/hess-25-2721-2021, https://doi.org/10.5194/hess-25-2721-2021, 2021
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How can we effectively train PhD candidates both (i) across different knowledge domains in water science and engineering and (ii) in computer science? To address this issue, the Water Informatics in Science and Engineering Centre for Doctoral Training (WISE CDT) offers a postgraduate programme that fosters enhanced levels of innovation and collaboration by training a cohort of engineers and scientists at the boundary of water informatics, science and engineering.
Onno Bokhove, Tiffany Hicks, Wout Zweers, and Thomas Kent
Hydrol. Earth Syst. Sci., 24, 2483–2503, https://doi.org/10.5194/hess-24-2483-2020, https://doi.org/10.5194/hess-24-2483-2020, 2020
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Wetropolis is a
table-topdemonstration model with extreme rainfall and flooding, including random rainfall, river flow, flood plains, an upland reservoir, a porous moor, and a city which can flood. It lets the viewer experience extreme rainfall and flood events in a physical model on reduced spatial and temporal scales with an event return period of 6.06 min rather than, say, 200 years. We disseminate its mathematical design and how it has been shown most prominently to over 500 flood victims.
Gianfranco Urciuoli, Luca Comegna, Marianna Pirone, and Luciano Picarelli
Hydrol. Earth Syst. Sci., 24, 1669–1676, https://doi.org/10.5194/hess-24-1669-2020, https://doi.org/10.5194/hess-24-1669-2020, 2020
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The aim of this paper is to demonstrate, through a numerical approach, that the presence of soil layers of higher permeability, a not unlikely condition in some deep landslides in clay, may be exploited to improve the efficiency of systems of drainage trenches for slope stabilization. The problem has been examined for the case that a unique pervious layer, parallel to the ground surface, is present at an elevation higher than the bottom of the trenches.
Bin Xiong, Lihua Xiong, Jun Xia, Chong-Yu Xu, Cong Jiang, and Tao Du
Hydrol. Earth Syst. Sci., 23, 4453–4470, https://doi.org/10.5194/hess-23-4453-2019, https://doi.org/10.5194/hess-23-4453-2019, 2019
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We develop a new indicator of reservoir effects, called the rainfall–reservoir composite index (RRCI). RRCI, coupled with the effects of static reservoir capacity and scheduling-related multivariate rainfall, has a better performance than the previous indicator in terms of explaining the variation in the downstream floods affected by reservoir operation. A covariate-based flood frequency analysis using RRCI can provide more reliable downstream flood risk estimation.
Elizabeth S. Cooper, Sarah L. Dance, Javier García-Pintado, Nancy K. Nichols, and Polly J. Smith
Hydrol. Earth Syst. Sci., 23, 2541–2559, https://doi.org/10.5194/hess-23-2541-2019, https://doi.org/10.5194/hess-23-2541-2019, 2019
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Flooding from rivers is a huge and costly problem worldwide. Computer simulations can help to warn people if and when they are likely to be affected by river floodwater, but such predictions are not always accurate or reliable. Information about flood extent from satellites can help to keep these forecasts on track. Here we investigate different ways of using information from satellite images and look at the effect on computer predictions. This will help to develop flood warning systems.
Bart van Osnabrugge, Remko Uijlenhoet, and Albrecht Weerts
Hydrol. Earth Syst. Sci., 23, 1453–1467, https://doi.org/10.5194/hess-23-1453-2019, https://doi.org/10.5194/hess-23-1453-2019, 2019
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A correct estimate of the amount of future precipitation is the most important factor in making a good streamflow forecast, but evaporation is also an important component that determines the discharge of a river. However, in this study for the Rhine River we found that evaporation forecasts only give an almost negligible improvement compared to methods that use statistical information on climatology for a 10-day streamflow forecast. This is important to guide research on low flow forecasts.
Cédric Rebolho, Vazken Andréassian, and Nicolas Le Moine
Hydrol. Earth Syst. Sci., 22, 5967–5985, https://doi.org/10.5194/hess-22-5967-2018, https://doi.org/10.5194/hess-22-5967-2018, 2018
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Inundation models are useful for hazard management and prevention. They are traditionally based on hydraulic partial differential equations (with satisfying results but large data and computational requirements). This study presents a simplified approach combining reach-scale geometric properties with steady uniform flow equations. The model shows promising results overall, although difficulties persist in the most complex urbanised reaches.
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
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We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Guillaume Le Bihan, Olivier Payrastre, Eric Gaume, David Moncoulon, and Frédéric Pons
Hydrol. Earth Syst. Sci., 21, 5911–5928, https://doi.org/10.5194/hess-21-5911-2017, https://doi.org/10.5194/hess-21-5911-2017, 2017
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This paper illustrates how an integrated flash flood monitoring (or forecasting) system may be designed to directly provide information on possibly flooded areas and associated impacts on a very detailed river network and over large territories. The approach is extensively tested in the regions of Alès and Draguignan, located in south-eastern France. Validation results are presented in terms of accuracy of the estimated flood extents and related impacts (based on insurance claim data).
Ashley Wright, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels
Hydrol. Earth Syst. Sci., 21, 3827–3838, https://doi.org/10.5194/hess-21-3827-2017, https://doi.org/10.5194/hess-21-3827-2017, 2017
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The accurate reduction of hydrologic model input data is an impediment towards understanding input uncertainty and model structural errors. This paper compares the ability of two transforms to reduce rainfall input data. The resultant transforms are compressed to varying extents and reconstructed before being evaluated with standard simulation performance summary metrics and descriptive statistics. It is concluded the discrete wavelet transform is most capable of preserving rainfall time series.
Ricardo Zubieta, Augusto Getirana, Jhan Carlo Espinoza, Waldo Lavado-Casimiro, and Luis Aragon
Hydrol. Earth Syst. Sci., 21, 3543–3555, https://doi.org/10.5194/hess-21-3543-2017, https://doi.org/10.5194/hess-21-3543-2017, 2017
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This paper indicates that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1 % and 15.7 %, respectively). Statistical analysis indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets for estimating observed streamflows in Andean–Amazonian regions (Ucayali Basin, southern regions of the Amazon Basin of Peru and Ecuador).
Anna Botto, Daniele Ganora, Pierluigi Claps, and Francesco Laio
Hydrol. Earth Syst. Sci., 21, 3353–3358, https://doi.org/10.5194/hess-21-3353-2017, https://doi.org/10.5194/hess-21-3353-2017, 2017
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The paper provides an easy-to-use implementation of the UNCODE framework, which allows one to estimate the design flood value by directly accounting for sample uncertainty. Other than a design tool, this methodology is also a practical way to quantify the value of data in the design process.
Amin Elshorbagy, Raja Bharath, Anchit Lakhanpal, Serena Ceola, Alberto Montanari, and Karl-Erich Lindenschmidt
Hydrol. Earth Syst. Sci., 21, 2219–2232, https://doi.org/10.5194/hess-21-2219-2017, https://doi.org/10.5194/hess-21-2219-2017, 2017
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Flood mapping is one of Canada's major national interests. This work presents a simple and effective method for large-scale flood hazard and risk mapping, applied in this study to Canada. Readily available data, such as remote sensing night-light data, topography, and stream network were used to create the maps.
D. C. Verdon-Kidd and A. S. Kiem
Hydrol. Earth Syst. Sci., 19, 4735–4746, https://doi.org/10.5194/hess-19-4735-2015, https://doi.org/10.5194/hess-19-4735-2015, 2015
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Rainfall intensity-frequency-duration (IFD) relationships are required for the design and planning of water supply and management systems around the world. Currently IFD information is based on the "stationary climate assumption". However, this paper provides evidence of regime shifts in annual maxima rainfall time series using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Importantly, current IFD relationships may under- or overestimate the design rainfall.
P. A. Marker, N. Foged, X. He, A. V. Christiansen, J. C. Refsgaard, E. Auken, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 19, 3875–3890, https://doi.org/10.5194/hess-19-3875-2015, https://doi.org/10.5194/hess-19-3875-2015, 2015
H. Vernieuwe, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, https://doi.org/10.5194/hess-19-2685-2015, 2015
H. Vuollekoski, M. Vogt, V. A. Sinclair, J. Duplissy, H. Järvinen, E.-M. Kyrö, R. Makkonen, T. Petäjä, N. L. Prisle, P. Räisänen, M. Sipilä, J. Ylhäisi, and M. Kulmala
Hydrol. Earth Syst. Sci., 19, 601–613, https://doi.org/10.5194/hess-19-601-2015, https://doi.org/10.5194/hess-19-601-2015, 2015
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The global potential for collecting usable water from dew on an
artificial collector sheet was investigated by utilising 34 years of
meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were
mostly below 0.1mm.
D. E. Mora, L. Campozano, F. Cisneros, G. Wyseure, and P. Willems
Hydrol. Earth Syst. Sci., 18, 631–648, https://doi.org/10.5194/hess-18-631-2014, https://doi.org/10.5194/hess-18-631-2014, 2014
M. T. Pham, W. J. Vanhaute, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 5167–5183, https://doi.org/10.5194/hess-17-5167-2013, https://doi.org/10.5194/hess-17-5167-2013, 2013
M. Schwarz, F. Giadrossich, and D. Cohen
Hydrol. Earth Syst. Sci., 17, 4367–4377, https://doi.org/10.5194/hess-17-4367-2013, https://doi.org/10.5194/hess-17-4367-2013, 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
L. Brocca, S. Liersch, F. Melone, T. Moramarco, and M. Volk
Hydrol. Earth Syst. Sci., 17, 3159–3169, https://doi.org/10.5194/hess-17-3159-2013, https://doi.org/10.5194/hess-17-3159-2013, 2013
T. A. McMahon, M. C. Peel, L. Lowe, R. Srikanthan, and T. R. McVicar
Hydrol. Earth Syst. Sci., 17, 1331–1363, https://doi.org/10.5194/hess-17-1331-2013, https://doi.org/10.5194/hess-17-1331-2013, 2013
E. Habib, Y. Ma, D. Williams, H. O. Sharif, and F. Hossain
Hydrol. Earth Syst. Sci., 16, 3767–3781, https://doi.org/10.5194/hess-16-3767-2012, https://doi.org/10.5194/hess-16-3767-2012, 2012
A. Pathirana, B. Gersonius, and M. Radhakrishnan
Hydrol. Earth Syst. Sci., 16, 2499–2509, https://doi.org/10.5194/hess-16-2499-2012, https://doi.org/10.5194/hess-16-2499-2012, 2012
K. X. Soulis and J. D. Valiantzas
Hydrol. Earth Syst. Sci., 16, 1001–1015, https://doi.org/10.5194/hess-16-1001-2012, https://doi.org/10.5194/hess-16-1001-2012, 2012
A. Elshorbagy, G. Corzo, S. Srinivasulu, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 14, 1943–1961, https://doi.org/10.5194/hess-14-1943-2010, https://doi.org/10.5194/hess-14-1943-2010, 2010
A. D. Koussis
Hydrol. Earth Syst. Sci., 14, 1093–1097, https://doi.org/10.5194/hess-14-1093-2010, https://doi.org/10.5194/hess-14-1093-2010, 2010
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Hydrol. Earth Syst. Sci., 13, 2221–2231, https://doi.org/10.5194/hess-13-2221-2009, https://doi.org/10.5194/hess-13-2221-2009, 2009
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