Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1559-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-21-1559-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
14 Mar 2017
Research article |
| 14 Mar 2017
Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling
Nadav Peleg
CORRESPONDING AUTHOR
ETH Zurich, Institute of Environmental Engineering, Hydrology and Water Resources Management, Zurich, Switzerland
Frank Blumensaat
Swiss Federal Institute of Aquatic Science and Technology, Eawag, Dübendorf, Switzerland
ETH Zurich, Institute of Environmental Engineering, Chairs of Urban Water Management, Zurich, Switzerland
Peter Molnar
ETH Zurich, Institute of Environmental Engineering, Hydrology and Water Resources Management, Zurich, Switzerland
Simone Fatichi
ETH Zurich, Institute of Environmental Engineering, Hydrology and Water Resources Management, Zurich, Switzerland
Paolo Burlando
ETH Zurich, Institute of Environmental Engineering, Hydrology and Water Resources Management, Zurich, Switzerland
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Anna Costa, Daniela Anghileri, and Peter Molnar
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Hydrologic modeling methodologies must be developed that are capable of predicting runoff in catchments with changing land cover conditions. This article investigates the efficacy of a recently developed approach that allows for runoff prediction in catchments with unknown land cover changes, through experimentation in a deforested catchment in Vietnam. The importance of key elements of the method in ensuring its success, such as the chosen hydrologic model, is investigated.
Anna Costa, Peter Molnar, Laura Stutenbecker, Maarten Bakker, Tiago A. Silva, Fritz Schlunegger, Stuart N. Lane, Jean-Luc Loizeau, and Stéphanie Girardclos
Hydrol. Earth Syst. Sci., 22, 509–528, https://doi.org/10.5194/hess-22-509-2018, https://doi.org/10.5194/hess-22-509-2018, 2018
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We explore the signal of a warmer climate in the suspended-sediment dynamics of a regulated and human-impacted Alpine catchment. We demonstrate that temperature-driven enhanced melting of glaciers, which occurred in the mid-1980s, played a dominant role in suspended sediment concentration rise, through increased runoff from sediment-rich proglacial areas, increased contribution of sediment-rich meltwater, and increased sediment supply in proglacial areas due to glacier recession.
Anna Costa, Daniela Anghileri, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-419, https://doi.org/10.5194/hess-2017-419, 2017
Manuscript not accepted for further review
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We develop a novel rating curve to simulate suspended sediment concentration (SSC) in Alpine catchments (Process-Based Rating Curve, PBRC). Instead of relating SSC to discharge, as in traditional approaches, we model SSC by differentiating the potential contributions of the main erosional and transport processes of Alpine environments: erosive rainfall, snowmelt, and icemelt. We show that PBRC significantly improves predictions of SSC, especially when analysing climate-induced changes.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
Søren Thorndahl, Thomas Einfalt, Patrick Willems, Jesper Ellerbæk Nielsen, Marie-Claire ten Veldhuis, Karsten Arnbjerg-Nielsen, Michael R. Rasmussen, and Peter Molnar
Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, https://doi.org/10.5194/hess-21-1359-2017, 2017
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This paper reviews how weather radar data can be used in urban hydrological applications. It focuses on three areas of research: (1) temporal and spatial resolution of rainfall data, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Moreover, the paper provides examples of urban hydrological applications which can benefit from radar rainfall data in comparison to tradition rain gauge measurements of rainfall.
Claudio I. Meier, Jorge Sebastián Moraga, Geri Pranzini, and Peter Molnar
Hydrol. Earth Syst. Sci., 20, 4177–4190, https://doi.org/10.5194/hess-20-4177-2016, https://doi.org/10.5194/hess-20-4177-2016, 2016
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We show that the derived distribution approach is able to characterize the interannual variability of precipitation much better than fitting a probabilistic model to annual rainfall totals, as long as continuously gauged data are available. The method is a useful tool for describing temporal changes in the distribution of annual rainfall, as it works for records as short as 5 years, and therefore does not require any stationarity assumption over long periods.
Bahareh Kianfar, Simone Fatichi, Athansios Paschalis, Max Maurer, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-536, https://doi.org/10.5194/hess-2016-536, 2016
Revised manuscript has not been submitted
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Raingauge observations show a large variability in extreme rainfall depths in the current climate. Climate model predictions of extreme rainfall in the future have to be compared with this natural variability. Our work shows that predictions of future extreme rainfall often lie within the range of natural variability of present-day climate, and therefore predictions of change are highly uncertain. We demonstrate this by using stochastic rainfall models and 10-min rainfall data in Switzerland.
Matteo Saletti, Peter Molnar, Marwan A. Hassan, and Paolo Burlando
Earth Surf. Dynam., 4, 549–566, https://doi.org/10.5194/esurf-4-549-2016, https://doi.org/10.5194/esurf-4-549-2016, 2016
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This study presents a new reduced-complexity model with few parameters linked to basic physical processes, which aims to reproduce the transport of sediment as bed load and the formation and stability of channel morphology in steep mountain streams. The model is able to simulate the formation and stability of steps, bed structures commonly encountered in steep channels, by assuming that their formation is due to intense sediment transport during high flows causing jamming of particles.
P. Tokarczyk, J. P. Leitao, J. Rieckermann, K. Schindler, and F. Blumensaat
Hydrol. Earth Syst. Sci., 19, 4215–4228, https://doi.org/10.5194/hess-19-4215-2015, https://doi.org/10.5194/hess-19-4215-2015, 2015
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We investigate for the first time the possibility of deriving high-resolution imperviousness maps for urban areas from UAV imagery and using this information as input for urban drainage models. We show that imperviousness maps generated using UAV imagery processed with modern classification methods achieve accuracy comparable with standard, off-the-shelf aerial imagery. We conclude that UAV imagery represents a valuable alternative data source for urban drainage model applications.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
N. Peleg, E. Shamir, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 19, 567–581, https://doi.org/10.5194/hess-19-567-2015, https://doi.org/10.5194/hess-19-567-2015, 2015
K. Džubáková, P. Molnar, K. Schindler, and M. Trizna
Hydrol. Earth Syst. Sci., 19, 195–208, https://doi.org/10.5194/hess-19-195-2015, https://doi.org/10.5194/hess-19-195-2015, 2015
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We use a high-resolution ground-based camera system with near-infrared sensitivity to quantify the response of riparian vegetation in an Alpine river to floods with the use of vegetation indices. The vegetation showed both damage and enhancement within 1 week following floods, with a selective impact determined by pre-flood vegetation vigour, morphological setting and intensity of flood forcing. The tested vegetation indices differed in the direction of predicted change in the range 0.7-35.8%.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
L. Gaál, P. Molnar, and J. Szolgay
Hydrol. Earth Syst. Sci., 18, 1561–1573, https://doi.org/10.5194/hess-18-1561-2014, https://doi.org/10.5194/hess-18-1561-2014, 2014
T. Grünewald, J. Stötter, J. W. Pomeroy, R. Dadic, I. Moreno Baños, J. Marturià, M. Spross, C. Hopkinson, P. Burlando, and M. Lehning
Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, https://doi.org/10.5194/hess-17-3005-2013, 2013
N. Peleg, M. Ben-Asher, and E. Morin
Hydrol. Earth Syst. Sci., 17, 2195–2208, https://doi.org/10.5194/hess-17-2195-2013, https://doi.org/10.5194/hess-17-2195-2013, 2013
S. Fatichi, S. Rimkus, P. Burlando, R. Bordoy, and P. Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3743-2013, https://doi.org/10.5194/hessd-10-3743-2013, 2013
Revised manuscript not accepted
Related subject area
Subject: Urban Hydrology | Techniques and Approaches: Stochastic approaches
Improving radar-based rainfall nowcasting by a nearest-neighbour approach – Part 1: Storm characteristics
The role of storm scale, position and movement in controlling urban flood response
Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series
Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times
Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?
Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator
Stochastic rainfall analysis for storm tank performance evaluation
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 26, 1631–1658, https://doi.org/10.5194/hess-26-1631-2022, https://doi.org/10.5194/hess-26-1631-2022, 2022
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In this paper we investigate whether similar storms behave similarly and whether the information obtained from past similar storms can improve storm nowcast based on radar data. Here a nearest-neighbour approach is employed to first identify similar storms and later to issue either a single or an ensemble nowcast based on k most similar past storms. The results indicate that the information obtained from similar storms can reduce the errors considerably, especially for convective storm nowcast.
Marie-Claire ten Veldhuis, Zhengzheng Zhou, Long Yang, Shuguang Liu, and James Smith
Hydrol. Earth Syst. Sci., 22, 417–436, https://doi.org/10.5194/hess-22-417-2018, https://doi.org/10.5194/hess-22-417-2018, 2018
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The effect of storm scale and movement on runoff flows in urban catchments remains poorly understood due to the complexity of urban land use and man-made infrastructure. In this study, interactions among rainfall, urbanisation and peak flows were analyzed based on 15 years of radar rainfall and flow observations. We found that flow-path networks strongly smoothed rainfall peaks. Unexpectedly, the storm position relative to impervious cover within the basins had little effect on flow peaks.
Søren Thorndahl, Aske Korup Andersen, and Anders Badsberg Larsen
Hydrol. Earth Syst. Sci., 21, 4433–4448, https://doi.org/10.5194/hess-21-4433-2017, https://doi.org/10.5194/hess-21-4433-2017, 2017
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Time series of rainfall are developed in order to represent future climate conditions. These series can be used in design of, for example, drainage systems where future rainfall loads are important to account for. The climate projections are evaluated on a number of key statistical parameters of rainfall such as yearly and seasonal precipitation amounts, number of extreme events and rainfall intensities, specific duration, and return periods.
Marie-Claire ten Veldhuis and Marc Schleiss
Hydrol. Earth Syst. Sci., 21, 1991–2013, https://doi.org/10.5194/hess-21-1991-2017, https://doi.org/10.5194/hess-21-1991-2017, 2017
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In this paper we analysed flow measurements from 17 watersheds in a (semi-)urban region, to characterise flow patterns according to basin features. Instead of sampling flows at fixed time intervals, we looked at how fast given amounts of flow were accumulated. By doing so, we could identify patterns of flow regulation in urban streams and quantify flashiness of hydrological response. We were able to show that in this region, higher urbanisation was clearly associated with lower basin flashiness.
Hossein Tabari, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Sajjad Saeed, Erwan Brisson, Nicole Van Lipzig, and Patrick Willems
Hydrol. Earth Syst. Sci., 20, 3843–3857, https://doi.org/10.5194/hess-20-3843-2016, https://doi.org/10.5194/hess-20-3843-2016, 2016
Hjalte Jomo Danielsen Sørup, Ole Bøssing Christensen, Karsten Arnbjerg-Nielsen, and Peter Steen Mikkelsen
Hydrol. Earth Syst. Sci., 20, 1387–1403, https://doi.org/10.5194/hess-20-1387-2016, https://doi.org/10.5194/hess-20-1387-2016, 2016
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Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological models to assess performance issues under all possible conditions. In the present study synthetic data at very fine spatial and temporal resolution are generated using a stochastic model. Data are generated for both present and future climate conditions. The results show that it is possible to generate spatially distributed data at resolutions relevant for urban hydrology.
I. Andrés-Doménech, A. Montanari, and J. B. Marco
Hydrol. Earth Syst. Sci., 14, 1221–1232, https://doi.org/10.5194/hess-14-1221-2010, https://doi.org/10.5194/hess-14-1221-2010, 2010
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Short summary
We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
We investigated the relative contribution of the spatial versus climatic rainfall variability...
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