Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3859-2017
© 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-21-3859-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Review article
| 
28 Jul 2017
Review article |
| 28 Jul 2017
Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review
Department of Water Management, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
Marie-Claire ten Veldhuis
Department of Water Management, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
Nick van de Giesen
Department of Water Management, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
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Elena Cristiano, Marie-Claire ten Veldhuis, Santiago Gaitan, Susana Ochoa Rodriguez, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 22, 2425–2447, https://doi.org/10.5194/hess-22-2425-2018, https://doi.org/10.5194/hess-22-2425-2018, 2018
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In this work we investigate the influence rainfall and catchment scales have on hydrological response. This problem is quite relevant in urban areas, where the response is fast due to the high degree of imperviousness. We presented a new approach to classify rainfall variability in space and time and use this classification to investigate rainfall aggregation effects on urban hydrological response. This classification allows the spatial extension of the main core of the storm to be identified.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-260, https://doi.org/10.5194/hess-2024-260, 2024
Preprint under review for HESS
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This research examines how future climate changes impact root zone storage, a crucial hydrological model parameter. Root zone storage—the soil water accessible to plants—adapts to climate but is often treated as constant in models. We estimated climate-adapted storage for six Austrian Alps catchments. Although storage increased, streamflow projections showed minimal change, indicating that dynamic root zone representation is less critical in humid regions but warrants more study in arid areas.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Jessica A. Eisma, Gerrit Schoups, Jeffrey C. Davids, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 27, 3565–3579, https://doi.org/10.5194/hess-27-3565-2023, https://doi.org/10.5194/hess-27-3565-2023, 2023
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Citizen scientists often submit high-quality data, but a robust method for assessing data quality is needed. This study develops a semi-automated program that characterizes the mistakes made by citizen scientists by grouping them into communities of citizen scientists with similar mistake tendencies and flags potentially erroneous data for further review. This work may help citizen science programs assess the quality of their data and can inform training practices.
Cynthia Maan, Marie-Claire ten Veldhuis, and Bas J. H. van de Wiel
Hydrol. Earth Syst. Sci., 27, 2341–2355, https://doi.org/10.5194/hess-27-2341-2023, https://doi.org/10.5194/hess-27-2341-2023, 2023
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Their flexible growth provides the plants with a strong ability to adapt and develop resilience to droughts and climate change. But this adaptability is badly included in crop and climate models. To model plant development in changing environments, we need to include the survival strategies of plants. Based on experimental data, we set up a simple model for soil-moisture-driven root growth. The model performance suggests that soil moisture is a key parameter determining root growth.
Jerom P.M. Aerts, Jannis M. Hoch, Gemma Coxon, Nick C. van de Giesen, and Rolf W. Hut
EGUsphere, https://doi.org/10.5194/egusphere-2023-1156, https://doi.org/10.5194/egusphere-2023-1156, 2023
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Hydrological model performance involves comparing simulated states and fluxes with observed counterparts. Often, it is overlooked that there is inherent uncertainty surrounding the observations. This can significantly impact the results. In this publication, we emphasize the significance of accounting for observation uncertainty in model comparison. We propose a practical method that is applicable for any observational time series with available uncertainty estimations.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Bart Schilperoort, Nick van de Giesen, Imasiku Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 1695–1722, https://doi.org/10.5194/hess-27-1695-2023, https://doi.org/10.5194/hess-27-1695-2023, 2023
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Miombo woodland plants continue to lose water even during the driest part of the year. This appears to be facilitated by the adapted features such as deep rooting (beyond 5 m) with access to deep soil moisture, potentially even ground water. It appears the trend and amount of water that the plants lose is correlated more to the available energy. This loss of water in the dry season by miombo woodland plants appears to be incorrectly captured by satellite-based evaporation estimates.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022, https://doi.org/10.5194/hess-26-4407-2022, 2022
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In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
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With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Petra Hulsman, Nick van de Giesen, Imasiku Nyambe, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-114, https://doi.org/10.5194/hess-2022-114, 2022
Manuscript not accepted for further review
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We compare performance of evaporation models in the Luangwa Basin located in a semi-arid and complex Miombo ecosystem in Africa. Miombo plants changes colour, drop off leaves and acquire new leaves during the dry season. In addition, the plant roots go deep in the soil and appear to access groundwater. Results show that evaporation models with structure and process that do not capture this unique plant structure and behaviour appears to have difficulties to correctly estimating evaporation.
Paul C. Vermunt, Susan C. Steele-Dunne, Saeed Khabbazan, Jasmeet Judge, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 26, 1223–1241, https://doi.org/10.5194/hess-26-1223-2022, https://doi.org/10.5194/hess-26-1223-2022, 2022
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This study investigates the use of hydrometeorological sensors to reconstruct variations in internal vegetation water content of corn and relates these variations to the sub-daily behaviour of polarimetric L-band backscatter. The results show significant sensitivity of backscatter to the daily cycles of vegetation water content and dew, particularly on dry days and for vertical and cross-polarizations, which demonstrates the potential for using radar for studies on vegetation water dynamics.
Punpim Puttaraksa Mapiam, Monton Methaprayun, Thom Bogaard, Gerrit Schoups, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 26, 775–794, https://doi.org/10.5194/hess-26-775-2022, https://doi.org/10.5194/hess-26-775-2022, 2022
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The density of rain gauge networks plays an important role in radar rainfall bias correction. In this work, we aimed to assess the extent to which daily rainfall observations from a dense network of citizen scientists improve the accuracy of hourly radar rainfall estimates in the Tubma Basin, Thailand. Results show that citizen rain gauges significantly enhance the performance of radar rainfall bias adjustment up to a range of about 40 km from the center of the citizen rain gauge network.
Vassilis Aschonitis, Dimos Touloumidis, Marie-Claire ten Veldhuis, and Miriam Coenders-Gerrits
Earth Syst. Sci. Data, 14, 163–177, https://doi.org/10.5194/essd-14-163-2022, https://doi.org/10.5194/essd-14-163-2022, 2022
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This work provides a global database of correction coefficients for improving the performance of the temperature-based Thornthwaite potential evapotranspiration formula and aridity indices (e.g., UNEP, Thornthwaite) that make use of this formula. The coefficients were produced using as a benchmark the ASCE-standardized reference evapotranspiration formula (formerly FAO-56) that requires temperature, solar radiation, wind speed, and relative humidity data.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Didier de Villiers, Marc Schleiss, Marie-Claire ten Veldhuis, Rolf Hut, and Nick van de Giesen
Atmos. Meas. Tech., 14, 5607–5623, https://doi.org/10.5194/amt-14-5607-2021, https://doi.org/10.5194/amt-14-5607-2021, 2021
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Ground-based rainfall observations across the African continent are sparse. We present a new and inexpensive rainfall measuring instrument (the intervalometer) and use it to derive reasonably accurate rainfall rates. These are dependent on a fundamental assumption that is widely used in parameterisations of the rain drop size distribution. This assumption is tested and found to not apply for most raindrops but is still useful in deriving rainfall rates. The intervalometer shows good potential.
Moctar Dembélé, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz
Hydrol. Earth Syst. Sci., 24, 5379–5406, https://doi.org/10.5194/hess-24-5379-2020, https://doi.org/10.5194/hess-24-5379-2020, 2020
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This study evaluates 102 combinations of rainfall and temperature datasets from satellite and reanalysis sources as input to a fully distributed hydrological model. The model is recalibrated for each input dataset, and the outputs are evaluated with streamflow, evaporation, soil moisture and terrestrial water storage data. Results show that no single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes.
Justus G. V. van Ramshorst, Miriam Coenders-Gerrits, Bart Schilperoort, Bas J. H. van de Wiel, Jonathan G. Izett, John S. Selker, Chad W. Higgins, Hubert H. G. Savenije, and Nick C. van de Giesen
Atmos. Meas. Tech., 13, 5423–5439, https://doi.org/10.5194/amt-13-5423-2020, https://doi.org/10.5194/amt-13-5423-2020, 2020
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In this work we present experimental results of a novel actively heated fiber-optic (AHFO) observational wind-probing technique. We utilized a controlled wind-tunnel setup to assess both the accuracy and precision of AHFO under a range of operational conditions (wind speed, angles of attack and temperature differences). AHFO has the potential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scale processes.
Jeffrey C. Davids, Martine M. Rutten, Anusha Pandey, Nischal Devkota, Wessel David van Oyen, Rajaram Prajapati, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 23, 1045–1065, https://doi.org/10.5194/hess-23-1045-2019, https://doi.org/10.5194/hess-23-1045-2019, 2019
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Wise management of water resources requires data. Nevertheless, the amount of water data being collected continues to decline. We evaluated potential citizen science approaches for measuring flows of headwater streams and springs. After selecting salt dilution as the preferred approach, we partnered with Nepali students to cost-effectively measure flows and water quality with smartphones at 264 springs and streams which provide crucial water supplies to the rapidly expanding Kathmandu Valley.
Tim van Emmerik, Susan Steele-Dunne, Pierre Gentine, Rafael S. Oliveira, Paulo Bittencourt, Fernanda Barros, and Nick van de Giesen
Biogeosciences, 15, 6439–6449, https://doi.org/10.5194/bg-15-6439-2018, https://doi.org/10.5194/bg-15-6439-2018, 2018
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Trees are very important for the water and carbon cycles. Climate and weather models often assume constant vegetation parameters because good measurements are missing. We used affordable accelerometers to measure tree sway of 19 trees in the Amazon rainforest. We show that trees respond very differently to the same weather conditions, which means that vegetation parameters are dynamic. With our measurements trees can be accounted for more realistically, improving climate and weather models.
Elena Cristiano, Marie-Claire ten Veldhuis, Santiago Gaitan, Susana Ochoa Rodriguez, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 22, 2425–2447, https://doi.org/10.5194/hess-22-2425-2018, https://doi.org/10.5194/hess-22-2425-2018, 2018
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In this work we investigate the influence rainfall and catchment scales have on hydrological response. This problem is quite relevant in urban areas, where the response is fast due to the high degree of imperviousness. We presented a new approach to classify rainfall variability in space and time and use this classification to investigate rainfall aggregation effects on urban hydrological response. This classification allows the spatial extension of the main core of the storm to be identified.
Koen Hilgersom, Marcel Zijlema, and Nick van de Giesen
Geosci. Model Dev., 11, 521–540, https://doi.org/10.5194/gmd-11-521-2018, https://doi.org/10.5194/gmd-11-521-2018, 2018
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This study models the local inflow of groundwater at the bottom of a stream with large density gradients between the groundwater and surface water. Modelling salt and heat transport in a water body is very challenging, as it requires large computation times. Due to the circular local groundwater inflow and a negligible stream discharge, we assume axisymmetry around the inflow, which is easily implemented in an existing model, largely reduces the computation times, and still performs accurately.
Hubertus M. Coerver, Martine M. Rutten, and Nick C. van de Giesen
Hydrol. Earth Syst. Sci., 22, 831–851, https://doi.org/10.5194/hess-22-831-2018, https://doi.org/10.5194/hess-22-831-2018, 2018
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Global hydrological models aim to model hydrological processes, like flows in a river, on a global scale, as opposed to traditional models which are regional. A big challenge in creating these models is the inclusion of impacts on the hydrological cycle caused by humans, for example by the operation of large (hydropower) dams. The presented study investigates a new way to include these impacts by dams into global hydrological models.
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.
Christian Bouwens, Marie-Claire ten Veldhuis, Marc Schleiss, Xin Tian, and Jerôme Schepers
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-751, https://doi.org/10.5194/hess-2017-751, 2018
Revised manuscript not accepted
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Urban drainage systems are challenged by both urbanization and climate change, intensifying flooding impacts by rainfall. We performed this study to better understand and predict this process. The paper provides an approach to analyze the functioning of an urban drainage system without the need to run hydrodynamic models. Rainfall thresholds for urban flood prediction were derived, which surprisingly are only approximately half of the theoretical drainage system design capacity.
Abdellah Ichiba, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, Philippe Bompard, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 22, 331–350, https://doi.org/10.5194/hess-22-331-2018, https://doi.org/10.5194/hess-22-331-2018, 2018
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This paper proposes a two-step investigation to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependency observed within GIS data inputted in urban hydrological models. Then an intensive multi-scale modelling work was carried out to confirm effects on model performances. The model was implemented at 17 spatial resolutions ranging from 100 to 5 m. Results allow the understanding of scale challenges in hydrology modelling.
Natalie C. Ceperley, Theophile Mande, Nick van de Giesen, Scott Tyler, Hamma Yacouba, and Marc B. Parlange
Hydrol. Earth Syst. Sci., 21, 4149–4167, https://doi.org/10.5194/hess-21-4149-2017, https://doi.org/10.5194/hess-21-4149-2017, 2017
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We relate land cover (savanna forest and agriculture) to evaporation in Burkina Faso, west Africa. We observe more evaporation and temperature movement over the savanna forest in the headwater area relative to the agricultural section of the watershed. We find that the fraction of available energy converted to evaporation relates to vegetation cover and soil moisture. From the results, evaporation can be calculated where ground-based measurements are lacking, frequently the case across Africa.
Matthieu Spekkers, Viktor Rözer, Annegret Thieken, Marie-Claire ten Veldhuis, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 17, 1337–1355, https://doi.org/10.5194/nhess-17-1337-2017, https://doi.org/10.5194/nhess-17-1337-2017, 2017
Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, Susana Ochoa-Rodriguez, Patrick Willems, Abdellah Ichiba, Li-Pen Wang, Rui Pina, Johan Van Assel, Guendalina Bruni, Damian Murla Tuyls, and Marie-Claire ten Veldhuis
Hydrol. Earth Syst. Sci., 21, 2361–2375, https://doi.org/10.5194/hess-21-2361-2017, https://doi.org/10.5194/hess-21-2361-2017, 2017
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Data from 10 urban or peri-urban catchments located in five EU countries are used to analyze the imperviousness distribution and sewer network geometry. Consistent scale invariant features are retrieved for both (fractal dimensions can be defined), which enables to define a level of urbanization. Imperviousness representation in operational model is also found to exhibit scale-invariant features (even multifractality). The research was carried out as part of the UE INTERREG IV RainGain project.
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.
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.
Rolf Hut, Niels Drost, Maarten van Meersbergen, Edwin Sutanudjaja, Marc Bierkens, and Nick van de Giesen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-225, https://doi.org/10.5194/gmd-2016-225, 2016
Revised manuscript not accepted
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A system that predicts the amount of water flowing in each river on earth, 9 days ahead, is build using existing parts of open source computer code build by different researchers in other projects.
The glue between all pre-existing parts are all open interfaces which means that the pieces system click together like a house of LEGOs. It is easy to remove a piece (a brick) and replace it with another, improved, piece.
The resulting predictions are available online at forecast.ewatercycle.org
Koen Hilgersom, Tim van Emmerik, Anna Solcerova, Wouter Berghuijs, John Selker, and Nick van de Giesen
Geosci. Instrum. Method. Data Syst., 5, 151–162, https://doi.org/10.5194/gi-5-151-2016, https://doi.org/10.5194/gi-5-151-2016, 2016
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Fibre optic distributed temperature sensing allows one to measure temperature patterns along a fibre optic cable with resolutions down to 25 cm. In geosciences, we sometimes wrap the cable to a coil to measure temperature at even smaller scales. We show that coils with narrow bends affect the measured temperatures. This also holds for the object to which the coil is attached, when heated by solar radiation. We therefore recommend the necessity to carefully design such distributed temperature probes.
K. E. R. Pramana, M. W. Ertsen, and N. C. van de Giesen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-9489-2015, https://doi.org/10.5194/hessd-12-9489-2015, 2015
Revised manuscript not accepted
J. Hoogeveen, J.-M. Faurès, L. Peiser, J. Burke, and N. van de Giesen
Hydrol. Earth Syst. Sci., 19, 3829–3844, https://doi.org/10.5194/hess-19-3829-2015, https://doi.org/10.5194/hess-19-3829-2015, 2015
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GlobWat is a freely distributed, global soil water balance model that is used by FAO to assess water use in irrigated agriculture, the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high-resolution data sets that are consistent at global level and is calibrated and validated against information published in global databases. The paper describes methodology, input and output data, calibration and validation of the model.
S. Gaitan and J. A. E. ten Veldhuis
Proc. IAHS, 370, 9–14, https://doi.org/10.5194/piahs-370-9-2015, https://doi.org/10.5194/piahs-370-9-2015, 2015
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The objective of this paper is to outline opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks. To that end, a cluster analysis is performed. Results indicate that incidence of
rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.
M. H. Spekkers, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Nat. Hazards Earth Syst. Sci., 15, 261–272, https://doi.org/10.5194/nhess-15-261-2015, https://doi.org/10.5194/nhess-15-261-2015, 2015
G. Bruni, R. Reinoso, N. C. van de Giesen, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Hydrol. Earth Syst. Sci., 19, 691–709, https://doi.org/10.5194/hess-19-691-2015, https://doi.org/10.5194/hess-19-691-2015, 2015
S. A. P. de Jong, J. D. Slingerland, and N. C. van de Giesen
Atmos. Meas. Tech., 8, 335–339, https://doi.org/10.5194/amt-8-335-2015, https://doi.org/10.5194/amt-8-335-2015, 2015
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By using two cylindrical thermometers with different diameters, one can determine what temperature a zero diameter thermometer would have. Such a virtual thermometer would not be affected by solar heating and would take on the temperature of the surrounding air. We applied this principle to atmospheric temperature measurements with fiber optic cables using distributed temperature sensing (DTS). With two unshielded cable pairs, one black pair and one white pair, good results were obtained.
M. H. Spekkers, M. Kok, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Nat. Hazards Earth Syst. Sci., 14, 2531–2547, https://doi.org/10.5194/nhess-14-2531-2014, https://doi.org/10.5194/nhess-14-2531-2014, 2014
S. V. Weijs, N. van de Giesen, and M. B. Parlange
Hydrol. Earth Syst. Sci., 17, 3171–3187, https://doi.org/10.5194/hess-17-3171-2013, https://doi.org/10.5194/hess-17-3171-2013, 2013
O. A. C. Hoes, R. W. Hut, N. C. van de Giesen, and M. Boomgaard
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-417-2013, https://doi.org/10.5194/nhessd-1-417-2013, 2013
Revised manuscript has not been submitted
M. H. Spekkers, M. Kok, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Hydrol. Earth Syst. Sci., 17, 913–922, https://doi.org/10.5194/hess-17-913-2013, https://doi.org/10.5194/hess-17-913-2013, 2013
Related subject area
Subject: Urban Hydrology | Techniques and Approaches: Modelling approaches
Simulation of spatially distributed sources, transport, and transformation of nitrogen from fertilization and septic systems in a suburban watershed
Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge: a case study of Shanghai
Exploring the driving factors of compound flood severity in coastal cities: a comprehensive analytical approach
Enhancing generalizability of data-driven urban flood models by incorporating contextual information
An optimized long short-term memory (LSTM)-based approach applied to early warning and forecasting of ponding in the urban drainage system
A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions
Impact of urban geology on model simulations of shallow groundwater levels and flow paths
Technical note: Modeling spatial fields of extreme precipitation – a hierarchical Bayesian approach
Intersecting near-real time fluvial and pluvial inundation estimates with sociodemographic vulnerability to quantify a household flood impact index
Forecasting green roof detention performance by temporal downscaling of precipitation time-series projections
Evaluating different machine learning methods to simulate runoff from extensive green roofs
Modeling and interpreting hydrological responses of sustainable urban drainage systems with explainable machine learning methods
The impact of the spatiotemporal structure of rainfall on flood frequency over a small urban watershed: an approach coupling stochastic storm transposition and hydrologic modeling
Space variability impacts on hydrological responses of nature-based solutions and the resulting uncertainty: a case study of Guyancourt (France)
Urban surface water flood modelling – a comprehensive review of current models and future challenges
Resampling and ensemble techniques for improving ANN-based high-flow forecast accuracy
Event selection and two-stage approach for calibrating models of green urban drainage systems
Modeling the high-resolution dynamic exposure to flooding in a city region
Drainage area characterization for evaluating green infrastructure using the Storm Water Management Model
Critical scales to explain urban hydrological response: an application in Cranbrook, London
Increase in flood risk resulting from climate change in a developed urban watershed – the role of storm temporal patterns
Patterns and comparisons of human-induced changes in river flood impacts in cities
Scale effect challenges in urban hydrology highlighted with a distributed hydrological model
Comparison of the impacts of urban development and climate change on exposing European cities to pluvial flooding
Hydrodynamics of pedestrians' instability in floodwaters
Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes
Using rainfall thresholds and ensemble precipitation forecasts to issue and improve urban inundation alerts
Enhancing the T-shaped learning profile when teaching hydrology using data, modeling, and visualization activities
On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution
Precipitation variability within an urban monitoring network via microcanonical cascade generators
Estimation of peak discharges of historical floods
Indirect downscaling of hourly precipitation based on atmospheric circulation and temperature
Assessing the hydrologic restoration of an urbanized area via an integrated distributed hydrological model
Using the Storm Water Management Model to predict urban headwater stream hydrological response to climate and land cover change
Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data
Contribution of directly connected and isolated impervious areas to urban drainage network hydrographs
Thermal management of an unconsolidated shallow urban groundwater body
Online multistep-ahead inundation depth forecasts by recurrent NARX networks
A statistical analysis of insurance damage claims related to rainfall extremes
Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China
Urbanization and climate change impacts on future urban flooding in Can Tho city, Vietnam
Multi-objective optimization for combined quality–quantity urban runoff control
Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach
Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks
Coupling urban event-based and catchment continuous modelling for combined sewer overflow river impact assessment
Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites
Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Laurence Lin, Amanda K. Suchy, Jonathan M. Duncan, and Arthur J. Gold
Hydrol. Earth Syst. Sci., 28, 4599–4621, https://doi.org/10.5194/hess-28-4599-2024, https://doi.org/10.5194/hess-28-4599-2024, 2024
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Human-induced nitrogen (N) from fertilization and septic effluents is the primary N source in urban watersheds. We developed a model to understand how spatial and temporal patterns of these loads affect hydrologic and biogeochemical processes at the hillslope level. The comparable simulations to observations showed the ability of our model to enhance insights into current water quality conditions, identify high-N-retention locations, and plan future restorations to improve urban water quality.
Hanqing Xu, Elisa Ragno, Sebastiaan N. Jonkman, Jun Wang, Jeremy D. Bricker, Zhan Tian, and Laixiang Sun
Hydrol. Earth Syst. Sci., 28, 3919–3930, https://doi.org/10.5194/hess-28-3919-2024, https://doi.org/10.5194/hess-28-3919-2024, 2024
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A coupled statistical–hydrodynamic model framework is employed to quantitatively evaluate the sensitivity of compound flood hazards to the relative timing of peak storm surges and rainfall. The findings reveal that the timing difference between these two factors significantly affects flood inundation depth and extent. The most severe inundation occurs when rainfall precedes the storm surge peak by 2 h.
Yan Liu, Ting Zhang, Yi Ding, Aiqing Kang, Xiaohui Lei, and Jianzhu Li
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-100, https://doi.org/10.5194/hess-2024-100, 2024
Revised manuscript accepted for HESS
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In coastal cities, rainfall and storm surges cause compound flooding. This study quantifies the contributions of rainfall and tides to compound flooding and analyzes interactions between different flood types. Findings show rainfall has a greater effect on flooding compared to tidal levels. The interaction between fluvial and pluvial flooding exacerbates the flood disaster. Notably, tidal levels have the most significant impact during the interaction phase of these flood types.
Tabea Cache, Milton Salvador Gomez, Tom Beucler, Jovan Blagojevic, João Paulo Leitao, and Nadav Peleg
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-63, https://doi.org/10.5194/hess-2024-63, 2024
Revised manuscript accepted for HESS
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We introduce a new deep-learning model that addresses limitations of existing urban flood models in handling varied terrains and rainfall events. Our model subdivides the city into small patches and presents a novel approach to incorporate broader spatial information. It accurately predicts high-resolution flood maps across diverse rainfall events and cities (on a minutes and meters scale) that haven’t been seen by the model, which offers valuable insights for urban flood mitigation strategies.
Wen Zhu, Tao Tao, Hexiang Yan, Jieru Yan, Jiaying Wang, Shuping Li, and Kunlun Xin
Hydrol. Earth Syst. Sci., 27, 2035–2050, https://doi.org/10.5194/hess-27-2035-2023, https://doi.org/10.5194/hess-27-2035-2023, 2023
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To provide a possibility for early warning and forecasting of ponding in the urban drainage system, an optimized long short-term memory (LSTM)-based model is proposed in this paper. It has a remarkable improvement compared to the models based on LSTM and convolutional neural network (CNN) structures. The performance of the corrected model is reliable if the number of monitoring sites is over one per hectare. Increasing the number of monitoring points further has little impact on the performance.
Qianqian Zhou, Shuai Teng, Zuxiang Situ, Xiaoting Liao, Junman Feng, Gongfa Chen, Jianliang Zhang, and Zonglei Lu
Hydrol. Earth Syst. Sci., 27, 1791–1808, https://doi.org/10.5194/hess-27-1791-2023, https://doi.org/10.5194/hess-27-1791-2023, 2023
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A deep-learning-based data-driven model for flood predictions in temporal and spatial dimensions, with the integration of a long short-term memory network, Bayesian optimization, and transfer learning is proposed. The model accurately predicts water depths and flood time series/dynamics for hyetograph inputs, with substantial improvements in computational time. With transfer learning, the model was well applied to a new case study and showed robust compatibility and generalization ability.
Ane LaBianca, Mette H. Mortensen, Peter Sandersen, Torben O. Sonnenborg, Karsten H. Jensen, and Jacob Kidmose
Hydrol. Earth Syst. Sci., 27, 1645–1666, https://doi.org/10.5194/hess-27-1645-2023, https://doi.org/10.5194/hess-27-1645-2023, 2023
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The study explores the effect of Anthropocene geology and the computational grid size on the simulation of shallow urban groundwater. Many cities are facing challenges with high groundwater levels close to the surface, yet urban planning and development seldom consider its impact on the groundwater resource. This study illustrates that the urban subsurface infrastructure significantly affects the groundwater flow paths and the residence time of shallow urban groundwater.
Bianca Rahill-Marier, Naresh Devineni, and Upmanu Lall
Hydrol. Earth Syst. Sci., 26, 5685–5695, https://doi.org/10.5194/hess-26-5685-2022, https://doi.org/10.5194/hess-26-5685-2022, 2022
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We present a new approach to modeling extreme regional rainfall by considering the spatial structure of extreme events. The developed models allow a probabilistic exploration of how the regional drainage network may respond to extreme rainfall events and provide a foundation for how future risks may be better estimated.
Matthew Preisser, Paola Passalacqua, R. Patrick Bixler, and Julian Hofmann
Hydrol. Earth Syst. Sci., 26, 3941–3964, https://doi.org/10.5194/hess-26-3941-2022, https://doi.org/10.5194/hess-26-3941-2022, 2022
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There is rising concern in numerous fields regarding the inequitable distribution of human risk to floods. The co-occurrence of river and surface flooding is largely excluded from leading flood hazard mapping services, therefore underestimating hazards. Using high-resolution elevation data and a region-specific social vulnerability index, we developed a method to estimate flood impacts at the household level in near-real time.
Vincent Pons, Rasmus Benestad, Edvard Sivertsen, Tone Merete Muthanna, and Jean-Luc Bertrand-Krajewski
Hydrol. Earth Syst. Sci., 26, 2855–2874, https://doi.org/10.5194/hess-26-2855-2022, https://doi.org/10.5194/hess-26-2855-2022, 2022
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Different models were developed to increase the temporal resolution of precipitation time series to minutes. Their applicability under climate change and their suitability for producing input time series for green infrastructure (e.g. green roofs) modelling were evaluated. The robustness of the model was validated against a range of European climates in eight locations in France and Norway. The future hydrological performances of green roofs were evaluated in order to improve design practice.
Elhadi Mohsen Hassan Abdalla, Vincent Pons, Virginia Stovin, Simon De-Ville, Elizabeth Fassman-Beck, Knut Alfredsen, and Tone Merete Muthanna
Hydrol. Earth Syst. Sci., 25, 5917–5935, https://doi.org/10.5194/hess-25-5917-2021, https://doi.org/10.5194/hess-25-5917-2021, 2021
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This study investigated the potential of using machine learning algorithms as hydrological models of green roofs across different climatic condition. The study provides comparison between conceptual and machine learning algorithms. Machine learning models were found to be accurate in simulating runoff from extensive green roofs.
Yang Yang and Ting Fong May Chui
Hydrol. Earth Syst. Sci., 25, 5839–5858, https://doi.org/10.5194/hess-25-5839-2021, https://doi.org/10.5194/hess-25-5839-2021, 2021
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This study uses explainable machine learning methods to model and interpret the statistical correlations between rainfall and the discharge of urban catchments with sustainable urban drainage systems. The resulting models have good prediction accuracies. However, the right predictions may be made for the wrong reasons as the model cannot provide physically plausible explanations as to why a prediction is made.
Zhengzheng Zhou, James A. Smith, Mary Lynn Baeck, Daniel B. Wright, Brianne K. Smith, and Shuguang Liu
Hydrol. Earth Syst. Sci., 25, 4701–4717, https://doi.org/10.5194/hess-25-4701-2021, https://doi.org/10.5194/hess-25-4701-2021, 2021
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The role of rainfall space–time structure in flood response is an important research issue in urban hydrology. This study contributes to this understanding in small urban watersheds. Combining stochastically based rainfall scenarios with a hydrological model, the results show the complexities of flood response for various return periods, implying the common assumptions of spatially uniform rainfall in urban flood frequency are problematic, even for relatively small basin scales.
Yangzi Qiu, Igor da Silva Rocha Paz, Feihu Chen, Pierre-Antoine Versini, Daniel Schertzer, and Ioulia Tchiguirinskaia
Hydrol. Earth Syst. Sci., 25, 3137–3162, https://doi.org/10.5194/hess-25-3137-2021, https://doi.org/10.5194/hess-25-3137-2021, 2021
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Our original research objective is to investigate the uncertainties of the hydrological responses of nature-based solutions (NBSs) that result from the multiscale space variability in both the rainfall and the NBS distribution. Results show that the intersection effects of spatial variability in rainfall and the spatial arrangement of NBS can generate uncertainties of peak flow and total runoff volume estimations in NBS scenarios.
Kaihua Guo, Mingfu Guan, and Dapeng Yu
Hydrol. Earth Syst. Sci., 25, 2843–2860, https://doi.org/10.5194/hess-25-2843-2021, https://doi.org/10.5194/hess-25-2843-2021, 2021
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This study presents a comprehensive review of models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. It explores the advantages and limitations of existing models and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.
Everett Snieder, Karen Abogadil, and Usman T. Khan
Hydrol. Earth Syst. Sci., 25, 2543–2566, https://doi.org/10.5194/hess-25-2543-2021, https://doi.org/10.5194/hess-25-2543-2021, 2021
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Flow distributions are highly skewed, resulting in low prediction accuracy of high flows when using artificial neural networks for flood forecasting. We investigate the use of resampling and ensemble techniques to address the problem of skewed datasets to improve high flow prediction. The methods are implemented both independently and in combined, hybrid techniques. This research presents the first analysis of the effects of combining these methods on high flow prediction accuracy.
Ico Broekhuizen, Günther Leonhardt, Jiri Marsalek, and Maria Viklander
Hydrol. Earth Syst. Sci., 24, 869–885, https://doi.org/10.5194/hess-24-869-2020, https://doi.org/10.5194/hess-24-869-2020, 2020
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Urban drainage models are usually calibrated using a few events so that they accurately represent a real-world site. This paper compares 14 single- and two-stage strategies for selecting these events and found significant variation between them in terms of model performance and the obtained values of model parameters. Calibrating parameters for green and impermeable areas in two separate stages improved model performance in the validation period while making calibration easier and faster.
Xuehong Zhu, Qiang Dai, Dawei Han, Lu Zhuo, Shaonan Zhu, and Shuliang Zhang
Hydrol. Earth Syst. Sci., 23, 3353–3372, https://doi.org/10.5194/hess-23-3353-2019, https://doi.org/10.5194/hess-23-3353-2019, 2019
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Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-hit bodies during an event, and thus it cannot satisfy the increasingly elaborate modeling and management of urban floods. In this study, a comprehensive method was proposed to simulate dynamic exposure to urban flooding considering human mobility. Several scenarios, including diverse flooding types and various responses of residents to flooding, were considered.
Joong Gwang Lee, Christopher T. Nietch, and Srinivas Panguluri
Hydrol. Earth Syst. Sci., 22, 2615–2635, https://doi.org/10.5194/hess-22-2615-2018, https://doi.org/10.5194/hess-22-2615-2018, 2018
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This paper demonstrates an approach to spatial discretization for analyzing green infrastructure (GI) using SWMM. Besides DCIA, pervious buffers should be identified for GI modeling. Runoff contributions from different spatial components and flow pathways would impact GI performance. The presented approach can reduce the number of calibration parameters and apply scale–independently to a watershed scale. Hydrograph separation can add insights for developing GI scenarios.
Elena Cristiano, Marie-Claire ten Veldhuis, Santiago Gaitan, Susana Ochoa Rodriguez, and Nick van de Giesen
Hydrol. Earth Syst. Sci., 22, 2425–2447, https://doi.org/10.5194/hess-22-2425-2018, https://doi.org/10.5194/hess-22-2425-2018, 2018
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In this work we investigate the influence rainfall and catchment scales have on hydrological response. This problem is quite relevant in urban areas, where the response is fast due to the high degree of imperviousness. We presented a new approach to classify rainfall variability in space and time and use this classification to investigate rainfall aggregation effects on urban hydrological response. This classification allows the spatial extension of the main core of the storm to be identified.
Suresh Hettiarachchi, Conrad Wasko, and Ashish Sharma
Hydrol. Earth Syst. Sci., 22, 2041–2056, https://doi.org/10.5194/hess-22-2041-2018, https://doi.org/10.5194/hess-22-2041-2018, 2018
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The study examines the impact of higher temperatures expected in a future climate on how rainfall varies with time during severe storm events. The results show that these impacts increase future flood risk in urban environments and that current design guidelines need to be adjusted so that effective adaptation measures can be implemented.
Stephanie Clark, Ashish Sharma, and Scott A. Sisson
Hydrol. Earth Syst. Sci., 22, 1793–1810, https://doi.org/10.5194/hess-22-1793-2018, https://doi.org/10.5194/hess-22-1793-2018, 2018
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This study investigates global patterns relating urban river flood impacts to socioeconomic development and changing hydrologic conditions, and comparisons are provided between 98 individual cities. This paper condenses and communicates large amounts of information to accelerate the understanding of relationships between local urban conditions and global processes, and to potentially motivate knowledge transfer between decision-makers facing similar circumstances.
Abdellah Ichiba, Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer, Philippe Bompard, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 22, 331–350, https://doi.org/10.5194/hess-22-331-2018, https://doi.org/10.5194/hess-22-331-2018, 2018
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This paper proposes a two-step investigation to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependency observed within GIS data inputted in urban hydrological models. Then an intensive multi-scale modelling work was carried out to confirm effects on model performances. The model was implemented at 17 spatial resolutions ranging from 100 to 5 m. Results allow the understanding of scale challenges in hydrology modelling.
Per Skougaard Kaspersen, Nanna Høegh Ravn, Karsten Arnbjerg-Nielsen, Henrik Madsen, and Martin Drews
Hydrol. Earth Syst. Sci., 21, 4131–4147, https://doi.org/10.5194/hess-21-4131-2017, https://doi.org/10.5194/hess-21-4131-2017, 2017
Chiara Arrighi, Hocine Oumeraci, and Fabio Castelli
Hydrol. Earth Syst. Sci., 21, 515–531, https://doi.org/10.5194/hess-21-515-2017, https://doi.org/10.5194/hess-21-515-2017, 2017
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In developed countries, the majority of fatalities during floods occurs as a consequence of inappropriate high-risk behaviour such as walking or driving in floodwaters. This work addresses pedestrians' instability in floodwaters. It analyses both the contribution of flood and human physical characteristics in the loss of stability highlighting the key role of subject height (submergence) and flow regime. The method consists of a re-analysis of experiments and numerical modelling.
Hjalte Jomo Danielsen Sørup, Stylianos Georgiadis, Ida Bülow Gregersen, and Karsten Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci., 21, 345–355, https://doi.org/10.5194/hess-21-345-2017, https://doi.org/10.5194/hess-21-345-2017, 2017
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In this study we propose a methodology changing present-day precipitation time series to reflect future changed climate. Present-day time series have a much finer resolution than what is provided by climate models and thus have a much broader application range. The proposed methodology is able to replicate most expectations of climate change precipitation. These time series can be used to run fine-scale hydrological and hydraulic models and thereby assess the influence of climate change on them.
Tsun-Hua Yang, Gong-Do Hwang, Chin-Cheng Tsai, and Jui-Yi Ho
Hydrol. Earth Syst. Sci., 20, 4731–4745, https://doi.org/10.5194/hess-20-4731-2016, https://doi.org/10.5194/hess-20-4731-2016, 2016
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Taiwan continues to suffer from floods. This study proposes the integration of rainfall thresholds and ensemble precipitation forecasts to provide probabilistic urban inundation forecasts. Utilization of ensemble precipitation forecasts can extend forecast lead times to 72 h, preceding peak flows and allowing response agencies to take necessary preparatory measures. This study also develops a hybrid of real-time observation and rainfall forecasts to improve the first 24 h inundation forecasts.
Christopher A. Sanchez, Benjamin L. Ruddell, Roy Schiesser, and Venkatesh Merwade
Hydrol. Earth Syst. Sci., 20, 1289–1299, https://doi.org/10.5194/hess-20-1289-2016, https://doi.org/10.5194/hess-20-1289-2016, 2016
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The use of authentic learning activities is especially important for place-based geosciences like hydrology, where professional breadth and technical depth are critical for practicing hydrologists. The current study found that integrating computerized learning content into the learning experience, using only a simple spreadsheet tool and readily available hydrological data, can effectively bring the "real world" into the classroom and provide an enriching educational experience.
G. Bruni, R. Reinoso, N. C. van de Giesen, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Hydrol. Earth Syst. Sci., 19, 691–709, https://doi.org/10.5194/hess-19-691-2015, https://doi.org/10.5194/hess-19-691-2015, 2015
P. Licznar, C. De Michele, and W. Adamowski
Hydrol. Earth Syst. Sci., 19, 485–506, https://doi.org/10.5194/hess-19-485-2015, https://doi.org/10.5194/hess-19-485-2015, 2015
J. Herget, T. Roggenkamp, and M. Krell
Hydrol. Earth Syst. Sci., 18, 4029–4037, https://doi.org/10.5194/hess-18-4029-2014, https://doi.org/10.5194/hess-18-4029-2014, 2014
F. Beck and A. Bárdossy
Hydrol. Earth Syst. Sci., 17, 4851–4863, https://doi.org/10.5194/hess-17-4851-2013, https://doi.org/10.5194/hess-17-4851-2013, 2013
D. H. Trinh and T. F. M. Chui
Hydrol. Earth Syst. Sci., 17, 4789–4801, https://doi.org/10.5194/hess-17-4789-2013, https://doi.org/10.5194/hess-17-4789-2013, 2013
J. Y. Wu, J. R. Thompson, R. K. Kolka, K. J. Franz, and T. W. Stewart
Hydrol. Earth Syst. Sci., 17, 4743–4758, https://doi.org/10.5194/hess-17-4743-2013, https://doi.org/10.5194/hess-17-4743-2013, 2013
H. Ozdemir, C. C. Sampson, G. A. M. de Almeida, and P. D. Bates
Hydrol. Earth Syst. Sci., 17, 4015–4030, https://doi.org/10.5194/hess-17-4015-2013, https://doi.org/10.5194/hess-17-4015-2013, 2013
Y. Seo, N.-J. Choi, and A. R. Schmidt
Hydrol. Earth Syst. Sci., 17, 3473–3483, https://doi.org/10.5194/hess-17-3473-2013, https://doi.org/10.5194/hess-17-3473-2013, 2013
J. Epting, F. Händel, and P. Huggenberger
Hydrol. Earth Syst. Sci., 17, 1851–1869, https://doi.org/10.5194/hess-17-1851-2013, https://doi.org/10.5194/hess-17-1851-2013, 2013
H.-Y. Shen and L.-C. Chang
Hydrol. Earth Syst. Sci., 17, 935–945, https://doi.org/10.5194/hess-17-935-2013, https://doi.org/10.5194/hess-17-935-2013, 2013
M. H. Spekkers, M. Kok, F. H. L. R. Clemens, and J. A. E. ten Veldhuis
Hydrol. Earth Syst. Sci., 17, 913–922, https://doi.org/10.5194/hess-17-913-2013, https://doi.org/10.5194/hess-17-913-2013, 2013
J. J. Lian, K. Xu, and C. Ma
Hydrol. Earth Syst. Sci., 17, 679–689, https://doi.org/10.5194/hess-17-679-2013, https://doi.org/10.5194/hess-17-679-2013, 2013
H. T. L. Huong and A. Pathirana
Hydrol. Earth Syst. Sci., 17, 379–394, https://doi.org/10.5194/hess-17-379-2013, https://doi.org/10.5194/hess-17-379-2013, 2013
S. Oraei Zare, B. Saghafian, and A. Shamsai
Hydrol. Earth Syst. Sci., 16, 4531–4542, https://doi.org/10.5194/hess-16-4531-2012, https://doi.org/10.5194/hess-16-4531-2012, 2012
R. Archetti, A. Bolognesi, A. Casadio, and M. Maglionico
Hydrol. Earth Syst. Sci., 15, 3115–3122, https://doi.org/10.5194/hess-15-3115-2011, https://doi.org/10.5194/hess-15-3115-2011, 2011
Y.-M. Chiang, L.-C. Chang, M.-J. Tsai, Y.-F. Wang, and F.-J. Chang
Hydrol. Earth Syst. Sci., 15, 185–196, https://doi.org/10.5194/hess-15-185-2011, https://doi.org/10.5194/hess-15-185-2011, 2011
I. Andrés-Doménech, J. C. Múnera, F. Francés, and J. B. Marco
Hydrol. Earth Syst. Sci., 14, 2057–2072, https://doi.org/10.5194/hess-14-2057-2010, https://doi.org/10.5194/hess-14-2057-2010, 2010
Yen-Ming Chiang, Li-Chiu Chang, Meng-Jung Tsai, Yi-Fung Wang, and Fi-John Chang
Hydrol. Earth Syst. Sci., 14, 1309–1319, https://doi.org/10.5194/hess-14-1309-2010, https://doi.org/10.5194/hess-14-1309-2010, 2010
Cited articles
Aronica, G. and Canarozzo, M.: Studying the hydrological response of urban catchments using a semi-distributed linear non-linear model, J. Hydrol., 238, 35–43, 2000.
Aronica, G., Freni, G., and Oliveri, E.: Uncertainty analysis of the influence of rainfall time resolution in the modelling of urban drainage systems, Hydrol. Process., 19, 1055–1071, 2005.
Bacchi, B. and Kottegoda, N.: Identification and calibration of spatial correlation patterns of rainfall, J. Hydrol., 165, 311–348, 1995.
Bergstrom, S. and Graham, L. P.: On the scale problem in hydrological modelling, J. Hydrol., 211, 253–265, 1998.
Berndtsson, R. and Niemczynowicz, J.: Spatial and temporal scales in rainfall analysis – some aspects and future perspective, J. Hydrol., 100, 293–313, 1986.
Berne, A. and Krajewski, W.: Radar for hydrology: Unfulfilled promise or unrecognized potential?, Adv. Water Resour., 51, 357–366, 2013.
Berne, A., Delrieu, G., Creutin, J., and Obled, C.: Temporal and spatial resolution of rainfall measurements required for urban hydrology, J. Hydrol., 299, 166–179, 2004.
Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: a review, Hydrol. Process., 9, 251–290, 1995.
Boogaard, F., Lucke, T., and Beecham, S.: Effect of Age of Permeable Pavements on Their Infiltration Function, Clean Soil Air Waters, 41, 146–152, 2013.
Bruni, G., Reinoso, R., van de Giesen, N. C., Clemens, F. H. L. R., and ten Veldhuis, J. A. E.: On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution, Hydrol. Earth Syst. Sci., 19, 691–709, https://doi.org/10.5194/hess-19-691-2015, 2015.
Cheng, S.and Wang, R.: An approach for evaluating the hydrological effects of urbanization and its application, Hydrol. Process., 16, 1403–1418, 2002.
Chirico, G. B., Grayson, R. B., Western, A. W., Woods, R., and Seed, A.: Sensitivity of simulated catchment response to the spatial resolution of rainfall, Proceedings of conference: MODSIM 2001, Modelling and Simulation Society of Australia and New Zealand inc, 10–13 December 2001, Canberra, Australia, 377–388, 2001.
Ciach, G. J. and Krajewski, W. F.: On the estimation of radar rainfall error variance, Adv. Water Resour., 22, 585–595, https://doi.org/10.1016/s0309-1708(98)00043-8, 1999.
Cole, S. and Moore, R.: Hydrological modelling using rain gauge- and radar-based estimators of areal rainfall, J. Hydrol., 358, 159–181, 2008.
Cui, X. and Li, X.: Role of surface evaporation in surface rainfall processes, J. Geophys. Res., 111, D17112, https://doi.org/10.1029/2005JD006876, 2006.
Dai, Q., Rico-Ramirez, M. A., Han, D., Islam, T., and Liguori, S.: Probabilistic radar rainfall nowcast using empirical and theoretical uncertainty models, Hydrol. Process., 29, 66–79, 2015.
Daniels, E. E., Lenderink, G., Hutjes, R. W. A., and Holtslag, A. A. M.: Observed urban effects on precipitation along the Dutch West coast, Int. J. Climatol., 36, 2111–2119, https://doi.org/10.1002/joc.4458, 2015.
Deidda, R.: Rainfall downscaling in a space time multifractal framework, Water Resour. Res., 36, 1779–1794, 2000.
Del Giudice, D., Löwe, R., Madsen, H., Mikkelsen, P. S., and Rieckermann, J.: Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors, Water Resour. Res., 51, 5004–5022, 2015.
Dunne, T.: Field studies of hillslope flow processes, in: Hillslope Hydrology, edited by: Kirkby, M. J., Wiley, New York, USA, 227–293, 1978.
Einfalt, T., Arnbjerg-Nielsen, K., Golz, C., Jensen, N., Quirmbach, M., Vaes, G., and Vieux, B.: Towards a Roadmap for Use of Radar Rainfall data use in Urban Drainage, J. Hydrol., 299, 186–202, 2004.
Emmanuel, I., Andrieu, H., Leblois, E., and Flahaut, B.: Temporal and spatial variability of rainfall at the urban hydrological scale, J. Hydrol., 430–431, 162–172, 2012.
Emmanuel, I., Andrieu, H., Leblois, E., Janey, N., and Payrastre, O.: Influence of rainfall spatial variability on rainfall-runoff modelling: benefit of a simulation approach?, J. Hydrol., 531, 337–348, 2015.
Fabry, F., Bellon, A., Duncan, M. R., and Austin, G. L.: High resolution rainfall measurements by radar for very small basins: the sampling problem reexamined, J. Hydrol., 161, 415–428, 1994.
Fatichi, S., Vivoni, E. R., Ogden, F. L., Ivanov, V. Y., Mirus, B., Gochis, D., Downer, C. W., Camporese, M., Davison, J. H., and Ebel, B. E. A.: An overview of current applications,challenges, and future trends in distributed process-based models in hydrology, J. Hydrol., 537, 45–60, 2016.
Faures, J., Goodrich, D. C., Woolhiser, D. A., and Sorooshian, S.: Impact of small scale spatial rainfall variability on runoff modelling, J. Hydrol., 173, 309–326, 1995.
Fencl, M., Rieckermann, J., Sýkora, P., Stránský, D., and Bareš, V.: Commercial microwave links instead of rain gauges: fiction or reality?, Water Sci. Technol., 71, 31–37, https://doi.org/10.2166/wst.2014.466, 2015.
Fencl, M., Dohnal, M., Rieckermann, J., and Bareš, V.: Gauge-adjusted rainfall estimates from commercial microwave links, Hydrol. Earth Syst. Sci., 21, 617–634, https://doi.org/10.5194/hess-21-617-2017, 2017.
Ferraris, L., Gabellani, S., Rebora, N., and Provenzale, A.: A comparison of stochastic models for spatial rainfall downscaling, Water Resour. Res., 39, 1368, https://doi.org/10.1029/2003WR002504, 2003.
Fletcher, T. D., Andrieu, H., and Hamel, P.: Understanding, management and modelling of urban hydrology and its consequences for receiving waters: a state of the art, Adv. Water Resour., 51, 261–279, 2013.
Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L., and Carbonneau, P. E.: Topographic structure from motion: a new development in photogrammetric measurement, Earth Surf. Proc. Land., 38, 421–430, 2013.
Foresti, L., Reyniers, M., Seed, A., and Delobbe, L.: Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium, Hydrol. Earth Syst. Sci., 20, 505–527, https://doi.org/10.5194/hess-20-505-2016, 2016.
Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling, Int. J. Climatol., 27, 1547–1578, https://doi.org/10.1002/joc.1556, 2007.
Gericke, O. J. and Smithers, J. C.: Review of methods used to estimate catchment response time for the purpose of peak discharge estimation, Hydrolog. Sci. J., 59, 1935–1971, 2014.
Gires, A., Onof, C., Tchiguirinskaia, I., Schertzer, D., and Lovejoy, S.: Analyses multifractales et spatio-temporelles des précipitations du modèle Méso-NH et des données radar, Hydrolog. Sci. J., 56, 380–396, 2011.
Gires, A., Onof, C., Maksimovic, C., Schertzer, D., Tchiguirinskaia, I., and Simoes, N.: Quantifying the impact of small scale unmeasured rainfall variability on urban hydrology through multifractal downscaling: a case study, J. Hydrol., 442-443, 117–128, 2012.
Gires, A., Tchiguirinskaia, I., Schertzer, D., Schellart, A., Berne, A., and Lovejoy, S.: Influence of small scale rainfall variability on standard comparison tools between radar and rain gauge data, Atmos. Res., 138, 125–138, 2014.
Gironás, J., Niemann, J., Roesner, L., Rodriguez, F., and Andrieu, H.: Evaluation of Methods for Representing Urban Terrain in Storm-Water Modeling, J. Hydrol. Eng., 15, 1–14, 2010.
Givati, A. and Rosenfeld, D.: Quantifying precipitation suppression due to air pollution, J. Appl. Meteorol., 43, 1038–1056, 2004.
Grimmond, C. and Oke, T.: An evapotranspiration-interception model for urban areas, Water Resour. Res., 27, 1739–1755, 1991.
Hart, Q. J., Brugnach, M., Temesgen, B., Rueda, C., Ustin, S. L., and Frame, K.: Daily reference evapotranspiration for California using satellite imagery and weather station measurement interpolation, Civ. Eng. Environ. Syst., 26, 19–33, https://doi.org/10.1080/10286600802003500, 2009.
Horton, R.: The role of infiltration in the hydrologic cycle, Eos Trans. AGU, 14, 446–460, 1933.
Horton, R.: Analysis of runoff-plat experiments with varing infiltration-capacity, EOS Earth and Space Science News, 20, 693–711, 1939.
Huff, F. A. and Changno, S. A. J.: Precipitation Modification By Major Urban Areas, B. Am. Meteorol. Soc., 54, 1220–1232, 1973.
Jensen, N. E. and Pedersen, L.: Spatial variability of rainfall: Variations within a single radar pixel, Atmos. Res., 77, 269–277, 2005.
Julien, P. Y. and Moglen, G. E.: Similarity and length scalefor spatially varied overland flow, Water Resour. Res., 26, 1819–1832, 1990.
Kolgomorov, A. N.: A refinement of previous hypotheses concerning the local structure of turbulence in a viscous incompressible fluid at high Reynolds number, J. Fluid Mech., 13, 82–85, 1962.
Krajewski, W. F. and Smith, J. A.: Radar hydrology: rainfall estimation, Adv. Water Resour., 25, 1387–1394, 2005.
Krajewski, W. F., Ciach, G. J., McCollum, J. R., and Bacotiu, C.: Initial validation of the global precipitation climatology project monthly rainfall over the United States, J. Appl. Meteorol., 39, 1071–1086, https://doi.org/10.1175/1520-0450(2000)039<1071:ivotgp>2.0.co;2, 2000.
Kuichling, E.: The Relation between the Rainfall and the Discharge of Sewers in Populous Districts, Transactions of ASCE, 20, 1–60, 1889.
Lanza, L. and Stagi, L.: High resolution performance of catching type rain gauges from the laboratory phase of the WMO Field Intercomparison of Rain Intensity Gauges, Atmos. Res., 94, 555–563, 2009.
Lanza, L. and Vuerich, E.: The WMO Field Intercomparison of Rain Intensity Gauges, Atmos. Res., 94, 534–543, 2009.
Larson, C. L.: A two phase approach to the prediction of peak rates and frequencies of runoff for small ungauged watersheds, Technical Report n. 53, Department of Civil Engineering, Standford University, Stanford, USA, 1965.
Leijnse, H., Uijlenhoet, R., and Stricker, J.: Rainfall measurement using radio links from cellular communication networks, Water Resour. Res., 43, W03201, https://doi.org/10.1029/2006WR005631, 2007.
Leitão, P. J., Simões, N. E., Pina, R. D., Ochoa-Rodriguez, S., Onof, C., and Marques, A. S.: Stochastic evaluation of the impact of sewer inlets' hydraulic capacity on urban pluvial flooding, Stoch. Environ. Res. Risk Assess., 1–16, https://doi.org/10.1007/s00477-016-1283-x, 2016.
Liguori, S. and Rico-Ramirez, M. A.: A review of current approaches to radar based Quantitative Precipitation Forecasts, International Journal of River Basin Management, 12, 391–402, 2013.
Litvak, E., Manago, K. F., Hogue, T. S., and Pataki, D. E.: Evapotranspiration of urban landscapes in Los Angeles, California at the municipal scale, Water Resour. Res., 53, 4236–4252, https://doi.org/10.1002/2016WR020254, 2017.
Lovejoy, S. and Schertzer, D.: Multifractal analysis techniques and the rain and cloud fields from 10−3 to 106 m, Non linear variability in geophysics, 111–144, https://doi.org/10.1007/978-94-009-2147-4_8, 1991.
Lucke, T., Boogaard, F., and van de Ven, F.: Evaluation of a new experimental test procedure to more accurately determine the surface infiltration rate of permeable pavement systems, Urban, Planning and Transport Research: An Open Access Journal, 2, 22–35, 2014.
Mandapaka, P. V., Krajeski, W. F., Ciach, G. J., Villarini, G., and Smith, J. A.: Estimation of radar-rainfall error spatial correlation, Adv. Water Resour., 32, 1020–1030, 2009.
Mansell, M. G.: Rural and urban hydrology, Thomas Telford Ltd, London, UK, 2003.
Marasco, D. E., Culligan, P. J., and McGillis, W.: Evaluation of common evapotranspiration models based on measurements from two extensive green roofs in New York City, Ecol. Eng., 84, 451–462, https://doi.org/10.1016/j.ecoleng.2015.09.001, 2015.
Marchi, L., Borga, M., Preciso, E., and Gaume, E.: Characterisation of selected extreme flash floods in Europe and implications for flood risk management, Hydrol. Process., 23, 2714–2727, 2010.
Marsan, D., Schertzer, D., and Lovejoy, S.: Causal space-time multifractal processes: Predictability and forecasting of rain fields, J. Geophys. Res., 101, 26333–26346, 1996.
Marshall, J. S. and Palmer, W. M. K.: The distribution of raindrops with size, McGill University, https://doi.org/10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO;2, 1948.
Mayer, H.: Automatic Object Extraction from Aerial Imagery – A Survey Focusing on Buildings, Comput. Vis. Image Und., 74, 138–149, 1999.
McCuen, R. H., Wong, S. L., and Rawls, W. J.: Estimating Urban Time of Concentration, J. Hydraul. Eng., 110, 887–904, https://doi.org/10.1061/(ASCE)0733-9429(1984)110:7(887), 1984.
McRobie, F. H., Wang, L.-P., Onof, C., and Kenney, S.: A spatial-temporal rainfall generator for urban drainage design, Water Sci. Technol., 68, 240–249, https://doi.org/10.2166/wst.2013.241, 2013.
Meselhe, E., Habib, E., Oche, O., and Gautam, S.: Sensitivity of conceptual and physically based hydrologic models to temporal and spatial rainfall sampling, J. Hydrol. Eng., 14, 711–720, 2009.
Montanari, A. and Grossi, G.: Estimating the uncertainty of hydrological forecasts: A statistical approach, Water Resour. Res., 44, W00B08, https://doi.org/10.1029/2008WR006897, 2008.
Morin, E., Enzel, Y., Shamir, U., and Garti, R.: The characteristic time scale for basin hydrological response using radar data, J. Hydrol., 252, 85–99, 2001.
Morin, E., Georgakakos, K. P., Shamir, U., Garti, R., and Enzel, Y.: Objective, observations-based, automatic estimation of the catchment response timescale, Water Resour. Res., 38, 1212, https://doi.org/10.1029/2001WR000808, 2002.
Morin, E., Georgakakos, K. P., Shamir, U., Garti, R., and Enzel, Y.: Investigating the effect of catchment characteristics on the response time scale using a distributed model and weather radar information, Weather Radar Information and Distributed Hydrological Modelling, Proceedings of symposium I-IS03 held during IUOG2003 at Sapporo, Japan, 30 June–11 July 2003, IAHS Publ., 282, 177–185, 2003.
Musy, A. and Higy, C.: Hydrology A Science of Nature, Science Publishers, CRC Press, Boca Raton, Florida, USA, 2010.
Muthusamy, M., Schellart, A., Tait, S., and Heuvelink, G. B. M.: Geostatistical upscaling of rain gauge data to support uncertainty analysis of lumped urban hydrological models, Hydrol. Earth Syst. Sci., 21, 1077–1091, https://doi.org/10.5194/hess-21-1077-2017, 2017.
Nielsen, J. E., Thorndahl, S., and Rasmussen, M. R.: Improving weather radar precipitation estimates by combining two types of radars, Atmos. Res., 139, 36–45, https://doi.org/10.1016/j.atmosres.2013.12.013, 2014.
Niemczynowicz, J.: The rainfall movement – A valuable complement to short-term rainfall data, J. Hydrol., 104, 311–326, 1988.
Niemczynowicz, J.: Urban hydrology and water management – present and future challenges, Urban Water, 1, 1–14, 1999.
Niemi, T. J., Guillaume, J. H. A., Kokkonen, T., Hoang, T. M. T., and Seed, A. W.: Role of spatial anisotropy in design storm generation: Experiment and interpretation, Water Resour. Res., 52, 69–89, https://doi.org/10.1002/2015WR017521, 2016.
Nikolopoulos, E., Borga, M., Zoccatelli, D., and Anagnostou, E. N.: Catchment scale storm velocity: quantification, scale dependence and effect on flood response, Hydrolog. Sci. J., 59, 1363–1376, 2014.
Notaro, V., Fontanazza, C. M., Freni, G., and Puleo, V.: Impact of rainfall data resolution in time and space on the urban flooding evaluation, Water Sci. Technol., 68, 1984–1993, 2013.
Nouri, H., Beecham, S., Kazemi, F., and Hassanli, A.: A review of ET measurement techniques for estimating the water requirements of urban landscape vegetation, Urban Water, 10, 247–259, 2013.
Ochoa-Rodriguez, S., Onof, C., Maksimovic, C., Wang, L., Willems, P., Assel, J., Gires, A., Ichiba, A., Bruni, G., and ten Veldhuis, A. E. J.: Urban pluvial flood modelling: current theory and practice. Review document related to Work Package 3, RainGain Project, WP3 review document, available at: http://www.raingain.eu (last access: 31 May 2017), 2015a.
Ochoa-Rodriguez, S., Wang, L., Gires, A., Pina, R., Reinoso-Rondinel, R., Bruni, G., Ichiba, A., Gaitan, S., Cristiano, E., Assel, J., Kroll, S., Murlà-Tuyls, D., Tisserand, B., Schertzer, D., Tchiguirinskaia, I., Onof, C., Willems, P., and ten Veldhuis, A. E. J.: Impact of Spatial and Temporal Resolution of Rainfall Inputs on Urban Hydrodynamic Modelling Outputs: A Multi-Catchment Investigation, J. Hydrol., 531, 389–407, 2015b.
Ogden, F. L. and Dawdy, D. R.: Peak discharge scaling in small hortonian watershed, J. Hydrol. Eng., 8, 64–73, 2003.
Ogden, F. L. and Julien, P. Y.: Runoff model sensitivity to radar rainfall resolution, J. Hydrol., 158, 1–18, 1994.
Ogden, F. L., Richardson, J. R., and Julien, P. Y.: Similarity in catchment response, Water Resour. Res., 31, 1543–1547, 1995.
Ogden, F. L., Pradhan, N. R., Downer, C. W., and Zahner, J. A.: Relative Importance of Impervious Area, Drainage Density, width Function, and Subsurface Storm Drainage on Flood Runoff from an Urbanized Catchment, Water Resour. Res., 47, 1–12, 2011.
Oke, T. R.: Initial Guidance to Obtain Representative Meteorological Observations at Urban Sites, OM Report No.81, WMO/TD No. 1250, World Meteorological Organization, Geneva, Switzerland, 2006.
Opzoekingscentrum voor de Wegenbouw: Waterdoorlatende Verhardingen met Betonstraatstenen, Report on pervious pavements, Brussel, Belgium, 2008.
Otto, T. and Russchenberg, H. W.: Estimation of Specific Differential Phase Backscatter Phase From Polarimetric Weather Radar Measurement of Rain, IEEE Geosci. Remote S., 5, 988–922, 2011.
Overeem, A., Holleman, I., and Bruihand, A.: Derivation of a 10 year radar based climatology of rainfall, J. Appl. Meteorol. Clim., 48, 1448–1463, 2009a.
Overeem, A., Buishand, A., and Holleman, I.: Extreme rainfall analysis and estimation of depth duration frequency curves using weather radar, Water Resour. Res., 45, W10424, https://doi.org/10.1029/2009WR007869, 2009b.
Paschalis, A., Molnar, P., Fatichi, S., and Burlando, P.: A stochastic model for high resolution space-time precipitation simulation, Water Resour. Res., 49, 8400–8417, https://doi.org/10.1002/2013WR014437, 2013.
Peleg, N. and Morin, E.: Stochastic convective rain-field simulation using a high-resolution synoptically conditioned weather generator (HiReS-WG), Water Resour. Res., 50, 2124–2139, https://doi.org/10.1002/2013WR014836, 2014.
Peleg, N., Ben-Asher, M., and Morin, E.: Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network, Hydrol. Earth Syst. Sci., 17, 2195–2208, https://doi.org/10.5194/hess-17-2195-2013, 2013.
Peleg, N., Marra, F., Fatichi, S., Paschalis, A., Molnar, P., and Burlando, P.: Spatial variability of extreme rainfall at radar subpixel scale, J. Hydrol., in press, https://doi.org/10.1016/j.jhydrol.2016.05.033, 2016.
Peleg, N., Blumensaat, F., Molnar, P., Fatichi, S., and Burlando, P.: Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling, Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, 2017.
Pina, R., Ochoa-Rodriguez, S., Simones, N.and Mijic, A., Sa Marques, A., and Maksimovik, C.: Semi-distributed or fully distributed rainfall-runoff models for urban pluvial flood modelling?, 13th International Conference on Urban Drainage, 7–12 September 2014, Sarawak, Malaysia, 2014.
Pina, R., Ochoa-Rodriguez, S., Simones, N., Mijic, A., Sa Marques, A., and Maksimovik, C.: Semi- vs fully- distributed urban stormwater models: model set up and comparison with two real case studies, Water, 8, 58, https://doi.org/10.3390/w8020058, 2016.
Quirmbach, M. and Schultz, G. A.: Comparison of rain gauge and radar data as input to an urban rainfall-runoff model, Water Sci. Technol., 45, 27–33, 2016.
Rafieeinasab, A., Norouzi, A., Kim, S., Habibi, H., Nazari, B., Seo, D., Lee, H., Cosgrove, B., and Cui, Z.: Toward high-resolution flash flood prediction in large urban areas – Analysis of sensitivity to spatiotemporal resolution of rainfall input and hydrologic modeling, J. Hydrol., 531, 370–388, 2015.
Ragab, R., Rosier, P., Dixon, A., Bromley, J., and Cooper, J. D.: Experimental study of water fluxes in a residential area: 2. Road infiltration, runoff and evaporation, Hydrol. Process., 17, 2423–2437, 2003.
Ramier, D., Berthier, E., and Andrieu, H.: The hydrological behaviour of urban streets: long-term observations and modelling of runoff losses and rainfall runoff transformation, Hydrol. Process., 25, 2161–2178, 2011.
Richards, L. A.: Capillary Conduction of Liquids Through Porous Mediums, Physics, 1, 318, https://doi.org/10.1063/1.1745010, 1931.
Rico-Ramirez, M. A., Liguori, S., and Schellart, A.: Quantifying radar rainfall uncertainties in urban drainage flow modelling, J. Hydrol., 528, 17–28, 2015.
Rodriguez-Iturbe, I. and Mejıa, J. M.: The design of rainfall networks in time and space, Water Resour. Res., 10, 713–728, https://doi.org/10.1029/WR010i004p00713, 1974.
Rossman, L. A.: Storm water management model user's manual, version 5.0, National Risk Management Research Laboratory, Office of Research and Development, US Environmental Protection Agency, Cincinnati, OH, USA, 2010.
Rummukainen, M.: Methods for statistical downscaling of GCM simulation, SWECLIM report, Rossby Centre, SMHI, Norrköping, Sweden, 1997.
Salvadore, E., Bronders, J., and Batelaan, O.: Hydrological modelling of urbanized catchments: A review and future directions, J. Hydrol., 529, 61–81, 2015.
Sangati, M., Borga, M., Rabuffeti, D., and Bechini, R.: Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: an evaluation based on the Sesia river basin, North Western Italy, Adv. Water Resour., 32, 1090–1106, 2009.
Schaake, J., Geyer, J., and Knapp, J.: Experimental examination of the rational method, Journal of Hydrological Division, 93, 353–370, 1967.
Schellart, A., Shepherd, W., and Saul, A.: Influence of rainfall estimation error and spatial variability on sewer flow prediction at a small urban scale, Adv. Water Resour., 45, 65–75, https://doi.org/10.1016/j.advwatres.2011.10.012, 2011.
Schertzer, D. and Lovejoy, S.: Multifractals, generalized scale invariance and complexity in geophysics, Int. J. Bifurcation Chaos, 21, 3417–3456, 2011.
Schilling, W.: Rainfall data for urban hydrology: What do we need?, Atmos. Res., 27, 5–21, 1991.
Segond, M.-L., Wheater, H. S., and Onof, C.: The significance of spatial rainfall representation for flood runoff estimation: A numerical evaluation based on the Lee catchment, UK, J. Hydrol., 347, 116–131, 2007.
Shamir, E., Imam, B., Morin, E., Gupta, H. V., and Sorooshian, S.: The role of hydrograph indices in parameter estimation of rainfall-runoff models, Hydrol. Process., 19, 2187–2207, 2005.
Shepherd, J. M.: Evidence of urban-induced precipitation variability in arid climate regimes, J. Arid Environ., 67, 607–628, 2006.
Shepherd, J. M., Pierce, H., and Negr, i. A. J.: Rainfall Modification by Major Urban Areas: Observations from Spaceborne Rain Radar on the TRMM Satellite, J. Appl. Meteor., 41, 689–701, 2002.
Singh, V. P.: Derivation of time of concentration, J. Hydrol., 30, 147–165, 1976.
Singh, V. P.: Effect of spatial and temporal variability in rainfall and watershed characteristics on stream flow hydrographs, Hydrol. Process., 11, 1649–1669, 1997.
Smith, A. J., Baeck, M. L., Morrison, J. E., Sturevant-Rees, P., Turner-Gillespie, D. F., and Bates, P. D.: The regional hydrology of extreme floods in an urbanizing drainage basin, American Meterological Society, 3, 267–282, 2002.
Smith, A. J., Baeck, M. L., Villarini, G., Welty, C., Miller, A. J., and Krajewski, W. F.: Analyses of a long term, high resolution radar rainfall data set for the Baltimore metropolitan region, Water Resour. Res., 48, W04504, https://doi.org/10.1029/2011WR010641, 2012.
Smith, B. K., Smith, A. J., Baeck, M. L., Villarini, G., and Wright, D. B.: Spectrum of storm event hydrologic response in urban watersheds, Water Resour. Res., 49, 2649–2663, 2013.
Smith, B. K., Smith, A. J., Baeck, M. L., and Miller, A. J.: Exploring storage and runoff generation processes for urban flooding through a physically based watershed model, Water Resour. Res., 51, 1552–1569, 2015.
Smith, J. A., Bradley, A. A., and Baeck, M. L.: The space-time structure of extreme storm rainfall on the Southern Plains, J. Appl. Meteorol., 33, 1402–1417, 1994.
Smith, J. A., Baeck, M. L., Meierdiercks, K. L., Nelson, P. A., Miller, A. J., and Holland, E. J.: Field studies of the storm event hydrologic response in an urbanizing watershed, Water Resour. Res., 41, W10413, https://doi.org/10.1029/2004WR003712, 2005.
Sørup, H. J. D., Christensen, O. B., Arnbjerg-Nielsen, K., and Mikkelsen, P. S.: Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator, Hydrol. Earth Syst. Sci., 20, 1387–1403, https://doi.org/10.5194/hess-20-1387-2016, 2016.
Stahl, K. and Hisdal, H.: Hydroclimatology in: Hydrological Drought – Processes and Estimation Methods, Elvisier, Amsterdam, the Netherlands, 19–51, 2004.
Thorndahl, S., Smith, J. A., Baeck, M. L., and Krajewski, W. F.: Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields, Atmos. Res., 144, 111–125, 2014.
Thorndahl, S., Einfalt, T., Willems, P., Nielsen, J. E., ten Veldhuis, M.-C., Arnbjerg-Nielsen, K., Rasmussen, M. R., and Molnar, P.: Weather radar rainfall data in urban hydrology, Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, 2017.
Tokarczyk, P., Leitao, J. P., Rieckermann, J., Schindler, K., and Blumensaat, F.: High-quality observation of surface imperviousness for urban runoff modelling using UAV imagery, Hydrol. Earth Syst. Sci., 19, 4215–4228, https://doi.org/10.5194/hess-19-4215-2015, 2015.
United States Department of Agriculture (USDA): Time of Concentration, in: National Engineering Handbook Hydrology, chap. 15, Part 630 Hydrology, eDirectives site, available at: https://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/national/water/manage/hydrology/?cid=stelprdb1043063 (last access: 26 July 2017), 2010.
van de Beek, C. Z., Leijnse, H., Stricker, J. N. M., Uijlenhoet, R., and Russchenberg, H. W. J.: Performance of high-resolution X-band radar for rainfall measurement in The Netherlands, Hydrol. Earth Syst. Sci., 14, 205–221, https://doi.org/10.5194/hess-14-205-2010, 2010.
van de Giesen, N., Stomph, T., and de Ridder, N.: Surface runoff scale effects in West African watersheds: modeling and management options, Agr. Water Manage., 72, 109–130, 2005.
van de Giesen, N., Stomph, T., Ebenezer Ajayi, A. E., and Bagayoko, F.: Scale effects in Hortonian surface runoff on agricultural slopes in West Africa: Field data and models, Agr. Ecosyst. Environ., 142, 95–101, 2011.
van de Ven, F. H. M.: Water balances of urban areas, Hydrological Processes and Water Management in Urban Areas, Proceedings of the Duisberg Symposium, 24–29 April 1988, Zoetermeer, the Netherlands, IAHS Publ., 198, 1990.
Van Loon, A. F.: Hydrological drought explaines, WIREs Water, 2, 359–392, 2015.
Versini, P. A., Gires, A., Abbes, J. B., Giangola-Murzyn, A., Tchinguirinskaia, I., and Schertzer, D.: Simulation of Green Roof Impact at Basin Scale by Using a Distributed Rainfall-Runoff Model, 13th International Conference on Urban Drainage (ICUD), 7–11 September 2014, Sarawak, Malaysia, 1–9, 2014.
Villarini, G., Mandapaka, P. V., Krajewski, W. F., and Moore, R. J.: Rainfall and sampling uncertainties: A rain gauge perspective, J. Geophys. Res.-Atmos., 113, D11102, https://doi.org/10.1029/2007jd009214, 2008.
Villarini, G., Seo, B. C., Serinaldi, F., and Krajewski, W. F.: Spatial and temporal modeling of radar rainfall uncertainties, Atmos. Res., 135–136, 91–101, https://doi.org/10.1016/j.atmosres.2013.09.007, 2014.
Wang, L. P., Ochoa-Rodriguez, S., Simoes, N., Onof, C., and Maksimovic, C.: Radar-raingauge data combination techniques: a revision and analysis of their suitability for urban hydrology, Water Sci. Technol., 68, 737–747, 2013.
Wang, L. P., Ochoa-Rodriguez, S., Onof, C., and Willems, P.: Singularity-sensitive gauge- based radar rainfall adjustment methods for urban hydrological applications, J. Hydrol., 531, 408–426, 2015a.
Wang, L. P., Ochoa-Rodriguez, S., van Assel, J., Pina, R. D., Pessemier, M., Kroll, S., Willems, P., and Onof, C.: Enhancement of radar rainfall estimates for urban hydrology through optical flow temporal interpolation and Bayesian gauge-based adjustement, J. Hydrol., 531, 408–426, https://doi.org/10.1016/j.jhydrol.2015.05.049, 2015b.
Wilby, R. and Wigley, T.: Downscaling general circulation model output: a review of methods and limitation, Prog. Phys. Geog., 21, 530–48, 1997.
Wilks, D. S. and Wilby, R. L.: The weather generation game: a review of stochastic weather models, Prog. Phys. Geog., 23, 329–357, 1999.
Winchell, M., Gupta, H. V., and Sorooshian, S.: On the simulation of infiltration and saturation excess runoff using radar based rainfall estimates: Effects of algorithm uncertainty and pixel aggregation, Water Resour. Res., 34, 2655–2670, 1998.
WMO, W. M. O.: Guide to Meteorological Instruments and Methods of Observation, Seventh edition, WMO-No. 8, Geneva, Switzerland, 2008.
Wood, S. J., Jones, D. A., and Moore, R. J.: Static and dynamic calibration of radar data for hydrological use, Hydrol. Earth Syst. Sci., 4, 545–554, https://doi.org/10.5194/hess-4-545-2000, 2000.
Wright, D., Smith, J., Villarini, G., and Baeck, M.: Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150–165, 2013.
Wright, D., Smith, J., and Baeck, M.: Flood frequency analysis using radar rainfall fields and stochastic storm transposition, Water Resour. Res., 50, 1592–1615, 2014.
Xu, C.: From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches, Prog. Phys. Geog., 23, 229–249, 1999.
Yang, L., Smith, J. A., Baeck, M. L., and Zhang, Y.: Flash flooding in small urban watersheds: storm event hydrological response, Water Resour. Res., 52, 4571–4589, https://doi.org/10.1002/2015WR018326, 2016.
Yao, L., Wei, W., and Chen, L.: How does imperviousness impact teh urban rainfall-runoff process under various storm cases?, Ecol. Indic., 60, 893–905, 2016.
Zoppou, C.: Review of urban storm water models, Environ. Model. Softw, 16, 195–231, 2000.
Short summary
In the last decades, new instruments were developed to measure rainfall and hydrological processes at high resolution. Weather radars are used, for example, to measure how rainfall varies in space and time. At the same time, new models were proposed to reproduce and predict hydrological response, in order to prevent flooding in urban areas. This paper presents a review of our current knowledge of rainfall and hydrological processes in urban areas, focusing on their variability in time and space.
In the last decades, new instruments were developed to measure rainfall and hydrological...
Special issue