Articles | Volume 23, issue 8
https://doi.org/10.5194/hess-23-3175-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3175-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
02 Aug 2019
Technical note |
| 02 Aug 2019
| 02 Aug 2019
Technical note: Stochastic simulation of streamflow time series using phase randomization
Manuela I. Brunner
CORRESPONDING AUTHOR
Mountain Hydrology and Mass Movements, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, ZH, Switzerland
András Bárdossy
Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart, Stuttgart, Germany
Reinhard Furrer
Institute of Mathematics, University of Zurich, Zurich, Switzerland
Related authors
Bailey J. Anderson, Manuela I. Brunner, Louise J. Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 28, 1567–1583, https://doi.org/10.5194/hess-28-1567-2024, https://doi.org/10.5194/hess-28-1567-2024, 2024
Short summary
Short summary
Elasticityrefers to how much the amount of water in a river changes with precipitation. We usually calculate this using average streamflow values; however, the amount of water within rivers is also dependent on stored water sources. Here, we look at how elasticity varies across the streamflow distribution and show that not only do low and high streamflows respond differently to precipitation change, but also these differences vary with water storage availability.
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
Short summary
Short summary
We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Manuela Irene Brunner
Hydrol. Earth Syst. Sci., 27, 2479–2497, https://doi.org/10.5194/hess-27-2479-2023, https://doi.org/10.5194/hess-27-2479-2023, 2023
Short summary
Short summary
I discuss different types of multivariate hydrological extremes and their dependencies, including regional extremes affecting multiple locations, such as spatially connected flood events; consecutive extremes occurring in close temporal succession, such as successive droughts; extremes characterized by multiple characteristics, such as floods with jointly high peak discharge and flood volume; and transitions between different types of extremes, such as drought-to-flood transitions.
Manuela Irene Brunner and Philippe Naveau
Hydrol. Earth Syst. Sci., 27, 673–687, https://doi.org/10.5194/hess-27-673-2023, https://doi.org/10.5194/hess-27-673-2023, 2023
Short summary
Short summary
Reservoir regulation affects various streamflow characteristics. Still, information on when water is stored in and released from reservoirs is hardly available. We develop a statistical model to reconstruct reservoir operation signals from observed streamflow time series. By applying this approach to 74 catchments in the Alps, we find that reservoir management varies by catchment elevation and that seasonal redistribution from summer to winter is strongest in high-elevation catchments.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
Short summary
Short summary
Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Manuela I. Brunner and Louise J. Slater
Hydrol. Earth Syst. Sci., 26, 469–482, https://doi.org/10.5194/hess-26-469-2022, https://doi.org/10.5194/hess-26-469-2022, 2022
Short summary
Short summary
Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System to increase the sample size available to estimate the frequency of extreme flood events. We demonstrate that such ensemble pooling produces more robust estimates than observation-based estimates.
Álvaro Ossandón, Manuela I. Brunner, Balaji Rajagopalan, and William Kleiber
Hydrol. Earth Syst. Sci., 26, 149–166, https://doi.org/10.5194/hess-26-149-2022, https://doi.org/10.5194/hess-26-149-2022, 2022
Short summary
Short summary
Timely projections of seasonal streamflow extremes on a river network can be useful for flood risk mitigation, but this is challenging, particularly under space–time nonstationarity. We develop a space–time Bayesian hierarchical model (BHM) using temporal climate covariates and copulas to project seasonal streamflow extremes and the attendant uncertainties. We demonstrate this on the Upper Colorado River basin to project spring flow extremes using the preceding winter’s climate teleconnections.
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634, https://doi.org/10.5194/esd-12-621-2021, https://doi.org/10.5194/esd-12-621-2021, 2021
Short summary
Short summary
Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Here, we show that the spatial extent and timescale of compound hot–dry events are strongly related, spatial compound event extents are largest at
sub-seasonal timescales, and short events are driven more by high temperatures, while longer events are more driven by low precipitation. Future climate impact studies should therefore be performed at different timescales.
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119, https://doi.org/10.5194/hess-25-105-2021, https://doi.org/10.5194/hess-25-105-2021, 2021
Short summary
Short summary
Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable model ideally reproduces both local flood characteristics and regional aspects of flooding. In this paper we investigate how such characteristics are represented by hydrologic models. Our results show that both the modeling of local and regional flood characteristics are challenging, especially under changing climate conditions.
Manuela I. Brunner and Eric Gilleland
Hydrol. Earth Syst. Sci., 24, 3967–3982, https://doi.org/10.5194/hess-24-3967-2020, https://doi.org/10.5194/hess-24-3967-2020, 2020
Short summary
Short summary
Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but yet unobserved streamflow time series with the same characteristics as the observed data. We propose a stochastic simulation approach in the frequency domain instead of the time domain. Our evaluation results suggest that the flexible, continuous simulation approach is valuable for a diverse range of water management applications.
Manuela I. Brunner, Lieke A. Melsen, Andrew J. Newman, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 24, 3951–3966, https://doi.org/10.5194/hess-24-3951-2020, https://doi.org/10.5194/hess-24-3951-2020, 2020
Short summary
Short summary
Streamflow seasonality is changing and expected to further change under the influence of climate change. We here assess how annual streamflow hydrographs will change in future by using a newly developed classification scheme. Our comparison of future with current annual hydrograph classes shows that robust changes are expected only for currently melt-influenced regions in the Rocky Mountains. These upstream changes may require the adaptation of management strategies in downstream regions.
Manuela I. Brunner, Daniel Farinotti, Harry Zekollari, Matthias Huss, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019, https://doi.org/10.5194/hess-23-4471-2019, 2019
Short summary
Short summary
River flow regimes are expected to change and so are extreme flow regimes. We propose two methods for estimating extreme flow regimes and show on a data set from Switzerland how these extreme regimes are expected to change. Our results show that changes in low- and high-flow regimes are distinct for rainfall- and melt-dominated regions. Our findings provide guidance in water resource planning and management.
Manuela I. Brunner, Katharina Liechti, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci., 19, 2311–2323, https://doi.org/10.5194/nhess-19-2311-2019, https://doi.org/10.5194/nhess-19-2311-2019, 2019
Short summary
Short summary
The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The return period estimates depended on the region, variable, and return period considered.
Manuela I. Brunner, Reinhard Furrer, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 23, 107–124, https://doi.org/10.5194/hess-23-107-2019, https://doi.org/10.5194/hess-23-107-2019, 2019
Short summary
Short summary
Floods often affect a whole region and not only a single location. When estimating the rarity of regional events, the dependence of floods at different locations should be taken into account. We propose a simple model that considers the dependence of flood events at different locations and the network structure of the river system. We test this model on a medium-sized catchment in Switzerland. The model allows for the simulations of flood event sets at multiple gauged and ungauged locations.
Bailey J. Anderson, Manuela I. Brunner, Louise J. Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 28, 1567–1583, https://doi.org/10.5194/hess-28-1567-2024, https://doi.org/10.5194/hess-28-1567-2024, 2024
Short summary
Short summary
Elasticityrefers to how much the amount of water in a river changes with precipitation. We usually calculate this using average streamflow values; however, the amount of water within rivers is also dependent on stored water sources. Here, we look at how elasticity varies across the streamflow distribution and show that not only do low and high streamflows respond differently to precipitation change, but also these differences vary with water storage availability.
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
Short summary
Short summary
We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Marvin Höge, Martina Kauzlaric, Rosi Siber, Ursula Schönenberger, Pascal Horton, Jan Schwanbeck, Marius Günter Floriancic, Daniel Viviroli, Sibylle Wilhelm, Anna E. Sikorska-Senoner, Nans Addor, Manuela Brunner, Sandra Pool, Massimiliano Zappa, and Fabrizio Fenicia
Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, https://doi.org/10.5194/essd-15-5755-2023, 2023
Short summary
Short summary
CAMELS-CH is an open large-sample hydro-meteorological data set that covers 331 catchments in hydrologic Switzerland from 1 January 1981 to 31 December 2020. It comprises (a) daily data of river discharge and water level as well as meteorologic variables like precipitation and temperature; (b) yearly glacier and land cover data; (c) static attributes of, e.g, topography or human impact; and (d) catchment delineations. CAMELS-CH enables water and climate research and modeling at catchment level.
Manuela Irene Brunner
Hydrol. Earth Syst. Sci., 27, 2479–2497, https://doi.org/10.5194/hess-27-2479-2023, https://doi.org/10.5194/hess-27-2479-2023, 2023
Short summary
Short summary
I discuss different types of multivariate hydrological extremes and their dependencies, including regional extremes affecting multiple locations, such as spatially connected flood events; consecutive extremes occurring in close temporal succession, such as successive droughts; extremes characterized by multiple characteristics, such as floods with jointly high peak discharge and flood volume; and transitions between different types of extremes, such as drought-to-flood transitions.
Manuela Irene Brunner and Philippe Naveau
Hydrol. Earth Syst. Sci., 27, 673–687, https://doi.org/10.5194/hess-27-673-2023, https://doi.org/10.5194/hess-27-673-2023, 2023
Short summary
Short summary
Reservoir regulation affects various streamflow characteristics. Still, information on when water is stored in and released from reservoirs is hardly available. We develop a statistical model to reconstruct reservoir operation signals from observed streamflow time series. By applying this approach to 74 catchments in the Alps, we find that reservoir management varies by catchment elevation and that seasonal redistribution from summer to winter is strongest in high-elevation catchments.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
Short summary
Short summary
Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Manuela I. Brunner and Louise J. Slater
Hydrol. Earth Syst. Sci., 26, 469–482, https://doi.org/10.5194/hess-26-469-2022, https://doi.org/10.5194/hess-26-469-2022, 2022
Short summary
Short summary
Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System to increase the sample size available to estimate the frequency of extreme flood events. We demonstrate that such ensemble pooling produces more robust estimates than observation-based estimates.
Álvaro Ossandón, Manuela I. Brunner, Balaji Rajagopalan, and William Kleiber
Hydrol. Earth Syst. Sci., 26, 149–166, https://doi.org/10.5194/hess-26-149-2022, https://doi.org/10.5194/hess-26-149-2022, 2022
Short summary
Short summary
Timely projections of seasonal streamflow extremes on a river network can be useful for flood risk mitigation, but this is challenging, particularly under space–time nonstationarity. We develop a space–time Bayesian hierarchical model (BHM) using temporal climate covariates and copulas to project seasonal streamflow extremes and the attendant uncertainties. We demonstrate this on the Upper Colorado River basin to project spring flow extremes using the preceding winter’s climate teleconnections.
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634, https://doi.org/10.5194/esd-12-621-2021, https://doi.org/10.5194/esd-12-621-2021, 2021
Short summary
Short summary
Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Here, we show that the spatial extent and timescale of compound hot–dry events are strongly related, spatial compound event extents are largest at
sub-seasonal timescales, and short events are driven more by high temperatures, while longer events are more driven by low precipitation. Future climate impact studies should therefore be performed at different timescales.
András Bárdossy, Jochen Seidel, and Abbas El Hachem
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, https://doi.org/10.5194/hess-25-583-2021, 2021
Short summary
Short summary
In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119, https://doi.org/10.5194/hess-25-105-2021, https://doi.org/10.5194/hess-25-105-2021, 2021
Short summary
Short summary
Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable model ideally reproduces both local flood characteristics and regional aspects of flooding. In this paper we investigate how such characteristics are represented by hydrologic models. Our results show that both the modeling of local and regional flood characteristics are challenging, especially under changing climate conditions.
Manuela I. Brunner and Eric Gilleland
Hydrol. Earth Syst. Sci., 24, 3967–3982, https://doi.org/10.5194/hess-24-3967-2020, https://doi.org/10.5194/hess-24-3967-2020, 2020
Short summary
Short summary
Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but yet unobserved streamflow time series with the same characteristics as the observed data. We propose a stochastic simulation approach in the frequency domain instead of the time domain. Our evaluation results suggest that the flexible, continuous simulation approach is valuable for a diverse range of water management applications.
Manuela I. Brunner, Lieke A. Melsen, Andrew J. Newman, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 24, 3951–3966, https://doi.org/10.5194/hess-24-3951-2020, https://doi.org/10.5194/hess-24-3951-2020, 2020
Short summary
Short summary
Streamflow seasonality is changing and expected to further change under the influence of climate change. We here assess how annual streamflow hydrographs will change in future by using a newly developed classification scheme. Our comparison of future with current annual hydrograph classes shows that robust changes are expected only for currently melt-influenced regions in the Rocky Mountains. These upstream changes may require the adaptation of management strategies in downstream regions.
Jieru Yan, András Bárdossy, Sebastian Hörning, and Tao Tao
Hydrol. Earth Syst. Sci., 24, 2287–2301, https://doi.org/10.5194/hess-24-2287-2020, https://doi.org/10.5194/hess-24-2287-2020, 2020
Short summary
Short summary
For applications such as flood forecasting of urban- or town-scale distributed hydrological modeling, high-resolution quantitative precipitation estimation (QPE) with enough accuracy is the most important driving factor and thus the focus of this paper. Considering the fact that rain gauges are sparse but accurate and radar-based precipitation estimates are inaccurate but densely distributed, we are merging the two types of data intellectually to obtain accurate QPEs with high resolution.
Manuela I. Brunner, Daniel Farinotti, Harry Zekollari, Matthias Huss, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019, https://doi.org/10.5194/hess-23-4471-2019, 2019
Short summary
Short summary
River flow regimes are expected to change and so are extreme flow regimes. We propose two methods for estimating extreme flow regimes and show on a data set from Switzerland how these extreme regimes are expected to change. Our results show that changes in low- and high-flow regimes are distinct for rainfall- and melt-dominated regions. Our findings provide guidance in water resource planning and management.
Manuela I. Brunner, Katharina Liechti, and Massimiliano Zappa
Nat. Hazards Earth Syst. Sci., 19, 2311–2323, https://doi.org/10.5194/nhess-19-2311-2019, https://doi.org/10.5194/nhess-19-2311-2019, 2019
Short summary
Short summary
The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The return period estimates depended on the region, variable, and return period considered.
Yingchun Huang, András Bárdossy, and Ke Zhang
Hydrol. Earth Syst. Sci., 23, 2647–2663, https://doi.org/10.5194/hess-23-2647-2019, https://doi.org/10.5194/hess-23-2647-2019, 2019
Short summary
Short summary
This study investigates whether higher temporal and spatial resolution of rainfall can lead to improved model performance. Four rainfall datasets were used to drive lumped and distributed HBV models to simulate daily discharges. Results show that a higher temporal resolution of rainfall improves the model performance if the station density is high. A combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement of the tested models.
Henning Lebrenz and András Bárdossy
Hydrol. Earth Syst. Sci., 23, 1633–1648, https://doi.org/10.5194/hess-23-1633-2019, https://doi.org/10.5194/hess-23-1633-2019, 2019
Short summary
Short summary
Many variables, e.g., in hydrology, geology, and social sciences, are only observed at a few distinct measurement locations, and their actual distribution in the entire space remains unknown. We introduce the new geostatistical interpolation method of
quantile kriging, providing an improved estimator and associated uncertainty. It can also host variables, which would not fulfill the implicit presumptions of the traditional geostatistical interpolation methods.
Jens Grundmann, Sebastian Hörning, and András Bárdossy
Hydrol. Earth Syst. Sci., 23, 225–237, https://doi.org/10.5194/hess-23-225-2019, https://doi.org/10.5194/hess-23-225-2019, 2019
Manuela I. Brunner, Reinhard Furrer, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 23, 107–124, https://doi.org/10.5194/hess-23-107-2019, https://doi.org/10.5194/hess-23-107-2019, 2019
Short summary
Short summary
Floods often affect a whole region and not only a single location. When estimating the rarity of regional events, the dependence of floods at different locations should be taken into account. We propose a simple model that considers the dependence of flood events at different locations and the network structure of the river system. We test this model on a medium-sized catchment in Switzerland. The model allows for the simulations of flood event sets at multiple gauged and ungauged locations.
Tobias Mosthaf and András Bárdossy
Hydrol. Earth Syst. Sci., 21, 2463–2481, https://doi.org/10.5194/hess-21-2463-2017, https://doi.org/10.5194/hess-21-2463-2017, 2017
Short summary
Short summary
Parametric distribution functions are commonly used to model precipitation amounts at gauged and ungauged locations. Nonparametric distributions offer a more flexible way to model precipitation amounts. However, the nonparametric models do not exhibit parameters that can be easily regionalized for application at ungauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate the usage of daily gauges for sub-daily resolutions.
András Bárdossy, Yingchun Huang, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 20, 2913–2928, https://doi.org/10.5194/hess-20-2913-2016, https://doi.org/10.5194/hess-20-2913-2016, 2016
Short summary
Short summary
This paper explores the simultaneous calibration method to transfer model parameters from gauged to ungauged catchments. It is hypothesized that the model parameters can be separated into two categories: one reflecting the dynamic behavior and the other representing the long-term water balance. The results of three numerical experiments indicate that a good parameter transfer to ungauged catchments can be achieved through simultaneous calibration of models for a number of catchments.
Takayuki Sugimoto, András Bárdossy, Geoffrey G. S. Pegram, and Johannes Cullmann
Hydrol. Earth Syst. Sci., 20, 2705–2720, https://doi.org/10.5194/hess-20-2705-2016, https://doi.org/10.5194/hess-20-2705-2016, 2016
Short summary
Short summary
This paper is aims to detect the climate change impacts on the hydrological regime from the long-term discharge records. A new method for stochastic analysis using copulas, which has the advantage of scrutinizing the data independent of marginal, is suggested in this paper. Two measures are used in the copula domain: one focuses on the asymmetric characteristic of data and the other compares the distances between the copulas. These are calculated for 100 years of daily discharges and the results are discussed.
Related subject area
Subject: Engineering Hydrology | Techniques and Approaches: Stochastic approaches
Uncertainty estimation of regionalised depth–duration–frequency curves in Germany
FarmCan: a physical, statistical, and machine learning model to forecast crop water deficit for farms
Identifying sensitivities in flood frequency analyses using a stochastic hydrologic modeling system
Characteristics and process controls of statistical flood moments in Europe – a data-based analysis
Objective functions for information-theoretical monitoring network design: what is “optimal”?
Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach
Numerical investigation on the power of parametric and nonparametric tests for trend detection in annual maximum series
Spatially dependent flood probabilities to support the design of civil infrastructure systems
Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice
Ensemble modeling of stochastic unsteady open-channel flow in terms of its time–space evolutionary probability distribution – Part 1: theoretical development
Ensemble modeling of stochastic unsteady open-channel flow in terms of its time–space evolutionary probability distribution – Part 2: numerical application
Characterizing the spatial variations and correlations of large rainstorms for landslide study
Assessment of extreme flood events in a changing climate for a long-term planning of socio-economic infrastructure in the Russian Arctic
Dealing with uncertainty in the probability of overtopping of a flood mitigation dam
Flood frequency analysis of historical flood data under stationary and non-stationary modelling
Selection of intense rainfall events based on intensity thresholds and lightning data in Switzerland
Towards modelling flood protection investment as a coupled human and natural system
A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation
Examination of homogeneity of selected Irish pooling groups
Estimation of high return period flood quantiles using additional non-systematic information with upper bounded statistical models
Design flood hydrographs from the relationship between flood peak and volume
Introducing empirical and probabilistic regional envelope curves into a mixed bounded distribution function
HESS Opinions "A random walk on water"
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 2075–2097, https://doi.org/10.5194/hess-27-2075-2023, https://doi.org/10.5194/hess-27-2075-2023, 2023
Short summary
Short summary
Design rainfall volumes at different duration and frequencies are necessary for the planning of water-related systems and facilities. As the procedure for deriving these values is subjected to different sources of uncertainty, here we explore different methods to estimate how precise these values are for different duration, locations and frequencies in Germany. Combining local and spatial simulations, we estimate tolerance ranges from approx. 10–60% for design rainfall volumes in Germany.
Sara Sadri, James S. Famiglietti, Ming Pan, Hylke E. Beck, Aaron Berg, and Eric F. Wood
Hydrol. Earth Syst. Sci., 26, 5373–5390, https://doi.org/10.5194/hess-26-5373-2022, https://doi.org/10.5194/hess-26-5373-2022, 2022
Short summary
Short summary
A farm-scale hydroclimatic machine learning framework to advise farmers was developed. FarmCan uses remote sensing data and farmers' input to forecast crop water deficits. The 8 d composite variables are better than daily ones for forecasting water deficit. Evapotranspiration (ET) and potential ET are more effective than soil moisture at predicting crop water deficit. FarmCan uses a crop-specific schedule to use surface or root zone soil moisture.
Andrew J. Newman, Amanda G. Stone, Manabendra Saharia, Kathleen D. Holman, Nans Addor, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 5603–5621, https://doi.org/10.5194/hess-25-5603-2021, https://doi.org/10.5194/hess-25-5603-2021, 2021
Short summary
Short summary
This study assesses methods that estimate flood return periods to identify when we would obtain a large flood return estimate change if the method or input data were changed (sensitivities). We include an examination of multiple flood-generating models, which is a novel addition to the flood estimation literature. We highlight the need to select appropriate flood models for the study watershed. These results will help operational water agencies develop more robust risk assessments.
David Lun, Alberto Viglione, Miriam Bertola, Jürgen Komma, Juraj Parajka, Peter Valent, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 5535–5560, https://doi.org/10.5194/hess-25-5535-2021, https://doi.org/10.5194/hess-25-5535-2021, 2021
Short summary
Short summary
We investigate statistical properties of observed flood series on a European scale. There are pronounced regional patterns, for instance: regions with strong Atlantic influence show less year-to-year variability in the magnitude of observed floods when compared with more arid regions of Europe. The hydrological controls on the patterns are quantified and discussed. On the European scale, climate seems to be the dominant driver for the observed patterns.
Hossein Foroozand and Steven V. Weijs
Hydrol. Earth Syst. Sci., 25, 831–850, https://doi.org/10.5194/hess-25-831-2021, https://doi.org/10.5194/hess-25-831-2021, 2021
Short summary
Short summary
In monitoring network design, we have to decide what to measure, where to measure, and when to measure. In this paper, we focus on the question of where to measure. Past literature has used the concept of information to choose a selection of locations that provide maximally informative data. In this paper, we look in detail at the proper mathematical formulation of the information concept as an objective. We argue that previous proposals for this formulation have been needlessly complicated.
Manuela I. Brunner and Eric Gilleland
Hydrol. Earth Syst. Sci., 24, 3967–3982, https://doi.org/10.5194/hess-24-3967-2020, https://doi.org/10.5194/hess-24-3967-2020, 2020
Short summary
Short summary
Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but yet unobserved streamflow time series with the same characteristics as the observed data. We propose a stochastic simulation approach in the frequency domain instead of the time domain. Our evaluation results suggest that the flexible, continuous simulation approach is valuable for a diverse range of water management applications.
Vincenzo Totaro, Andrea Gioia, and Vito Iacobellis
Hydrol. Earth Syst. Sci., 24, 473–488, https://doi.org/10.5194/hess-24-473-2020, https://doi.org/10.5194/hess-24-473-2020, 2020
Short summary
Short summary
We highlight the need for power evaluation in the application of null hypothesis significance tests for trend detection in extreme event analysis. In a wide range of conditions, depending on the underlying distribution of data, the test power may reach unacceptably low values. We propose the use of a parametric approach, based on model selection criteria, that allows one to choose the null hypothesis, to select the level of significance, and to check the test power using Monte Carlo experiments.
Phuong Dong Le, Michael Leonard, and Seth Westra
Hydrol. Earth Syst. Sci., 23, 4851–4867, https://doi.org/10.5194/hess-23-4851-2019, https://doi.org/10.5194/hess-23-4851-2019, 2019
Short summary
Short summary
While conventional approaches focus on flood designs at individual locations, there are many situations requiring an understanding of spatial dependence of floods at multiple locations. This research describes a new framework for analyzing flood characteristics across civil infrastructure systems, including conditional and joint probabilities of floods. This work leads to a new flood estimation paradigm, which focuses on the risk of the entire system rather than each system element in isolation.
Cong Jiang, Lihua Xiong, Lei Yan, Jianfan Dong, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 23, 1683–1704, https://doi.org/10.5194/hess-23-1683-2019, https://doi.org/10.5194/hess-23-1683-2019, 2019
Short summary
Short summary
We present the methods addressing the multivariate hydrologic design applied to the engineering practice under nonstationary conditions. A dynamic C-vine copula allowing for both time-varying marginal distributions and a time-varying dependence structure is developed to capture the nonstationarities of multivariate flood distribution. Then, the multivariate hydrologic design under nonstationary conditions is estimated through specifying the design criterion by average annual reliability.
Alain Dib and M. Levent Kavvas
Hydrol. Earth Syst. Sci., 22, 1993–2005, https://doi.org/10.5194/hess-22-1993-2018, https://doi.org/10.5194/hess-22-1993-2018, 2018
Short summary
Short summary
A new method is proposed to solve the stochastic unsteady open-channel flow system in only one single simulation, as opposed to the many simulations usually done in the popular Monte Carlo approach. The derivation of this new method gave a deterministic and linear Fokker–Planck equation whose solution provided a powerful and effective approach for quantifying the ensemble behavior and variability of such a stochastic system, regardless of the number of parameters causing its uncertainty.
Alain Dib and M. Levent Kavvas
Hydrol. Earth Syst. Sci., 22, 2007–2021, https://doi.org/10.5194/hess-22-2007-2018, https://doi.org/10.5194/hess-22-2007-2018, 2018
Short summary
Short summary
A newly proposed method is applied to solve a stochastic unsteady open-channel flow system (with an uncertain roughness coefficient) in only one simulation. After comparing its results to those of the Monte Carlo simulations, the new method was found to adequately predict the temporal and spatial evolution of the probability density of the flow variables of the system. This revealed the effectiveness, strength, and time efficiency of this new method as compared to other popular approaches.
Liang Gao, Limin Zhang, and Mengqian Lu
Hydrol. Earth Syst. Sci., 21, 4573–4589, https://doi.org/10.5194/hess-21-4573-2017, https://doi.org/10.5194/hess-21-4573-2017, 2017
Short summary
Short summary
Rainfall is the primary trigger of landslides. However, the rainfall intensity is not uniform in space, which causes more landslides in the area of intense rainfall. The primary objective of this paper is to quantify spatial correlation characteristics of three landslide-triggering large storms in Hong Kong. The spatial maximum rolling rainfall is represented by a trend surface and a random field of residuals. The scales of fluctuation of the residuals are found between 5 km and 30 km.
Elena Shevnina, Ekaterina Kourzeneva, Viktor Kovalenko, and Timo Vihma
Hydrol. Earth Syst. Sci., 21, 2559–2578, https://doi.org/10.5194/hess-21-2559-2017, https://doi.org/10.5194/hess-21-2559-2017, 2017
Short summary
Short summary
This paper presents the probabilistic approach to evaluate design floods in a changing climate, adapted in this case to the northern territories. For the Russian Arctic, the regions are delineated, where it is suggested to correct engineering hydrological calculations to account for climate change. An example of the calculation of a maximal discharge of 1 % exceedance probability for the Nadym River at Nadym is provided.
Eleni Maria Michailidi and Baldassare Bacchi
Hydrol. Earth Syst. Sci., 21, 2497–2507, https://doi.org/10.5194/hess-21-2497-2017, https://doi.org/10.5194/hess-21-2497-2017, 2017
Short summary
Short summary
In this research, we explored how the sampling uncertainty of flood variables (flood peak, volume, etc.) can reflect on a structural variable, which in our case was the maximum water level (MWL) of a reservoir controlled by a dam. Next, we incorporated additional information from different sources for a better estimation of the uncertainty in the probability of exceedance of the MWL. Results showed the importance of providing confidence intervals in the risk assessment of a structure.
M. J. Machado, B. A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito
Hydrol. Earth Syst. Sci., 19, 2561–2576, https://doi.org/10.5194/hess-19-2561-2015, https://doi.org/10.5194/hess-19-2561-2015, 2015
Short summary
Short summary
A flood frequency analysis using a 400-year historical flood record was carried out using a stationary model (based on maximum likelihood estimators) and a non-stationary model that incorporates external covariates (climatic and environmental). The stationary model was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.
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
P. E. O'Connell and G. O'Donnell
Hydrol. Earth Syst. Sci., 18, 155–171, https://doi.org/10.5194/hess-18-155-2014, https://doi.org/10.5194/hess-18-155-2014, 2014
A. I. Requena, L. Mediero, and L. Garrote
Hydrol. Earth Syst. Sci., 17, 3023–3038, https://doi.org/10.5194/hess-17-3023-2013, https://doi.org/10.5194/hess-17-3023-2013, 2013
S. Das and C. Cunnane
Hydrol. Earth Syst. Sci., 15, 819–830, https://doi.org/10.5194/hess-15-819-2011, https://doi.org/10.5194/hess-15-819-2011, 2011
B. A. Botero and F. Francés
Hydrol. Earth Syst. Sci., 14, 2617–2628, https://doi.org/10.5194/hess-14-2617-2010, https://doi.org/10.5194/hess-14-2617-2010, 2010
L. Mediero, A. Jiménez-Álvarez, and L. Garrote
Hydrol. Earth Syst. Sci., 14, 2495–2505, https://doi.org/10.5194/hess-14-2495-2010, https://doi.org/10.5194/hess-14-2495-2010, 2010
B. Guse, Th. Hofherr, and B. Merz
Hydrol. Earth Syst. Sci., 14, 2465–2478, https://doi.org/10.5194/hess-14-2465-2010, https://doi.org/10.5194/hess-14-2465-2010, 2010
D. Koutsoyiannis
Hydrol. Earth Syst. Sci., 14, 585–601, https://doi.org/10.5194/hess-14-585-2010, https://doi.org/10.5194/hess-14-585-2010, 2010
Cited articles
Blum, A. G., Archfield, S. A., and Vogel, R. M.: On the probability distribution of daily streamflow in the United States, Hydrol. Earth Syst. Sci., 21, 3093–3103, https://doi.org/10.5194/hess-21-3093-2017, 2017. a, b, c
Borgomeo, E., Farmer, C. L., and Hall, J. W.: Numerical rivers: A synthetic
streamflow generator for water resources vulnerability assessments, Water
Resour. Res., 51, 5382–5405, https://doi.org/10.1002/2014WR016259, 2015. a, b, c
Bracken, C., Rajagopalan, B., and Zagona, E.: A hidden Markov model combined
with climate indices for multidecadal streamflow simulation, Water Resour. Res., 50, 7836–7846, https://doi.org/10.1002/2014WR015567, 2014. a
Brunner, M. I. and Furrer, R.: PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization, CRAN, available at: https://cran.r-project.org/web/packages/PRSim/index.html, last access: July 2019. a
Burr, I. W.: Cumulative frequency functions, Ann. Math. Stat., 13, 215–232, 1942. a
Cario, M. C. and Nelson, B. L.: Autoregressive to anything: Time-series input
processes for simulation, Operat. Res. Lett., 19, 51–58,
https://doi.org/10.1016/0167-6377(96)00017-X, 1996. a
Embrechts, P., McNeil, A. J., and Straumann, D.: Correlation and dependence in risk management: Properties and pitfalls, chap. 7, in: Risk Management, edited by: Dempster, M. A. H., Cambridge University Press, Cambridge, 176–223, https://doi.org/10.1017/cbo9780511615337.008, 2010. a
Erkyihun, S. T., Rajagopalan, B., Zagona, E., Lall, U., and Nowak, K.:
Wavelet-based time series bootstrap model for multidecadal streamflow
simulation using climate indicators, Water Resour. Res., 52, 4061–4077, https://doi.org/10.1002/2016WR018696, 2016. a
Fleming, S. W., Marsh Lavenue, A., Aly, A. H., and Adams, A.: Practical
applications of spectral analysis of hydrologic time series, Hydrol. Process., 16, 565–574, https://doi.org/10.1002/hyp.523, 2002. a, b
FOEN – Federal Office for the Environment: Hydrological Data Service for watercourses and lakes, Hydrol. Data Serv., available at: https://www.bafu.admin.ch/bafu/en/home/topics/water/state/data/obtaining-monitoring-data-on-the-topic-of-water/hydrological-data-service-for-watercourses-and-lakes.html
(last access: July 2019), 2009. a
Griffiths, G. A.: A theoretically based Wakeby distribution for annual flood
series, Hydrolog. Sci. J., 34, 231–248, https://doi.org/10.1080/02626668909491332, 1989. a
Grygier, J. A. N. C. and Stedinger, J. R.: Condensed disaggregation procedures and conservation corrections for stochastic hydrology, Water Resour. Manage., 24, 1574–1584, 1988. a
Herman, J. D., Reed, P. M., Zeff, H. B., Characklis, G. W., and Lamontagne, J.: Synthetic drought scenario generation to support bottom-up water supply
vulnerability assessments, J. Water Resour. Pl. Manage., 142, 1–13, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000701, 2016. a, b, c
Hörning, S. and Bárdossy, A.: Phase annealing for the conditional
simulation of spatial random fields, Comput. Geosci., 112, 101–111, https://doi.org/10.1016/j.cageo.2017.12.008, 2018. a
Hosking, J. R. M.: Modeling persistence in hydrological time series using
fractional differencing, Water Resour. Res., 20, 1898–1908,
https://doi.org/10.1029/WR020i012p01898, 1984. a
Houghton, J. C.: Birth of a parent: The Wakeby Distribution for modeling flood flows, Water Resour. Res., 14, 1105–1109, https://doi.org/10.1029/WR014i006p01105, 1978. a
Ilich, N.: An effective three-step algorithm for multi-site generation of
stochastic weekly hydrological time series, Hydrolog. Sci. J., 59, 85–98, https://doi.org/10.1080/02626667.2013.822643, 2014. a
Keylock, C. J.: A wavelet-based method for surrogate data generation, Physica D, 225, 219–228, https://doi.org/10.1016/j.physd.2006.10.012, 2007. a
Keylock, C. J.: A resampling method for generating synthetic hydrological time series with preservation of cross-correlative structure and higher-order
properties, Water Resour. Res., 48, 1–18, https://doi.org/10.1029/2012WR011923, 2012. a
Kim, J. S., Huh, Y., and Suh, M. W.: A method to generate autocorrelated
stochastic signals based on the random phase spectrum, J. Text. Inst., 101, 471–479, https://doi.org/10.1080/14685240802528443, 2010. a, b
Koutsoyiannis, D.: Generic and parsimonious stochastic modelling for hydrology and beyond, Hydrolog. Sci. J., 61, 225–244,
https://doi.org/10.1080/02626667.2015.1016950, 2016. a
Koutsoyiannis, D.: Time's arrow in stochastic characterization and
simulation of atmospheric and hydrological processes, Hydrolog. Sci. J., 64, 1013–1037, https://doi.org/10.1080/02626667.2019.1600700, 2019. a
Kugiumtzis, D.: Test your surrogate data before you test for nonlinearity,
Phyd. Rev. E, 60, 2808–2816, https://doi.org/10.1103/PhysRevE.60.2808, 1999. a
Kwon, H. H., Lall, U., and Khalil, A. F.: Stochastic simulation model for
nonstationary time series using an autoregressive wavelet decomposition:
Applications to rainfall and temperature, Water Resour. Res., 43, 1–15, https://doi.org/10.1029/2006WR005258, 2007. a
Lall, U. and Sharma, A.: A nearest neighbor bootstrap for resampling
hydrologic time series, Water Resour. Res., 32, 679–693, 1996. a
Lancaster, G., Iatsenko, D., Pidde, A., Ticcinelli, V., and Stefanovska, A.:
Surrogate data for hypothesis testing of physical systems, Phys. Rep., 748, 1–60, https://doi.org/10.1016/j.physrep.2018.06.001, 2018. a
Lee, T. and Salas, J. D.: Copula-based stochastic simulation of hydrological
data applied to Nile River flows, Hydrol. Res., 42, 318–330, https://doi.org/10.2166/nh.2011.085, 2011. a, b
Li, S. T. and Hammond, J. L.: Generation of Pseudorandom Numbers with Specified Univariate Distributions and Correlation Coefficients, IEEE T. Syst. Man Cybernet., SMC-5, 557–561, https://doi.org/10.1109/TSMC.1975.5408380, 1975. a
Maiwald, T., Mammen, E., Nandi, S., and Timmer, J.: Surrogate data – A
qualitative and quantitative analysis, in: Mathematical methods in time series analysis and digital image processing, chap. 2, edited by: Dahlhaus, R., Kurths, J., Maass, P., and Timmer, J., 41–74, Springer, Berlin, Heidelberg, 2008. a, b, c, d
Mandelbrot, B. B.: Une classe de processus stochastiques homothetiques a soi: Application a la loi climatologique de H. E. Hurst, Comptes rendus de l'Académie des sciences, 260, 3274–3276, 1965. a
Mandelbrot, B. B.: A fast fractional Gaussian noise generator, Water Resour. Res., 7, 543–553, 1971. a
Mehrotra, R. and Sharma, A.: A nonparametric stochastic downscaling framework
for daily rainfall at multiple locations, J. Geophys. Res.-Atmos., 111, 1–16, https://doi.org/10.1029/2005JD006637, 2006. a
Mejia, J. M., Rodriguez-Iturbe, I., and Dawdy, D. R.: Streamflow simulation:
2. The broken line process as a potential model for hydrologic simulation,
Water Resour. Res., 8, 931–941, https://doi.org/10.1029/WR008i004p00931, 1972. a
Mielke, P. W.: Another family of distributions for describing and analyzing
precipitation data, J. Appl. Meteorol., 12, 275–280, 1973. a
Nguyen, H., Mehrotra, R., and Sharma, A.: Correcting systematic biases across multiple atmospheric variables in the frequency domain, Clim. Dynam., 52, 1283–1298, https://doi.org/10.1007/s00382-018-4191-6, 2019. a
Papalexiou, S. M.: Unified theory for stochastic modelling of hydroclimatic
processes: Preserving marginal distributions, correlation structures, and
intermittency, Adv. Water Resour., 115, 234–252,
https://doi.org/10.1016/j.advwatres.2018.02.013, 2018. a, b, c, d
Pender, D., Patidar, S., Pender, G., and Haynes, H.: Stochastic simulation of daily streamflow sequences using a hidden Markov model, Hydrol. Res., 47, 75–88, https://doi.org/10.2166/nh.2015.114, 2015. a, b, c, d
Prairie, J., Nowak, K., Rajagopalan, B., Lall, U., and Fulp, T.: A stochastic
nonparametric approach for streamflow generation combining observational and paleoreconstructed data, Water Resour. Res., 44, 1–11,
https://doi.org/10.1029/2007WR006684, 2008. a
Radziejewski, M., Bardossy, A., and Kundzewicz, Z.: Detection of change in
river flow using phase randomization, Hydrolog. Sci. J., 45, 547–558, https://doi.org/10.1080/02626660009492356, 2000. a, b
Schmitz, A. and Schreiber, T.: Improved surrogate data for nonlinearity
tests, Phys. Rev. Lett., 77, 635–638, https://doi.org/10.1103/PhysRevLett.77.635, 1996. a
Schreiber, T. and Schmitz, A.: Surrogate time series, Physica D, 142, 346–382, https://doi.org/10.1016/S0167-2789(00)00043-9, 2000. a, b
Serinaldi, F. and Lombardo, F.: General simulation algorithm for
autocorrelated binary processes, Phys. Rev. E, 95, 1–9,
https://doi.org/10.1103/PhysRevE.95.023312, 2017. a
Shumway, R. H. and Stoffer, D. S.: Time series analysis and its applications.
With R examples, 4th Edn., Springer International Publishing AG, Cham,
https://doi.org/10.1007/978-1-4419-7865-3, 2017. a, b, c, d
Srinivas, V. V. and Srinivasan, K.: Hybrid matched-block bootstrap for
stochastic simulation of multiseason streamflows, J. Hydrol., 329, 1–15, https://doi.org/10.1016/j.jhydrol.2006.01.023, 2006. a, b
Srivastav, R. K. and Simonovic, S. P.: An analytical procedure for multi-site, multi-season streamflow generation using maximum entropy bootstrapping, Environ. Model. Softw., 59, 59–75,
https://doi.org/10.1016/j.envsoft.2014.05.005, 2014. a
Stacy, E. W. and Mihram, G. A.: Parameter estimation for a generalized Gamma
distribution, Technometrics, 7, 349–358, https://doi.org/10.1080/00401706.1965.10490268, 1965. a
Stagge, J. H. and Moglen, G. E.: A nonparametric stochastic method for
generating daily climate-adjusted streamflows, Water Resour. Res., 49,
6179–6193, https://doi.org/10.1002/wrcr.20448, 2013. a
Theiler, J., Eubank, S., Longtin, A., Galdrikian, B., and Farmer, J. D.:
Testing for nonlinearity in time series: the method of surrogate data,
Physica D, 58, 77–94, https://doi.org/10.1016/0167-2789(92)90102-S, 1992. a
Tsoukalas, I., Efstratiadis, A., and Makropoulos, C.: Stochastic periodic
autoregressive to anything (SPARTA) modeling and simulation of cyclostationary processes with arbitrary marginal distributions, Water
Resour. Res., 54, 161–185, https://doi.org/10.1111/j.1752-1688.1969.tb04897.x, 2018a. a
Venema, V., Bachner, S., Rust, H. W., and Simmer, C.: Statistical characteristics of surrogate data based on geophysical measurements, Nonlin. Processes Geophys., 13, 449–466, https://doi.org/10.5194/npg-13-449-2006, 2006. a
Wang, W., Hu, S., and Li, Y.: Wavelet transform method for synthetic
generation of daily streamflow, Water Resour. Manage., 25, 41–57,
https://doi.org/10.1007/s11269-010-9686-9, 2010. a
Short summary
This study proposes a procedure for the generation of daily discharge data which considers temporal dependence both within short timescales and across different years. The simulation procedure can be applied to individual and multiple sites. It can be used for various applications such as the design of hydropower reservoirs, the assessment of flood risk or the assessment of drought persistence, and the estimation of the risk of multi-year droughts.
This study proposes a procedure for the generation of daily discharge data which considers...
