Articles | Volume 21, issue 3
https://doi.org/10.5194/hess-21-1651-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-1651-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Heterogeneity measures in hydrological frequency analysis: review and new developments
Ana I. Requena
CORRESPONDING AUTHOR
Institut National de la Recherche Scientifique (INRS), Centre Eau Terre Environnement (ETE), Quebec, G1K-9A9, Canada
Fateh Chebana
Institut National de la Recherche Scientifique (INRS), Centre Eau Terre Environnement (ETE), Quebec, G1K-9A9, Canada
Taha B. M. J. Ouarda
Institute Center for Water and Environment (iWATER), Masdar Institute of Science and Technology, P.O. Box 54224, Abu Dhabi, United Arab Emirates
Institut National de la Recherche Scientifique (INRS), Centre Eau Terre Environnement (ETE), Quebec, G1K-9A9, Canada
Related authors
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
Martin Durocher, Fateh Chebana, and Taha B. M. J. Ouarda
Hydrol. Earth Syst. Sci., 20, 4717–4729, https://doi.org/10.5194/hess-20-4717-2016, https://doi.org/10.5194/hess-20-4717-2016, 2016
Short summary
Short summary
For regional flood frequency, it is challenging to identify regions with similar hydrological properties. Therefore, previous works have mainly proposed to use regions with similar physiographical properties. This research proposes instead to nonlinearly predict the desired hydrological properties before using them for delineation. The presented method is applied to a case study in Québec, Canada, and leads to hydrologically relevant regions, while enhancing predictions made inside them.
This article is included in the Encyclopedia of Geosciences
K. Niranjan Kumar, D. V. Phanikumar, T. B. M. J. Ouarda, M. Rajeevan, M. Naja, and K. K. Shukla
Ann. Geophys., 34, 123–132, https://doi.org/10.5194/angeo-34-123-2016, https://doi.org/10.5194/angeo-34-123-2016, 2016
Short summary
Short summary
The link between upper-tropospheric planetary-scale Rossby waves and surface meteorological parameters is examined. The propagating Rossby waves along with undulations in the subtropical jet create convergence and divergence regions in the mid-troposphere. The surface relative humidity, wind speeds, and temperature are synchronized with the phase of the propagating Rossby waves. The present study finds important implications for medium-range forecasting through Rossby wave propagation.
This article is included in the Encyclopedia of Geosciences
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
H. Wazneh, F. Chebana, and T. B. M. J. Ouarda
Hydrol. Earth Syst. Sci., 17, 2281–2296, https://doi.org/10.5194/hess-17-2281-2013, https://doi.org/10.5194/hess-17-2281-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Stochastic approaches
Monthly new water fractions and their relationships with climate and catchment properties across Alpine rivers
Technical note: Two-component electrical-conductivity-based hydrograph separation employing an exponential mixing model (EXPECT) provides reliable high-temporal-resolution young water fraction estimates in three small Swiss catchments
Flood frequency analysis using mean daily flows vs. instantaneous peak flows
On the regional-scale variability in flow duration curves in Peninsular India
Towards a conceptualization of the hydrological processes behind changes of young water fraction with elevation: a focus on mountainous alpine catchments
A mixed distribution approach for low-flow frequency analysis – Part 2: Comparative assessment of a mixed probability vs. copula-based dependence framework
A mixed distribution approach for low-flow frequency analysis – Part 1: Concept, performance, and effect of seasonality
Significant regime shifts in historical water yield in the Upper Brahmaputra River basin
A geostatistical spatially varying coefficient model for mean annual runoff that incorporates process-based simulations and short records
Low-flow estimation beyond the mean – expectile loss and extreme gradient boosting for spatiotemporal low-flow prediction in Austria
Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods: a case study on data from Uccle, Belgium
A space–time Bayesian hierarchical modeling framework for projection of seasonal maximum streamflow
Parsimonious statistical learning models for low-flow estimation
Development of a Wilks feature importance method with improved variable rankings for supporting hydrological inference and modelling
Technical Note: Improved partial wavelet coherency for understanding scale-specific and localized bivariate relationships in geosciences
Effects of climate anomalies on warm-season low flows in Switzerland
Histogram via entropy reduction (HER): an information-theoretic alternative for geostatistics
Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework
A methodology to estimate flow duration curves at partially ungauged basins
The role of flood wave superposition in the severity of large floods
Contribution of low-frequency climatic–oceanic oscillations to streamflow variability in small, coastal rivers of the Sierra Nevada de Santa Marta (Colombia)
Stochastic reconstruction of spatio-temporal rainfall patterns by inverse hydrologic modelling
An assessment of trends and potential future changes in groundwater-baseflow drought based on catchment response times
More frequent flooding? Changes in flood frequency in the Pearl River basin, China, since 1951 and over the past 1000 years
Topography significantly influencing low flows in snow-dominated watersheds
A discrete wavelet spectrum approach for identifying non-monotonic trends in hydroclimate data
Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China
Estimating unconsolidated sediment cover thickness by using the horizontal distance to a bedrock outcrop as secondary information
On the probability distribution of daily streamflow in the United States
The European 2015 drought from a hydrological perspective
ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction
Ordinary kriging as a tool to estimate historical daily streamflow records
Trends in floods in West Africa: analysis based on 11 catchments in the region
Implementation and validation of a Wilks-type multi-site daily precipitation generator over a typical Alpine river catchment
Spatial controls on groundwater response dynamics in a snowmelt-dominated montane catchment
Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions?
Data compression to define information content of hydrological time series
Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?
Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain
Exploring the physical controls of regional patterns of flow duration curves – Part 1: Insights from statistical analyses
Land cover and water yield: inference problems when comparing catchments with mixed land cover
An elusive search for regional flood frequency estimates in the River Nile basin
Interannual hydroclimatic variability and its influence on winter nutrient loadings over the Southeast United States
Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal scale of adjustment
Contrasting trends in floods for two sub-arctic catchments in northern Sweden – does glacier presence matter?
Long-range forecasting of intermittent streamflow
Applying sequential Monte Carlo methods into a distributed hydrologic model: lagged particle filtering approach with regularization
Low-frequency variability of European runoff
Comparison of catchment grouping methods for flow duration curve estimation at ungauged sites in France
Regional flow duration curves for ungauged sites in Sicily
Marius G. Floriancic, Michael P. Stockinger, James W. Kirchner, and Christine Stumpp
Hydrol. Earth Syst. Sci., 28, 3675–3694, https://doi.org/10.5194/hess-28-3675-2024, https://doi.org/10.5194/hess-28-3675-2024, 2024
Short summary
Short summary
The Alps are a key water resource for central Europe, providing water for drinking, agriculture, and hydropower production. To assess water availability in streams, we need to understand how much streamflow is derived from old water stored in the subsurface versus more recent precipitation. We use tracer data from 32 Alpine streams and statistical tools to assess how much recent precipitation can be found in Alpine rivers and how this amount is related to catchment properties and climate.
This article is included in the Encyclopedia of Geosciences
Alessio Gentile, Jana von Freyberg, Davide Gisolo, Davide Canone, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 28, 1915–1934, https://doi.org/10.5194/hess-28-1915-2024, https://doi.org/10.5194/hess-28-1915-2024, 2024
Short summary
Short summary
Can we leverage high-resolution and low-cost EC measurements and biweekly δ18O data to estimate the young water fraction at higher temporal resolution? Here, we present the EXPECT method that combines two widespread techniques: EC-based hydrograph separation and sine-wave models of the seasonal isotope cycles. The method is not without its limitations, but its application in three small Swiss catchments is promising for future applications in catchments with different characteristics.
This article is included in the Encyclopedia of Geosciences
Anne Bartens, Bora Shehu, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 28, 1687–1709, https://doi.org/10.5194/hess-28-1687-2024, https://doi.org/10.5194/hess-28-1687-2024, 2024
Short summary
Short summary
River flow data are often provided as mean daily flows (MDF), in which a lot of information is lost about the actual maximum flow or instantaneous peak flows (IPF) within a day. We investigate the error of using MDF instead of IPF and identify means to predict IPF when only MDF data are available. We find that the average ratio of daily flood peaks and volumes is a good predictor, which is easily and universally applicable and requires a minimum amount of data.
This article is included in the Encyclopedia of Geosciences
Pankaj Dey, Jeenu Mathai, Murugesu Sivapalan, and Pradeep P. Mujumdar
Hydrol. Earth Syst. Sci., 28, 1493–1514, https://doi.org/10.5194/hess-28-1493-2024, https://doi.org/10.5194/hess-28-1493-2024, 2024
Short summary
Short summary
This study explores the regional streamflow variability in Peninsular India. This variability is governed by monsoons, mountainous systems, and geologic gradients. A linkage between these influencing factors and streamflow variability is established using a Wegenerian approach and flow duration curves.
This article is included in the Encyclopedia of Geosciences
Alessio Gentile, Davide Canone, Natalie Ceperley, Davide Gisolo, Maurizio Previati, Giulia Zuecco, Bettina Schaefli, and Stefano Ferraris
Hydrol. Earth Syst. Sci., 27, 2301–2323, https://doi.org/10.5194/hess-27-2301-2023, https://doi.org/10.5194/hess-27-2301-2023, 2023
Short summary
Short summary
What drives young water fraction, F*yw (i.e., the fraction of water in streamflow younger than 2–3 months), variations with elevation? Why is F*yw counterintuitively low in high-elevation catchments, in spite of steeper topography? In this paper, we present a perceptual model explaining how the longer low-flow duration at high elevations, driven by the persistence of winter snowpacks, increases the proportion of stored (old) water contributing to the stream, thus reducing F*yw.
This article is included in the Encyclopedia of Geosciences
Gregor Laaha
Hydrol. Earth Syst. Sci., 27, 2019–2034, https://doi.org/10.5194/hess-27-2019-2023, https://doi.org/10.5194/hess-27-2019-2023, 2023
Short summary
Short summary
In seasonal climates with a warm and a cold season, low flows are generated by different processes so that return periods used as a measure of event severity will be inaccurate. We propose a novel mixed copula estimator that is shown to outperform previous calculation methods. The new method is highly relevant for a wide range of European river flow regimes and should be used by default.
This article is included in the Encyclopedia of Geosciences
Gregor Laaha
Hydrol. Earth Syst. Sci., 27, 689–701, https://doi.org/10.5194/hess-27-689-2023, https://doi.org/10.5194/hess-27-689-2023, 2023
Short summary
Short summary
Knowing the severity of an extreme event is of particular importance to hydrology and water policies. In this paper we propose a mixed distribution approach for low flows. It provides one consistent approach to quantify the severity of summer, winter, and annual low flows based on their respective annualities (or return periods). We show that the new method is much more accurate than existing methods and should therefore be used by engineers and water agencies.
This article is included in the Encyclopedia of Geosciences
Hao Li, Baoying Shan, Liu Liu, Lei Wang, Akash Koppa, Feng Zhong, Dongfeng Li, Xuanxuan Wang, Wenfeng Liu, Xiuping Li, and Zongxue Xu
Hydrol. Earth Syst. Sci., 26, 6399–6412, https://doi.org/10.5194/hess-26-6399-2022, https://doi.org/10.5194/hess-26-6399-2022, 2022
Short summary
Short summary
This study examines changes in water yield by determining turning points in the direction of yield changes and highlights that regime shifts in historical water yield occurred in the Upper Brahmaputra River basin, both the climate and cryosphere affect the magnitude of water yield increases, climate determined the declining trends in water yield, and meltwater has the potential to alleviate the water shortage. A repository for all source files is made available.
This article is included in the Encyclopedia of Geosciences
Thea Roksvåg, Ingelin Steinsland, and Kolbjørn Engeland
Hydrol. Earth Syst. Sci., 26, 5391–5410, https://doi.org/10.5194/hess-26-5391-2022, https://doi.org/10.5194/hess-26-5391-2022, 2022
Short summary
Short summary
The goal of this work was to make a map of the mean annual runoff for Norway for a 30-year period. We first simulated runoff by using a process-based model that models the relationship between runoff, precipitation, temperature, and land use. Next, we corrected the map based on runoff observations from streams by using a statistical method. We were also able to use data from rivers that only had a few annual observations. We find that the statistical correction improves the runoff estimates.
This article is included in the Encyclopedia of Geosciences
Johannes Laimighofer, Michael Melcher, and Gregor Laaha
Hydrol. Earth Syst. Sci., 26, 4553–4574, https://doi.org/10.5194/hess-26-4553-2022, https://doi.org/10.5194/hess-26-4553-2022, 2022
Short summary
Short summary
Our study uses a statistical boosting model for estimating low flows on a monthly basis, which can be applied to estimate low flows at sites without measurements. We use an extensive dataset of 260 stream gauges in Austria for model development. As we are specifically interested in low-flow events, our method gives specific weight to such events. We found that our method can considerably improve the predictions of low-flow events and yields accurate estimates of the seasonal low-flow variation.
This article is included in the Encyclopedia of Geosciences
Jorn Van de Velde, Matthias Demuzere, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 26, 2319–2344, https://doi.org/10.5194/hess-26-2319-2022, https://doi.org/10.5194/hess-26-2319-2022, 2022
Short summary
Short summary
An important step in projecting future climate is the bias adjustment of the climatological and hydrological variables. In this paper, we illustrate how bias adjustment can be impaired by bias nonstationarity. Two univariate and four multivariate methods are compared, and for both types bias nonstationarity can be linked with less robust adjustment.
This article is included in the Encyclopedia of Geosciences
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.
This article is included in the Encyclopedia of Geosciences
Johannes Laimighofer, Michael Melcher, and Gregor Laaha
Hydrol. Earth Syst. Sci., 26, 129–148, https://doi.org/10.5194/hess-26-129-2022, https://doi.org/10.5194/hess-26-129-2022, 2022
Short summary
Short summary
This study aims to predict long-term averages of low flow on a hydrologically diverse dataset in Austria. We compared seven statistical learning methods and included a backward variable selection approach. We found that separating the low-flow processes into winter and summer low flows leads to good performance for all the models. Variable selection results in more parsimonious and more interpretable models. Linear approaches for prediction and variable selection are sufficient for our dataset.
This article is included in the Encyclopedia of Geosciences
Kailong Li, Guohe Huang, and Brian Baetz
Hydrol. Earth Syst. Sci., 25, 4947–4966, https://doi.org/10.5194/hess-25-4947-2021, https://doi.org/10.5194/hess-25-4947-2021, 2021
Short summary
Short summary
We proposed a test statistic feature importance method to quantify the importance of predictor variables for random-forest-like models. The proposed method does not rely on any performance measures to evaluate variable rankings, which can thus result in unbiased variable rankings. The resulting variable rankings based on the proposed method could help random forest achieve its optimum predictive accuracy.
This article is included in the Encyclopedia of Geosciences
Wei Hu and Bing Si
Hydrol. Earth Syst. Sci., 25, 321–331, https://doi.org/10.5194/hess-25-321-2021, https://doi.org/10.5194/hess-25-321-2021, 2021
Short summary
Short summary
Partial wavelet coherency method is improved to explore the bivariate relationships at different scales and locations after excluding the effects of other variables. The method was tested with artificial datasets and applied to a measured dataset. Compared with others, this method has the advantages of capturing phase information, dealing with multiple excluding variables, and producing more accurate results. This method can be used in different areas with spatial or temporal datasets.
This article is included in the Encyclopedia of Geosciences
Marius G. Floriancic, Wouter R. Berghuijs, Tobias Jonas, James W. Kirchner, and Peter Molnar
Hydrol. Earth Syst. Sci., 24, 5423–5438, https://doi.org/10.5194/hess-24-5423-2020, https://doi.org/10.5194/hess-24-5423-2020, 2020
Short summary
Short summary
Low river flows affect societies and ecosystems. Here we study how precipitation and potential evapotranspiration shape low flows across a network of 380 Swiss catchments. Low flows in these rivers typically result from below-average precipitation and above-average potential evapotranspiration. Extreme low flows result from long periods of the combined effects of both drivers.
This article is included in the Encyclopedia of Geosciences
Stephanie Thiesen, Diego M. Vieira, Mirko Mälicke, Ralf Loritz, J. Florian Wellmann, and Uwe Ehret
Hydrol. Earth Syst. Sci., 24, 4523–4540, https://doi.org/10.5194/hess-24-4523-2020, https://doi.org/10.5194/hess-24-4523-2020, 2020
Short summary
Short summary
A spatial interpolator has been proposed for exploring the information content of the data in the light of geostatistics and information theory. It showed comparable results to traditional interpolators, with the advantage of presenting generalization properties. We discussed three different ways of combining distributions and their implications for the probabilistic results. By its construction, the method provides a suitable and flexible framework for uncertainty analysis and decision-making.
This article is included in the Encyclopedia of Geosciences
Thea Roksvåg, Ingelin Steinsland, and Kolbjørn Engeland
Hydrol. Earth Syst. Sci., 24, 4109–4133, https://doi.org/10.5194/hess-24-4109-2020, https://doi.org/10.5194/hess-24-4109-2020, 2020
Short summary
Short summary
Annual runoff is a measure of how much water flows through a river during a year and is an important quantity, e.g. when planning infrastructure. In this paper, we suggest a new statistical model for annual runoff estimation. The model exploits correlation between rivers and is able to detect whether the annual runoff in the target river follows repeated patterns over time relative to neighbouring rivers. In our work we show for what cases the latter represents a benefit over comparable methods.
This article is included in the Encyclopedia of Geosciences
Elena Ridolfi, Hemendra Kumar, and András Bárdossy
Hydrol. Earth Syst. Sci., 24, 2043–2060, https://doi.org/10.5194/hess-24-2043-2020, https://doi.org/10.5194/hess-24-2043-2020, 2020
Short summary
Short summary
The paper presents a new, simple and model-free methodology to estimate the streamflow at partially gauged basins, given the precipitation gauged at another basin. We show that the FDC is not a characteristic of the basin only, but of both the basin and the weather. Because of the dependence on the climate, discharge data at the target site are here retrieved using the Antecedent Precipitation Index (API) of the donor site as it represents in a streamflow-like way the precipitation of the basin.
This article is included in the Encyclopedia of Geosciences
Björn Guse, Bruno Merz, Luzie Wietzke, Sophie Ullrich, Alberto Viglione, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 24, 1633–1648, https://doi.org/10.5194/hess-24-1633-2020, https://doi.org/10.5194/hess-24-1633-2020, 2020
Short summary
Short summary
Floods are influenced by river network processes, among others. Flood characteristics of tributaries may affect flood severity downstream of confluences. The impact of flood wave superposition is investigated with regard to magnitude and temporal matching of flood peaks. Our study in Germany and Austria shows that flood wave superposition is not the major driver of flood severity. However, there is the potential for large floods at some confluences in cases of temporal matching of flood peaks.
This article is included in the Encyclopedia of Geosciences
Juan Camilo Restrepo, Aldemar Higgins, Jaime Escobar, Silvio Ospino, and Natalia Hoyos
Hydrol. Earth Syst. Sci., 23, 2379–2400, https://doi.org/10.5194/hess-23-2379-2019, https://doi.org/10.5194/hess-23-2379-2019, 2019
Short summary
Short summary
This study evaluated the influence of low-frequency oscillations that are linked to large-scale oceanographic–atmospheric processes, on streamflow variability in small mountain rivers of the Sierra Nevada de Santa Marta, Colombia, aiming to explore streamflow variability, estimate the net contribution to the energy of low-frequency oscillations to streamflow anomalies, and analyze the linkages between streamflow anomalies and large-scale, low-frequency oceanographic–atmospheric processes.
This article is included in the Encyclopedia of Geosciences
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
Jost Hellwig and Kerstin Stahl
Hydrol. Earth Syst. Sci., 22, 6209–6224, https://doi.org/10.5194/hess-22-6209-2018, https://doi.org/10.5194/hess-22-6209-2018, 2018
Short summary
Short summary
Due to the lack of long-term observations, insights into changes of groundwater resources are obscured. In this paper we assess past and potential future changes in groundwater drought in headwater catchments using a baseflow approach. There are a few past trends which are highly dependent on the period of analysis. Catchments with short response times are found to have a higher sensitivity to projected seasonal precipitation shifts, urging for a local management based on response times.
This article is included in the Encyclopedia of Geosciences
Qiang Zhang, Xihui Gu, Vijay P. Singh, Peijun Shi, and Peng Sun
Hydrol. Earth Syst. Sci., 22, 2637–2653, https://doi.org/10.5194/hess-22-2637-2018, https://doi.org/10.5194/hess-22-2637-2018, 2018
Qiang Li, Xiaohua Wei, Xin Yang, Krysta Giles-Hansen, Mingfang Zhang, and Wenfei Liu
Hydrol. Earth Syst. Sci., 22, 1947–1956, https://doi.org/10.5194/hess-22-1947-2018, https://doi.org/10.5194/hess-22-1947-2018, 2018
Short summary
Short summary
Topography plays an important role in determining the spatial heterogeneity of ecological, geomorphological, and hydrological processes. Topography plays a more dominant role in low flows than high flows. Our analysis also identified five significant TIs: perimeter, slope length factor, surface area, openness, and terrain characterization index. These can be used to compare watersheds when low flow assessments are conducted, specifically in snow-dominated regions.
This article is included in the Encyclopedia of Geosciences
Yan-Fang Sang, Fubao Sun, Vijay P. Singh, Ping Xie, and Jian Sun
Hydrol. Earth Syst. Sci., 22, 757–766, https://doi.org/10.5194/hess-22-757-2018, https://doi.org/10.5194/hess-22-757-2018, 2018
Zhi Li and Jiming Jin
Hydrol. Earth Syst. Sci., 21, 5531–5546, https://doi.org/10.5194/hess-21-5531-2017, https://doi.org/10.5194/hess-21-5531-2017, 2017
Short summary
Short summary
We developed an efficient multisite and multivariate GCM downscaling method and generated climate change scenarios for SWAT to evaluate the streamflow variability within a watershed in China. The application of the ensemble techniques enables us to better quantify the model uncertainties. The peak values of precipitation and streamflow have a tendency to shift from the summer to spring season over the next 30 years. The number of extreme flooding and drought events will increase.
This article is included in the Encyclopedia of Geosciences
Nils-Otto Kitterød
Hydrol. Earth Syst. Sci., 21, 4195–4211, https://doi.org/10.5194/hess-21-4195-2017, https://doi.org/10.5194/hess-21-4195-2017, 2017
Short summary
Short summary
The GRANADA open-access database (NGU, 2016a) was used to derive point recordings of thickness of sediment above the bedrock D(u). For each D(u) the horizontal distance to nearest outcrop L(u) was derived from geological maps. The purpose was to utilize L(u) as a secondary function for estimation of D(u). Two estimation methods were employed: ordinary kriging (OK) and co-kriging (CK). A cross-validation analysis was performed to evaluate the additional information in the secondary function L(u).
This article is included in the Encyclopedia of Geosciences
Annalise G. Blum, Stacey A. Archfield, and Richard M. Vogel
Hydrol. Earth Syst. Sci., 21, 3093–3103, https://doi.org/10.5194/hess-21-3093-2017, https://doi.org/10.5194/hess-21-3093-2017, 2017
Short summary
Short summary
Flow duration curves are ubiquitous in surface water hydrology for applications including water allocation and protection of ecosystem health. We identify three probability distributions that can provide a reasonable fit to daily streamflows across much of United States. These results help us understand of the behavior of daily streamflows and enhance our ability to predict streamflows at ungaged river locations.
This article is included in the Encyclopedia of Geosciences
Gregor Laaha, Tobias Gauster, Lena M. Tallaksen, Jean-Philippe Vidal, Kerstin Stahl, Christel Prudhomme, Benedikt Heudorfer, Radek Vlnas, Monica Ionita, Henny A. J. Van Lanen, Mary-Jeanne Adler, Laurie Caillouet, Claire Delus, Miriam Fendekova, Sebastien Gailliez, Jamie Hannaford, Daniel Kingston, Anne F. Van Loon, Luis Mediero, Marzena Osuch, Renata Romanowicz, Eric Sauquet, James H. Stagge, and Wai K. Wong
Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, https://doi.org/10.5194/hess-21-3001-2017, 2017
Short summary
Short summary
In 2015 large parts of Europe were affected by a drought. In terms of low flow magnitude, a region around the Czech Republic was most affected, with return periods > 100 yr. In terms of deficit volumes, the drought was particularly severe around S. Germany where the event lasted notably long. Meteorological and hydrological events developed differently in space and time. For an assessment of drought impacts on water resources, hydrological data are required in addition to meteorological indices.
This article is included in the Encyclopedia of Geosciences
Joost V. L. Beckers, Albrecht H. Weerts, Erik Tijdeman, and Edwin Welles
Hydrol. Earth Syst. Sci., 20, 3277–3287, https://doi.org/10.5194/hess-20-3277-2016, https://doi.org/10.5194/hess-20-3277-2016, 2016
Short summary
Short summary
Oceanic–atmospheric climate modes, such as El Niño–Southern Oscillation (ENSO), are known to affect the streamflow regime in many rivers around the world. A new method is presented for ENSO conditioning of the ensemble streamflow prediction (ESP) method, which is often used for seasonal streamflow forecasting. The method was tested on three tributaries of the Columbia River, OR. Results show an improvement in forecast skill compared to the standard ESP.
This article is included in the Encyclopedia of Geosciences
William H. Farmer
Hydrol. Earth Syst. Sci., 20, 2721–2735, https://doi.org/10.5194/hess-20-2721-2016, https://doi.org/10.5194/hess-20-2721-2016, 2016
Short summary
Short summary
The potential of geostatistical tools, leveraging the spatial structure and dependency of correlated time series, for the prediction of daily streamflow time series at unmonitored locations is explored. Simple geostatistical tools improve on traditional estimates of daily streamflow. The temporal evolution of spatial structure, including seasonal fluctuations, is also explored. The proposed method is contrasted with more advanced geostatistical methods and shown to be comparable.
This article is included in the Encyclopedia of Geosciences
B. N. Nka, L. Oudin, H. Karambiri, J. E. Paturel, and P. Ribstein
Hydrol. Earth Syst. Sci., 19, 4707–4719, https://doi.org/10.5194/hess-19-4707-2015, https://doi.org/10.5194/hess-19-4707-2015, 2015
Short summary
Short summary
The region of West Africa is undergoing important climate and environmental changes affecting the magnitude and occurrence of floods. This study aims to analyze the evolution of flood hazard in the region and to find links between flood hazards pattern and rainfall or vegetation index patterns.
This article is included in the Encyclopedia of Geosciences
D. E. Keller, A. M. Fischer, C. Frei, M. A. Liniger, C. Appenzeller, and R. Knutti
Hydrol. Earth Syst. Sci., 19, 2163–2177, https://doi.org/10.5194/hess-19-2163-2015, https://doi.org/10.5194/hess-19-2163-2015, 2015
R. S. Smith, R. D. Moore, M. Weiler, and G. Jost
Hydrol. Earth Syst. Sci., 18, 1835–1856, https://doi.org/10.5194/hess-18-1835-2014, https://doi.org/10.5194/hess-18-1835-2014, 2014
C. Teutschbein and J. Seibert
Hydrol. Earth Syst. Sci., 17, 5061–5077, https://doi.org/10.5194/hess-17-5061-2013, https://doi.org/10.5194/hess-17-5061-2013, 2013
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
S. A. Archfield, A. Pugliese, A. Castellarin, J. O. Skøien, and J. E. Kiang
Hydrol. Earth Syst. Sci., 17, 1575–1588, https://doi.org/10.5194/hess-17-1575-2013, https://doi.org/10.5194/hess-17-1575-2013, 2013
P. Cowpertwait, D. Ocio, G. Collazos, O. de Cos, and C. Stocker
Hydrol. Earth Syst. Sci., 17, 479–494, https://doi.org/10.5194/hess-17-479-2013, https://doi.org/10.5194/hess-17-479-2013, 2013
L. Cheng, M. Yaeger, A. Viglione, E. Coopersmith, S. Ye, and M. Sivapalan
Hydrol. Earth Syst. Sci., 16, 4435–4446, https://doi.org/10.5194/hess-16-4435-2012, https://doi.org/10.5194/hess-16-4435-2012, 2012
A. I. J. M. van Dijk, J. L. Peña-Arancibia, and L. A. (Sampurno) Bruijnzeel
Hydrol. Earth Syst. Sci., 16, 3461–3473, https://doi.org/10.5194/hess-16-3461-2012, https://doi.org/10.5194/hess-16-3461-2012, 2012
P. Nyeko-Ogiramoi, P. Willems, F. M. Mutua, and S. A. Moges
Hydrol. Earth Syst. Sci., 16, 3149–3163, https://doi.org/10.5194/hess-16-3149-2012, https://doi.org/10.5194/hess-16-3149-2012, 2012
J. Oh and A. Sankarasubramanian
Hydrol. Earth Syst. Sci., 16, 2285–2298, https://doi.org/10.5194/hess-16-2285-2012, https://doi.org/10.5194/hess-16-2285-2012, 2012
H. Lee, D.-J. Seo, Y. Liu, V. Koren, P. McKee, and R. Corby
Hydrol. Earth Syst. Sci., 16, 2233–2251, https://doi.org/10.5194/hess-16-2233-2012, https://doi.org/10.5194/hess-16-2233-2012, 2012
H. E. Dahlke, S. W. Lyon, J. R. Stedinger, G. Rosqvist, and P. Jansson
Hydrol. Earth Syst. Sci., 16, 2123–2141, https://doi.org/10.5194/hess-16-2123-2012, https://doi.org/10.5194/hess-16-2123-2012, 2012
F. F. van Ogtrop, R. W. Vervoort, G. Z. Heller, D. M. Stasinopoulos, and R. A. Rigby
Hydrol. Earth Syst. Sci., 15, 3343–3354, https://doi.org/10.5194/hess-15-3343-2011, https://doi.org/10.5194/hess-15-3343-2011, 2011
S. J. Noh, Y. Tachikawa, M. Shiiba, and S. Kim
Hydrol. Earth Syst. Sci., 15, 3237–3251, https://doi.org/10.5194/hess-15-3237-2011, https://doi.org/10.5194/hess-15-3237-2011, 2011
L. Gudmundsson, L. M. Tallaksen, K. Stahl, and A. K. Fleig
Hydrol. Earth Syst. Sci., 15, 2853–2869, https://doi.org/10.5194/hess-15-2853-2011, https://doi.org/10.5194/hess-15-2853-2011, 2011
E. Sauquet and C. Catalogne
Hydrol. Earth Syst. Sci., 15, 2421–2435, https://doi.org/10.5194/hess-15-2421-2011, https://doi.org/10.5194/hess-15-2421-2011, 2011
F. Viola, L. V. Noto, M. Cannarozzo, and G. La Loggia
Hydrol. Earth Syst. Sci., 15, 323–331, https://doi.org/10.5194/hess-15-323-2011, https://doi.org/10.5194/hess-15-323-2011, 2011
Cited articles
Akaike, H.: Information theory and an extension of the maximum likelihood principle, in: Second International Symposium on Information Theory, edited by: Petrov, B. N. and Csaki, F., Acad. Kiadó, Budapest, 267–281, 1973.
Ali, G., Tetzlaff, D., Soulsby, C., McDonnell, J. J., and Capell, R.: A comparison of similarity indices for catchment classification using a cross-regional dataset, Adv. Water Resour., 40, 11–22, 2012.
Alila, Y.: A hierarchical approach for the regionalization of precipitation annual maxima in Canada, J. Geophys. Res.-Atmos., 104, 31645–31655, 1999.
Bocchiola, D., De Michele, C., and Rosso, R.: Review of recent advances in index flood estimation, Hydrol. Earth Syst. Sci., 7, 283–296, https://doi.org/10.5194/hess-7-283-2003, 2003.
Brath, A., Castellarin, A., Franchini, M., and Galeati, G.: Estimating the index flood using indirect methods, Hydrolog. Sci. J., 46, 399–418, 2001.
Burn, D. H.: Cluster analysis as applied to regional flood frequency, J. Water Res. Pl.-ASCE, 115, 567–582, 1989.
Burn, D. H. and Goel, N.: The formation of groups for regional flood frequency analysis, Hydrolog. Sci. J., 45, 97–112, 2000.
Canaves, J. M., Page, R., Wilson, I. A., and Stevens, R. C.: Protein biophysical properties that correlate with crystallization success in Thermotoga maritima: maximum clustering strategy for structural genomics, J. Mol. Biol., 344, 977–991, 2004.
Castellarin, A., Burn, D., and Brath, A.: Assessing the effectiveness of hydrological similarity measures for flood frequency analysis, J. Hydrol., 241, 270–285, 2001.
Castellarin, A., Burn, D., and Brath, A.: Homogeneity testing: How homogeneous do heterogeneous cross-correlated regions seem?, J. Hydrol., 360, 67–76, 2008.
Ceriani, L. and Verme, P.: The origins of the Gini index: extracts from Variabilità e Mutabilità (1912) by Corrado Gini, J. Econ. Inequal., 10, 421–443, 2012.
Chokmani, K. and Ouarda, T. B. M. J.: Physiographical space-based kriging for regional flood frequency estimation at ungauged sites, Water Resour. Res., 40, W12514, https://doi.org/10.1029/2003WR002983, 2004.
Chebana, F. and Ouarda, T. B. M. J.: Multivariate L-moment homogeneity test, Water Resour. Res., 43, W08406, https://doi.org/10.1029/2006WR005639, 2007.
Chebana, F. and Ouarda, T. B. M. J.: Index flood-based multivariate regional frequency analysis, Water Resour. Res., 45, W10435, https://doi.org/10.1029/2008WR007490, 2009.
Chowdhury, J. U., Stedinger, J. R., and Lu, L.: Goodness-of-fit tests for regional generalized extreme value flood distributions, Water Resour. Res., 27, 1765–1776, 1991.
Cunnane, C.: Methods and merits of regional flood frequency analysis, J. Hydrol., 100, 269–290, 1988.
Dalrymple, T.: Flood frequency analyses, US Geol. Surv. Water Supply Pap. 1543A, US Geological Survey, Washington, 11–51, 1960.
Das, S. and Cunnane, C.: Examination of homogeneity of selected Irish pooling groups, Hydrol. Earth Syst. Sci., 15, 819–830, https://doi.org/10.5194/hess-15-819-2011, 2011.
Das, S. and Cunnane, C.: Performance of flood frequency pooling analysis in a low CV context, Hydrolog. Sci. J., 57, 433–444, 2012.
Elamir, E. A. and Seheult, A. H.: Exact variance structure of sample L-moments, J. Stat. Plan. Infer., 124, 337–359, 2004.
Farsadnia, F., Kamrood, M. R., Nia, A. M., Modarres, R., Bray, M., and Han, D.: Identification of homogeneous regions for regionalization of watersheds by two-level self-organizing feature maps, J. Hydrol., 509, 387–397, 2014.
Fill, H. D. and Stedinger, J. R.: Homogeneity tests based upon Gumbel distribution and a critical appraisal of Dalrymple's test, J. Hydrol., 166, 81–105, 1995.
Gastwirth, J. L.: The estimation of the Lorenz curve and Gini index, Rev. Econ. Stat., 54, 306–316, 1972.
Gini, C.: Variabilità e Mutuabilità. Contributo allo Studio delle Distribuzioni e delle Relazioni Statistiche, C. Cuppini, Bologna, 1912.
Glasser, G. J.: Variance formulas for the mean difference and coefficient of concentration, J. Am. Stat. Assoc., 57, 648–654, 1962.
Hausser, J. and Strimmer, K.: Entropy inference and the James–Stein estimator, with application to nonlinear gene association networks, J. Mach. Learn. Res., 10, 1469–1484, 2009.
Hosking, J. R. M.: L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics, J. R. Stat. Soc. Ser. B, 52, 105–124, 1990.
Hosking, J. R. M.: Regional frequency analysis using L-moments, R package, version 3.0-1, http://CRAN.R-project.org/package=lmomRFA (last access: October 2016), 2015.
Hosking, J. R. M. and Wallis, J. R.: Some statistics useful in regional frequency analysis, Water Resour. Res., 29, 271–281, 1993.
Hosking, J. R. M. and Wallis, J. R.: Regional frequency analysis: an approach based on L-moments, Cambridge University Press, Cambridge, 240 pp., 1997.
Ilorme, F. and Griffis, V. W.: A novel procedure for delineation of hydrologically homogeneous regions and the classification of ungauged sites for design flood estimation, J. Hydrol., 492, 151–162, 2013.
Kouider, A., Gingras, H., Ouarda, T. B. M. J., Ristic-Rudolf, Z., and Bobée, B.: Analyse fréquentielle locale et régionale et cartographie des crues au Québec, Rep. R-627-el, INRS-ETE, Ste-Foy, Canada, 2002.
Kullback, S. and Leibler, R. A.: On information and sufficiency, Ann. Math. Stat., 22, 79–86, 1951.
Laio, F., Di Baldassarre, G., and Montanari, A.: Model selection techniques for the frequency analysis of hydrological extremes, Water Resour. Res., 45, W07416, https://doi.org/10.1029/2007WR006666, 2009.
Li, H. and Reynolds, J.: On definition and quantification of heterogeneity, Oikos, 73, 280–284, 1995.
Mays, D. C., Faybishenko, B. A. and Finsterle, S.: Information entropy to measure temporal and spatial complexity of unsaturated flow in heterogeneous media, Water Resour. Res., 38, 49-1–49-11, 2002.
Mishra, B. K., Takara, K., and Tachikawa, Y.: Regionalization of Nepalese river basins for flood frequency analysis, J. Hydraul. Eng., 52, 91–96, 2008.
Ouali, D., Chebana, F., and Ouarda, T. B. M. J.: Non-linear canonical correlation analysis in regional frequency analysis, Stoch. Environ. Res. Risk. A., 30, 449–462, 2016.
Ouarda, T. B. M. J.: Hydrological frequency analysis, Regional, Encyclopedia of Environmetrics, John Wiley & Sons, Ltd, https://doi.org/10.1002/9780470057339.vnn043, 2013.
Ouarda, T. B. M. J.: Regional flood frequency modeling, in: chap. 77, Chow's Handbook of Applied Hydrology, 3rd Edn., edited by: Singh, V. P., Mc-Graw Hill, New York, 77.1–77.8, 2016.
Ouarda, T. B. M. J. and Shu, C.: Regional low-flow frequency analysis using single and ensemble artificial neural networks, Water Resour. Res., 45, W11428, https://doi.org/10.1029/2008WR007196, 2009.
Ouarda, T. B. M. J., Girard, C., Cavadias, G. S., and Bobée, B.: Regional flood frequency estimation with canonical correlation analysis, J. Hydrol., 254, 157–173, 2001.
Requena, A. I., Chebana, F., and Mediero, L.: A complete procedure for multivariate index-flood model application, J. Hydrol., 535, 559–580, 2016.
Salinas, J. L., Laaha, G., Rogger, M., Parajka, J., Viglione, A., Sivapalan, M., and Blöschl, G.: Comparative assessment of predictions in ungauged basins – Part 2: Flood and low flow studies, Hydrol. Earth Syst. Sci., 17, 2637–2652, https://doi.org/10.5194/hess-17-2637-2013, 2013.
Scholz, F. W. and Stephens, M. A.: K-sample Anderson–Darling tests, J. Am. Stat. Assoc., 82, 918–924, 1987.
Scholz, F. W. and Zhu, A.: kSamples: K-Sample Rank Tests and their Combinations, R package version 1.0.1, http://CRAN.R-project.org/package=kSamples (last access: February 2016), 2015.
Seidou, O., Ouarda, T. B. M. J., Barbet, M., Bruneau, P., and Bobée, B.: A parametric Bayesian combination of local and regional information in flood frequency analysis, Water Resour. Res., 42, W11408, https://doi.org/10.1029/2005WR004397, 2006.
Shu, C. and Burn, D. H.: Homogeneous pooling group delineation for flood frequency analysis using a fuzzy expert system with genetic enhancement, J. Hydrol., 291, 132–149, 2004.
Shu, C., and Ouarda, T. B. M. J.: Flood frequency analysis at ungauged sites using artificial neural networks in canonical correlation analysis physiographic space, Water Resour. Res., 43, W07438, https://doi.org/10.1029/2006WR005142, 2007.
Smith, A., Sampson, C., and Bates, P.: Regional flood frequency analysis at the global scale, Water Resour. Res., 51, 539–553, 2015.
Stedinger, J. and Lu, L.: Appraisal of regional and index flood quantile estimators, Stoch. Hydrol. Hydraul., 9, 49–75, 1995.
Viglione, A.: Confidence intervals for the coefficient of L-variation in hydrological applications, Hydrol. Earth Syst. Sci., 14, 2229–2242, https://doi.org/10.5194/hess-14-2229-2010, 2010.
Viglione, A.: nsRFA: Non-supervised Regional Frequency Analysis, R package version 0.7-12, http://CRAN.R-project.org/package=nsRFA (last access: October 2016), 2014.
Viglione, A., Laio, F., and Claps, P.: A comparison of homogeneity tests for regional frequency analysis, Water Resour. Res., 43, W03428, https://doi.org/10.1029/2006WR005095, 2007.
Warner, R. M.: Applied statistics: From bivariate through multivariate techniques, Sage, California, 2008.
Wazneh, H., Chebana, F., and Ouarda, T. B. M. J.: Delineation of homogeneous regions for regional frequency analysis using statistical depth function, J. Hydrol., 521, 232–244, 2015.
Weijs, S. V., Schoups, G., and van de Giesen, N.: Why hydrological predictions should be evaluated using information theory, Hydrol. Earth Syst. Sci., 14, 2545–2558, https://doi.org/10.5194/hess-14-2545-2010, 2010.
Wiltshire, S.: Regional flood frequency analysis I: Homogeneity statistics, Hydrolog. Sci. J., 31, 321–333, 1986.
Wright, M. J., Ferreira, C., and Houck, M.: Evaluation of heterogeneity statistics as reasonable proxies of the error of precipitation quantile estimation in the Minneapolis-St. Paul region, J. Hydrol., 513, 457–466, 2014.
Wright, M. J., Houck, M. H., and Ferreira, C. M.: Discriminatory Power of Heterogeneity Statistics with Respect to Error of Precipitation Quantile Estimation, J. Hydrol. Eng., 20, 04015011, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001172, 2015.
Wu, J., Tan, Y., Deng, H., and Zhu, D.: A new measure of heterogeneity of complex networks based on degree sequence, Unifying Themes in Complex Systems, Springer, Berlin, 66–73, 2010.
Yitzhaki, S. and Schechtman, E.: The Gini Methodology: A primer on a statistical methodology, in: Vol. 272, Springer Science & Business Media, New York, 2012.
Zeileis, A.: ineq: Measuring Inequality, Concentration, and Poverty, R package version 0.2-13, http://CRAN.R-project.org/package=ineq (last access: October 2016), 2014.
Short summary
The notion of a measure to quantify the degree of heterogeneity of a region from which information is required to estimate the magnitude of events at ungauged sites is introduced. These heterogeneity measures are needed to compare regions, evaluate the impact of particular sites, and rank the performance of delineating methods. A framework to define and assess their desirable properties is proposed. Several heterogeneity measures are presented and/or developed to be assessed, giving guidelines.
The notion of a measure to quantify the degree of heterogeneity of a region from which...