Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-321-2021
© Author(s) 2021. 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-25-321-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note
| 
19 Jan 2021
Technical note |
| 19 Jan 2021
| 19 Jan 2021
Technical Note: Improved partial wavelet coherency for understanding scale-specific and localized bivariate relationships in geosciences
The New Zealand Institute for Plant and Food Research Limited, Private Bag 4704, Christchurch 8140, New Zealand
University of Saskatchewan, Department of Soil Science, Saskatoon, SK S7N 5A8, Canada
Related authors
Joseph Alexander Paul Pollacco, Trevor Webb, Stephen McNeill, Wei Hu, Sam Carrick, Allan Hewitt, and Linda Lilburne
Hydrol. Earth Syst. Sci., 21, 2725–2737, https://doi.org/10.5194/hess-21-2725-2017, https://doi.org/10.5194/hess-21-2725-2017, 2017
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Descriptions of soil hydraulic properties, such as soil moisture release curve, θ(h), and saturated hydraulic conductivities, Ks, are a prerequisite for hydrological models. Because it is usually more difficult to describe Ks than θ(h) from pedotransfer functions, we developed a physical unimodal model to compute Ks solely from hydraulic parameters derived from the Kosugi θ(h). We further adaptations to this model to adapt it to dual-porosity structural soils.
Wei Hu and Bing Cheng Si
Hydrol. Earth Syst. Sci., 20, 3183–3191, https://doi.org/10.5194/hess-20-3183-2016, https://doi.org/10.5194/hess-20-3183-2016, 2016
Short summary
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Bivariate wavelet coherence has been used to explore scale- and location-specific relationships between two variables. In reality, a process occurring on land surface is usually affected by more than two factors. Therefore, this manuscript is to develop a multiple wavelet coherence method. Results showed that new method outperforms other multivariate methods. Matlab codes for a new method are provided. This method can be widely applied in geosciences where a variable is controlled by many factors.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci., 20, 571–587, https://doi.org/10.5194/hess-20-571-2016, https://doi.org/10.5194/hess-20-571-2016, 2016
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Spatiotemporal SWC was decomposed into into three terms (spatial forcing, temporal forcing, and interactions between spatial and temporal forcing) for near surface and root zone; Empirical orthogonal function indicated that underlying patterns exist in the interaction term at small watershed scales; Estimation of spatially distributed SWC benefits from decomposition of the interaction term; The suggested decomposition of SWC with time stability analysis has potential in SWC downscaling.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-12829-2013, https://doi.org/10.5194/hessd-10-12829-2013, 2013
Revised manuscript not accepted
Han Fu, Eric J. Neil, Huijie Li, and Bingcheng Si
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-422, https://doi.org/10.5194/hess-2022-422, 2023
Manuscript not accepted for further review
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Current hydrological models segregate water and isotope transport within soil. Thus, MOIST, a MATLAB-based one-dimensional isotope and soil water transport model, was developed. Results indicated that MOIST had good performances on simulating transport of isotope and water within soil under theoretical and realistic conditions, even outperformed than HYDRUS-1D. Suggesting a great potential of MOIST in promoting understandings of ecohydrological processes in terrestrial ecosystems.
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, and Guo-Yue Niu
Geosci. Model Dev., 15, 3405–3416, https://doi.org/10.5194/gmd-15-3405-2022, https://doi.org/10.5194/gmd-15-3405-2022, 2022
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This study aimed to improve runoff simulations and explore deep soil hydrological processes for a highly varying soil depth and complex terrain watershed in the Loess Plateau, China. The actual soil depths and river channels were incorporated into the model to better simulate the runoff in this watershed. The soil evaporation scheme was modified to better describe the evaporation processes. Our results showed that the model significantly improved the runoff simulations.
Hongxiu Wang, Jingjing Jin, Buli Cui, Bingcheng Si, Xiaojun Ma, and Mingyi Wen
Hydrol. Earth Syst. Sci., 25, 5399–5413, https://doi.org/10.5194/hess-25-5399-2021, https://doi.org/10.5194/hess-25-5399-2021, 2021
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Evaporation led to progressively more heavy-isotope-enriched bulk soil water (BW) following the precipitation/irrigation of heavy-isotope-depleted new water but causes progressively more heavy-isotope-depleted BW following irrigation of heavy-isotope-enriched new water. The results indicated that δ2H and δ18O in evaporating water (EW) were similar to new water and differed from BW. However, the evaporative water loss calculated from BW did not differ significantly from that of EW.
Nicholas J. Kinar, John W. Pomeroy, and Bing Si
Geosci. Instrum. Method. Data Syst., 9, 293–315, https://doi.org/10.5194/gi-9-293-2020, https://doi.org/10.5194/gi-9-293-2020, 2020
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Heat pulse probes are widely used to monitor soil thermal and physical properties for agricultural and hydrological monitoring related to crop productivity, drought, snowmelt, and evapotranspiration. Changes in the effective probe spacing distance can cause measurement inaccuracy. This paper uses a novel heat pulse probe and theory to compensate for changes in effective distance, thereby enabling more accurate sensor outputs useful for forecasts and predictions of drought and flooding.
Wei Xiang, Bingcheng Si, Min Li, and Han Li
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-679, https://doi.org/10.5194/hess-2019-679, 2020
Revised manuscript not accepted
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Soil evaporation is an essential component of the terrestrial water cycle, but it is often difficult to assess over a long period. We, for the first time, combined deep soil water isotopes and line-conditioned excess to estimate evaporation to precipitation ratio. Our work underlines that deep soil water stable isotopes have the potential to estimate long-term average evaporation rates against the back of the increasing interest of evaporation estimation in eco-hydrological studies.
Joseph Alexander Paul Pollacco, Trevor Webb, Stephen McNeill, Wei Hu, Sam Carrick, Allan Hewitt, and Linda Lilburne
Hydrol. Earth Syst. Sci., 21, 2725–2737, https://doi.org/10.5194/hess-21-2725-2017, https://doi.org/10.5194/hess-21-2725-2017, 2017
Short summary
Short summary
Descriptions of soil hydraulic properties, such as soil moisture release curve, θ(h), and saturated hydraulic conductivities, Ks, are a prerequisite for hydrological models. Because it is usually more difficult to describe Ks than θ(h) from pedotransfer functions, we developed a physical unimodal model to compute Ks solely from hydraulic parameters derived from the Kosugi θ(h). We further adaptations to this model to adapt it to dual-porosity structural soils.
Wei Hu and Bing Cheng Si
Hydrol. Earth Syst. Sci., 20, 3183–3191, https://doi.org/10.5194/hess-20-3183-2016, https://doi.org/10.5194/hess-20-3183-2016, 2016
Short summary
Short summary
Bivariate wavelet coherence has been used to explore scale- and location-specific relationships between two variables. In reality, a process occurring on land surface is usually affected by more than two factors. Therefore, this manuscript is to develop a multiple wavelet coherence method. Results showed that new method outperforms other multivariate methods. Matlab codes for a new method are provided. This method can be widely applied in geosciences where a variable is controlled by many factors.
Mark J. P. Sigouin and Bing C. Si
The Cryosphere, 10, 1181–1190, https://doi.org/10.5194/tc-10-1181-2016, https://doi.org/10.5194/tc-10-1181-2016, 2016
Short summary
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The cosmic-ray soil moisture probe (CRP) uses the natural above ground neutron intensity to measure soil water content at a landscape scale. The goal of our research was to use the CRP to monitor how much water is in snowpacks, since snow and soil water affect neutron intensity similarly. We developed a relationship between neutron intensity and snow water. We used the relationship to estimate snow water non-invasively in an area of ~ 300 m radius using neutron intensity readings from the CRP.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci., 20, 571–587, https://doi.org/10.5194/hess-20-571-2016, https://doi.org/10.5194/hess-20-571-2016, 2016
Short summary
Short summary
Spatiotemporal SWC was decomposed into into three terms (spatial forcing, temporal forcing, and interactions between spatial and temporal forcing) for near surface and root zone; Empirical orthogonal function indicated that underlying patterns exist in the interaction term at small watershed scales; Estimation of spatially distributed SWC benefits from decomposition of the interaction term; The suggested decomposition of SWC with time stability analysis has potential in SWC downscaling.
W. Hu and B. C. Si
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-12829-2013, https://doi.org/10.5194/hessd-10-12829-2013, 2013
Revised manuscript not accepted
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
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
Heterogeneity measures in hydrological frequency analysis: review and new developments
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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.
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
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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).
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
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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.
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
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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.
Ana I. Requena, Fateh Chebana, and Taha B. M. J. Ouarda
Hydrol. Earth Syst. Sci., 21, 1651–1668, https://doi.org/10.5194/hess-21-1651-2017, https://doi.org/10.5194/hess-21-1651-2017, 2017
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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.
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
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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.
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
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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.
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
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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.
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
Abramovich, F. and Benjamini, Y.: Adaptive thresholding of wavelet coefficients, Comput. Stat. Data Anal., 22, 351–361, 1996.
Aloui, C., Hkiri, B., Hammoudeh, S., and Shahbaz, M.: A multiple and partial wavelet analysis of the oil price, inflation, exchange rate, and economic growth nexus in Saudi Arabia, Emerg. Mark. Finance Trade, 54, 935–956, 2018.
Altarturi, B. H. M., Alshammari, A. A., Saiti, B., and Erol, T.: A three-way analysis of the relationship between the USD value and the prices of oil and gold: A wavelet analysis, AIMS Energy, 6, 487–504, 2018.
Biswas, A. and Si, B. C.: Identifying scale specific controls of soil water storage in a hummocky landscape using wavelet coherency, Geoderma, 165, 50–59, 2011.
Centeno, L. N., Hu, W., Timm, L. C., She, D. L., Ferreira, A. D., Barros, W. S., Beskow, S., and Caldeira, T. L.: Dominant Control of Macroporosity on Saturated Soil Hydraulic Conductivity at Multiple Scales and Locations Revealed by Wavelet Analyses, J. Soil Sci. Plant Nutr., 20, 1686–1702, 2020.
Das, N. N. and Mohanty, B. P.: Temporal dynamics of PSR-based soil moisture across spatial scales in an agricultural landscape during SMEX02: A wavelet approach, Remote Sens. Environ., 112, 522–534, 2008.
Graf, A., Bogena, H. R., Drüe, C., Hardelauf, H., Pütz, T., Heinemann, G., and Vereecken, H.: Spatiotemporal relations between water budget components and soil water content in a forested tributary catchment, Water Resour. Res., 50, 4837–4857, 2014.
Grinsted, A., Moore, J. C., and Jevrejeva, S.: Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlin. Processes Geophys., 11, 561–566, https://doi.org/10.5194/npg-11-561-2004, 2004.
Gu, X. F., Sun, H. G., Tick, G. R., Lu, Y. H., Zhang, Y. K., Zhang, Y., and Schilling, K.: Identification and Scaling Behavior Assessment of the Dominant Hydrological Factors of Nitrate Concentrations in Streamflow, J. Hydrol. Eng., 25, 06020002, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001934, 2020.
Hargreaves, G. H.: Accuracy of estimated reference crop evapotranspiration, J. Irrig. Drain. Eng., 115, 1000–1007, 1989.
Hu, W., Chau, H. W., Qiu, W. W., and Si, B. C.: Environmental controls on the spatial variability of soil water dynamics in a small watershed, J. Hydrol., 551, 47–55, 2017a.
Hu, W. and Si, B. C.: Technical note: Multiple wavelet coherence for untangling scale-specific and localized multivariate relationships in geosciences, Hydrol. Earth Syst. Sci., 20, 3183–3191, https://doi.org/10.5194/hess-20-3183-2016, 2016.
Hu, W. and Si, B.: Matlab code for multiple wavelet coherence and partial wavelet coherency, https://doi.org/10.6084/m9.figshare.13031123, 2020.
Hu, W., Si, B. C., Biswas, A., and Chau, H. W.: Temporally stable patterns but seasonal dependent controls of soil water content: Evidence from wavelet analyses, Hydrol. Process., 31, 3697–3707, 2017b.
Jia, X., Zha, T., Gong, J., Zhang, Y., Wu, B., Qin, S., and Peltola, H.: Multi-scale dynamics and environmental controls on net ecosystem CO2 exchange over a temperate semiarid shrubland, Agric. For. Meteorol., 259, 250–259, 2018.
Kenney, J. F. and Keeping, E. S.: Mayhematics of Statistics, D. van Nostrand, New York, United States, 1939.
Koopmans, L. H.: The spectral analysis of time series, Academic Press, New York, United States, 1974.
Lakshmi, V., Piechota, T., Narayan, U., and Tang, C.: Soil moisture as an indicator of weather extremes, Geophys. Res. Lett., 31, L11401, https://doi.org/10.1029/2004GL019930, 2004.
Li, Z.: Applicability of simple estimating method for reference crop evapotranspiration in Loess Plateau, Trans. Chin. Soc. Agricult. Eng., 28, 106–111, 2012.
Mares, I., Mares, C., Dobrica, V., and Demetrescu, C.: Comparative study of statistical methods to identify a predictor for discharge at Orsova in the Lower Danube Basin, Hydrolog. Sci. J., 65, 371–386, 2020.
Mihanoviæ, H., Orliæ, M., and Pasariæ, Z.: Diurnal thermocline oscillations driven by tidal flow around an island in the Middle Adriatic, J. Mar. Syst., 78, S157–S168, 2009.
Mutascu, M. and Sokic, A.: Trade openness-CO2 emissions nexus: a wavelet evidence from EU, Environ. Model. Assess., 25, 1–18, 2020.
Nalley, D., Adamowski, J., Biswas, A., Gharabaghi, B., and Hu, W.: A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO, J. Hydrol., 574, 288–307, 2019.
Ng, E. K. and Chan, J. C.: Geophysical applications of partial wavelet coherence and multiple wavelet coherence, J. Atmos. Ocean. Technol, 29, 1845–1853, 2012a.
Ng, E. K. and Chan, J. C.: Interannual variations of tropical cyclone activity over the north Indian Ocean, Int. J. Climatol., 32, 819–830, 2012b.
Polansky, L., Wittemyer, G., Cross, P. C., Tambling, C. J., and Getz, W. M.: From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data, Ecology, 91, 1506–1518, 2010.
Rathinasamy, M., Agarwal, A., Parmar, V., Khosa, R., and Bairwa, A.: Partial wavelet coherence analysis for understanding the standalone relationship between Indian Precipitation and Teleconnection patterns, arXiv [preprint], arXiv:1702.06568, 2017.
Schaefli, B., Maraun, D., and Holschneider, M.: What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology, Adv. Water. Resour., 30, 2511–2525, 2007.
Schulte, J. A., Duffy, C., and Najjar, R. G.: Geometric and topological approaches to significance testing in wavelet analysis, Nonlin. Processes Geophys., 22, 139–156, https://doi.org/10.5194/npg-22-139-2015, 2015.
Sen, A. and Choudhury, K. D.: On the co-movement of crude, gold prices and stock index in the Indian market, International Journal of Financial Engineering, 7, 2050036, https://doi.org/10.1142/S242478632050036X, 2020.
Shen, X., Huang, H.-C., and Cressie, N.: Nonparametric hypothesis testing for a spatial signal, J. Am. Stat. Assoc, 97, 1122–1140, 2002.
Si, B. C.: Spatial scaling analyses of soil physical properties: A review of spectral and wavelet methods, Vadose Zone J., 7, 547–562, 2008.
Si, B. C. and Farrell, R. E.: Scale-dependent relationship between wheat yield and topographic indices: A wavelet approach, Soil Sci. Soc. Am. J., 68, 577–587, 2004.
Si, B. C. and Zeleke, T. B.: Wavelet coherency analysis to relate saturated hydraulic properties to soil physical properties, Water Resour. Res., 41, W11424, https://doi.org/10.1029/2005WR004118, 2005.
Song, X. M., Zhang, C. H., Zhang, J. Y., Zou, X. J., Mo, Y. C., and Tian, Y. M.: Potential linkages of precipitation extremes in Beijing-Tianjin-Hebei region, China, with large-scale climate patterns using wavelet-based approaches, Theor. Appl. Climatol., 141, 1251–1269, 2020.
Su, L., Miao, C., Duan, Q., Lei, X., and Li, H.: Multiple wavelet coherence of world's large rivers with meteorological factors and ocean signals, J. Geophys. Res. Atmos., 124, 4932–4954, 2019.
Szolgayová, E., Arlt, J., Blöschl, G., and Szolgay, J.: Wavelet based deseasonalization for modelling and forecasting of daily discharge series considering long range dependence, J. Hydrol. Hydromech., 62, 24–32, 2014.
Tan, X., Gan, T. Y., and Shao, D.: Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large-climate anomalies, J. Geophys. Res.-Atmos., 121, 14469–14486, 2016.
Torrence, C. and Compo, G. P.: A practical guide to wavelet analysis, B. Am. Meteorol. Soc., 79, 61–78, 1998.
Wendroth, O., Alomran, A. M., Kirda, C., Reichardt, K., and Nielsen, D. R.: State-Space Approach to Spatial Variability of Crop Yield, Soil Sci. Soc. Am. J., 56, 801–807, 1992.
Westfall, P. H. and Young, S. S.: Resampling-based multiple testing: Examples and methods for p-value adjustment, John Wiley & Sons, New York, United States, 1993.
Wu, K., Zhu, J., Xu, M., and Yang, L.: Can crude oil drive the co-movement in the international stock market? Evidence from partial wavelet coherence analysis, North Am. J. Econ. Finance, 2020, 101194, https://doi.org/10.1016/j.najef.2020.101194, 2020.
Yan, R. and Gao, R. X.: A tour of the tour of the Hilbert-Huang transform: an empirical tool for signal analysis, IEEE Instrum. Meas. Mag., 10, 40–45, 2007.
Zhao, R., Biswas, A., Zhou, Y., Zhou, Y., Shi, Z., and Li, H.: Identifying localized and scale-specific multivariate controls of soil organic matter variations using multiple wavelet coherence, Sci. Total Environ., 643, 548–558, 2018.
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.
Partial wavelet coherency method is improved to explore the bivariate relationships at different...
