a, b careful: The challenge of scale invariance for comparative analyses in power law models of the streamflow recession

Dralle, David; Karst, Nathaniel J.; Thompson, Sally

doi:10.1002/2015gl066007

Cited by 48 publications

(66 citation statements)

References 43 publications

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“…This is a consequence of a mathematical artifact that impacts fitted values of the recession scale parameter, arising when fitting power laws to datasets with arbitrarily chosen scaling (Dralle et al, 2015). The issue can be avoided by setting the recession exponent to a fixed value (e.g., the median; Biswal and Marani, 2010), but this comes at the expense of biasing the fitted values of a due to constraints on the exponent.…”

Section: Methods Combination Comparisonsmentioning

confidence: 99%

“…Recently, several authors have attributed physical meaning to observed variability across individual recessions within a single catchment, triggering an increase in event-scale recession analyses (Dralle et al, 2015(Dralle et al, , 2016Ghosh et al, 2016;Ye et al, 2014;Wittenberg, 1999;Marani, 2010, 2014;Biswal and Nagesh, 2014;Harman et al, 2009;Mutzner et al, 2013;Bart and Hope, 2014;Shaw, 2016;Patnaik et al, 2015;Shaw and Riha, 2012;Vogel and Kroll, 1996;Chen and Krajewski, 2016). Whereas classical, lumped recession analysis seeks a single recession model parameterization to describe all hydrograph recessions for an individual catchment, the goal of event-scale recession analysis is to interpret variations in catchment response to rainfall as a function of the properties of rainfall events (e.g., Harman et al, 2009) or the catchment state (e.g., Biswal and Marani, 2010;Shaw and Riha, 2012).…”

Section: N Dralle Et Al: Event-scale Recession Analysis Uncertaintymentioning

confidence: 99%

“…Among the many issues associated with event-scale analysis (Dralle et al, 2015), perhaps the most challenging are the numerous subjective choices needed to establish consistent criteria for recession identification and fitting (Westerberg and McMillan, 2015). For lumped analyses, Brutsaert and Nieber (1977) established a derivative-based method, which avoids the issue of needing to determine the precise start day of a recession event.…”

Section: N Dralle Et Al: Event-scale Recession Analysis Uncertaintymentioning

confidence: 99%

“…1. The study catchments are relatively steep, forested, and situated within the US western coastal mediterranean climate region (Peel and Finlayson, 2007), which is characterized by a distinct rainy season (with little or no snowfall), followed by a pronounced dry season during which precipitation makes a minimal contribution to the water balance (Power et al, 2015;Dralle et al, 2015). While average annual rainfall for the study catchments ranges from about 1m to 2m, the highly variable rainfall climatology characteristic of mediterranean regions (Fatichi et al, 2012) might be considered ideal for a recession sensitivity analysis, as catchments experience a large range of recession behaviors and wetness states.…”

Section: Study Sitesmentioning

confidence: 99%

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Event-scale power law recession analysis: quantifying methodological uncertainty

Dralle

Karst

Charalampous

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.

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Section: Methods Combination Comparisonsmentioning

confidence: 99%

Section: N Dralle Et Al: Event-scale Recession Analysis Uncertaintymentioning

confidence: 99%

Section: N Dralle Et Al: Event-scale Recession Analysis Uncertaintymentioning

confidence: 99%

Section: Study Sitesmentioning

confidence: 99%

See 2 more Smart Citations

Event-scale power law recession analysis: quantifying methodological uncertainty

Dralle

Karst

Charalampous

et al. 2017

Hydrol. Earth Syst. Sci.

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“…the exponent β can vary with the chosen methodology [Rupp and Selker, 2006;Stoelzle et al, 2013;Dralle et al, 2015;Thomas et al, 2015], spatial variation of rainfall and groundwater discharge [Biswal and Nagesh Kumar, 2014], and the quality of data [Rupp and Selker, 2006;Stoelzle et al, 2013]. Questions still remain about whether the α parameter is a meaningful way to summarize recession behavior.…”

Section: /2016gl067927mentioning

confidence: 99%

Streamflow sensitivity to water storage changes across Europe

Berghuijs

Hartmann

Woods

2016

Geophysical Research Letters

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Terrestrial water storage is the primary source of river flow. We introduce storage sensitivity of streamflow (ϵS), which for a given flow rate indicates the relative change in streamflow per change in catchment water storage. ϵS can be directly derived from streamflow observations. Analysis of 725 catchments in Europe reveals that ϵS is high in, e.g., parts of Spain, England, Germany, and Denmark, whereas flow regimes in parts of the Alps are more resilient (that is, less sensitive) to storage changes. A regional comparison of ϵS with observations indicates that ϵS is significantly correlated with variability of low (R2 = 0.41), median (R2 = 0.27), and high flow conditions (R2 = 0.35). Streamflow sensitivity provides new guidance for a changing hydrosphere where groundwater abstraction and climatic changes are altering water storage and flow regimes.

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Characterizing the spatial correlation of daily streamflows

Betterle

Schirmer

Botter

2017

Water Resources Research

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In this study we propose an analytical framework to estimate the spatial correlation of daily flows at two arbitrary locations within a given hydrologic district or river basin. The method builds on the description of the coupled streamflow dynamics at the outlet of two catchments, which are represented as correlated shot noises forced by Poisson rainfall. Novel analytical expressions for the spatial correlation of discharge are derived using a limited number of parameters that encapsulate effective precipitation regime and catchment drainage rates. The method is suited to describe how heterogeneity of climate and landscape features impact the spatial and temporal variability of flow regimes along river systems. The analysis suggests that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, unless the drainage rates of the two catchments differ by almost one order of magnitude. The method also portrays how the topological arrangement of the two outlets along the river network influences the underlying streamflow correlation and shows how nested catchments tend to maximize the spatial correlation of flow regimes. To demonstrate the potential of the tool, the model is tested on a set of 16 catchments belonging to a 120,000 km2 region of the United States. The application evidences satisfactory performance in reproducing the observed spatial correlation of daily streamflows among the study sites (RMSE < 0.1). The approach provides a clue for the characterization of water availability in space at seasonal time scale, with implications for water resources assessment, risk prevention, and ecological studies.

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a, b careful: The challenge of scale invariance for comparative analyses in power law models of the streamflow recession

Cited by 48 publications

References 43 publications

Event-scale power law recession analysis: quantifying methodological uncertainty

Event-scale power law recession analysis: quantifying methodological uncertainty

Streamflow sensitivity to water storage changes across Europe

Characterizing the spatial correlation of daily streamflows

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