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Regional regression models of percentile flows for the contiguous US: Expert versus data-driven independent variable selection
Geoffrey Fouad1, Andrι Skupin, and Christina L. Tague
Hydrology and Earth System Sciencs 2016-12-19
Abstract
Percentile flows are statistics derived from the flow duration curve (FDC) that describe the flow equaled or exceeded for a given percent of time. These statistics provide important information for managing rivers, but are often unavailable since most basins are ungauged. A common approach for predicting percentile flows is to deploy regional regression models based on gauged percentile flows and related independent variables derived from physical and climatic data. The first step of this process identifies groups of basins through a cluster analysis of the independent variables, followed by the development of a regression model for each group. This entire process hinges on the independent variables selected to summarize the physical and climatic state of basins. Distributed physical and climatic datasets now exist for the contiguous United States (US). However, it remains unclear how to best represent these data for the development of regional regression models. The study presented here developed regional regression models for the contiguous US, and evaluated the effect of different approaches for selecting the initial set of independent variables on the predictive performance of the regional regression models. An expert assessment of the dominant controls on the FDC was used to identify a small set of independent variables likely related to percentile flows. A data-driven approach was also applied to evaluate two larger sets of variables that consist of either (1) the averages of data for each basin or (2) both the averages and statistical distribution of basin data distributed in space and time. The small set of variables from the expert assessment of the FDC and two larger sets of variables for the data-driven approach were each applied for a regional regression procedure. Differences in predictive performance were evaluated using 184 validation basins withheld from regression model development. The small set of independent variables selected through expert assessment produced similar, if not better, performance than the two larger sets of variables. A parsimonious set of variables only consisted of mean annual precipitation, potential evapotranspiration, and baseflow index. Additional variables in the two larger sets of variables added little to no predictive information. Regional regression models based on the parsimonious set of variables were developed using 734 calibration basins, and were converted into a tool for predicting 13 percentile flows in the contiguous US. Supplementary Material for this paper includes an R graphical user interface for predicting the percentile flows of basins within the range of conditions used to calibrate the regression models. The equations and performance statistics of the models are also supplied in tabular form.
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Scaling, Similarity, and the Fourth Paradigm for Hydrology
Christa D. Peters-Lidard, Martyn Clark, Luis Samaniego, Niko E. C. Verhoest, Tim van Emmerik,Remko Uijlenhoet, Kevin Achieng, Trenton E. Franz, Ross Woods
Hydrology and Earth System Sciences 2017-01-13
Abstract
In this review of hydrologic scaling and similarity, we posit that roadblocks in the search for universal laws of hydrology are hindered by our focus on computational simulation (the third-paradigm), and assert that it is time for hydrology to embrace a fourth paradigm of data-intensive science. Advances in information-based hydrologic science, coupled with an explosion of hydrologic data and advances in parameter estimation and modelling, have laid the foundation for a data-driven framework for scrutinizing hydrological scaling and similarity hypotheses. We summarize important scaling and similarity concepts (hypotheses) that require testing, describe a mutual information framework for testing these hypotheses, describe boundary condition, state/flux, and parameter data requirements across scales to support testing these hypotheses, and discuss some challenges to overcome while pursuing the fourth hydrological paradigm. We call upon the hydrologic sciences community to develop a focused effort towards adopting the fourth paradigm and apply this to outstanding challenges in scaling and similarity.
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Analysing surface energy balance closure and partitioning over a semi-arid savanna FLUXNET site in Skukuza, Kruger National Park, South Africa
Nobuhle P. Majozi, Chris M. Mannaerts, Abel Ramoelo, Renaud Mathieu1, Alecia Nickless, Wouter Verhoef
Hydrology and Earth System Sciences 2017-01-23
Abstract
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Uncertainty quantification in application of linear lumped rainfall-runoff models
Ching-Min Chang and Hund-Der Yeh
Hydrology and Earth System Sciences 2017-01-23
Abstract
This study proposes a stochastic framework for a linear lumped rainfall-runoff problem at the catchment scale. An autoregressive (AR) model is adopted to account for the temporal variability of the rainfall process. For a stochastic description, solutions of the surface flow problem are derived in terms of first two statistical moments of the runoff discharge through the nonstationary Fourier-Stieltjes representation approach. The closed-form expression for the variance of runoff discharge allows to assessing the impacts of rainfall and storage parameters, respectively, on the discharge variability. It is found that the temporal variability of the runoff discharge induced by a random rainfall process persists longer for smaller values of the storage or rainfall parameters.
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HESS Opinions: The complementary merits of top-down and bottom-up modelling philosophies in hydrology
Markus Hrachowitz, Martyn Clark
Hydrology and Earth System Sciences 2017-01-24
Abstract
In hydrology, the two somewhat competing modelling philosophies of bottom-up and top-down approaches are the basis of most process-based models. Differing mostly (1) in their respective degree of detail in resolving the modelling domain and (2) in their respective degree of explicitly treating conservation laws, these two philosophies suffer from similar limitations. Nevertheless, a better understanding of their respective basis (i.e. micro-scale vs. macro-scale) as well as their respective short comings bears the potential of identifying the complementary value of the two philosophies for improving our models. In this manuscript we analyse several frequently communicated beliefs and assumptions to identify, discuss and emphasize the functional similarity of the two modelling philosophies. We argue that deficiencies in model applications largely do not depend on the modelling philosophy but rather on the way a model is implemented. Based on the premises that top-down models can be implemented at any desired degree of detail and that any type of model remains to some degree conceptual we argue that a convergence of the two modelling strategies may hold some value for progressing the development of hydrological models.
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Comparison of performance of tile drainage routines in SWAT 2009 and 2012 in an extensively tile-drained watershed in the Midwest
Tian Guo, Margaret Gitau, Venkatesh Merwade, Jeffrey Arnold, Raghavan Srinivasan, Michael Hirschi, and Bernard Engel
Hydrology and Earth System Sciences 2017-02-14
Abstract
Subsurface tile drainage systems are widely used in agricultural watersheds in the Midwestern U.S. Tile drainage systems enable the Midwest area to become highly productive agricultural lands, but can also create environmental problems, for example nitrate-N contamination associated with drainage waters. The Soil and Water Assessment Tool (SWAT) has been used to model watersheds with tile drainage. SWAT2012 revisions 615 and 645 provide new tile drainage routines. However, few studies have used these revisions to study tile drainage impacts at both field and watershed scales. Moreover, SWAT2012 revision 645 improved the soil moisture based curve number calculation method, which has not been fully tested. This study used long-term (1991–2003) field site and river station data from the Little Vermilion River (LVR) watershed to evaluate performance of tile drainage routines in SWAT2009 revision 528 (the old routine) and SWAT2012 revisions 615 and 645 (the new routine). Both routines provided reasonable but unsatisfactory uncalibrated flow and nitrate loss results. Calibrated monthly tile flow, surface flow, nitrate-N in tile and surface flow, sediment and annual corn and soybean yield results from SWAT with the old and new tile drainage routines were compared with observed values. Generally, the new routine provided acceptable simulated tile flow (NSE?=?0.50–0.68) and nitrate in tile flow (NSE?=?0.50–0.77) for both field sites with random pattern tile and constant tile spacing, while the old routine simulated tile flow and nitrate in tile flow results for the field site with constant tile spacing were unacceptable (NSE?=??0.77– ?0.20 and ?0.99–0.21 respectively). The new modified curve number calculation method in revision 645 (NSE?=?0.56–0.82) better simulated surface runoff than revision 615 (NSE?=??5.95?~?0.5). Calibration provided reasonable parameter sets for the old and new routines in LVR watershed, and the validation results showed that the new routine has the potential to accurately simulate hydrologic processes in mildly-sloped watersheds.
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