Exploring the physical controls of regional patterns of flow duration curves – Part 4: A synthesis of empirical analysis, process modeling and catchment classification

Abstract

Abstract. The paper reports on a four-pronged study of the physical controls on regional patterns of the flow duration curve (FDC). This involved a comparative analysis of longterm continuous data from nearly 200 catchments around the US, encompassing a wide range of climates, geology, and ecology. The analysis was done from three different perspectives -statistical analysis, process-based modeling, and databased classification -followed by a synthesis, which is the focus of this paper. Streamflow data were separated into fast and slow flow responses, and associated signatures, and both total flow and its components were analyzed to generate patterns. Regional patterns emerged in all aspects of the study. The mixed gamma distribution described well the shape of the FDC; regression analysis indicated that certain climate and catchment properties were first-order controls on the shape of the FDC. In order to understand the spatial patterns revealed by the statistical study, and guided by the hypothesis that the middle portion of the FDC is a function of the regime curve (RC, mean within-year variation of flow), we set out to classify these catchments, both empirically and through process-based modeling, in terms of their regime behavior. The classification analysis showed that climate seasonality and aridity, either directly (empirical classes) or through phenology (vegetation processes), were the dominant controls on the RC. Quantitative synthesis of these results determined that these classes were indeed related to the FDC through its slope and related statistical parameters. Qualitative synthesis revealed much diversity in the shapes of the FDCs even within each climate-based homogeneous class, especially in the low-flow tails, suggesting that catchment properties may have become the dominant controls. Thus, while the middle portion of the FDC contains the average response of the catchment, and is mainly controlled by climate, the tails of the FDC, notably the low-flow tails, are mainly controlled by catchment properties such as geology and soils. The regime behavior explains only part of the FDC; to gain a deeper understanding of the physical controls on the FDC, these extremes must be analyzed as well. Thus, to completely separate the climate controls from the catchment controls, the roles of catchment properties such as soils, geology, topography etc. must be explored in detail.

Identifying the connective strength between model parameters and performance criteria

“…This is in line with studies stating that each FDC segment can be related to certain catchment processes (Yilmaz et al, 2008;Yaeger et al, 2012;Pfannerstill et al, 2015). The strong connective strength of model parameters regulating water balance to mid-flows as well as of parameters from slow reacting aquifer storages to very low flows is derived in this study.…”

“…FDC signatures consider that different discharge magnitudes are controlled by different processes. Whilst the high-flow segment is mainly impacted by precipitation and fast runoff components, low flows are controlled by evapotranspiration and deep groundwater storages (Yilmaz et al, 2008;Cheng et al, 2012;Pokhrel et al, 2012;Yaeger et al, 2012;Guse et al, 2016) For the evaluation of each FDC segment, the RSR, the ratio of the root mean square error to the standard deviation, was calculated for each FDC segment (Eq. 3) (Moriasi et al, 2007), which allows fair comparison between different segments (Haas et al, 2016).…”

“…Signature measures are directly related to catchment functions with the aim to consider the relevance of a certain hydrological component individually (Yilmaz et al, 2008;van Werkhoven et al, 2009;Pokhrel et al, 2012). Signature measures based on flow duration curves (FDC) provide diagnostic information of how a model performs for different discharge magnitudes (Yilmaz et al, 2008;Cheng et al, 2012;Yaeger et al, 2012;Pfannerstill et al, 2014b). Pfannerstill et al (2014b) showed that a separation of the flow duration curve into five segments improved the model results for different discharge magnitudes and reduced the trade-off between satisfying results both for high and low flows in the same model run.…”

What makes Darwinian hydrology "Darwinian"? Asking a different kind of question about landscapes

“…This structure has been investigated through the prism of signatures including the flood frequency curve (e.g., Robinson and Sivapalan, 1997), water balance partitioning Harman et al, 2011;Sivapalan et al, 2011a), flow duration curve Yaeger et al, 2012;Ye et al, 2012), recession curve (e.g., Wittenberg, 2003), preferred states in the soil moisture distribution (e.g., Western and Grayson, 2001), and seasonal variations in the fluxes measured at an eddy-flux tower . The study of regimes adopts the Darwinian approach of analyzing populations but in the temporal domain (understanding a population of events within a watershed).…”

A comparative assessment of rainfall–runoff modelling against regional flow duration curves for ungauged catchments

“…It is well documented that hydro-climatological processes within a catchment are reflected in the FDC (e.g. Cheng et al, 2012;Ye et al, 2012;Coopersmith et al, 2012;Yaeger et al, 2012;Botter et al, 2008), and therefore the model parameters identified solely by a regional FDC are expected to provide reliable predictions in ungauged catchments (e.g. Westerberg et al, 2014;Yu and Yang, 2000).…”