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 long-term 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 data-based 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.

Highlights

  • Catchment signatures quantify hydrologic responses to rainfall inputs in a compact manner; by distilling catchment behavior into a few signatures, classification of variable behavior across many different catchments can be made

  • Guided by the hypothesis that the regime curve (RC) provides the backbone to the shape of the flow duration curve (FDC) (Yokoo and Sivapalan, 2011), we classified these same catchments in terms of their regime behavior

  • This classification was done both empirically (Coopersmith et al, 2012) and with the aid of process-based modeling (Ye et al, 2012), and both methods showed that climate seasonality followed by aridity were the dominant controls on the regime behavior across the continent, overriding the catchment controls of topography, soils, etc

Read more

Summary

Introduction

Catchment signatures quantify hydrologic responses to rainfall inputs in a compact manner; by distilling catchment behavior into a few signatures, classification of variable behavior across many different catchments can be made One such signature, the regime curve (RC), describes the intraannual variability of monthly (or even daily) average (ensemble mean) streamflows. The regime curve (RC), describes the intraannual variability of monthly (or even daily) average (ensemble mean) streamflows Another signature, the flow duration curve (FDC), plots daily streamflow magnitude (on a log scale) as a function of the percent of time it is exceeded. With this idea of regionalization based on clusters of similar behavior, the prediction of the FDC or any other hydrologic signature can be greatly improved in cases where this function is not determined, such as ungauged basins

Objectives
Methods
Findings
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call