Abstract
Abstract. There has been an intensive search in recent years for suitable strategies to organize and classify the very heterogeneous group of catchments that characterize our landscape. One strand of this work has focused on testing the value of hydrological signatures derived from widely available hydro-meteorological observations for this catchment classification effort. Here we extend this effort by organizing 314 catchments across the contiguous US into 12 distinct clusters using six signature characteristics for a baseline decade (1948–1958, period 1). We subsequently develop a regression tree and utilize it to classify these catchments for three subsequent decades (periods 2–4). This analysis allows us to assess the movement of catchments between clusters over time, and therefore to assess whether their hydrologic similarity/dissimilarity changes. We find examples in which catchments initially assigned to a single class diverge into multiple classes (e.g., midwestern catchments between periods 1 and 2), but also cases where catchments from different classes would converge into a single class (e.g., midwestern catchments between periods 2 and 3). We attempt to interpret the observed changes for causes of this temporal variability in hydrologic behavior. Generally, the changes in both directions were most strongly controlled by changes in the water balance of catchments characterized by an aridity index close to one. Changes to climate characteristics of catchments – mean annual precipitation, length of cold season or the seasonality of precipitation throughout the year – seem to explain most of the observed class transitions between slightly water-limited and slightly energy-limited states. Inadequate temporal information on other time-varying aspects, such as land use change, limits our ability to further disentangle causes for change.
Highlights
The topic of catchment classification has garnered increasing attention in recent years, suggesting that there is significant interest in increasing our understanding of how and why catchments are similar or dissimilar to one another (McDonnell and Woods, 2004; Wagener et al, 2007)
The potential impact of both climate and land use change on hydrologic signatures is briefly discussed before we identify the signature value changes in our data set
RQP, BFI, RSD, Q10, and Q90 exhibit the highest variability between periods 2 and 3, while we found the highest variability for slope of the FDC (SFDC) between periods 1 and 2
Summary
The topic of catchment classification has garnered increasing attention in recent years, suggesting that there is significant interest in increasing our understanding of how and why catchments are similar or dissimilar to one another (McDonnell and Woods, 2004; Wagener et al, 2007). Approaches to catchment classification can be based on physical catchment characteristics (Winter, 2001; Wolock et al, 2004; Gharari et al, 2011; Cheng et al, 2012; Haines et al, 1988), on streamflow characteristics (Olden et al, 2011; Ley et al, 2011; Corduas, 2011; Sawicz et al, 2011; Moliere et al, 2009; Pegg and Pierce, 2002), or on environmental tracers (Flury and Wai, 2003; Tetzlaff et al, 2009). Data required to capture physical characteristics of a catchment are (essentially) available worldwide, assumptions about the connection between these data to hydrologic behavior need to be formulated and there is a general lack of suitable subsurface descriptors (Winter, 2001).
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