Abstract
Abstract. Predictions of hydrological responses in ungauged catchments can benefit from a classification scheme that can organize and pool together catchments that exhibit a level of hydrologic similarity, especially similarity in some key variable or signature of interest. Since catchments are complex systems with a level of self-organization arising from co-evolution of climate and landscape properties, including vegetation, there is much to be gained from developing a classification system based on a comparative study of a population of catchments across climatic and landscape gradients. The focus of this paper is on climate seasonality and seasonal runoff regime, as characterized by the ensemble mean of within-year variation of climate and runoff. The work on regime behavior is part of an overall study of the physical controls on regional patterns of flow duration curves (FDCs), motivated by the fact that regime behavior leaves a major imprint upon the shape of FDCs, especially the slope of the FDCs. As an exercise in comparative hydrology, the paper seeks to assess the regime behavior of 428 catchments from the MOPEX database simultaneously, classifying and regionalizing them into homogeneous or hydrologically similar groups. A decision tree is developed on the basis of a metric chosen to characterize similarity of regime behavior, using a variant of the Iterative Dichotomiser 3 (ID3) algorithm to form a classification tree and associated catchment classes. In this way, several classes of catchments are distinguished, in which the connection between the five catchments' regime behavior and climate and catchment properties becomes clearer. Only four similarity indices are entered into the algorithm, all of which are obtained from smoothed daily regime curves of climatic variables and runoff. Results demonstrate that climate seasonality plays the most significant role in the classification of US catchments, with rainfall timing and climatic aridity index playing somewhat secondary roles in the organization of the catchments. In spite of the tremendous heterogeneity of climate, topography, and runoff behavior across the continental United States, 331 of the 428 catchments studied are seen to fall into only six dominant classes.
Highlights
This work is aimed at developing a catchment classification system that will help organize a large and diverse population of catchments within the continental United States into homogeneous groups on the basis of climate seasonality and runoff regime
Considering that we want to develop a catchment classification system on the basis of regime behavior, and the fact that we have 4 different similarity indices that might collectively determine similarity of regime behavior, how can we develop a robust classification system? One way to develop such a classification system is via “decision trees” that can recursively divide the 428 catchments into self-similar groups in such a way that, at each step in the decision tree, the variability of a catchment attribute within each group is less than the variability between groups
This paper has presented the application of a clustering algorithm (i.e., Iterative Dichotomiser 3, or ID3 algorithm) for classifying catchments across the continental United States with respect to their climatic seasonality and regime behavior
Summary
This work is aimed at developing a catchment classification system that will help organize a large and diverse population of catchments within the continental United States into homogeneous groups on the basis of climate seasonality and runoff regime. The work is part of a broader study aimed at better understanding of the physical controls of the flow duration curve (FDC) It has been motivated by the observation that a catchment’s regime curve (ensemble mean of the within-year variation of runoff) has a major impact on the shape of the FDC (Yokoo and Sivapalan, 2011), serving as the connective tissue between high and low flows that appear at the extreme ends of the FDC. Taking this idea further, Sawicz et al (2011) classified catchments located in the eastern half of the United States, using several catchment-based signatures including the runoff ratio, the slope of a flow duration curve, and other streamflow properties This was followed by a comparative study of several catchments based on detailed physically based modeling that can account for differences in topography, soil types, geomorphology, and vegetation (Carillo et al, 2011). The paper concludes with a hydrologic assessment of the catchment classification achieved, including lessons learned and questions left for future work
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