Catchment classification: hydrological analysis of catchment behavior through process-based modeling along a climate gradient
Authors: Carrillo G. , Troch P. A. , Sivapalan M. , Wagener T. , Harman C. , Sawicz K. 
Published: May 2011

Abstract. Catchment classification is an efficient method to synthesize our understanding of how climate variability and catchment characteristics interact to define hydrological response. One way to accomplish catchment classification is to empirically relate climate and catchment characteristics to hydrologic behavior and to quantify the skill of predicting hydrologic response based on the combination of climate and catchment characteristics. Since there are important subsurface properties that cannot be readily measured, the skill of classification reflects (the lack of) the amount of cross-correlation between observable landscape features and unobservable subsurface features. The resulting empirical approach is also strongly controlled by the dataset used, and therefore lacks the power to generalize beyond the heterogeneity of characteristics found in the dataset. An alternative approach, that can partially alleviate the above-mentioned issue of observability, uses our current level of hydrological understanding, expressed in the form of a process-based model, to interrogate how climate and catchment characteristics interact to produce the observed hydrologic response. In this paper we present a general method of hydrologic analysis by means of a process-based model to support a bottom-up catchment classification system complementary to top-down classification methods. The model uses topographic, geomorphologic, soil and vegetation information at the catchment scale and conditions parameter values using readily available data on precipitation, temperature and streamflow. It is applicable to a wide range of catchments in different climate settings. We have developed a step-by-step procedure to analyze the observed hydrologic response and to assign parameter values related to specific components of the model. We applied this procedure to 12 catchments across a climate gradient east of the Rocky Mountains, USA. We show that the model is capable of reproducing the observed hydrologic behavior measured through hydrologic signatures chosen at different temporal scales. Next, we analyze the dominant time scales of catchment response and their dimensionless ratios with respect to climate and observable landscape features in an attempt to explain hydrologic partitioning. We find that only a limited number of model parameters can be related to observable landscape features. However, several climate-model time scales, and the associated dimensionless numbers, show scaling relationships with respect to the investigated hydrological signatures (runoff coefficient, baseflow index, and slope of the flow duration curve). Moreover, our analysis revealed systematic co-variation of climate, vegetation and soil related time scales along the climate gradient. If such co-variation can be shown to be robust across many catchments along different climate gradients, it opens perspective for model parameterization in ungauged catchments as well as prediction of hydrologic response in a rapidly changing environment.