No abstract

The notion that landscape features have coevolved over time is well known in the Earth sciences. Hydrologists have recently called for a more rigorous connection between emerging spatial patterns of landscape features and the hydrological response of catchments, and have termed this concept catchment coevolution. In this paper we review recent literature on this subject and attempt to synthesize what we have learned into a general framework that would improve predictions of hydrologic change. We first present empirical evidence of the interaction and feedback of landscape evolution and changes in hydrological response. From this review it is clear that the independent drivers of catchment coevolution are climate, geology, and tectonics. We identify common currency that allows comparing the levels of activity of these independent drivers, such that, at least conceptually, we can quantify the rate of evolution or aging. Knowing the hydrologic age of a catchment by itself is not very meaningful without linking age to hydrologic response. Two avenues of investigation have been used to understand the relationship between (differences in) age and hydrological response: (i) one that is based on relating present landscape features to runoff processes that are hypothesized to be responsible for the current fingerprints in the landscape; and (ii) one that takes advantage of an experimental design known as space-for-time substitution. Both methods have yielded significant insights in the hydrologic response of landscapes with different histories. If we want to make accurate predictions of hydrologic change, we will also need to be able to predict how the catchment will further coevolve in association with changes in the activity levels of the drivers (e.g., climate). There is ample evidence in the literature that suggests that whole-system prediction of catchment coevolution is, at least in principle, plausible. With this imperative we outline a research agenda that implements the concepts of catchment coevolution for building a holistic framework toward improving predictions of hydrologic change.

ABSTRACT:Establishing relationships between coupled ocean-atmospheric patterns and precipitation accumulation is important to describe and predict spatio-temporal variability on annual or seasonal scales, and also to evaluate how this variability is influenced by global warming. The objective of this study was to examine the leading modes of interannual and seasonal (summer, autumn, winter, and spring) precipitation variability in South America-Chile, and their significant relationship to seasonally aggregated gridded data and climatic indices. Applying exhaustive data quality control measures to data from 238 rain gauges with different lengths of records between 1893 and 2013, a new data set was created with the objective of obtaining reliable records for further analysis. A comprehensive analysis through empirical orthogonal functions (EOF) allowed for determination of the leading modes of annual and seasonal precipitation and their main spatial patterns for the whole country. The percentage of explained variance in the relationship between seasonally aggregated indices and the leading modes of precipitation confirmed that most of the interannual and winter precipitation variability in Chile is linked to the seasonal aggregation of El Nino Southern Oscillation (ENSO). The leading modes of summer, autumn, and spring precipitation were mostly linked to seasonal aggregations of the Madden and Julian Oscillation (MJO), and the Antarctic Oscillation (AAO).