| description abstract | Hydrologic impacts of land disturbance and management can be confounded by rainfall variability. As a consequence, attempts to gauge and quantify these effects through streamflow monitoring are typically subject to uncertainties. This paper addresses the quantification and delineation of different sources of how uncertainty is manifested in a long-term hydrologic monitoring study and through two concepts: (1) detectability, i.e., the chance of observing anticipated changes in streamflow following a known change in land cover; and (2) interpretational uncertainty, i.e., the chance of improperly attributing an observed effect to the wrong cause. The paper offers probabilistic interpretation of each concept and illustrates, through a set of hypothetical monitoring experiments, the dependence of these entities on factors such as monitoring duration and the choice of indicators. Central to the experiments is a resampling scheme which randomly redistributes historical rainfall events and thereby generates an ensemble of weather scenarios. The rainfall events are coupled with a hydrologic model to generate of preurbanization and simulated posturbanization runoff events. In each hypothetical monitoring experiment, two indicators, i.e., runoff ratio and scaled peak discharge rates, are computed and compared for designated subsets of the preurbanization and posturbanization rainfall-runoff time series and the outcomes of the experiments are then synthesized to derive the probabilities. The results suggest that (1) the duration of observation very likely enhances detectability but does not necessarily reduce interpretational uncertainties, and (2) extending the duration of baseline monitoring alone yields only a minor decrease in uncertainty. | |
