[1] A systematic approach is described for determining the minimum level of model complexity required to predict runoff in New Zealand catchments, with minimal calibration, at decreasing timescales. Starting with a lumped conceptual model representing the most basic hydrological processes needed to capture water balance, model complexity is systematically increased in response to demonstrated deficiencies in model predictions until acceptable accuracy is achieved. Sensitivity and error analyses are performed to determine the dominant physical controls on streamflow variability. It is found that dry catchments are sensitive to a threshold storage parameter, producing inaccurate results with little confidence, while wet catchments are relatively insensitive, producing more accurate results with more confidence. Sensitivity to the threshold parameter is well correlated with climate and timescale, and in combination with the results of two previous studies, this allowed the postulation of a qualitative relationship between model complexity, timescale, and the climatic dryness index (DI). This relationship can provide an a priori understanding of the model complexity required to accurately predict streamflow with confidence in small catchments under given climate and timescales and a conceptual framework for model selection. The objective of the paper is therefore not to present a perfect model for any of the catchments studied but rather to present a systematic approach to modeling based on making inferences from data that can be applied with respect to different model designs, catchments and timescales.
1. The Atlantic salmon (Salmo salar L.) has worldwide ecological, cultural, and economic importance. The species has undergone extensive decline across its native range, yet concerns have been raised about its invasive potential in the Pacific. Knowledge on the distribution of this species is vital for addressing conservation goals.2. This study presents an environmental DNA assay to detect S. salar in water samples, using quantitative polymerase chain reaction technology. Species-specific primers and a minor groove binding probe were designed for the assay, based on the mitochondrial cytochrome oxidase I gene.3. The results of this study indicate that environmental DNA is a highly effective tool for detecting S. salar in situ, and could provide an alternative, non-invasive method for determining the distribution of this species.
Abstract:We present a systematic approach to achieving accurate hourly streamflow predictions at locations internal to a catchment, potentially with minimal calibration. Each step in this approach is meant to provide insight into the relative importance of catchment and climatic properties (rainfall, soil, vegetation, topography), their spatial variability, and their influence on the spatial and temporal variability of streamflows. This has been made possible through the use of a simple conceptual model design requiring minimal calibration and with physically meaningful catchment parameters estimated mostly a priori from landscape data, and climatic variables. Eight model types originating from this simple conceptual model design, with complexity ranging from lumped to fully distributed, were tested over summer and winter periods at the Mahurangi Catchment, New Zealand, and the preferred model identified using statistical assessment criteria. Results of the simulations suggest that, although the required model complexity was found to be a function of the season (summer versus winter), a fully distributed representation is most appropriate for accurate predictions under all seasonal climate conditions. Using this model, the success of hourly flow predictions in space-time was assessed and sensitivity analysis used to identify the dominant controls on the timing and magnitude of hourly flow predictions and to investigate the adequacy of the assumption of homogeneity for a number of catchment properties.
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