Conversely, downscaling involves disaggregation and singling out.
It is argued that upscaling typically consists of two steps: distributing and aggregating. The third section addresses the linkages across scales from a modelling point of view. The second section discusses heterogeneity and variability in catchments and touches on the implications of randomness and organization for scaling. ‘Process scale’, ‘observation scale’ and ‘modelling (working) scale’ require different definitions. This is important as researchers do not seem to have agreed on the meaning of concepts such as scale or upscaling. The first section gives some basic definitions. Published by John Wiley & Sons, Ltd.read more read lessĪbstract: A framework is provided for scaling and scale issues in hydrology. Results indicate that, with the previously existing procedures, researchers and practitioners may have incorrectly identified the possibility of significant trends. This alternative approach and the previously existing approaches were employed to assess the significance of a trend in serially correlated annual mean and annual minimum streamflow data of some pristine river basins in Ontario, Canada.
JOURNAL OF HYDROLOGICAL PROCESSES SERIAL
In essence, it was advocated that a trend first be removed in a series prior to ascertaining the magnitude of serial correlation. These results indicate that the commonly used pre-whitening procedure for eliminating the effect of serial correlation on the MK test leads to potentially inaccurate assessments of the significance of a trend and certain procedures will be more appropriate for eliminating the impact of serial correlation on the MK test. Furthermore, it was shown that removal of a positive serial correlation component from time series by pre-whitening resulted in a reduction in the magnitude of the existing trend and the removal of a trend component from a time series as a first step prior to pre-whitening eliminates the influence of the trend on the serial correlation and does not seriously affect the estimate of the true AR(1). Simulation experiments demonstrated that the existence of serial correlation alters the variance of the estimate of the Mann–Kendall (MK) statistic and the presence of a trend alters the estimate of the magnitude of serial correlation.
Some hydrologic models that make use of digital representations of topography are also considered.read more read lessĪbstract: This study investigated using Monte Carlo simulation the interaction between a linear trend and a lag-one autoregressive (AR(1)) process when both exist in a time series.
We describe elevation data sources, digital elevation model structures, and the analysis of digital elevation data for hydrological, geomorphological, and biological applications. Digital elevation models are the primary data used in the analysis of catchment topography. Furthermore, topography can be used to develop more physically realistic structures for hydrologic and water quality models that directly account for the impact of topography on the hydrology. Many geographic information systems are being developed that store topographic information as the primary data for analysing water resource and biological problems. The spatial distribution of topographic attributes can often be used as an indirect measure of the spatial variability of these processes and allows them to be mapped using relatively simple techniques. and biological processes active in the landscape. Abstract: The topography of a catchment has a major impact on the hydrological, geomorphological.
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