[1] A physiographical space-based kriging method is proposed for regional flood frequency estimation. The methodology relies on the construction of a continuous physiographical space using physiographical and meteorological characteristics of gauging stations and the use of multivariate analysis techniques. Two multivariate analysis methods were tested: canonical correlation analysis (CCA) and principal components analysis. Ordinary kriging, a geostatistical technique, was then used to interpolate flow quantiles through the physiographical space. Data from 151 gauging stations across the southern part of the province of Quebec, Canada, were used to illustrate this approach. In order to evaluate the performance of the proposed method, two validation techniques, cross validation and split-sample validation, were applied to estimate flood quantiles corresponding to the 10, 50, and 100 year return periods. Results of the proposed method were compared to those produced by a traditional regional estimation method using the canonical correlation analysis. The proposed method yielded satisfactory results. It allowed, for instance, for estimating the 10 year return period specific flow with a coefficient of determination of up to 0.78. However, this performance decreases with the increase in the quantile return period. Results also showed that the proposed method works better when the physiographical space is defined using canonical correlation analysis. It is shown that kriging in the CCA physiographical space yields results as precise as the traditional estimation method, with a fraction of the effort and the computation time.

Permafrost thaw ponds result from the irregular melting and erosion of frozen soils, and they are active sites of greenhouse gas emissions to the atmosphere throughout the circumpolar North. In the discontinuous permafrost region of Nunavik, Canada, thaw ponds show pronounced differences in color even among nearby ponds, ranging from white to green, brown and black. To quantify this optical variation and to determine its underlying controlling mechanisms, we studied the apparent and inherent optical properties and limnological characteristics of the ponds. The pond colors were well separated on a color coordinate diagram, with axis values determined from above‐water spectral reflectance measurements. Our analyses of optical properties and their empirical relationships with optically active substances showed that the differences in color could entirely be attributed to variations in the concentration of two optically active substances: dissolved organic carbon, which was a major contributor to spectral absorption, and nonalgal suspended particulate matter, which contributed to spectral scattering as well as absorption. The latter component was dominated by small sized particles that had unusually high mass‐specific absorption and scattering properties. Analysis of high spatial resolution, multispectral satellite imagery of these ponds showed that these two optically important constituents could be estimated by multivariate modeling. The results indicate that remote sensing surveys will provide valuable synoptic observations of permafrost thaw ponds across the vast subarctic region, and may allow scaling up of local greenhouse gas flux measurements to regional and circumpolar scales.

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