Whether the presence of permafrost systematically alters the rate of riverbank erosion is a fundamental geomorphic question with significant importance to infrastructure, water quality, and biogeochemistry of high latitude watersheds. For over four decades this question has remained unanswered due to a lack of data. Using remotely sensed imagery, we addressed this knowledge gap by quantifying riverbank erosion rates across the Arctic and subarctic. To compare these rates to non-permafrost rivers we assembled a global dataset of published riverbank erosion rates. We found that erosion rates in rivers influenced by permafrost are on average six times lower than non-permafrost systems; erosion rate differences increase up to 40 times for the largest rivers. To test alternative hypotheses for the observed erosion rate difference, we examined differences in total water yield and erosional efficiency between these rivers and non-permafrost rivers. Neither of these factors nor differences in river sediment loads provided compelling alternative explanations, leading us to conclude that permafrost limits riverbank erosion rates. This conclusion was supported by field investigations of rates and patterns of erosion along three rivers flowing through discontinuous permafrost in Alaska. Our results show that permafrost limits maximum bank erosion rates on rivers with stream powers greater than 900 W/m-1. On smaller rivers, however, hydrology rather thaw rate may be dominant control on bank erosion. Our findings suggest that Arctic warming and hydrological changes should increase bank erosion rates on large rivers but may reduce rates on rivers with drainage areas less than a few thousand km2.
Spectral PCA (sPCA), in contrast to classical PCA, offers the advantage of identifying organized spatio-temporal patterns within specific frequency bands and extracting dynamical modes. However, the unavoidable tradeoff between frequency resolution and robustness of the PCs leads to high sensitivity to noise and overfitting, which limits the interpretation of the sPCA results. We propose herein a simple non-parametric implementation of sPCA using the continuous analytic Morlet wavelet as a robust estimator of the cross-spectral matrices with good frequency resolution. To improve the interpretability of the results, especially when several modes of similar amplitude exist within the same frequency band, we propose a rotation of the complex-valued eigenvectors to optimize their spatial regularity (smoothness). The developed method, called rotated spectral PCA (rsPCA), is tested on synthetic data simulating propagating waves and shows impressive performance even with high levels of noise in the data. Applied to global historical geopotential height (GPH) and sea surface temperature (SST) daily time series, the method accurately captures patterns of atmospheric Rossby waves at high frequencies (3 to 60 days periods) in both GPH and SST and the El Niño-Southern Oscillation (ENSO) at low frequencies (2 to 7 years periodicity) in SST. At high frequencies the rsPCA successfully unmixes the identified waves, revealing spatially coherent patterns with robust propagation dynamics.
The morphologies of global river deltas are characterized to a first-order by their channel networks, shorelines, and planform geometries (Galloway, 1975). These characteristics can vary significantly between deltas and can impact their resilience (
At water level, the erosion of frozen bank materials by rivers leaves distinctive geomorphic features indicative of the presence of permafrost (ground that remains below 0°C for two or more consecutive years). These features include thermal-erosion niching (bank undercutting), massive cantilever failures in non-cohesive sediments, and exposed ground ice (Figure 1). From above and at larger spatial scales, however, no clear geomorphic signature of permafrost has been documented in river planform (McNamara & Kane, 2009). Due to this lack of a planform signature of permafrost on rivers, an examination of riverbank erosion rates is required to answer the fundamental
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