Abstract
Abstract. For remote and vast northern watersheds, hydrological data are often sparse and incomplete. Landscape hydrology provides useful approaches for the indirect assessment of the hydrological characteristics of watersheds through analysis of landscape properties. In this study, we used unsupervised geographic object-based image analysis (GeOBIA) paired with the fuzzy c-means (FCM) clustering algorithm to produce seven high-resolution territorial classifications of key remotely sensed hydro-geomorphic metrics for the 1985–2019 time period, each with a frequency of 5 years. Our study site is the George River watershed (GRW), a 42 000 km2 watershed located in Nunavik, northern Quebec (Canada). The subwatersheds within the GRW, used as the objects of the GeOBIA, were classified as a function of their hydrological similarities. Classification results for the period 2015–2019 showed that the GRW is composed of two main types of subwatersheds distributed along a latitudinal gradient, which indicates broad-scale differences in hydrological regimes and water balances across the GRW. Six classifications were computed for the period 1985–2014 to investigate past changes in hydrological regime. The time series of seven classifications showed a homogenization of subwatershed types associated with increases in vegetation productivity and in water contents in soil and vegetation, mostly concentrated in the northern half of the GRW, which were the major changes occurring in the land cover metrics of the GRW. An increase in vegetation productivity likely contributed to an augmentation in evaporation and may be a primary driver of fundamental shifts in the GRW water balance, potentially explaining a measured decline of about 1 % (∼ 0.16 km3 yr−1) in the George River’s discharge since the mid-1970s. Permafrost degradation over the study period also likely affected the hydrological regime and water balance of the GRW. However, the shifts in permafrost extent and active layer thickness remain difficult to detect using remote-sensing-based approaches, particularly in areas of discontinuous and sporadic permafrost.
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