03 Jul 2023
 | 03 Jul 2023
Status: this preprint is currently under review for the journal HESS.

Pairing remote sensing and clustering in landscape hydrology for large-scale changes identification. Applications to the subarctic watershed of the George River (Nunavik, Canada)

Eliot Sicaud, Daniel Fortier, Jean-Pierre Dedieu, and Jan Franssen

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 spanning five 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 seven-classification time series showed a homogenization of subwatershed types associated to increases in vegetation productivity and in water content 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 evapotranspiration 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 y−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.

Eliot Sicaud et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2023-101', Anonymous Referee #1, 28 Jul 2023
    • AC1: 'Reply on RC1', Eliot Sicaud, 21 Aug 2023
  • RC2: 'Comment on hess-2023-101', Anonymous Referee #2, 22 Aug 2023
    • AC2: 'Reply on RC2', Eliot Sicaud, 29 Aug 2023

Eliot Sicaud et al.

Data sets

Pairing Remote Sensing and Clustering in Landscape Hydrology for Large-Scale Changes Identification. Applications to the Subarctic Watershed of the George River (Nunavik, Canada). Dataset and Code. Eliot Sicaud, Daniel Fortier, Jean-Pierre Dedieu, and Jan Franssen

Eliot Sicaud et al.


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Short summary
For vast northern watersheds, hydrological data are often sparse and incomplete. Our study used remote sensing and clustering to produce classifications of the George River watershed (GRW). Results show two types of subwatersheds with different hydrological behaviors. The GRW experienced a homogenization of subwatershed types due to an increase of vegetation productivity, which could explain the measured decline of 1 % (~0.16 km3 y-1) in the George River’s discharge since the mid-1970s.