SUPR
Remote sensing based detection of water resilience loss
Dnr:

NAISS 2024/22-998

Type:

NAISS Small Compute

Principal Investigator:

Romi Amilia Lotcheris

Affiliation:

Stockholms universitet

Start Date:

2024-08-19

End Date:

2025-03-01

Primary Classification:

10502: Environmental Sciences (social aspects to be 507)

Allocation

Abstract

The hydrological cycle is critical for Earth system stability, governing a range of coupled processes in terrestrial ecosystems, from biodiversity to carbon sequestration. In parallel, people, places, and economies are linked across geographies and socioeconomic contexts by networks of virtual water trade. Through this complex connectivity, changes to the water cycle driven by Anthropogenic activity can propagate through the Earth system across scales. Through land-atmosphere coupling, changes in precipitation patterns can drive further change locally and in downwind regions through a mutual causal link. Likewise, changes to ecosystem vegetation structure driven by hydrological extremes can affect precipitation patterns and water storage at the continental scale. The question of rate of change is particularly relevant for systems subject to fast increasing pressure from human activity. Managing anthropogenic water cycle modifications demands an understanding of hydro-climatic variability, vulnerability, and spatial-temporal connectivity. However, the degree to which changes in driving hydrological variables, including precipitation, evaporation, and soil moisture, have affected ecosystem resilience, and vice-versa through land-atmosphere feedbacks, remains an open question. While the impacts of anthropogenic change on the water cycle at the regional or catchment scale have been well-documented, there is limited quantification of the Earth system-wide water cycle responses to Anthropogenic change. We hypothesise that through the mutual causal link described above, a loss of vegetation resilience will also be detectable in the hydrological drivers of this resilience loss; a change in vegetation begets a change in precipitation, and vice versa. Here, using remotely sensed time series data, we employ both early warning signals of resilience loss and indicators of rate-based tipping to detect non-linear changes to key hydrological variables at the global scale. In doing so, we aim to present an initial assessment of global water resilience and areas vulnerable to resilience loss. Changes to hydrological variables can have wide-reaching impacts on ecological (e.g., affecting biodiversity, ecosystem structure and function), and social systems (e.g., affecting crop yields in breadbasket regions). Here, we present a new dimension to the characterisation of regions vulnerable to resilience loss.