Preprints
https://doi.org/10.5194/egusphere-2024-3248
https://doi.org/10.5194/egusphere-2024-3248
02 Dec 2024
 | 02 Dec 2024
Status: this preprint is open for discussion.

The Hydrological Archetypes of Wetlands

Abigail E. Robinson, Anna Scaini, Francisco J. Peña, Peter A. Hambäck, Christoph Humborg, and Fernando Jaramillo

Abstract. Wetlands are valuable and diverse environments that contribute to a vast range of ecosystem services, such as flood control, drought resilience, and carbon sequestration. The provision of these ecosystem services depends on their hydrological functioning, which refers to how water is stored and moved within a wetland environment. Since the hydrological functions of wetlands vary widely based on location, wetland type, hydrological connectivity, vegetation, and seasonality, there is no single approach to defining these functions. Consequently, accurately identifying their hydrological functions to quantify ecosystem services remains challenging. To address this issue, we investigate the hydrological regimes of wetlands, focusing on water extent, to better understand their hydrological functions. We achieve this goal using Sentinel-1 SAR imagery and a self-supervised deep learning model (DeepAqua) to predict surface water extent for 43 Ramsar sites in Sweden between 2020–2023. The wetlands are grouped into the following archetypes based on their hydrological similarity: 'autumn drying', ‘summer dry', 'spring surging', 'summer flooded', ‘spring flooded' and ‘slow drying'. The archetypes represent great heterogeneity, with flashy regimes being more prominent at higher latitudes and smoother regimes found preferentially in central and southern Sweden. Additionally, many archetypes show exceptional similarity in the timing and duration of flooding and drying events, which only became apparent when grouped. We attempt to link hydrological functions to the archetypes whereby headwater wetlands like the spring-surging archetype have the potential to accentuate floods and droughts, while slow-drying wetlands, typical of floodplain wetlands, are more likely to provide services such as flood attenuation and low flow supply. Additionally, although wetlands can be classified in myriad ways, we propose that classifying wetlands based on the hydrological regime is useful for identifying hydrological functions specific to the site and season. Lastly, we foresee that hydrological regime-based classification can be easily applied to other wetland-rich landscapes to understand the hydrological functions better and identify their respective ecosystem services.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Abigail E. Robinson, Anna Scaini, Francisco J. Peña, Peter A. Hambäck, Christoph Humborg, and Fernando Jaramillo

Status: open (until 13 Jan 2025)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Abigail E. Robinson, Anna Scaini, Francisco J. Peña, Peter A. Hambäck, Christoph Humborg, and Fernando Jaramillo

Data sets

Supplementary data Abigail E. Robinson https://doi.org/10.5281/zenodo.13833605

Model code and software

hydrological_archetypes Abigail E. Robinson https://github.com/ab-e-rob/hydrological_archetypes

Abigail E. Robinson, Anna Scaini, Francisco J. Peña, Peter A. Hambäck, Christoph Humborg, and Fernando Jaramillo
Metrics will be available soon.
Latest update: 02 Dec 2024
Download
Short summary
Wetlands are vital for flood control and drought resistance. These benefits are hard to pinpoint because they depend on water storage and movement, which are extremely variable. To address this, we study seasonal patterns of wetland water area using satellite imagery and AI. Out of 43 Swedish wetlands, we identify 6 groups with similar patterns, linking some to flood buffering and others to flood risk. This method can improve wetland management by identifying specific benefits.