Four decades of satellite observations reveal climate-driven shifts and spatial heterogeneity in shallow lake Chlorophyll-a dynamics
(2026) In Water Research 289.- Abstract
Shallow lakes worldwide face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of Chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to the high costs and logistical constraints of traditional sampling approaches across large, heterogeneous water bodies. Lake Balaton, a large shallow lake system (80 km long, 7 km wide, 3.7 m mean depth) in Central Europe, exemplifies these monitoring challenges while serving as a representative system for understanding climate-driven changes in temperate shallow lakes. Despite decades of in-situ measurements along the lake's centerline, fine-scale spatial patterns and long-term temporal trends in Chl-a remain poorly characterized due to sparse... (More)
Shallow lakes worldwide face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of Chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to the high costs and logistical constraints of traditional sampling approaches across large, heterogeneous water bodies. Lake Balaton, a large shallow lake system (80 km long, 7 km wide, 3.7 m mean depth) in Central Europe, exemplifies these monitoring challenges while serving as a representative system for understanding climate-driven changes in temperate shallow lakes. Despite decades of in-situ measurements along the lake's centerline, fine-scale spatial patterns and long-term temporal trends in Chl-a remain poorly characterized due to sparse samplings. Using a machine-learning-derived optical remote sensing dataset (1984–2023) at 30 m spatial resolution, we conducted comprehensive spatiotemporal analysis of Chl-a dynamics and examined relationships with bathymetry, nutrient loading, and light availability features. Our analysis reveals an exponential west-to-east decline in Chl-a concentrations with distance from the primary nutrient source, characterized by a consistent decay rate of 0.04–0.06 km-1 (typically 0.05 km-1). Littoral zones consistently exhibited 1.3–2.8 times higher optical Chl-a concentrations than pelagic zones, reflecting integrated signals from phytoplankton, benthic algae, and submerged macrophytes. Phenological analysis demonstrated significant climate-driven shifts, with peak Chl-a timing advancing by 20 days over the study period and growing season onset occurring 10 days earlier, consistent with regional warming trends. These findings provide a transferable framework for satellite-based water quality monitoring in shallow lake systems and demonstrate the critical importance of accounting for spatial heterogeneity and climate-driven temporal shifts in lake management strategies globally.
(Less)
- author
- Li, Huan ; Somogyi, Boglárka ; Chen, Xiaona ; Wan, Wei ; Duan, Zheng LU ; Woolway, R. Iestyn and Tóth, Viktor R.
- organization
- publishing date
- 2026-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Asynchronous change, Ecological management, Littoral and pelagic zones, Section profile, Water quality
- in
- Water Research
- volume
- 289
- article number
- 124925
- publisher
- Elsevier
- external identifiers
-
- scopus:105021317237
- pmid:41223622
- ISSN
- 0043-1354
- DOI
- 10.1016/j.watres.2025.124925
- language
- English
- LU publication?
- yes
- id
- 943ea653-1321-4c14-ba2e-f54a184914e6
- date added to LUP
- 2026-01-30 09:33:39
- date last changed
- 2026-01-30 09:46:23
@article{943ea653-1321-4c14-ba2e-f54a184914e6,
abstract = {{<p>Shallow lakes worldwide face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of Chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to the high costs and logistical constraints of traditional sampling approaches across large, heterogeneous water bodies. Lake Balaton, a large shallow lake system (80 km long, 7 km wide, 3.7 m mean depth) in Central Europe, exemplifies these monitoring challenges while serving as a representative system for understanding climate-driven changes in temperate shallow lakes. Despite decades of in-situ measurements along the lake's centerline, fine-scale spatial patterns and long-term temporal trends in Chl-a remain poorly characterized due to sparse samplings. Using a machine-learning-derived optical remote sensing dataset (1984–2023) at 30 m spatial resolution, we conducted comprehensive spatiotemporal analysis of Chl-a dynamics and examined relationships with bathymetry, nutrient loading, and light availability features. Our analysis reveals an exponential west-to-east decline in Chl-a concentrations with distance from the primary nutrient source, characterized by a consistent decay rate of 0.04–0.06 km<sup>-1</sup> (typically 0.05 km<sup>-1</sup>). Littoral zones consistently exhibited 1.3–2.8 times higher optical Chl-a concentrations than pelagic zones, reflecting integrated signals from phytoplankton, benthic algae, and submerged macrophytes. Phenological analysis demonstrated significant climate-driven shifts, with peak Chl-a timing advancing by 20 days over the study period and growing season onset occurring 10 days earlier, consistent with regional warming trends. These findings provide a transferable framework for satellite-based water quality monitoring in shallow lake systems and demonstrate the critical importance of accounting for spatial heterogeneity and climate-driven temporal shifts in lake management strategies globally.</p>}},
author = {{Li, Huan and Somogyi, Boglárka and Chen, Xiaona and Wan, Wei and Duan, Zheng and Woolway, R. Iestyn and Tóth, Viktor R.}},
issn = {{0043-1354}},
keywords = {{Asynchronous change; Ecological management; Littoral and pelagic zones; Section profile; Water quality}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Water Research}},
title = {{Four decades of satellite observations reveal climate-driven shifts and spatial heterogeneity in shallow lake Chlorophyll-a dynamics}},
url = {{http://dx.doi.org/10.1016/j.watres.2025.124925}},
doi = {{10.1016/j.watres.2025.124925}},
volume = {{289}},
year = {{2026}},
}