Biophysical Assessment of Lake Ecosystem Services for Flood Regulation

Remote Sensing for Environmental Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Kamaleddin Aghaloo Ph.D. kamal [at] mruni.eu Environmental Management Laboratory, Mykolas Romeris University
Vilnius, Lithuania
Miguel Inácio Ph.D. miguel.inacio [at] mruni.eu Environmental Management Laboratory, Mykolas Romeris University
Vilnius, Lithuania
Paulo Pereira Ph.D. pereiraub [at] gmail.com Environmental Management Laboratory, Mykolas Romeris University
Vilnius, Lithuania

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 20.07.2026 - 10:45
Abstract 

Lakes and adjacent wetland networks provide essential benefits for flood protection, but climate change and rapid urbanisation increasingly strain these ecosystems and their services. Traditional approaches to planning and management primarily rely on subjective, qualitative assessments of ecosystems, neglecting the relationship between supply and demand. However, accurately quantifying and mapping the benefits that can be delivered to people is important for supporting their health and well-being. This study presents a framework for high-resolution mapping of lake ecosystem services (ES) for flood regulation and coastal protection across two urban lake basins in Lithuania. A framework is proposed, and a geographic information system (GIS)-based analysis is utilised to prepare, process, and integrate geospatial data layers representing biophysical characteristics at 10-meter resolution within a 5-km buffer around the lakes. To model flood-regulation supply and demand, 13 variables representing soil, land, population, and built-area characteristics were used. Using Spearman's rank correlation, redundant variables were identified and removed. After reclassification, a weighted-sum function in ArcGIS Pro was used to combine the variables and create supply and demand models. Correlation analysis further identified the indicators that contributed most to each model. Finally, a surplus/deficit map was created by subtracting demand from supply using the Raster Calculator tool. Results revealed a spatial concentration of deficit areas in the northern part of Lake Mastis. This study provides municipalities with a powerful analytical tool for evidence-based planning decisions to safeguard vulnerable communities.

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