Landscape functioning in reservoir water quality prediction: Current use and predictive capacity

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Portela, AP (Author) Other; Gonçalves, J (Author) Other; Ana Seneca (Author) FCUP; Vaz, AS (Author) Other; de Lima, LT (Author) Other; Pinto, I (Author) Other; Rodrigues, S (Author) Other; Antunes, SC (Author) FCUP; Joao Honrado (Author) FCUP

Journal

The Journal is awaiting validation by the Administrative Services.

Title: ECOHYDROLOGY

ISSN: 1936-0584

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-016-W9W

DOI: 10.1002/eco.2702

Abstract (EN): Reservoirs fulfil several societal needs, including water storage, energy production, flood control and recreation. However, the interruption of the river continuum may cause water quality declines that compromise water use. The surrounding landscape is a key driver of water quality variation in space and time, both across and within catchments. Therefore, understanding how landscape composition, structure and functioning influence reservoir water quality can help address management challenges. Here, we aim to investigate the current use and predictive capacity of landscape functioning indicators for reservoir water quality prediction. First, we carried out a literature review to investigate which landscape factors are most frequently studied as drivers of water quality in lentic systems. Then, we tested the predictive capacity of landscape functioning indicators in four reservoirs in Portugal using linear mixed models and multi-model inference. The literature review shows that most studies assess the effects of landscape composition while landscape functioning is rarely included. Our test using four reservoirs suggests that landscape functioning indicators, namely greenness and brightness, can complement landscape composition and structure indicators, improving the capacity to predict total suspended solids, chlorophyll-a, and total phosphorous. Landscape functioning indicators portrayed temporal variability in ecosystem dynamics that was not encompassed by landscape composition or structure indicators and may be relevant to predict specific water quality parameters. Our results show landscape functioning indicators can improve modelling of landscape contributions to water quality and thus have great potential to contribute to monitoring, modelling and forecast systems for water quality and ecological status.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14