Utilize este identificador para referenciar este registo: https://hdl.handle.net/10316/106769
Título: Current and Future Ecological Status Assessment: A New Holistic Approach for Watershed Management
Autor: Fonseca, André R.
Santos, João A.
Varandas, Simone G.P.
Monteiro, Sandra M.
Martinho, José L. 
Cortes, Rui M. V.
Cabecinha, Edna 
Palavras-chave: hydrological modelling; climate change; water quality; biological functional traits; macroinvertebrates; HSPF
Data: 2020
Editora: MDPI
Projeto: ALICE EAPA_261/2016 funded by Atlantic Area: European Regional Development Fund (ERDF) through INTERREG Atlantic Area 2020 Transnational Cooperation Program 
Post-Doctoral fellowship BPD/UTAD/7/2018 
UIDB/04033/2020 
Título da revista, periódico, livro ou evento: Water (Switzerland)
Volume: 12
Número: 10
Resumo: The Paiva River catchment, located in Portugal, integrates the Natura 2000 network of European Union nature protection areas. Resorting to topography, climate and land-use data, a semi-distributed hydrological model (Hydrological Simulation Program–FORTRAN) was run in order to simulate the hydrological cycle of the river and its tributaries. The model was calibrated over a 25-year period and validated within a 31-year period. Its performance was verified by comparing the recorded and simulated daily flows. The values of the Nash–Sutcli e coe cient of e ciency of 0.95 and 0.76, and coe cient of determination of 0.95 and 0.82, were achieved for calibration and validation, respectively, thus showing a quite satisfactory model performance. Subsequently, the climate change impacts on temperature and precipitation, as well as their extremes, and on the flowrates were also assessed for a future period (2041–2070) under two anthropogenic forcing scenarios (representative concentration pathways 4.5 and 8.5). A procedure for selecting the most relevant metrics for assessing the ecological condition of the Paiva River was developed based upon a set of 52 invertebrate families sampled. Correspondence analyses were carried out for biological datasets (traits/metrics) with physicochemical and land use/land cover matrices separately. Out of all variables, water quality and flow and agriculture land use explained most of the variance observed. The integrated analysis undertaken in the present study is an important advance when compared to previous studies and it provides key information to stakeholders and decision-makers, particularly when planning suitable adaptation measures to cope with changing climates in the forthcoming decades.
URI: https://hdl.handle.net/10316/106769
ISSN: 2073-4441
DOI: 10.3390/w12102839
Direitos: openAccess
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