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An integrated modeling approach to predict trophic state changes in a large Brazilian reservoir

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  • Barbosa, Carolina Cerqueira
  • Calijuri, Maria do Carmo
  • Anjinho, Phelipe da Silva
  • dos Santos, André Cordeiro Alves

Abstract

Process-based ecological models have been used to study freshwater ecosystems and water quality on a broad scale. However, it is also of pivotal importance to incorporate watershed dynamics and nutrient releases in the downstream freshwaters. Integrated modeling approaches have been used to understand the combined effect of climate warming and land use and land cover (LULC) changes in lake ecosystems. Moreover, most basin-scale water quality models require many datasets and parameters to perform reliable simulations which contributes to reduce studies in poorly monitored basins, most of them located in the Global South. In this study, we developed a coupled hydrological-biogeochemical-ecological modeling framework forced by two regionalized climate models and three LULC change scenarios to forecast trophic state changes in a subtropical multipurpose reservoir for the decade 2050-2060. The projections indicated an average air temperature increase between 2°C and 3°C and a downward trend of the average rainfall and longwave radiation for the 2050s in comparison to the last decade. We found a pattern of 28% increase in total phosphorus (TP) and total chlorophyll-a (TChla) concentrations in the reservoir compared with the historical baseline. The climate warming projections along the 2059 projected LULC and basin's increased economic development scenarios have predicted trophic state index (TSI) shifts between mesotrophic and eutrophic conditions (53.3

Suggested Citation

  • Barbosa, Carolina Cerqueira & Calijuri, Maria do Carmo & Anjinho, Phelipe da Silva & dos Santos, André Cordeiro Alves, 2023. "An integrated modeling approach to predict trophic state changes in a large Brazilian reservoir," Ecological Modelling, Elsevier, vol. 476(C).
    • Handle: RePEc:eee:ecomod:v:476:y:2023:i:c:s0304380022003258
    DOI: 10.1016/j.ecolmodel.2022.110227
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