O objetivo desse estudo é definir o interpolador que melhor represente a espacialidade das chuvas em Belo Horizonte para 3 períodos de tempo, para a chuva acumulada mensal, para o total diário e eventos diários de maior intensidade (mm/h), a partir de 14 pluviômetros de báscula instalados em nove regionais administrativas. A fim de um melhor entendimento dos eventos de chuva e sua variabilidade utilizaram-se técnicas de geoestatísticas para identificação da sua distribuição espacial. Comparou-se os métodos de interpolação por IDW, RBF e KRG através de tratamentos estatísticos dos resíduos gerados pelo método de validação cruzada. Os dados observados e calculados foram comparados a partir da média, desvio padrão, erro médio quadrático (REMQ), correlação (r), de concordância (d) e o índice de confiança (c), gerando uma qualificação do desempenho de ótimo a péssimo para os diferentes interpoladores. A correlação entre os valores indica o grau de dispersão dos dados obtidos em relação à média. O índice d indica o grau de afastamento dos valores estimados em relação aos observados. Seus valores variam de zero, para nenhuma concordância, a 1, para a concordância perfeita. Os resultados obtidos mostram que o método KRG foi o interpolador com os melhores parâmetros estatísticos para chuvas mensais e eventos diários de maior intensidade. Os totais diários apresentaram melhores parâmetros através do método RBF, apesar da análise visual do mapa apontar para melhor suavização das isoietas por KRG.
Urban lakes mitigate the negative impacts on the hydrological cycle and improve the quality of life in cities. Worldwide, the concern increases for the protection and management of urban water bodies. Since the physical-chemical and biological conditions of a small aquatic ecosystem can vary rapidly over time, traditional low frequency measurement approaches (weekly or monthly sampling) limits the knowledge and the transfer of research outcomes to management decision-making. In this context, this paper presents an automatic monitoring system including a full-scale experimental site and a data transfer platform for high-frequency observations (every 5 min) in a small and shallow urban lake (Lake Champs-sur-Marne, Paris, France, 10.3 ha). Lake stratification and mixing periods can be clearly observed, these periods are compared with the dynamic patterns of chlorophyll-a, phycocyanin, dissolved oxygen and pH. The results indicate that the phytoplankton growth corresponds with dissolved oxygen cycles. However, thermal stratification cannot totally explain the entire dynamic patterns of different physical-chemical and ecological variables. Besides, the cyanobacteria is one of the dominating groups of phytoplankton blooms during the lake stratification periods (8 August-29 September 2016). During the cooling mixed period (29 September-19 October 2016), the high concentration of chlorophyll-a is mainly caused by the other phytoplankton species, such as diatoms. Perspectives are discussed in order to apply this observation system for real-time management of water bodies and lakes.
Urban lakes and reservoirs provide important ecosystem services. However, their water quality is being affected by anthropogenic pressures. The thermal regime is a strong driver of the vertical transport of nutrients, phytoplankton and oxygen. Thermal stratification can modify biogeochemical processes. In this paper, a three-dimensional hydrodynamic model was implemented and validated with high-frequency measurement of water temperature. The simulation results were in agreement with the measurements. For all simulation period, the model performance was evaluated based on hourly values, presenting a maximum RMSE of 0.65 ºC and Relative Error of 2.08%. The results show that high-frequency measurement associated with a three-dimensional model could help to understand and identify the reasons for the changes in the thermal condition of a shallow urban lake. The impact of the stream inflow on the temperature was highlighted, showing that during higher discharge events, when the river temperature is colder than the lake water, it flows into the lake deeper layers. The inflow water sank to the deeper layers where the lake morphology changes. The model showed an impact along the entire lake, showing the importance of monitoring the inflow water temperature. This modelling tool could be further used to study specific patterns of reservoir hydrodynamics.
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