ABSTRACT
The expansion of urban areas contributes to the growth of impervious surfaces, leading to increased pollution and altering the configuration, composition, and context of land covers. This study employed machine learning methods (partial least square regressor and the Shapley Additive exPlanations) to explore the intricate relationships between urban expansion, land cover changes, and water quality in a watershed with a park and lake. To address this, we first evaluated the spatio-temporal variation of some physicochemical and microbiological water quality variables, generated yearly land cover maps of the basin adopting several machine learning classifiers, and computed the most suitable landscape metrics that better represent the land cover. The main results highlighted the importance of spatial arrangement and the size of the contributing watershed on water quality. Compact urban forms appeared to mitigate the impact on pollutants. This research provides valuable insights into the intricate relationship between landscape characteristics and water quality dynamics, informing targeted watershed management strategies aimed at mitigating pollution and ensuring the health and resilience of aquatic ecosystems.
Subject(s)
Environmental Monitoring , Machine Learning , Water Quality , Environmental Monitoring/methods , Uruguay , Urbanization , EcosystemABSTRACT
The growth of urbanization worldwide has contributed to the deterioration of the ecological status of water bodies. Efforts at improving the ecological status have been made either in isolated form or by means of integrated measures by stakeholders, but in many cases, these measures have not been evaluated to determine their benefit. In this study, we implemented a scenario analysis to restore the ecological water quality in the Cuenca River and its tributaries, which are located in the southern Andes of Ecuador. For this analysis, an integrated ecological model (IEM) was developed. The IEM linked an urban wastewater system (IUWS) model, which gave satisfactory results in its calibration and validation processes, with ecological models. The IUWS is a mechanistic model that incorporated the river water quality model, a wastewater treatment plant (WWTP) with activated sludge technology, and discharges from the sewage system. The ecological status of the waterways was evaluated with the Andean Biotic Index (ABI), which was predicted using generalized linear models (GLMs). The GLMs were calculated with physicochemical results from the IUWS model. Four scenarios that would enhance the current ecological water quality were analyzed. In these scenarios, the inclusion of a new WWTP with carbon, and with carbon and nitrogen removal as well as the addition of retention tanks before the discharges of combined sewer overflows (CSOs) were assessed. The new WWTP with carbon and nitrogen removal would bring about a better restoration of the ecological water quality due to better nitrogen removal. The retention tanks would help to enhance the ecological status of the rivers during rainy seasons. The integrated model implemented in this study was shown to be an essential tool to support decisions in the Cuenca River basin management.
ABSTRACT
RESUMO Com o crescimento da população e o consequente aumento da urbanização, o lançamento de resíduos sólidos nos sistemas de drenagem urbana tem aumentado nos últimos anos, principalmente nas regiões periféricas das cidades. Este estudo teve como objetivo qualificar e quantificar os resíduos sólidos no arroio Cancela-Tamandai, localizado em área urbana, no município de Santa Maria (RS). Foram coletados ao todo 1.153,2 kg de resíduos sólidos com uma precipitação pluviométrica total para o período de novembro de 2012 a janeiro de 2013 de 518,94 mm, sendo, desses, 93,9% composto por matéria orgânica, sendo a maioria vegetação. O arroio Cancela-Tamandai apresentou uma carga de resíduos sólidos igual a 17,27 ou 0,424 kg.hab-1.ano-1. A curva de previsão de resíduos sólidos orgânicos drenados em função da precipitação pluviométrica apresentou correlação de 76,4%, um parâmetro importante para a tomada de decisão dos gestores municipais em relação aos resíduos sólidos gerados. Assim, conceber estratégias para o monitoramento desses resíduos representa passo importante na busca de soluções que visem um melhor gerenciamento de bacias hidrográficas urbanas.
ABSTRACT With population growth, and the resulting increase in urbanization, the disposal of solid waste in the urban drainage system has increased in recent years, especially in the outskirts of the cities. This study aimed to qualify and quantify the solid waste in Cancela-Tamandai's stream, located in an urban area, in the municipality of Santa Maria (RS). Were collected in total 1.153.2 kg of solid waste with a rainfall total for the period of 518.94 mm, 93.9% of these being composed of organic matter with the majority of vegetation debrid. Cancela-Tamandai's watershed presented a load of solid waste equal to 17.27 or 0.424 kg.inhab-1.year-1. The prediction curve of drained solid waste due to the rainfall correlated 76.4%, important parameter for decision making of municipal managers in relation to solid waste generated. Thus, devise strategies for monitoring these residues represents an important step in finding solutions aimed at better management of urban watersheds.