Abstract
Lake Sapanca is the drinking water source of the Sakarya province of Turkey. Intensive urbanization in the region is the main obstacle to implementing appropriate physical planning and measures to adapt to rapid change. The monitoring of the water quality parameters in the planning and management of the lakes is significant. The Artificial Neural Network (ANN), a mathematical representation of the human brain’s functioning, was employed to estimate the Lake’s Dissolved Oxygen (DO) concentration. pH, Magnesium (Mg), Temperature (Temp), Chemical Oxygen Demand (COD), Orthophosphate (o-PO4), Nitrite Nitrogen (NO2-N), and Nitrate Nitrogen (NO3-N) were used as independent parameters. The successful ANN model gives better results compared to the traditional multiple linear regression (MLR) analysis. The developed model can be used for forecast purposes to complete the missing data in the future and support the decision process for pollution reduction through sustainable environmental management. The eutrophication threat for Lake Sapanca has been revealed. The main objective is to create the scientific infrastructure that will draw attention to the rapid urbanization problem with ANN and eutrophication models’ outputs. It has been understood that the protection of the water budget of Lake Sapanca is the primary solution method in terms of ecological sustainability to eliminate the existing pollution.
Highlights
IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
The results show that Artificial Neural Network (ANN) is a reliable approach for accurately predicting the concentration fluctuation of quality parameters for drinking water provided from Lake Sapanca
multiple linear regression (MLR) and ANN models were compared depends on the assessment according to R2 and mean squared error (MSE) (see Equations (4) and (5))
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rapid urbanization with a fast-growing population and migration dynamics causes problems that are difficult to solve in environmental and natural resources [1]. Uncontrolled urbanization affects many ecological issues and causes concerns about the cities’ future and the quality of life [2]. Increasing construction and unplanned development parallel with the population increase makes it impossible to preserve rural ecological areas and establish sustainable cities [3]. The green spaces planning strategy is one of the well-known planning methods to conserve natural resources, and it is crucial among the ecological sustainability [4]
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