Comparative assessment of Watershed Hydrological Health (WHH) using multi-criteria decision-making approach based on PSR framework

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123833 - 123833

Published: Dec. 27, 2024

Language: Английский

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Reducing the computational cost and time of environmental flow estimation based on machine learning approaches

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 15, 2024

Abstract In recent decades, the reckless exploitation of rivers has caused significant changes in their ecosystems and upstream flow. It is imperative to understand that preservation river solely relies on maintaining environmental flow (EF). Estimating EF requires filed sampling, which are both time-consuming costly. Thus, purpose this research estimate for a generalize its result adjacent using modelling. To determine EF, physical habitat simulation (PHABSIM) model was used. Habitat suitability indexes (HSI) were created based survey water velocity, depth, channel index temperature river. predict other rivers, linear regression (LR) two different types neural network models, including Adaptive Neuro-Fuzzy Inference System (ANFIS) multi-layer perceptron (MLP) utilized. study, 80% 20% data used training testing phases, respectively. Among ANFIS model, date obtained phase as follows R 2 = 0.98, RMSE 0.0248 MAE 0.0006 well 0.97, 0.0295 0.0008. The accuracy them higher compared MLP LR models predicting EF. Therefore, hybrid can be suitable alternative method estimating

Language: Английский

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Decision models enhancing environmental flow sustainability: A strategic approach to water resource management

AIMS environmental science, Journal Year: 2024, Volume and Issue: 11(6), P. 900 - 917

Published: Jan. 1, 2024

<p>Proper water resource management is essential for maintaining a sustainable supply chain and meeting demand. The urgent need to preserve river ecosystems by sustaining environmental flow (EF) in the realm of has been highlighted drastic changes upstream dynamics brought about careless exploitation last few decades. To optimize EF basin management, we present an integrated modeling approach. We focused on Pir Khezran River basin. Our objective was estimate generalize findings adjacent rivers using techniques, thus providing valuable insights applications. assessment optimization under uncertain conditions achieved combining physical habitat simulation (PHABSIM) with advanced techniques like Adaptive Neuro-Fuzzy Inference Systems (ANFIS) Multilayer Perceptron (MLP) neural networks. This approach contributes solutions conservation effectively optimizing EF, as demonstrated results. research, therefore, makes contributions various areas such ecological preservation, systems, policy considerations.</p>

Language: Английский

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Utilizing InVEST ecosystem services model combined with deep learning and fallback bargaining for effective sediment retention in Northern Iran

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 14, 2024

Language: Английский

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