prošireni sažetak izlaganja sa skupa
This research aims to determine the impact of climate change on the E-flow by modelling low flows, sediment, total N, and total P under eight future climate change scenarios, using Indicators of Hydrological Alterations (IHAs) and biological indicators for the Sutla River downstream of the dam Vonarje. Since water temperature is a primary abiotic factor, the water temperature model was created using the machine learning tool Weka to calculate water temperature based on air temperature, physical-chemical indicators, abiotic and biological indicators for future scenarios.
E-flow; Climate change scenarios; Biological indicators; Sutla River; Machine learning; Water temperature; Model
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The ever-growing usage and adaptation of HTTP/3 in web traffic leverages Quick UDP Internet Connections (QUIC) as a transport protocol. QUIC is widely recognized for reduced latency, enhanced…
