A novel additive regression model for streamflow forecasting in German rivers-Reference-Cited by-同舟云学术

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A novel additive regression model for streamflow forecasting in German rivers

Published:2024-06 Issue: Volume:22 Page:102104
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Granata Francesco,Di Nunno Fabio^ORCID,Pham Quoc Bao

Publisher

Elsevier BV

Reference42 articles.

1. A review of methods for monitoring streamflow for sustainable water resource management;Dobriyal;Appl. Water Sci.,2017

2. Decision support system for optimizing Reservoir operations using ensemble streamflow predictions;Alemu;J. Water Resour. Plann. Manag.,2011

3. Large area hydrologic modeling and assessment. Part I. model development;Arnold;J. Am. Water Resour. Assoc.,1998

4. A process-based, distributed hydrologic model based on a large-scale method for surface– subsurface coupling;Shen;Adv. Water Resour.,2010

5. Modeling of river flow rate as a function of rainfall and temperature using response surface methodology based on historical time series;Kostić;J. Hydroinf.,2016

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1. Development of Functional Quantile Autoregressive Model for River Flow Curve Forecasting;Earth and Space Science;2024-08

2. Estimation of water quality in Korattur Lake, Chennai, India, using Bayesian optimization and machine learning;Frontiers in Environmental Science;2024-07-09

3. Dissolved oxygen forecasting in the Mississippi River: advanced ensemble machine learning models;Environmental Science: Advances;2024

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