Short-Term Daily Univariate Streamflow Forecasting Using Deep Learning Models by Eyob Betru Wegayehu, Fiseha Behulu Muluneh

“…Hence, in this study, we compared Stacked Long Short-Term Memory (S-LSTM), Bidirectional Long Short-Term Memory (Bi-LSTM), and Gated Recurrent Unit (GRU) with the classical Multilayer Perceptron (MLP) network for one-step daily streamflow forecasting. The analysis used daily time series data collected from Borkena (in Awash river basin) and Gummera (in Abay river basin) streamflow stations. …”
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An explainable Bayesian gated recurrent unit model for multi-step streamflow forecasting by Lizhi Tao, Yueming Nan, Zhichao Cui, Lei Wang, Dong Yang

“…The EB-GRU outperforms the MLP and SVM at each lead time, particularly at shorter lead times, highlighting its effectiveness in capturing short-term streamflow dynamics. The analysis of uncertainty quantization shows that noise in the input data is the primary source of overall uncertainty in model prediction, whereas a notable increase is observed in the uncertainty caused by the model in the flood season. …”
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Effectiveness of three machine learning models for prediction of daily streamflow and uncertainty assessment by Luka Vinokić, Milan Dotlić, Veljko Prodanović, Slobodan Kolaković, Slobodan P. Simonovic, Milan Stojković

“…This study evaluates three Machine Learning (ML) models—Temporal Kolmogorov-Arnold Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks (TCN)—focusing on their capabilities to improve prediction accuracy and efficiency in streamflow forecasting. We adopt a data-centric approach, utilizing large, validated datasets to train the models, and apply SHapley Additive exPlanations (SHAP) to enhance the interpretability and reliability of the ML models. …”
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Tree‐Ring Insights Into Past and Future Streamflow Variations in Beijing, Northern China by Honghua Cao, Feng Chen, Mao Hu, Tiyuan Hou, Xiaoen Zhao, Shijie Wang, Heli Zhang

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The Music of Rivers: The Mathematics of Waves Reveals Global Structure and Drivers of Streamflow Regime by Brian C. Brown, Aimee H. Fullerton, Darin Kopp, Flavia Tromboni, Arial J. Shogren, J. Angus Webb, Claire Ruffing, Matthew Heaton, Lenka Kuglerová, Daniel C. Allen, Lillian McGill, Jay P. Zarnetske, Matt R. Whiles, Jeremy B. Jones Jr., Benjamin W. Abbott

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Use of Non-Parametric Approaches on Normality of Hydrologic Variables by Kadri Yürekli, Müberra Erdoğan, Mehmet Murat Cömert

“…Parametric approaches in statistical analysis assume that any given data are normally distributed. …”
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Archetypal flow regime change classes and their associations with anthropogenic drivers of global streamflow alterations by Vili Virkki, Reetik Kumar Sahu, Mikhail Smilovic, Josias Láng-Ritter, Miina Porkka, Matti Kummu

“…Here, we advance this understanding by providing an observation-based association analysis of streamflow change and its drivers. We use observed streamflow data in 3,293 catchments globally and combine them with data on precipitation, evapotranspiration, water use, and damming. …”
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Climate change projections and hydrological modelling to predict the streamflow in Berach-Banas catchment, Rajasthan by Kuldeep Pareta, Yogita Dashora

“…The climate change impact analysis indicated a consistent increase in streamflow rates for 2030, 2050, and 2090 compared to 2022, likely driven by rising temperatures and changes in precipitation patterns. …”
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Spatial and temporal aspects of high streamflow periods within the Danube drainage basin in Bulgaria by Kalin SEYMENOV

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Deep Learning‐Based Approach for Enhancing Streamflow Prediction in Watersheds With Aggregated and Intermittent Observations by Nikunj K. Mangukiya, Ashutosh Sharma

“…Abstract Accurate daily streamflow estimates are crucial for water resources management. …”
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Future streamflow along the French part of the Meuse River – a closer look at uncertainties by G. Thirel, L. Collet, F. Rousset, O. Delaigue, D. François, J. Gailhard, M. Le Lay, C. Perrin, M. Reverdy, R. Samacoits, M. Terrier, J.-P. Vidal, J.-P. Wagner

“…Climate projections from two Representative Concentration Pathways (RCPs) and five General Circulation Model/Regional Climate Model (GCM/RCM) couples were retrieved to feed four hydrological models run with several parameter sets to assess future streamflow. A variance analysis tool was employed to partition the sources of uncertainty. …”
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Hydrologic responses of watershed assessment to land cover and climate change using soil and water assessment tool model by R.C.C. Puno, G.R. Puno, B.A.M. Talisay

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A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments by P. Yeste, P. Yeste, P. Yeste, M. García-Valdecasas Ojeda, M. García-Valdecasas Ojeda, S. R. Gámiz-Fortis, S. R. Gámiz-Fortis, Y. Castro-Díez, Y. Castro-Díez, A. Bronstert, M. J. Esteban-Parra, M. J. Esteban-Parra

“…<p>The simultaneous incorporation of streamflow and evaporation data into sensitivity analysis and calibration approaches has great potential to improve the representation of hydrologic processes in modelling frameworks. …”
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Linking Stochastic Resonance With Long Short‐Term Memory Neural Network for Streamflow Simulation Enhancement by Xungui Li, Jian Sun, Qiyong Yang, Yi Tian, Xiaoli Yang

“…Results indicate that SR improves accuracy at approximately 70% of 1,244 stations, particularly in regions with high‐quality data. Comparative analysis shows that incorporating SR enhances the performance of deep learning models, highlighting its potential for improving both global and peak streamflow simulation accuracy. …”
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Hydrological Assessment Using the SWAT Model in the Jundiaí River Basin, Brazil: Calibration, Model Performance, and Land Use Change Impact Analysis by Larissa Brêtas Moura, Tárcio Rocha Lopes, Sérgio Nascimento Duarte, Pietro Sica, Marcos Vinícius Folegatti

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Evolutionary characteristics and attributions of ecological drought in river: A case study in the Yellow River Basin by Zifeng Yin, Shanhu Jiang, Liliang Ren, Menghao Wang, Hao Cui, Limin Zhang, Yating Liu

Subjects: “…Streamflow reconstruction…”
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The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification by André Almagro, Antônio Alves Meira Neto, Noemi Vergopolan, Tirthankar Roy, Peter A. Troch, Paulo Tarso S. Oliveira

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A 60-year analysis of past hydroclimatic variability and trends in the Mouhoun river catchment in West Africa by Tazen Fowé, Roland Yonaba, Moukhtar Tamaro Konaté, Lawani Adjadi Mounirou, Elias Nkiaka, Harouna Karambiri

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Long-term hydrological drought monitoring and trend analysis in Blue Nile River basin by Kassa Abera Tareke

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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

“…Accurate streamflow prediction is essential for water resource management and ecological conservation. …”
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