Article
Engineering, Environmental
Ilsang Ohn, Seonghyeon Kim, Seung Beom Seo, Young-Oh Kim, Yongdai Kim
Summary: There is a growing interest in model-wise uncertainty decomposition in hydrological projections. This paper proposes a novel method for decomposing total uncertainties into model-wise uncertainties, which can be applied with general uncertainty measures and provide an intuitive interpretation. The results of analyzing real data by the proposed method are presented in the paper.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2021)
Article
Engineering, Civil
Patrice Dion, Jean-Luc Martel, Richard Arsenault
Summary: This study proposes a methodology based on a multi-hydrological model approach, addressing the biases and under-dispersion issues in ensemble streamflow predictions. By assimilating data and post-processing individual ESPs, the methodology successfully improves reliability in short-term hydrological forecasts through a multi-model approach.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Basil Kraft, Martin Jung, Marco Koerner, Sujan Koirala, Markus Reichstein
Summary: This study presents a hybrid approach to global hydrological modeling that combines machine learning methods with physical principles. The results show that the hybrid model can reproduce key patterns of the global water cycle and provide insights into the physical responses. It offers a new data-driven perspective on modeling the global hydrological cycle, complementing existing global modeling frameworks.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Review
Geochemistry & Geophysics
Hadush Meresa, Yongqiang Zhang, Jing Tian, Ning Ma, Xuanze Zhang, Hadi Heidari, Shahid Naeem
Summary: Understanding the potential impacts of climate change on extreme hydrological events is crucial for water resource and risk management. Integrated modeling frameworks play a key role in studying these impacts, with various components contributing to uncertainty in predicting extreme flows in different regions.
SURVEYS IN GEOPHYSICS
(2023)
Article
Energy & Fuels
Paul Dicke, Simon Resch, Frank Steinbacher, Matthias Luther, Reinhard German
Summary: Electrochemical batteries are becoming increasingly important in our renewable powered society, and the capability to simulate these systems is crucial. A modular, versatile modeling methodology is presented in this work, able to simulate different technologies and sizes of storage units, while considering nonlinearities and various characteristics. Comprehensive simulation results for different storage systems are provided to showcase the fidelity, parametrization, and versatility of the approach.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Meteorology & Atmospheric Sciences
Titas Ganguly, Dhyan S. Arya
Summary: This study proposes a comprehensive framework for ranking and generating ensemble data for GCMs and validates it using precipitation and temperature data from India. The results show that Bayesian framework-based rankings outperform other methods and the orthonormal distribution-based Bayesian ranking performs well in precipitation. The weighted ensemble has closer proximity to the observed data distribution compared to the traditional mathematical average. The assessment of projected extremes shows varying levels of confidence in the attribution of precipitation extremes to anthropogenic causes under different climate scenarios.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Water Resources
Jitao Zhou, Xiaofeng Wang, Jiaohao Ma, Zixu Jia, Xiaoxue Wang, Xinrong Zhang, Xiaoming Feng, Zechong Sun, You Tu, Wenjie Yao
Summary: This study focused on the source regions of the Yellow River and Yangtze River in the central-eastern part of the Tibetan Plateau. Using the SWAT model, the effects of different types, sources, and resolutions of input data on the model output were tested. The results showed that meteorological data is crucial for the model's runoff simulation, and ground meteorological observation station data outperforms reanalysis data. The selection of DEM resolution and LULC data had minimal effects on the simulation, and the best input data combination was OBS + 90m DEM + CNLULC.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2023)
Article
Astronomy & Astrophysics
Sippora Stellingwerf, Emily Riddle, Thomas M. Hopson, Jason C. Knievel, Barbara Brown, Mekonnen Gebremichael
Summary: This study examines the performance of ensemble forecast systems in Ethiopian catchments, with the European model showing the best performance in predicting daily rainfall variations and the Canadian model demonstrating the most realistic ensemble spread. The multi-model ensemble outperforms individual models in terms of skill and can provide reliable forecasts up to 9 days ahead.
EARTH AND SPACE SCIENCE
(2021)
Article
Multidisciplinary Sciences
Mohamed Zaghloul, Mofreh Salem, Amr Ali-Eldin
Summary: This paper introduces a framework based on query feature modeling and ensemble learning to predict query performance, demonstrating its effectiveness and advantages compared to related work.
Article
Engineering, Civil
Liting Zhou, Pan Liu, Xiaojing Zhang, Lei Cheng, Qian Xia, Kang Xie, Weibo Liu, Jun Xia
Summary: This study proposes a framework to investigate the impacts of temporal relative influence of hydrological processes on structure identification and validates its effectiveness. The results indicate that considering the temporal relative influence of hydrological processes can improve the identifiability of model structures, with quickflow and soil evaporation being the most identifiable processes, followed by infiltration, baseflow, and snow balance processes.
JOURNAL OF HYDROLOGY
(2023)
Article
Computer Science, Information Systems
Sadia Afroze, Md. Rajib Hossain, Mohammed Moshiul Hoque, M. Ali Akber Dewan
Summary: This paper proposes a deep learning-based ensemble technique (V-ensemble) to identify speaking modes in low-resolution and noisy images. The proposed system integrates mouth region extraction and mouth state detection modules and achieves the highest accuracy on three datasets.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Mechanics
Maryam Aliakbari, Mohammadreza Soltany Sadrabadi, Peter Vadasz, Amirhossein Arzani
Summary: Modeling fluid flow and transport in heterogeneous systems with unknown spatially varying parameters is challenging. Physics-informed neural networks (PINN) have been popular, but sensitive to hyperparameters and can produce unrealistic patterns in inverse problems. In this study, an ensemble PINN (ePINN) approach is proposed to mitigate these issues by using an ensemble of parallel neural networks with meaningful initializations. The results show that ePINN can produce more realistic and accurate solutions for inverse problems in heterogeneous systems.
Article
Environmental Sciences
Arthur Kolling Neto, Vinicius Alencar Siqueira, Cleber Henrique de Araujo Gama, Rodrigo Cauduro Dias de Paiva, Fernando Mainardi Fan, Walter Collischonn, Reinaldo Silveira, Cassia Silmara Aver Paranhos, Camila Freitas
Summary: This study evaluates the accuracy of medium-range weekly streamflow forecasts for 147 large Brazilian hydropower plants and compares them with operational forecasts issued by the National Electric System Operator. The study finds that simple corrections on continental-scale hydrological models can result in competitive forecasts even for regional-scale applications.
Article
Computer Science, Information Systems
Arya Hadizadeh Moghaddam, Saeedeh Momtazi
Summary: The advancement of social media has led to an increase in the amount of frequently shared content. Researchers have focused on using natural language processing to detect real-life events, and various algorithms have been developed for this purpose. This paper proposes a Semantic Modular Model that clusters documents, ignores irrelevant ones, and extracts more important keywords. Compared to state-of-the-art methods, the proposed model performs better in event identification and keyword extraction, achieving a 7.9% improvement in mean keyword-precision metric.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Environmental Sciences
Anil Kumar, Rakesh Khosa, Ashwin Kumar Gosian
Summary: River flooding is a global concern that causes significant damage to lives and infrastructure. This research focuses on the effects of reservoirs operation on massive flooding in the Periyar River Basin. A two-step modelling technique was used to simulate flood scenarios and identify flood-prone areas. The proposed framework can be an effective tool for planning and managing natural disasters, such as flash floods.
Article
Meteorology & Atmospheric Sciences
Islem Hajji, Daniel F. Nadeau, Biljana Music, Francois Anctil, Jingfeng Wang
Summary: Snow cover is crucial for the water and energy budgets in cold regions, posing a challenge for hydrologic models. An innovative approach based on the theory of maximum entropy production (MEP) was developed to model energy budgets for snow-covered surfaces, generalizing to simulate water vapor fluxes over the entire snowpack lifecycle. The study demonstrates the effectiveness of the proposed approach for modeling total surface water vapor fluxes over the snowpack's lifecycle, with support from field observations.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2021)
Article
Water Resources
Judith Fournier, Antoine Thiboult, Daniel F. Nadeau, Nikki Vercauteren, Francois Anctil, Annie-Claude Parent, Ian B. Strachan, Alain Tremblay
Summary: This study utilized long-term eddy covariance observations to estimate evaporation in two northern hydropower reservoirs using different methods, with the bulk transfer equation showing the highest accuracy. Accuracy in estimating open water evaporation requires representative measurements of wind speed and water surface temperature.
HYDROLOGICAL PROCESSES
(2021)
Article
Soil Science
Jean-Daniel Sylvain, Francois Anctil, Evelyne Thiffault
Summary: The study combines bias correction and ensemble modeling to improve the accuracy of digital soil mapping, reduce conditional bias, and provide uncertainty assessment. The performance of ensemble modeling surpasses individual models and underdispersion in uncertainty analysis is identified. Global mapping products show low performance and important conditional bias compared to the proposed approach.
Article
Engineering, Civil
Mohammed Amine Bessar, Francois Anctil, Pascal Matte
Summary: The reliability and accuracy of the hydrometeorological ensemble prediction system coupled with a hydraulic module were evaluated in this study, showing that the proposed system provides reliable ensemble flow and water level forecasts across different forecast horizons.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
Flore Sergeant, Rene Therrien, Ludovic Oudin, Anne Jost, Francois Anctil
Summary: The study found that during the period from 1970 to 2000, there was a significant decrease in recession slope and initial recession outflow in most Arctic catchments, contrary to previous research. High topography and low permafrost extent were identified as controlling factors that complicated the relationship between recession parameters and active layer thickness evolution.
JOURNAL OF HYDROLOGY
(2021)
Article
Meteorology & Atmospheric Sciences
Georg Lackner, Daniel F. Nadeau, Florent Domine, Annie-Claude Parent, Gonzalo Leonardini, Aaron Boone, Francois Anctil, Vincent Fortin
Summary: This study examines the surface energy budget of a subarctic shrub tundra site in eastern Canada, finding that turbulent heat fluxes in this region are more complex compared to other Arctic sites, mainly influenced by the soil moisture properties.
JOURNAL OF HYDROMETEOROLOGY
(2021)
Article
Environmental Sciences
Marinela del Carmen Valencia Giraldo, Simon Ricard, Francois Anctil
Summary: There is ongoing debate about whether probabilistic (top-down) or possibilistic (bottom-up) approaches are more suitable for estimating potential future climate impacts. In the context of deep uncertainty, bottom-up approaches that assess the sensitivity and vulnerability of systems to climate changes have become more popular. This study proposes a refined framework that combines the scenario-neutral method of the bottom-up approach with elements of the top-down approach. The results reveal regional and differential behaviors of hydroclimatology and low flows under different climate scenarios.
Article
Water Resources
Adrien Pierre, Daniel F. Nadeau, Antoine Thiboult, Alain N. Rousseau, Alain Tremblay, Pierre-Erik Isabelle, Francois Anctil
Summary: Water bodies such as lakes and reservoirs influence the regional climate through the evaporation of water. This study analyzed in-situ observations of a reservoir in a subarctic environment to understand its impact. The results showed that the annual evaporation rate was 590 +/- 66 mm, accounting for approximately 51% of the annual precipitation. The study also revealed the opposite diurnal cycles of sensible and latent heat fluxes during the open water period.
HYDROLOGICAL PROCESSES
(2023)
Article
Engineering, Civil
Michael Osina Torres, Amaury Tilmant, Emixi Valdez Medina, Francois Anctil, Maria-Helena Ramos
Summary: Improving the operational effectiveness of hydropower systems is crucial due to the shift to renewable energy sources and increasing costs associated with new hydro facilities. This study focuses on the relationship between short-term streamflow forecasts and hydropower generation, as well as the impact of uncertainties on energy output. A numerical experiment using hydrologic ensemble forecasts and reservoir optimization models was conducted in Canada. The results show that forecast quality affects energy production, but it is not a one-to-one causal relationship. Additionally, the diversity of hydrological models contributes to energy production, suggesting the value of model structure diversity.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2023)
Article
Engineering, Civil
F. Sergeant, R. Therrien, F. Anctil, Laura Gatel
Summary: In cold regions, climate warming causes permafrost thaw and changes the groundwater flow dynamics from local to regional systems. The recession slope of arctic catchment hydrograph is linearly related to permafrost thawing depth, making recession analysis a valuable method to study permafrost thawing dynamics in areas with limited permafrost observations. However, the linear relationship is influenced by permafrost extent, landscape topography, and aquifer properties.
JOURNAL OF HYDROLOGY
(2023)
Article
Geosciences, Multidisciplinary
Pierre Valois, Francois Anctil, Genevieve Cloutier, Maxime Tessier, Naomie Herpin-Saunier
Summary: The frequency and severity of flooding events are expected to increase with climate change in Quebec. A longitudinal study conducted in the province examined the adaptive behaviors of residents in high flood risk zones, finding that there has been no significant increase in adaptive behavior between 2015 and 2019. However, households that have experienced a flood or flood alert in the past are more likely to adapt. The study also identified income, flood experience, and perception of living in a flood-prone zone as important predictors of behavior adoption rates.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2023)
Article
Geosciences, Multidisciplinary
Simon Ricard, Philippe Lucas-Picher, Antoine Thiboult, Francois Anctil
Summary: A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. The method combines asynchronous hydroclimatic modelling and quantile perturbation applied to streamflow observations. The results show that the proposed workflow produces useful and reliable hydrologic scenarios, which can predict seasonal mean flows similar to a conventional hydroclimatic modelling approach.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2023)
Article
Geosciences, Multidisciplinary
Jing Xu, Francois Anctil, Marie-Amelie Boucher
Summary: Forecast uncertainties are inevitable in deterministic analysis of dynamical systems. Ensemble forecasting is an effective tool to represent error growth and capture uncertainties. This study compares the performance of evolutionary multi-objective optimization with a conventional state-of-the-art post-processor in eliminating forecast biases and maintaining proper dispersion. The evolutionary multi-objective optimization method demonstrated superiority in communicating with end-users for performance improvement.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Emixi Sthefany Valdez, Francois Anctil, Maria-Helena Ramos
Summary: This study investigates the interactions between a precipitation post-processor and other uncertainty quantification tools in a hydrometeorological forecasting chain. The results show that the post-processor significantly improves the quality of precipitation forecasts, but its effectiveness in improving hydrological forecasts depends on various factors such as the configuration of the forecasting system, forecast attribute, lead time, and catchment size. Therefore, the combined effect of the precipitation post-processor and other uncertainty quantification methods should be considered when designing or enhancing hydrometeorological ensemble forecasting systems.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Geography, Physical
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, Francois Anctil, Matthieu Lafaysse, Marie Dumont
Summary: Arctic landscapes are covered in snow for at least 6 months a year, and the energy balance of the snow cover plays a key role in influencing various factors. The study aimed to quantify major heat fluxes above, within, and below a low-Arctic snowpack. Results showed that radiative losses are counterbalanced by sensible heat flux, with minimal latent heat flux. The model reproduced the observed energy balance well, but had deficiencies in simulating turbulent heat fluxes at an hourly timescale due to atmospheric stratification effects.
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)