Article
Environmental Sciences
Xiaomang Liu, Kun Yang, Vagner G. Ferreira, Peng Bai
Summary: The traditional calibration strategy of hydrologic models based on runoff observations has limitations. This study used remote sensing ET and TWSC products to design calibration schemes, and found that multi-objective calibration using the combination of ET and TWSC products achieved better accuracy in runoff simulation.
WATER RESOURCES RESEARCH
(2022)
Article
Water Resources
Vikas Kumar Vidyarthi, Ashu Jain
Summary: The past semi-distributed approaches for simulating rainfall-runoff still require a large amount of hydro-meteorological data for calibration. Therefore, there is a need for research efforts to develop innovative semi-distributed models that require minimal data and effort. This study proposes four semi-distributed models using a simplified lumped model in a distributed sense, gradually incorporating spatial distribution of hydro-meteorological and physiographical features in a basin. The results show that the semi-distributed models outperform the lumped model, and accuracy increases with the spatial variations in data.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Environmental Sciences
Felipe Quintero, Nicolas Velasquez
Summary: This paper introduces the HLM-Tetis model structure and its improvements over the previous HLM model structure. By adding modules to simulate snow processes, improving flexibility in simulating infiltration and percolation, and enhancing flexibility in deriving total runoff, the model has been applied to flood events in five basins in Iowa where previous model structures had limitations.
Article
Environmental Sciences
Wei Wang, Jia Liu, Chuanzhe Li, Yuchen Liu, Fuliang Yu
Summary: The study evaluated the potential of the WRF model and its 3DVar module in improving rainfall-runoff prediction accuracy, showing that assimilating radar reflectivity and observations can enhance initial conditions. The coupled atmospheric-hydrologic systems provide more accurate flood forecasts, with the grid-based Hebei model offering the most stable predictions.
Article
Engineering, Civil
Conrad Wasko, Yawen Shao, Elisabeth Vogel, Louise Wilson, Q. J. Wang, Andrew Frost, Chantal Donnelly
Summary: Changes in the hydrologic cycle have significant impacts on agricultural productivity, water resources availability, and environmental management in Australia. While northern parts of Australia have experienced increasing rainfall and water availability, the southwest and southeast coast have seen declines in rainfall, affecting runoff and soil moisture. Standardised runoff index indicates increasing streamflow droughts across large parts of Australia.
JOURNAL OF HYDROLOGY
(2021)
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
Environmental Sciences
Wade T. Crow, Jianzhi Dong, Rolf H. Reichle
Summary: This study demonstrates the importance of the rank correlation between surface soil moisture and storm-scale runoff in calibrating streamflow estimates in ungauged basins. A new calibration approach based on L4_SM has been successfully developed to identify LSM configurations with high rank correlation with observed runoff coefficients.
WATER RESOURCES RESEARCH
(2022)
Article
Mathematics
Lloyd Ling, Zulkifli Yusop, Joan Lucille Ling
Summary: This article reassesses the effectiveness of the SCS Curve Number (CN0.2) runoff model and performs model calibration using inferential statistics. Results show that the uncalibrated SCS model underestimates runoff amounts for rainfall depths less than 70 mm, while overpredicting in larger storm events. The study highlights the importance of validating the SCS model with rainfall-runoff datasets before its application for runoff prediction.
Article
Engineering, Civil
Shilei Chen, Lihua Xiong, Ling Zeng, Jong-Suk Kim, Quan Zhang, Cong Jiang
Summary: Runoff movement in karst catchments is complex, and distributed models are crucial for accurate simulation. Models considering karst landform and topographic index show improved accuracy in rainfall-runoff simulation in large-scale karst catchments.
JOURNAL OF HYDROLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Marjan Asgari, Wanhong Yang, John Lindsay, Hui Shao, Yongbo Liu, Rodrigo De Queiroga Miranda, Maryam Mehri Dehnavi
Summary: A research gap in calibrating distributed watershed hydrologic models is addressed by proposing a fault-tolerant and portable parallel calibration approach. The approach utilizes multiple perturbation factors and parallel dynamic searching strategies to achieve a balance between exploration and exploitation. Using Chapel programming language, the approach achieves super-linear speedup and high parallel efficiency, while maintaining low communication overhead and benefiting from knowledge-sharing in the convergence behavior of the parallel DDS algorithm.
ENVIRONMENTAL MODELLING & SOFTWARE
(2023)
Article
Engineering, Civil
Thien Huy Truong Nguyen, Bree Bennett, Michael Leonard
Summary: Stochastic rainfall models are important for evaluating hydrological risks, but there are discrepancies between rainfall metrics and flow metrics. The performance of different models varies depending on the strictness of the flow-based comparison and the region analyzed.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Chaowei Xu, Ziyan Han, Hao Fu
Summary: In this study, an integrated approach based on remote sensing and hydrologic-hydrodynamic modeling was developed to simulate the rainfall-runoff process in a farm dam-dominated basin. The developed model showed improved performance in simulating flood flow and peak appearance time compared to classical hydrological models.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Environmental Sciences
Yizhuo Wen, Aili Yang, Xiangming Kong, Yueyu Su
Summary: A Bayesian-model-averaging Copula (BMAC) approach is proposed for correlation analysis of monthly rainfall and runoff in Xiangxi River watershed, China. The method improves the representation of marginal distribution of hydrological variables and calibrates the joint distributions of rainfall and runoff using Gumbel Copula.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Engineering, Civil
Jie Jian, Dongryeol Ryu, Q. J. Wang
Summary: A new method using water level data to calibrate rainfall-runoff models, combined with discharge estimates derived from regionalization, has shown promising results in extending runoff prediction capability and performing better in wetter catchments.
JOURNAL OF HYDROLOGY
(2021)
Article
Geosciences, Multidisciplinary
Antoine Pelletier, Vazken Andreassian
Summary: The study investigates whether using groundwater level data through a composite calibration framework can improve streamflow simulation performance. While the additional data may be unnecessary for streamflow simulation, they improve parameter stability and the model's ability to simulate groundwater levels in various hydrogeological and hydroclimatic contexts.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Engineering, Civil
Di Zhang, Dongsheng Wang, Qidong Peng, Junqiang Lin, Tiantian Jin, Tiantian Yang, Soroosh Sorooshian, Yi Liu
Summary: Stratified water intake facilities play an important role in monitoring the outflow temperature of hydropower projects. This study applies surrogate models based on theory-guided machine learning to predict the outflow temperature for the Jinping-I Hydropower Plant in China. The results show that the model can guide the operation of stratified intake facilities with high prediction accuracy and short prediction time.
JOURNAL OF HYDROLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Vesta Afzali Gorooh, Ata Akbari Asanjan, Phu Nguyen, Kuolin Hsu, Soroosh Sorooshian
Summary: This study develops a CNN algorithm called Deep-STEP, which uses satellite data and surface information to automatically extract geospatial features related to precipitation and achieve high spatiotemporal resolution estimation. The algorithm has the advantages of learning complex precipitation systems, automatic feature extraction, and fusion of different resolution data.
JOURNAL OF HYDROMETEOROLOGY
(2022)
Article
Environmental Sciences
Yuhang Zhang, Aizhong Ye, Phu Nguyen, Bita Analui, Soroosh Sorooshian, Kuolin Hsu
Summary: Accurate and reliable near-real-time satellite precipitation estimation is crucial for flood forecasting and drought monitoring. We propose a probabilistic post-processing method based on quantile modeling, which improves the overall quality of precipitation estimates and provides both deterministic and probabilistic predictions. The experiment demonstrates that our method outperforms other products in complex terrains and effectively improves the quality of precipitation estimates.
WATER RESOURCES RESEARCH
(2022)
Article
Multidisciplinary Sciences
Eric J. Shearer, Vesta Afzali Gorooh, Phu Nguyen, Kuo-Lin Hsu, Soroosh Sorooshian
Summary: Climate modeling studies predict that anthropogenic warming leads to increased precipitation rates and volumes from tropical cyclones (TCs). An experimental global high-resolution climate data record of precipitation, produced using infrared satellite imagery, shows a general increase in mean and extreme rainfall rates during the period of 1980-2019. All TC basins have experienced intensification in precipitation rates, with the highest increases observed in the North Atlantic, South Indian, and South Pacific basins. Increases in TC rainfall rates have also led to higher mean precipitation volumes globally, particularly from the strongest TCs.
SCIENTIFIC REPORTS
(2022)
Article
Public, Environmental & Occupational Health
John I. Githure, Delenasaw Yewhalaw, Harrysone Atieli, Elizabeth Hemming-Schroeder, Ming-Chieh Lee, Xiaoming Wang, Guofa Zhou, Daibin Zhong, Christopher L. King, Arlene Dent, Wolfgang Richard Mukabana, Teshome Degefa, Kuolin Hsu, Andrew K. Githeko, Gordon Okomo, Lilyana Dayo, Kora Tushune, Charles O. Omondi, Hiwot S. Taffese, James W. Kazura, Guiyun Yan
Summary: Malaria control programs in Africa face significant challenges including insecticide resistance, outdoor transmission, lack of surveillance tools, weak healthcare system, and environmental changes. The ICEMR collaborates with government ministries to align research efforts and advance knowledge in malaria epidemiology, transmission, and control. Research findings will inform health policy and strategic planning for sustainable malaria control and elimination.
AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE
(2022)
Article
Public, Environmental & Occupational Health
Guiyun Yan, Ming-Chieh Lee, Guofa Zhou, Ai -Ling Jiang, Teshome Degefa, Daibin Zhong, Xiaoming Wang, Elizabeth Hemming-Schroeder, Wolfgang R. Mukabana, Arlene E. Dent, Christopher L. King, Kuolin Hsu, James Beeson, John I. Githure, Harrysone Atieli, Andrew K. Githeko, Delenasaw Yewhalaw, James W. Kazura
Summary: Food insecurity, recurrent famine, and poverty threaten the health of millions in Africa. Constructing dams and rural irrigation schemes can address these issues. The International Center of Excellence for Malaria Research in sub-Saharan Africa focuses on the control and elimination of malaria in malaria-endemic areas of Kenya and Ethiopia where water resource development projects are taking place. The center's progress includes studying malaria vector ecology and behavior, epidemiology, and pathogenesis, and predicting the impact of water resource development on malaria risks.
AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE
(2022)
Article
Water Resources
Ai-Ling Jiang, Kuolin Hsu, Brett F. Sanders, Soroosh Sorooshian
Summary: Land surface depressions are important in the transformation of rainfall to ponding, infiltration, and runoff. However, existing digital elevation models (DEMs) used by hydrologic models rarely capture these depressions at relevant spatial scales. This study presents a new topographic conditioning workflow, called the Depression-Preserved DEM Processing (D2P) algorithm, which effectively preserves depressions for hydrologic modeling. The D2P algorithm successfully resolves 86% of ponds with minimal impact on topography, resulting in a more robust characterization of surface water dynamics and attenuated peak streamflow in hydrologic simulations.
ADVANCES IN WATER RESOURCES
(2023)
Article
Meteorology & Atmospheric Sciences
Jose Gomis-Cebolla, Viera Rattayova, Sergio Salazar-Galan, Felix Frances
Summary: This study evaluates the performance of the ERA5 and ERA5-Land reanalysis precipitation products from ECMWF at the country scale in Spain. A comprehensive assessment is conducted using various methods including continuous, categorical, probability distribution function, spatial pattern, and temporal trend analyses. The results show a good agreement between the observations and ERA5-Land/ERA5 estimates, with high correlation values, low root mean square error, and good efficiency. However, the performance varies depending on climatic region, precipitation intensity, and orography. The ERA5-Land/ERA5 tends to overestimate light and moderate precipitation but underestimate heavy and violent precipitation categories.
ATMOSPHERIC RESEARCH
(2023)
Article
Water Resources
Carles Beneyto, Jose Angel Aranda, Felix Frances
Summary: Stochastic weather generators are powerful tools that can extend precipitation records. However, they rely on available information, which is often scarce in arid and semi-arid regions. This study aims to investigate the uncertainty associated with the amount of information used in the weather generation calibration process. Monte Carlo simulation showed that incorporating a regional study of annual maximum daily precipitation reduced the uncertainty of all quantile estimates. It also highlighted the importance of integrating additional information in regions with extreme precipitation patterns.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Water Resources
Cyril Thebault, Charles Perrin, Vazken Andreassian, Guillaume Thirel, Sebastien Legrand, Olivier Delaigue
Summary: This study aimed to investigate the impact of inconsistencies in commonly available streamflow time series on the efficiency and parameter estimates of rainfall-runoff models. Data from 30 catchments in France from 1998 to 2018 were collected and used for hydrological modeling. The results suggest that common suspicious streamflow data have a limited impact on model efficiency and parameter estimates overall, but can lead to instability and lack of robustness in single catchment studies.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Water Resources
Jonathan Romero-Cuellar, Felix Frances
Summary: This study introduces a methodology to assess climate change impact models using uncertainty analysis of streamflow statistics. The results show that the ABC post-processor outperformed the ensemble method in all verification metrics.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Environmental Sciences
Carles Beneyto, Gloria Vignes, Jose Angel Aranda, Felix Frances
Summary: This paper assesses the uncertainty of daily flood quantile estimates obtained by synthetic continuous simulation (SCS) under different precipitation regimes, climate extremality, and basin hydrological characteristics. The findings show that integrating regional precipitation quantiles in the model calibration reduces uncertainty, while basin size, climate extremality, and hydrological characteristics have minimal impact on uncertainty.
Article
Geosciences, Multidisciplinary
Alban de Lavenne, Vazken Andreassian, Louise Crochemore, Goran Lindstrom, Berit Arheimer
Summary: This article presents a new approach to quantifying the multi-year hydrological memory of a catchment, using streamflow and climate data. The study finds a strong relationship between the humidity index and memory, with drier regions having longer memory. The work highlights the importance of accounting for catchment memory in elasticity analysis.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Antoine Pelletier, Vazken Andreassian
Summary: The study investigates whether using groundwater level data through a composite calibration framework can improve streamflow simulation performance. While the additional data may be unnecessary for streamflow simulation, they improve parameter stability and the model's ability to simulate groundwater levels in various hydrogeological and hydroclimatic contexts.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
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)