Article
Environmental Sciences
Qingyun Yan, Ting Hu, Shuanggen Jin, Weimin Huang, Yan Jia, Tiexi Chen, Jian Wang
Summary: This paper proposes an effective method for calibrating the CyGNSS G product, by considering different criteria and target data, implementing six calibration schemes, and evaluating the resulting products through visual inspection and soil moisture retrieval results. The effectiveness and robustness of the schemes are demonstrated, providing an efficient way to improve relevant remote sensing applications in the future.
Article
Engineering, Civil
Elhadi Mohsen Hassan Abdalla, Knut Alfredsen, Tone Merete Muthanna
Summary: Conceptual rainfall-runoff models (CRRMs) can be used as a design tool for green roofs. This study showed how changing the calibration practice can reduce the uncertainty of CRRM parameters and enhance their interpretation. The study also demonstrated the ability of the CRRM to simulate runoff from green roofs across different climatic conditions and roof configurations.
JOURNAL OF HYDROLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Jinfeng Ma, Jing Zhang, Ruonan Li, Hua Zheng, Weifeng Li
Summary: The study developed a framework integrating BO and high-performance computing, with model evaluations on a Hadoop cluster to automate model calibration. The case study showed that the framework can reduce execution times effectively while maintaining accuracy, and provides evaluation of different surrogate models and acquisition functions with real-time visualization.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Civil
Roozbeh Moazenzadeh, Azizallah Izady
Summary: This study aims to improve the hydrological response of the Neishaboor watershed in Iran using the Soil Water Assessment Tool (SWAT). Monthly streamflow data and AET values were used for SWAT calibration and validation. The results showed that several parameters of the SWAT model were sensitive to AET estimation. The proposed hybrid calibration method had reasonable performance in AET estimation, although there was a tendency for the SWAT-based AET to under-predict compared to SEBAL-based AET.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Yiwen Mei, Juliane Mai, Hong Xuan Do, Andrew Gronewold, Howard Reeves, Sandra Eberts, Richard Niswonger, R. Steven Regan, Randall J. Hunt
Summary: This study uses six different single- and multi-objective model calibration schemes based on different combinations of observed data, such as gaged streamflow, global-scale gridded soil moisture, actual evapotranspiration (ET), and runoff products for the calibration of a process-based hydrological model for 20 catchments in the Lake Michigan watershed. The results show that including gridded soil moisture in the model calibration improves the performance of ET simulation for most catchments, leading to the overall best-performing models. The monthly streamflow simulation performance using gridded runoff products is outperformed by gaged streamflow, but the discrepancy is reduced with increasing catchment scale. A new visualization method synthesizing model performance for streamflow, soil moisture, and ET simulations is proposed.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
J. M. Thornton, R. Therrien, G. Mariethoz, N. Linde, P. Brunner
Summary: This study investigates the application of integrated models in mountain regions, where the model considers surface flow, groundwater flow, and evapotranspiration to represent the hydrological regime of the catchment. By calibrating the model, certain features of the hydrological regime are successfully reproduced. However, the model's performance is affected by simplifications and assumptions commonly used in physically-based modeling. This research demonstrates the feasibility and benefits of integrated models in complex mountain systems.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Ayan Santos Fleischmann, Ahmad Al Bitar, Aline Meyer Oliveira, Vinicius Alencar Siqueira, Bibiana Rodrigues Colossi, Rodrigo Cauduro Dias de Paiva, Yann Kerr, Anderson Ruhoff, Fernando Mainardi Fan, Paulo Rogenes Monteiro Pontes, Walter Collischonn
Summary: Hydrological models can be calibrated effectively by using multiple variables, such as in situ discharge and remote sensing soil moisture data, to improve accuracy and precision. In tropical humid areas, a synergistic calibration approach combining field observations and remote sensing data is preferable for providing reasonable estimates of discharge and soil moisture basin-wide.
Article
Environmental Sciences
Klin Li, Yutong Lu
Summary: This paper proposes a hydrological parameter calibration training framework consisting of a transformer-based parameter learning model (ParaFormer) and a surrogate model based on LSTM. ParaFormer uses self-attention mechanisms to learn a global mapping from observed data to the parameters to be calibrated, capturing spatial correlations. The surrogate model takes the calibrated parameters as inputs and simulates the observable variables, overcoming the challenges of combining complex hydrological models with a deep learning platform.
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
Environmental Sciences
Venkatesh Budamala, Amit Baburao Mahindrakar
Summary: Complex hydrological models require significant computational cost, while pseudo-models offer a cheaper and effective alternative. In this study, Gaussian Process regression was found to be the best pseudo-model for optimizing the SWAT hydrological model using the PMO method, resulting in accurate streamflow predictions during calibration and validation.
GEOCARTO INTERNATIONAL
(2021)
Article
Environmental Sciences
Rashid Mahmood, Shaofeng Jia
Summary: The objective of this study was to address the unsatisfactory simulations of important hydrological components by the Hydrological Modeling System (HEC-HMS). The auto-calibration method of HEC-HMS was found to generate irrational parameters, especially with the inclusion of advanced and complex loss methods. To overcome these issues, a comprehensive approach was designed to estimate initial parameters and manually calibrate the model, resulting in satisfactory simulations of all important hydrological components.
Article
Geosciences, Multidisciplinary
E. Andres Quichimbo, Michael Bliss Singer, Katerina Michaelides, Daniel E. J. Hobley, Rafael Rosolem, Mark O. Cuthbert
Summary: Dryland regions face challenges under climate change due to water scarcity, and predicting water partitioning is crucial. The DRYP model, tested in the Walnut Gulch Experimental Watershed, effectively quantifies key components of the dryland water balance.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2021)
Article
Geosciences, Multidisciplinary
Marco Dal Molin, Dmitri Kavetski, Fabrizio Fenicia
Summary: Catchment-scale hydrological models are widely used to represent hydrological processes and support water resource management. SuperflexPy is an open-source Python framework that allows for building conceptual hydrological models with a high degree of control over model specifications.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2021)
Article
Environmental Sciences
Suli Pan, Yue-Ping Xu, Haiting Gu, Bai Yu, Weidong Xuan
Summary: The study compared the effectiveness of different calibration schemes on hydrological model parameters and found that multi-variable calibration (including runoff and remote sensing-based evapotranspiration) can improve the performance of the model in runoff and evapotranspiration simulation, especially in extreme flow simulations.
Article
Chemistry, Multidisciplinary
Anna N. Popova, Vladimir S. Sukhomlinov, Aleksandr S. Mustafaev
Summary: The article presents a nonlinear theory on how third elements affect the analysis of elemental composition using atomic emission spectroscopy, showing significant decrease in deviations of impurity concentrations. This theory allows for reducing the number of analytical procedures for materials with different compositions but the same matrix element, making it possible to determine the composition of iron-based alloys using one calibration curve.
APPLIED SCIENCES-BASEL
(2021)
Editorial Material
Computer Science, Interdisciplinary Applications
Soroosh Sorooshian
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2021)
Article
Meteorology & Atmospheric Sciences
Mohammed Ombadi, Phu Nguyen, Soroosh Sorooshian, Kuo-lin Hsu
Summary: The study highlights significant biases in simulating annual precipitation by GCMs in the Nile River basin and underestimation of interannual variability. The BMA model projections reveal high uncertainty in the region, with considerable variations in the magnitude and direction of change in the Blue Nile and Upper White Nile basins.
JOURNAL OF HYDROMETEOROLOGY
(2021)
Article
Engineering, Civil
Mojtaba Sadeghi, Eric J. Shearer, Hamidreza Mosaffa, Vesta Afzali Gorooh, Matin Rahnamay Naeini, Negin Hayatbini, Pari-Sima Katiraie-Boroujerdy, Bita Analui, Phu Nguyen, Soroosh Sorooshian
Summary: The study suggests that the increase in flood numbers in Iran during early spring is related to the increase in intensity and volume of heavy precipitation events. Atmospheric river conditions affect heavy precipitation events in Iran, with most of the atmospheric river pathways involving Africa and the Red Sea.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
Mohammed Ombadi, Phu Nguyen, Soroosh Sorooshian, Kuo-lin Hsu
Summary: This study examines the dynamic complexity of hydrologic basins using phase space reconstruction techniques, finding that most basins exhibit low dimensionality and moderate nonlinearity. Dynamics dimensionality is primarily related to basin size, while strength of nonlinearity is linked to vegetation cover extent. The results have implications for catchment similarity, classification frameworks, model selection, and parameter extrapolation to ungauged basins.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Yuhang Zhang, Aizhong Ye, Phu Nguyen, Bita Analui, Soroosh Sorooshian, Kuolin Hsu
Summary: This study evaluated the simulated discharge from eight quasi-global SPEs at different spatial scales and found a scale effect in their application in discharge simulation. When the catchment area is larger than 20,000 km(2), the overall performance of discharge simulation improves, while below 20,000 km(2), the discharge simulation capability is more randomized and relies heavily on local precipitation accuracy. The study highlights the need for more advanced retrieval algorithms, data sources, and bias correction methods to improve the overall quality of SPEs for hydrological simulations.
Article
Multidisciplinary Sciences
Mojtaba Sadeghi, Phu Nguyen, Matin Rahnamay Naeini, Kuolin Hsu, Dan Braithwaite, Soroosh Sorooshian
Summary: Accurate long-term global precipitation estimates, especially for heavy precipitation rates, are essential for climatological studies. The PERSIANN-CCS-CDR dataset provides reliable precipitation estimates with high spatiotemporal resolution and a longer period of record, particularly for extreme events.
Article
Environmental Sciences
Pengcheng Qin, Hongmei Xu, Min Liu, Luliu Liu, Chan Xiao, Iman Mallakpour, Matin Rahnamay Naeini, Kuolin Hsu, Soroosh Sorooshian
Summary: This study assesses the impacts of climate change on major dams in the Upper Yangtze River Basin. The findings reveal that dam inflow will increase, hydropower generation will increase with greater interannual variability, and flood events will become more frequent and severe in the future. Additionally, the regulation function of dams will strengthen in the flood season and weaken in the dry season.
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
Meteorology & Atmospheric Sciences
Iman Mallakpour, Mojtaba Sadeghi, Hamidreza Mosaffa, Ata Akbari Asanjan, Mojtaba Sadegh, Phu Nguyen, Soroosh Sorooshian, Amir AghaKouchak
Summary: Variability and spatiotemporal changes in precipitation characteristics can have profound impacts. A study using multiple precipitation datasets showed substantial discrepancies in the changes in extreme and non-extreme precipitation events. While there is relative agreement among datasets on changes in total annual precipitation, there are widespread discrepancies in other percentiles of the precipitation distribution.
WEATHER AND CLIMATE EXTREMES
(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
Environmental Sciences
Hossein Salehi, Mojtaba Sadeghi, Saeed Golian, Phu Nguyen, Conor Murphy, Soroosh Sorooshian
Summary: This study evaluates the application of PERSIANN datasets for precipitation estimation and hydrological modeling in the Russian River catchment. The results show that CCS-CDR is the most accurate dataset among all PERSIANN family datasets. PDIR performs significantly better than CCS in near-real-time precipitation estimation, and it also shows improved accuracy in hydrological simulations.
Review
Multidisciplinary Sciences
A. AghaKouchak, B. Pan, O. Mazdiyasni, M. Sadegh, S. Jiwa, W. Zhang, C. A. Love, S. Madadgar, S. M. Papalexiou, S. J. Davis, K. Hsu, S. Sorooshian
Summary: Despite improvements in weather and climate modelling, drought prediction remains a challenge. Developing bottom-up models and focusing on stability rather than event-based verification is crucial. Opportunities lie in artificial intelligence and machine learning.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2022)
Correction
Multidisciplinary Sciences
Eric J. Shearer, Vesta Afzali Gorooh, Phu Nguyen, Kuo-Lin Hsu, Soroosh Sorooshian
SCIENTIFIC REPORTS
(2022)