Article
Meteorology & Atmospheric Sciences
Danian Liu, Yeqiang Shu, Dongxiao Wang, Weiqiang Wang, Tingting Zu, Wei Zhou
Summary: This study investigates the forecast of a strong eddy shedding event from the Kuroshio Loop Current (LC) during the winter 2016-2017, and the results indicate that assimilation of satellite sea surface height anomaly data in the subtropical countercurrent (STCC) region improves the forecast performance and assimilation in the Northern Equatorial Current (NEC) region also contributes to the formation of a strong Kuroshio LC and the occurrence of eddy shedding.
Article
Environmental Sciences
Caleb G. Pan, Peter B. Kirchner, John S. Kimball, Jinyang Du, Michael A. Rawlins
Summary: The study developed a regional snow phenology record using satellite remote sensing, investigating the relationship between snowmelt, spring flood pulse, and river ice breakup in the Yukon River basin. Results showed the potential value of satellite-based snow metrics for regional monitoring and forecasting of the spring flood pulse and river ice breakup timing.
Article
Engineering, Civil
Chengxin Luo, Wei Ding, Chi Zhang, Xuan Yang
Summary: To effectively mitigate droughts, multiple hydrological forecasts are needed. This study proposes a novel Model Predictive Control (MPC) that integrates streamflow forecast, regime state forecast, and annual streamflow volume state forecast. By incorporating these forecasts, significant performance gains can be achieved in drought mitigation. However, forecast value is influenced by forecast uncertainty and other factors.
JOURNAL OF HYDROLOGY
(2023)
Article
Geosciences, Multidisciplinary
Keighobad Jafarzadegan, Peyman Abbaszadeh, Hamid Moradkhani
Summary: Real-time probabilistic flood inundation mapping is crucial for flood risk warning and decision-making, and traditional flood hazard maps cannot accurately represent the actual dynamics of flooding rivers. Introducing data assimilation techniques is an effective way to improve the accuracy and reliability of flood inundation mapping.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2021)
Article
Environmental Sciences
Tarkeshwar Singh, Francois Counillon, Jerry Tjiputra, Yiguo Wang, Mohamad El Gharamti
Summary: This study demonstrates the ability of ensemble data assimilation methods to provide improved estimates of biogeochemical (BGC) model parameters and shows how BGC observations can effectively constrain errors in ocean physics. The method quickly converges and significantly reduces parameter errors.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Environmental Sciences
Danielle Tijerina, Laura Condon, Katelyn FitzGerald, Aubrey Dugger, Mary Michael O'Neill, Kevin Sampson, David Gochis, Reed Maxwell
Summary: High-resolution, coupled, process-based hydrology models have been developed at continental scales for operational flood forecasting and hydrologic prediction. The Continental Hydrologic Intercomparison Project (CHIP) aims to compare these models to understand model bias and improve hydrology model configuration and process representation.
WATER RESOURCES RESEARCH
(2021)
Article
Energy & Fuels
Farhana Akter, Syed Imtiaz, Sohrab Zendehboudi, Kamal Hossain
Summary: Ensemble Kalman filter (EnKF) is widely used in reservoir modelling for history matching, but faces challenges when dealing with mismatch between the reservoir and the model. By introducing modifications and conducting sensitivity analysis, improvements in history matching efficiency are possible in cases of high model mismatch and measurement uncertainty.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
(2021)
Article
Water Resources
Andrew M. Badger, Nels Bjarke, Noah P. Molotch, Ben Livneh
Summary: The study shows that a more uniform spatial snowpack distribution leads to an average of 31 days earlier snowmelt and produces less total streamflow, with maximum decreases as large as 7.5%. Snowpack uniformity can reduce total streamflow by as much as 13.2%, primarily due to the impact of solar radiation, driving earlier snowmelt and changes in soil water storage.
HYDROLOGICAL PROCESSES
(2021)
Article
Engineering, Civil
Ming Li, David E. Robertson, Quan J. Wang, James C. Bennett, Jean-Michel Perraud
Summary: Ephemeral rivers present challenges for hydrological forecasters, but a staged error model designed for these rivers can provide effective solutions. The model involves innovative approaches in ensemble generation and parameter estimation, leading to skillful and reliable forecast performance even at extended lead times.
JOURNAL OF HYDROLOGY
(2021)
Article
Astronomy & Astrophysics
Jianhui He, Xinan Yue
Summary: Perturbing different model external forcing parameters can generate better ensemble members of ionosphere and thermosphere, leading to an improvement in forecast capability according to sensitivity tests and data assimilation experiments.
JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS
(2021)
Article
Chemistry, Analytical
Tipo Cui, Xiaohui Sun, Chenglin Wen
Summary: This paper proposes a new design method of sampling-driven Kalman filter to improve the performance of the filter for nonlinear systems. By integrating the advantages of UKF statistical sampling and EnKF random sampling, the shortcomings of both methods can be overcome. The new method obtains a large sample data ensemble through a new sampling mechanism, and optimizes the ensemble by selecting and assigning sample weights based on the centroid of the data ensemble, thus establishing a new Kalman filter.
Article
Meteorology & Atmospheric Sciences
Lili Lei, Yangjinxi Ge, Zhe-Min Tan, Yi Zhang, Kekuan Chu, Xin Qiu, Qifeng Qian
Summary: This study evaluates the ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) for western North Pacific typhoons in 2016. The results show that the WRF/EnKF system provides better ensemble forecasts and higher predictability for typhoon intensity compared to NCEP and ECMWF ensemble forecasts.
ADVANCES IN ATMOSPHERIC SCIENCES
(2022)
Article
Environmental Sciences
Alvaro Ossandon, Balaji Rajagopalan, Upmanu Lall, J. S. Nanditha, Vimal Mishra
Summary: The novel BHNM model leverages the spatial dependence induced by river network topology and hydrometeorological variables to improve ensemble forecasts of daily streamflow, demonstrating high skill in predicting monsoon period streamflow in Central India. Incorporating upstream flow information and precipitation as covariates allows for modeling spatial correlation of flows with parsimony. The validation results show that the BHNM model outperforms a null-model of generalized linear regression, highlighting its reliability and skillfulness in streamflow predictions.
WATER RESOURCES RESEARCH
(2021)
Article
Engineering, Civil
Behmard Sabzipour, Richard Arsenault, Magali Troin, Jean-Luc Martel
Summary: Data assimilation is an important step in improving hydrological model predictions. This study aims to identify optimal seasonal parameterizations to reduce uncertainty in initial conditions in a snow-dominated catchment in Canada. Sensitivity analysis shows that forecast performance is sensitive to individual hyperparameters and the choice of state variables.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Sisi Li, Mingliang Liu, Jennifer C. Adam, Huawei Pi, Fengge Su, Dongyue Li, Zhaofei Liu, Zhijun Yao
Summary: Snowmelt water plays a crucial role in the water resources management of the Three-River Headwater Region, with its contribution to total streamflow analyzed using a snowmelt tracking algorithm and VIC model. The study identified the ratio of snowfall to precipitation, variations in April 1 snow water equivalent, and the decreasing trend in f(Q,snow) from 1971 to 2007. The findings suggest a shrinking snow solid water resource and a weakening role of snow in the snow-hydrological regime in the TRHR, impacting water supplement and runoff regulation.
Article
Computer Science, Interdisciplinary Applications
Scott Haag, David Tarboton, Martyn Smith, Ali Shokoufandeh
COMPUTERS & GEOSCIENCES
(2020)
Article
Computer Science, Interdisciplinary Applications
Tian Gan, David G. Tarboton, Jeffery S. Horsburgh, Pabitra Dash, Ray Idaszak, Hong Yi
ENVIRONMENTAL MODELLING & SOFTWARE
(2020)
Article
Computer Science, Software Engineering
Prasad Calyam, Nancy Wilkins-Diehr, Mark Miller, Emre H. Brookes, Ritu Arora, Amit Chourasia, Douglas M. Jennewein, Viswanath Nandigam, M. Drew LaMar, Sean B. Cleveland, Greg Newman, Shaowen Wang, Ilya Zaslavsky, Michael A. Cianfrocco, Kevin Ellett, David Tarboton, Keith G. Jeffery, Zhiming Zhao, Juan Gonzalez-Aranda, Mark J. Perri, Greg Tucker, Leonardo Candela, Tamas Kiss, Sandra Gesing
Summary: Evaluation of the value of science gateways/VREs to the user community is crucial for obtaining resources and increasing adoption. This article features various exemplar science gateways/VREs and details how they define impact in terms of their purpose, operation principles, and user base size. The exemplars recognize the need for continuous evolution with technological advancements to enhance their operations for greater success.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Young-Don Choi, Jonathan L. Goodall, Jeffrey M. Sadler, Anthony M. Castronova, Andrew Bennett, Zhiyu Li, Bart Nijssen, Shaowen Wang, Martyn P. Clark, Daniel P. Ames, Jeffery S. Horsburgh, Hong Yi, Christina Bandaragoda, Martin Seul, Richard Hooper, David G. Tarboton
Summary: To enable reproducible environmental modeling research, advanced cyberinfrastructure is needed. Recent efforts have focused on advancing online repositories for data and model sharing, online computational environments, and model APIs. Integrating these efforts can advance reproducible environmental modeling.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Water Resources
Belize Lane, Irene Garousi-Nejad, Melissa A. Gallagher, David G. Tarboton, Emad Habib
Summary: The era of 'big data' in hydrology is leading to the development and adoption of open web-based platforms to harness datasets and data services. However, the potential of utilizing these platforms to enhance student learning remains largely untapped, despite advancements in hydrology education and web-based learning modules.
HYDROLOGICAL PROCESSES
(2021)
Article
Water Resources
Irene Garousi-Nejad, David G. G. Tarboton
Summary: This study compares the outputs of the US National Water Model (NWM) with observed data on snow water equivalent (SWE) and snow-covered area fraction (SCAF) in the Western United States. The NWM generally underestimates SWE and tends to melt snow early. There are also discrepancies between modelled and observed SCAF, attributed to model parameterization and observation limitations. The study identifies areas for improvement in the NWM's predictions related to snow.
HYDROLOGICAL PROCESSES
(2022)
Article
Environmental Sciences
Sara A. Goeking, David G. Tarboton
Summary: Forest cover and streamflow are generally expected to vary inversely, but recent studies have shown that forest disturbance due to drought and insect epidemics may not lead to changes or even decrease in streamflow. This study analyzed hydrologic, climatic, and forest data for 159 watersheds in the western U.S. and found that many watersheds experienced decreased streamflow despite the decrease in forest cover. The study also identified drivers other than disturbance, precipitation, and temperature that influence streamflow change, and found that the effect of tree mortality on streamflow depends on aridity.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Sara A. Goeking, David G. Tarboton
Summary: Forest change has a significant impact on hydrologic processes, and understanding the sensitivity of streamflow response to forest disturbance and recovery is important. This study developed stratum-specific leaf area index (LAI) datasets to improve the representation of vegetation in ecohydrologic modeling. By combining different estimation methods and machine learning algorithms, annual gridded LAI datasets were produced. The results showed that estimating both overstory and understory LAI was more accurate compared to estimating only overstory LAI. Distinguishing between overstory and understory LAI components can improve the simulation of how forest change affects hydrologic processes.
Article
Engineering, Environmental
Homa Salehabadi, David G. Tarboton, Bradley Udall, Kevin G. Wheeler, John C. Schmidt
Summary: Since 1995, much has been learned about Colorado River hydrology. By analyzing historical flows, tree-ring reconstructions, and climate change, researchers have gained a better understanding of future drought conditions. The study shows that even more severe droughts are possible, based on tree-ring reconstructed flows and future flows projected from climate models. This has significant implications for the management and operation of reservoirs in the Colorado River Basin.
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
(2022)
Article
Environmental Sciences
Tian Gan, David G. Tarboton, Tseganeh Z. Gichamo
Summary: This research compares the performance of the SNOW-17 model and the UEB model in predicting snowmelt. The results show that the UEB model is more suitable for simulating basin snowmelt and discharge under different climate and terrain conditions.
Article
Environmental Sciences
Madeline F. Merck, David G. Tarboton
Summary: The paper analyzes the long-term historical salinity and water surface elevation data record of the Great Salt Lake, aiming to better understand the movement of salt and changes to salinity in time and space, as well as the occurrence and extent of its deep brine layer. This work is important due to the lake's salinity-dependent ecosystem and industries, as well as the role played by the deep brine layer in the concentration of salt and contaminants.
Article
Geosciences, Multidisciplinary
Arefeh Safaei-Moghadam, David Tarboton, Barbara Minsker
Summary: Waze data can be used to predict pluvial flash flooding, especially those associated with surface depressions.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2023)
Article
Education & Educational Research
Melissa A. Gallagher, Emad H. Habib, Douglas Williams, Belize Lane, Jenny L. Byrd, David Tarboton
Summary: Creating high-quality curricular materials requires curriculum design knowledge and a significant time commitment; many instructors lack time and necessary skills; HydroLearn platform provides professional learning experiences for hydrology and water resources instructors to address these issues.
FRONTIERS IN EDUCATION
(2022)
Article
Education & Educational Research
Madeline F. Merck, Melissa A. Gallagher, Emad Habib, David Tarboton
Summary: It was found that engineering students were able to actively participate in the modeling process and enhance their skills using technology in an online mathematical modeling module. However, difficulties with technology or modeling decisions could hinder learning progress.
INTERNATIONAL JOURNAL OF RESEARCH IN UNDERGRADUATE MATHEMATICS EDUCATION
(2021)
Article
Water Resources
Irene Garousi-Nejad, David Tarboton
Summary: This study compared the US National Water Model (NWM) snow outputs to observed snow water equivalent (SWE) and snow-covered area fraction (SCAF) in the Western United States, finding that the model generally under-predicted SWE, with model input temperatures slightly cooler than observed and a tendency to melt snow early.
HYDROLOGICAL PROCESSES
(2022)