Search

Your search keyword '"Krajewski, Witold F."' showing total 749 results
Start Over Author "Krajewski, Witold F."
749 results on '"Krajewski, Witold F."'

7. Insights On Streamflow Predictability Across Scales Using Horizontal Visibility Graph Based Networks

Author

Ghimire, Ganesh R., Jadidoleslam, Navid, Krajewski, Witold F., and Tsonis, Anastasios A.

Subjects
Physics - Physics and Society, Statistics - Applications, physics.data-an
Abstract

Streamflow is a dynamical process that integrates water movement in space and time within basin boundaries. The authors characterize the dynamics associated with streamflow time series data from about seventy-one U.S. Geological Survey (USGS) stream-gauge stations in the state of Iowa. They employ a novel approach called visibility graph (VG). It uses the concept of mapping time series into complex networks to investigate the time evolutionary behavior of dynamical system. The authors focus on a simple variant of VG algorithm called horizontal visibility graph (HVG). The tracking of dynamics and hence, the predictability of streamflow processes, are carried out by extracting two key pieces of information called characteristic exponent, {\lambda} of degree distribution and global clustering coefficient, GC pertaining to HVG derived network. The authors use these two measures to identify whether streamflow process has its origin in random or chaotic processes. They show that the characterization of streamflow dynamics is sensitive to data attributes. Through a systematic and comprehensive analysis, the authors illustrate that streamflow dynamics characterization is sensitive to the normalization, and the time-scale of streamflow time-series. At daily scale, streamflow at all stations used in the analysis, reveals randomness with strong spatial scale (basin size) dependence. This has implications for predictability of streamflow and floods. The authors demonstrate that dynamics transition through potentially chaotic to randomly correlated process as the averaging time-scale increases. Finally, the temporal trends of {\lambda} and GC are statistically significant at about 40% of the total number of stations analyzed. Attributing this trend to factors such as changing climate or land use requires further research., Comment: 34 pages and 12 figures

Published
2019
Full Text
View/download PDF

10. List of contributors

Author

Anagnostou, Emmanouil, primary, Anquetin, Sandrine, additional, Astitha, Marina, additional, Ayalew, Tibebu, additional, Calovi, Martina, additional, Cannon, Forest, additional, DeCastro, Amy, additional, Cerrai, Diego, additional, Cervone, Guido, additional, Chen, Dan, additional, Doan, Quang-Van, additional, Clemente, Laura, additional, Eghdami, Masih, additional, Di Giuseppe, F., additional, Juliano, Timothy W., additional, Muñoz-Esparza, Domingo, additional, Di Napoli, C., additional, Fonley, Morgan, additional, Frediani, Maria, additional, Hu, Weiming, additional, Jadidoleslam, Navid, additional, Jimenez, Pedro, additional, Knievel, Jason C., additional, Khan, Sana, additional, Kirschbaum, Dalia B., additional, Kosovi, Branko, additional, Krajewski, Witold F., additional, Kusaka, Hiroyuki, additional, Magnusson, Linus, additional, Mantilla, Ricardo, additional, Monache, Luca Delle, additional, Nikolopoulos, Efthymios, additional, Pappenberger, F., additional, Prudhomme, C., additional, Quintero, Felipe, additional, Ramamurthy, Prathap, additional, Ray, Pallav, additional, Ruin, Isabelle, additional, Small, Scott, additional, Siems-Anderson, Amanda, additional, Terti, Galateia, additional, Tewari, Mukul, additional, Velasquez, Nicolas, additional, and Wang, Zhihua, additional

Published
2023
Full Text
View/download PDF

14. Forecast-Informed Reservoir Operation within an Actively Managed Distributed Storage Network Using the High-Resolution Rapid Refresh Product.

Author

Post, Riley, Quintero, Felipe, and Krajewski, Witold F.

Subjects
RAINFALL frequencies, FLOOD damage, HYDROLOGIC models, DECISION making, FLOODS
Abstract

An increase in extreme rainfall frequency across the midwestern United States has been accompanied by an increase in damaging floods. The US has over 90,000 dams, more than 75% of which are small and rarely used for flood mitigation. Recent research focused on operating these ponds for flood reduction using gated outlets, a technique known as activated distributed storage, has confirmed its potential for reducing flood impacts. Here, the authors build upon this work by developing a hydrologic model to simulate the active management of a distributed network of 130 ponds that employs up to 18 h of forecasted rainfall for operational decision making, a process known as forecast-informed reservoir operation (FIRO). Using five observed rainfall events and a single dam operations scheme, the effects of using FIRO for real-time gate operations on both downstream peak flows and basin wide storage utilization are evaluated. Simulation results that use the high-resolution rapid refresh (HRRR) product, were compared to those that (1) use no rainfall forecasts for decision making; and (2) use 18 h of observed rainfall mimicking an ideal forecast. Regardless of forecast accuracy or rainfall accumulation, shorter forecast lead times result in operational decisions that release water early in an event, vacating storage, while longer lead times result in increased storage throughout an event, thus reducing downstream flows. These results indicate that rainfall forecasts may not be solely capable of addressing the complexities governing a distributed storage network's ability to release water. This suggests that a more nuanced approach, utilizing optimal control of the storage network is required to unlock the technique's full potential. [ABSTRACT FROM AUTHOR]

Published
2025
Full Text
View/download PDF

22. Hydrologic Validation and Flood Analysis

Author

Krajewski, Witold F., Quintero, Felipe, El Saadani, Mohamed, Goska, Radoslaw, Stoffel, Markus, Series Editor, Cramer, Wolfgang, Advisory Editor, Luterbacher, Urs, Advisory Editor, Toth, F., Advisory Editor, Levizzani, Vincenzo, editor, Kidd, Christopher, editor, Kirschbaum, Dalia B., editor, Kummerow, Christian D., editor, Nakamura, Kenji, editor, and Turk, F. Joseph, editor

Published
2020
Full Text
View/download PDF

28. Compressed Sensing Applied to Weather Radar

Author

Mishra, Kumar Vijay, Kruger, Anton, and Krajewski, Witold F.

Subjects
Computer Science - Information Theory
Abstract

We propose an innovative meteorological radar, which uses reduced number of spatiotemporal samples without compromising the accuracy of target information. Our approach extends recent research on compressed sensing (CS) for radar remote sensing of hard point scatterers to volumetric targets. The previously published CS-based radar techniques are not applicable for sampling weather since the precipitation echoes lack sparsity in both range-time and Doppler domains. We propose an alternative approach by adopting the latest advances in matrix completion algorithms to demonstrate the sparse sensing of weather echoes. We use Iowa X-band Polarimetric (XPOL) radar data to test and illustrate our algorithms., Comment: 4 pages, 5 figrues

Published
2014

Catalog

Books, media, physical & digital resources
See catalog results