NH31D:
Remote Sensing: Monitoring, Prediction, and Hazard Mitigation of Hydroclimatic Extreme Events Posters
Submit an Abstract to this Session
Session ID#: 46663
Session Description:
Hydroclimatic extremes have significant socio-economic and ecological impacts. This session seeks studies of hydroclimatic extremes including:
(a) Prediction and monitoring of extreme events using satellite/radar-derived remote sensing data.
(b) Analysis and monitoring of infrastructure for risk mitigation, resilience, and reliability through the use of remotely sensed, field based, and in-situ observations.
(c) Analysis of hydroclimatic extremes and their precursors using in-situ and remotely sensed data as well as dynamic statistical, and learning-based models.
(d) Dynamics of hydroclimatic extremes;
1. Diagnosis, assessment and prediction of extremes and their severity, duration and spatiotemporal patterns;
2. Non-stationary analysis of extremes; and
3. Uncertainty analysis of data and models used for monitoring extreme events.
Case studies that focus on regional or continental aspects are encouraged.
Primary Convener: Ali Mehran, University of North Georgia, Oakwood, GA, United States
Conveners: Guy Schumann, Remote Sensing Solutions, Inc., Pasadena, United States, Phu Nguyen, University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States and Daniel B Wright, University of Wisconsin-Madison, Department of Civil and Environmental Engineering, Madison, United States
Primary Liaison: Daniel B Wright, University of Wisconsin-Madison, Department of Civil and Environmental Engineering, Madison, United States
Chairs: Phu Nguyen, University of California, Irvine, Department of Civil and Environmental Engineering, Irvine, United States and Daniel B Wright, University of Wisconsin-Madison, Department of Civil and Environmental Engineering, Madison, United States
OSPA Liaison: Guy Schumann, Remote Sensing Solutions, Inc., Pasadena, United States
Abstracts Submitted to this Session:
Hiroto Nagai1, Tomohiro Watanabe2, Takeo Tadono2 and Takeshi Motohka3, (1)Waseda University, Tokyo, Japan, (2)JAXA, Tsukuba, Japan, (3)JAXA, ALOS-4 Project, Tsukuba, Japan
Estifanos Lemma Goshu, Indian Institute of Technology Bombay, Mumbai, India; Debre Berhan University, Natural Resource Management, Debre Berhan, Ethiopia, Raaj Ramsankaran, Indian Institute of Technology Bombay, Civil Engineering, Mumbai, India; University of Nebraska, The Daugherty Water for Food Global Institute, Lincolon, NE, United States and Francisco Munoz-Arriola, Department of Biological Systems Engineering & School of Natural Resources, University of Nebraska-Lincoln, Lincoln, United States
YI LIU, Huazhong University of Science and Technology, School of Hydropower and Information Engineering,, Wuhan, China; Georgia Institute of Technology Main Campus, Atlanta, GA, United States
Bar Avni Naor1, Francesco Marra2, Alon Ronen1, James A Smith3 and Efrat Morin4, (1)Hebrew University of Jerusalem, Institute of Earth Sciences, Jerusalem, Israel, (2)Institute of Atmospheric Sciences and Climate, National Research Council of Italy, Bologna, Italy, (3)Princeton Univ, Civil and Environmental Engineering, Princeton, NJ, United States, (4)The Hebrew University of Jerusalem, The Fredy and Nadine Herrmann Institute of Earth Sciences, Jerusalem, Israel
Bala Narapusetty, Climate Prediction Center College Park, College Park, MD, United States, Dan C Collins, Climate Prediction Center College Park, College Park, United States, Raghuram G Murtugudde, Univ of MD--ESSIC, College Park, United States, Christa D Peters-Lidard, NASA GSFC, Greenbelt, United States and Jon Gottschalck, NOAA, Climate Prediction Center, Washington, DC, United States
