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A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa
Authors:Marouane Temimi  Teodosio Lacava  Tarendra Lakhankar  Valerio Tramutoli  Hosni Ghedira  Riadh Ata  Reza Khanbilvardi
Institution:1. NOAA‐CREST, City University of New York, 160 Convent Avenue, New York, NY, 10031, USA;2. Institute of Methodologies for Environmental Analysis (IMAA) –National Research Council (CNR), C.da Santa Loja, 85050, Tito Scalo (PZ), Italy;3. Department of Engineering and Physics of Environment (DIFA) –University of Basilicata –via dell'Ateneo Lucano, 10, 85100 Potenza, Italy;4. Water and Environmental Engineering Program, Masdar Institute, Abu Dhabi, United Arab Emirates;5. Electricité de France EDF LNHE/ National Hydraulics and Environment Lab., Chatou, France
Abstract:The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi‐temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR‐E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time‐lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21‐day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters. Copyright © 2011 John Wiley & Sons, Ltd.
Keywords:flood  river discharge  soil moisture  passive microwave  Kalman filter
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