Detecting floodplain inundation frequency using MODIS time-series imagery

Floodplains play an important role in riverine hydrological and ecological environments. Accurate estimate of the spatial and temporal inundation frequency patterns is an critical step to understand how the inundation conditions affect local hydrology and floodplain ecosystems. This study presents a methodology to detect spatial-temporal changes in inundation extent associated with flood inundation frequency based on MODIS 8-day composite time-series imagery (MOD09A1) from 2000 to 2010. It takes Chowilla floodplain located in the northwestern Murray-Darling Basin of Australia as a study area. The GIS-based framework includes extraction of flow peaks from time-series of observed flow data, inundation detection from MODIS using the Open Water Likelihood index, inundation validation using modified Normalized Difference Water Index on Landsat TM image, and flood extent and frequency mapping. The study shows that the maximum inundated areas that have been inundated at least once are 12.5% of the total study area. The areas with different inundated frequencies were calculated and linked with ecological significant flood return periods. The areas that were inundated twice in the 11 years, which is equivalent to a 1-in-5 Average Recurrence Interval, occupies 27.8% of total inundated area. The results of this study provide an important indicator for the health condition and spatial distribution of some dominant species in the floodplain, such as river red gum. This, in turn, improves knowledge of eco-hydrology characteristics of floodplain ecosystem.

[1]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[2]  S. K. McFeeters.  The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features , 1996 .

[3]  P. Frazier,et al.  Water body detection and delineation with Landsat TM data. , 2000 .

[4]  Richard T. Kingsford,et al.  Ecological impacts of dams, water diversions and river management on floodplain wetlands in Australia , 2000 .

[5]  Robin Pfister,et al.  Earth Observing System Data Gateway , 2001 .

[6]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[7]  J. Gallant,et al.  A multiresolution index of valley bottom flatness for mapping depositional areas , 2003 .

[8]  I. Overton,et al.  Modelling floodplain inundation on a regulated river: integrating GIS, remote sensing and hydrological models , 2005 .

[9]  Hanqiu Xu.  Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[10]  T. Sakamoto,et al.  Detecting temporal changes in the extent of annual flooding within the cambodia and the vietnamese mekong delta from MODIS time-series imagery , 2007 .

[11]  M. Friedl,et al.  Using MODIS data to characterize seasonal inundation patterns in the Florida Everglades , 2008 .

[12]  Mainuddin,et al.  River water balance accounts across the Murray-Darling Basin, 1990-2006 , 2008 .

[13]  G. Gísladóttir,et al.  Inundation extent as a key parameter for assessing the magnitude and return period of flooding events in southern Iceland , 2010 .

[14]  Guy Byrne,et al.  MODIS-based standing water detection for flood and large reservoir mapping: Algorithm development and applications for the Australian continent , 2011 .