Estimate of flood inundation and retention on wetlands using remote sensing and GIS

Chen, Yongqin David; Wang, Bing; Pollino, Carmel; Cuddy, Susan M.; Merrin, Linda; Huang, Chang

doi:10.1002/eco.1467

Cited by 52 publications

(33 citation statements)

References 30 publications

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“…Moderate resolution imagery, such as MODIS (Moderate Resolution Imaging Spectroradiometer) data, is a suitable tool for floodplain monitoring and modeling [17][18][19][20]. The advantages of using MODIS for hydrological research are low cost, open access as well as diverse spatial and temporal resolution [11,17,[21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Coupled Ground- and Space-Based Assessment of Regional Inundation Dynamics to Assess Impact of Local and Upstream Changes on Evaporation in Tropical Wetlands

et al. 2015

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Abstract:Modifications of human land use and climate change are known to be a threat for the health and proper functioning of tropical wetlands. They interfere with the seasonal flood pulse, which is seen as the most important driver for biodiversity and directly controls evaporation. In order to investigate the impact of local and upstream changes on wetlands, a regional assessment of evaporation is crucial but challenging in such often remote and poorly gauged ecosystems. Evaporation is the major water balance component of these wetlands and links the flood pulse with the ecosystem. It can therefore be seen as a proxy for their functioning. In the last decades, information from space became an important data source to assess remote wetland areas. Here, we developed a new approach to quantify regional evaporation driven by inundation dynamics as its dominant control. We used three water and vegetation indices (mNDWI (modified Normalized Difference Water Index), NDVI (Normalized Difference Vegetation Index), and EVI (Enhanced Vegetation Index)) from MODIS (Moderate Resolution Imaging Spectroradiometer) surface reflectance products to assess regional inundation dynamics between the dry and wet seasons. Two years of continual in situ water level measurements at different locations in our study area, the OPEN ACCESS Remote Sens. 2015, 7 9770Pantanal wetland of South America, provided the reference to evaluate our method. With process-based modeling that used the inundation dynamics to determine the water available for evaporation, we were able to estimate actual evaporation (AET) on a regional scale. Relating AET to changes in discharge due to upstream flow modifications and on local precipitation over the last 13 years, we found that the Pantanal is more vulnerable to alternated inundation dynamics than to changes in local precipitation. We concluded that coupling ground-and space-based information in this remote wetland area is a valuable first step to investigate the status of the Pantanal ecosystem.

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Section: Introductionmentioning

confidence: 99%

Coupled Ground- and Space-Based Assessment of Regional Inundation Dynamics to Assess Impact of Local and Upstream Changes on Evaporation in Tropical Wetlands

et al. 2015

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“…The usefulness of the MODIS OWL algorithm has already been seen in a number of applications within Australia (e.g., [20,21,32]). However to make it more robust, it is desirable to apply a simple set of rules so that the MODIS OWL algorithm is a more operational and automated procedure for mapping flood events.…”

Section: Discussionmentioning

confidence: 99%

The Strengths and Limitations in Using the Daily MODIS Open Water Likelihood Algorithm for Identifying Flood Events

2014

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Abstract:Daily, or more frequent, maps of surface water have important applications in environmental and water resource management. In particular, surface water maps derived from remote sensing imagery play a useful role in the derivation of spatial inundation patterns over time. MODIS data provide the most realistic means to achieve this since they are daily, although they are often limited by cloud cover during flooding events, and their spatial resolutions (250-1000 m pixel) are not always suited to small river catchments. This paper tests the suitability of the MODIS sensor for identifying flood events through comparison with streamflow and rainfall measurements at a number of sites during the wet season in Northern Australia. This is done using the MODIS Open Water Likelihood (OWL) algorithm which estimates the water fraction within a pixel. On a temporal scale, cloud cover often inhibits the use of MODIS imagery at the start and lead-up to the peak of a flood event, but there are usually more cloud-free data to monitor the flood's recession. Particularly for smaller flood events, the MODIS view angle, especially when the view angle is towards the sun, has a strong influence on total estimated flood extent. Our results showed that removing pixels containing less than 6% water can eliminate most commission errors when mapping surface water. The exception to this rule was for some spectrally dark pixels occurring along the edge of the MODIS swath where the relative azimuth angle (i.e., angle between the MODIS' and sun's azimuth angle) was low. Using only MODIS OWL pixels with a low view angle, or a range distance of less than 1000 km, also improves the results and minimizes multi-temporal errors in flood identification and extent. Given these limitations, MODIS OPEN ACCESSRemote Sens. 2014, 6 11792 OWL surface water maps are sensitive to the dynamics of water movement when compared to streamflow data and does appear to be a suitable product for the identification and mapping of inundation extent at large regional/basin scales.

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“…During the wet season from April to September, the floodplains are inundated and thus form a big lake with a water area bigger than 3000 km 2 [37]. During the dry season from October to March, the water area can shrink to less than 1000 km 2 , forming a narrow meandering channel. Levees have been built around the lake to control flood and facilitate management [38], which lead to numerous small lakes and tributaries, especially during the dry season when the lake is divided into many connected and disconnected segments.…”

Section: Study Areamentioning

confidence: 99%

Surface Water Mapping from Suomi NPP-VIIRS Imagery at 30 m Resolution via Blending with Landsat Data

et al. 2016

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Abstract:Monitoring the dynamics of surface water using remotely sensed data generally requires both high spatial and high temporal resolutions. One effective and popular approach for achieving this is image fusion. This study adopts a widely accepted fusion model, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), for blending the newly available coarse-resolution Suomi NPP-VIIRS data with Landsat data in order to derive water maps at 30 m resolution. The Pan-sharpening technique was applied to preprocessing NPP-VIIRS data to achieve a higher-resolution before blending. The modified Normalized Difference Water Index (mNDWI) was employed for mapping surface water area. Two fusion alternatives, blend-then-index (BI) or index-then-blend (IB), were comparatively analyzed against a Landsat derived water map. A case study of mapping Poyang Lake in China, where water distribution pattern is complex and the water body changes frequently and drastically, was conducted. It has been revealed that the IB method derives more accurate results with less computation time than the BI method. The BI method generally underestimates water distribution, especially when the water area expands radically. The study has demonstrated the feasibility of blending NPP-VIIRS with Landsat for achieving surface water mapping at both high spatial and high temporal resolutions. It suggests that IB is superior to BI for water mapping in terms of efficiency and accuracy. The finding of this study also has important reference values for other blending works, such as image blending for vegetation cover monitoring.

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Estimate of flood inundation and retention on wetlands using remote sensing and GIS

Cited by 52 publications

References 30 publications

Coupled Ground- and Space-Based Assessment of Regional Inundation Dynamics to Assess Impact of Local and Upstream Changes on Evaporation in Tropical Wetlands

Coupled Ground- and Space-Based Assessment of Regional Inundation Dynamics to Assess Impact of Local and Upstream Changes on Evaporation in Tropical Wetlands

The Strengths and Limitations in Using the Daily MODIS Open Water Likelihood Algorithm for Identifying Flood Events

Surface Water Mapping from Suomi NPP-VIIRS Imagery at 30 m Resolution via Blending with Landsat Data

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