A multi-sensor monitoring system of surface water level changes in wetlands

Author(s):  
Shimon Wdowinski ◽  
Heming Liao ◽  
Boya (Paul) Zhang

<p>Wetlands store roughly 10% of global surface water in the terrestrial portion of the water cycle, cover roughly 9% of the Earth’s surface, and provide critical habitat for a wide variety of plant and animal species. Over the past century, many wetland areas have been lost, degraded, or stressed mainly due to anthropogenic activities, as water diversion, agricultural development, and urbanization, but also in response to natural processes, as sea level rise and climate change. Global and regional monitoring of wetland health and response to their natural and anthropogenic stressors are important and are best conducted using space-based remote sensing techniques, due to wetlands’ vast extent and often inaccessibility.</p><p>Several space-based remote sensing technologies provide high spatial resolution observations of wetland water level and its changes over time. These techniques include Synthetic Aperture Radar (SAR), optical imagery, radar and laser altimetry, and Surface Water Ocean Topography (SWOT). SAR observations include two independent observables, amplitude and phase; each observable is sensitive to different hydrological parameters. Radar and laser altimetry missions provide cm-level accuracy water level measurements along the satellite track. The SWOT mission, which is scheduled for a February 2022 launch, will use radar interferometer for repeated measurements of cm-level water level measurements over a 50-100 km wide swaths. As part of a NASA supported project, we develop a space-based multi-sensor monitoring system of surface water level changes in wetlands. The multi-sensor system will generate detailed multi-temporal maps of wetland inundation extent, water levels, and water level changes. The development of the multi-sensor monitoring system will be conducted over the south Florida Everglades, which can be considered as a natural laboratory due to its variable land cover and the availability of ground-based hydrological observations. Preliminary results based on Interferometric Synthetic Aperture Radar (InSAR) observations yielded detailed maps of water level changes of the entire Everglades wetlands with 100 m spatial resolution and 3-4 cm accuracy level. After development, the system will be tested in two other wetland areas located in Louisiana, and Peace–Athabasca Delta (Alberta, Canada).</p>

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Diego Arosio ◽  
Stefano Munda ◽  
Greta Tresoldi ◽  
Monica Papini ◽  
Laura Longoni ◽  
...  

AbstractThis work is based on the assumption that a resistivity meter can effectively monitor water saturation in earth levees and can be used as a warning system when saturation exceeds the expected seasonal maxima. We performed time-lapse ERT measurements to assess the capability of this method to detect areas where seepage is critical. These measurements were also very useful to design a prototype monitoring system with remarkable savings by customizing the specifications according to field observations. The prototype consists of a remotely controlled low-power resistivity meter with a spread of 48 stainless steel 20 × 20 cm plate electrodes buried at half-meter depth. We deployed the newly-designed permanent monitoring system on a critical levee segment. A weather station and an ultrasonic water level sensor were also installed in order to analyse the correlation of resistivity with temperature, rainfalls and water level seasonal variations.The preliminary analysis of the monitoring data shows that the resistivity maps follow a very reasonable trend related with the saturation/drying cycle of the levee caused by the seasonal variations of the water level in the irrigation channel. Sharp water level changes cause delayed and smooth resistivity variations. Rainfalls and, to a lesser extent, temperature seem to have an influence on the collected data but effects are apparently negligible beyond 1 m depth. The system is currently operating and results are continuously monitored.


2008 ◽  
Vol 22 (22) ◽  
pp. 4448-4454 ◽  
Author(s):  
Selcuk Reis ◽  
Haci Murat Yilmaz

2008 ◽  
Vol 112 (3) ◽  
pp. 681-696 ◽  
Author(s):  
Shimon Wdowinski ◽  
Sang-Wan Kim ◽  
Falk Amelung ◽  
Timothy H. Dixon ◽  
Fernando Miralles-Wilhelm ◽  
...  

2021 ◽  
Vol 4 (1) ◽  
pp. 11-16
Author(s):  
Alovsat Shura Guliyev ◽  
Tatiana A. Khlebnikova

The article considers an algorithm for determining the statistical model from several inhomogeneous images of the Earth's surface obtained by different sensors (optoelectronic scanning device, synthetic aperture radar (SAR)) over the sea areas. The object of the study are the methods of remote sensing of the Earth used for detection and mapping of oil spills. The aim of the research was to perform testing for a possible variation of the statistical model inside a non-uniform sliding window based on a semi-automatic approach. The proposed algorithm makes it possible to determine the spatial extent of oil production sites and oil pollution in offshore waters using multi-time RSA data and a multi-zone combined image with a spatial resolution of 10 m. First, homogeneous regions are analyzed in the image, and then the model of the analysis zone is expanded to the more general case of inhomogeneous regions that are observed in the analysis windows.


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