Abstract

Remote sensing allowed monitoring the reservoir water level by estimating its surface extension. Surface extension has been estimated using different approaches, employing both optical (Landsat 5 TM, Landsat 7 ETM+ SLC-Off, Landsat 8 OLI-TIRS and ASTER images) and Synthetic Aperture Radar (SAR) images (Cosmo SkyMed and TerraSAR-X). Images were characterized by different acquisition modes, geometric and spectral resolutions, allowing the evaluation of alternative and/or complementary techniques. For each kind of image, two techniques have been tested: The first based on an unsupervised classification and suitable to automate the process, the second based on visual matching with contour lines with the aim of fully exploiting the dataset. Their performances were evaluated by comparison with water levels measured in situ (r2 = 0.97 using the unsupervised classification, r2 = 0.95 using visual matching) demonstrating that both techniques are suitable to quantify reservoir surface extension. However ~90% of available images were analyzed using the visual matching method, and just 37 images out of 58 using the other method. The evaluation of the water level from the water surface, using both techniques, could be easily extended to un-gauged reservoirs to manage the variations of the levels during normal operation. In addition, during the period of investigation, the use of Global Navigation Satellite System (GNSS) allowed the estimation of dam displacements. The advantage of using as reference a GNSS permanent station positioned relatively far from the dam, allowed the exclusion of any interaction with the site deformations. By comparing results from both techniques, relationships between the orthogonal displacement component via GNSS, estimated water levels via remote sensing and in situ measurements were investigated. During periods of changing water level (April 2011–September 2011 and October 2011–March 2012), the moving average of displacement time series (middle section on the dam crest) shows a range of variability of ±2 mm. The dam deformation versus reservoir water level behavior differs during the reservoir emptying and filling periods indicating a hysteresis-kind loop.

Highlights

  • Remote sensing allowed monitoring the reservoir water level by estimating its surface extension

  • While differences were of few millimeters for the planimetric components, the time series appears scattered for vertical Global Navigation Satellite System (GNSS) components

  • Based on these preliminary studies, displacements were monitored over two years and water levels were investigated for a longer period than that closely related to the displacement monitoring (08 April 2011–13 May 2013), using satellite images from

Read more

Summary

State of Art and Introduction

Real-time monitoring and protection of strategic structures such as dams are necessary since these have social, economic, and environmental importance. The advanced permanent scatterers InSAR technique, allowed evaluating the rate of continuous non-linear deformations of a dam over time caused (among factors) by variable water level [15] Both remote sensing and GNSS techniques are helpful where data is unavailable, or where it is not feasible to retrieve data elsewhere. The accuracy of GNSS data are in a range of ±10 mm, while the accuracy of spirit leveling allowed to obtain better results for vertical deformations [17] Based on these preliminary studies, displacements were monitored over two years and water levels were investigated for a longer period than that closely related to the displacement monitoring (08 April 2011–13 May 2013), using satellite images from. The satellite dataset included different types of imagery (both optical and SAR) to investigate the relationship between the variables during both an emptying and filling period of the reservoir

Theory and Methods
Radiometric Calibration of Remote Sensing Data
Flow diagram of optical
Pixel Aggregate on SAR Images
Visual Matching
Classification
GNSS Processing
Study Area
Materials
Remote Sensing
Pixel Aggregate of SAR and Optical Images
13. Temporal
Comparison between Displacements and Water Levels
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.