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| Type: | Resource | |
| Storage: | The size of this resource is 488.4 KB | |
| Created: | Apr 22, 2021 at 8:32 a.m. | |
| Last updated: | Apr 22, 2021 at 3:05 p.m. | |
| DOI: | 10.4211/hs.4fe324512fa34b2884a1b5c32b70e2c7 | |
| Citation: | See how to cite this resource | |
| Content types: | Single File Content |
| Sharing Status: | Published |
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| Views: | 659 |
| Downloads: | 76 |
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Abstract
Recently, the satellite images have been used in remote sensing allowing observations with high temporal and spatial distribution. The use of water indices has proved to be an effective methodology in the monitoring of surface water resources. However, precise or automatic methodologies using satellite imagery to determine reservoir volumes are lacking. To fulfil that gap, this methodology proposes 3 stages: use Google Earth Engine (GEE) to select images; automatically calculate flooded surface areas applying water indices; determine the volume stored in reservoirs over those years based on the relation between the flooded area and the stored volume. The method was applied in four reservoirs and contemplate Landsat 4 and 5 ETM and Landsat 8 OLI. For the calculation of the flooded area the NDWI Indexes (McFeeters, 1996; Gao, 1996), and the MNDWI index (Xu, 2006) were applied and tested. The estimation of stored volume of water was made based on the area indices and a cross-check between real stored volume and calculated volume was made. Finally, an analysis on the selection of the best fit water indices was made. The results of every case studies herein displayed showed a quantifiable proficiency and reliability for quite a varied natural conditions. As a conclusion, this methodology could be seen as a tool for water resources management in developing countries, and not only, to measure automatically trends of stored volumes and its relation with the precipitation, and could eventually be extended to other types of surface water bodies, as lakes and coastal lagoons.
Subject Keywords
Coverage
Spatial
Temporal
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Content
Related Resources
| The content of this resource is derived from | Roxo reservoir - curves that relate the flooded area to the stored volume - https://snirh.apambiente.pt/index.php?idMain=1&idItem=7&albufcode=45 |
| The content of this resource is derived from | Google Earth Engine Landat 4 Images - https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LT04_C01_T1_SR |
| The content of this resource is derived from | Google Earth Engine Landat 5 Images - https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LT05_C01_T1_SR |
| The content of this resource is derived from | Google Earth Engine Landat 8 Images - https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C01_T1_SR |
| The content of this resource is derived from | Alvito Reservoir - Curves that relate the flooded area to the stored volume - https://snirh.apambiente.pt/index.php?idMain=1&idItem=7&albufcode=59 |
| The content of this resource is derived from | Caia reservoir - curves that relate the flooded area to the stored volume - https://snirh.apambiente.pt/index.php?idMain=1&idItem=7&albufcode=42 |
| The content of this resource is derived from | Maranhão reservoir - curves that relate the flooded area to the stored volume - https://snirh.apambiente.pt/index.php?idMain=1&idItem=7&albufcode=29 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| Portuguese Foundation for Science and Technology (FCT) | PTDC/CTA-OHR/32360/2017 (DRONEWATER) |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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