Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas
In river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-12-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://www.hydrol-earth-syst-sci.net/21/6445/2017/hess-21-6445-2017.pdf |
| _version_ | 1830483242107535360 |
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| author | N. Avisse A. Tilmant M. F. Müller H. Zhang |
| author_facet | N. Avisse A. Tilmant M. F. Müller H. Zhang |
| author_sort | N. Avisse |
| collection | DOAJ |
| description | In river basins with water storage facilities, the availability
of regularly updated information on reservoir level and capacity is of
paramount importance for the effective management of those systems. However,
for the vast majority of reservoirs around the world, storage levels are
either not measured or not readily available due to financial, political, or
legal considerations. This paper proposes a novel approach using Landsat
imagery and digital elevation models (DEMs) to retrieve information on
storage variations in any inaccessible region. Unlike existing approaches,
the method does not require any in situ measurement and is appropriate for
monitoring small, and often undocumented, irrigation reservoirs. It consists
of three recovery steps: (i) a 2-D dynamic classification of Landsat spectral
band information to quantify the surface area of water, (ii) a statistical
correction of DEM data to characterize the topography of each reservoir, and
(iii) a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan
Line Corrector failure. The method is applied to quantify reservoir storage
in the Yarmouk basin in southern Syria, where ground monitoring is impeded by
the ongoing civil war. It is validated against available in situ measurements
in neighbouring Jordanian reservoirs. Coefficients of determination range
from 0.69 to 0.84, and the normalized root-mean-square error from 10 to
16 % for storage estimations on six Jordanian reservoirs with maximal water
surface areas ranging from 0.59 to 3.79 km<sup>2</sup>. |
| first_indexed | 2024-12-21T17:47:45Z |
| format | Article |
| id | doaj.art-254426ec6ea44dbabfdf4382d146b806 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-12-21T17:47:45Z |
| publishDate | 2017-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-254426ec6ea44dbabfdf4382d146b8062022-12-21T18:55:26ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382017-12-01216445645910.5194/hess-21-6445-2017Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areasN. Avisse0A. Tilmant1M. F. Müller2H. Zhang3Department of Civil Engineering and Water Engineering, Université Laval, Québec, QC G1V 0A6, CanadaDepartment of Civil Engineering and Water Engineering, Université Laval, Québec, QC G1V 0A6, CanadaDepartment of Civil & Environmental Engineering & Earth Science, University of Notre Dame, Notre Dame, IN 46556, USADepartment of Engineering, School of Engineering and Computing Sciences, Texas A & M University – Corpus Christi, Corpus Christi, TX 78412, USAIn river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not measured or not readily available due to financial, political, or legal considerations. This paper proposes a novel approach using Landsat imagery and digital elevation models (DEMs) to retrieve information on storage variations in any inaccessible region. Unlike existing approaches, the method does not require any in situ measurement and is appropriate for monitoring small, and often undocumented, irrigation reservoirs. It consists of three recovery steps: (i) a 2-D dynamic classification of Landsat spectral band information to quantify the surface area of water, (ii) a statistical correction of DEM data to characterize the topography of each reservoir, and (iii) a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan Line Corrector failure. The method is applied to quantify reservoir storage in the Yarmouk basin in southern Syria, where ground monitoring is impeded by the ongoing civil war. It is validated against available in situ measurements in neighbouring Jordanian reservoirs. Coefficients of determination range from 0.69 to 0.84, and the normalized root-mean-square error from 10 to 16 % for storage estimations on six Jordanian reservoirs with maximal water surface areas ranging from 0.59 to 3.79 km<sup>2</sup>.https://www.hydrol-earth-syst-sci.net/21/6445/2017/hess-21-6445-2017.pdf |
| spellingShingle | N. Avisse A. Tilmant M. F. Müller H. Zhang Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas Hydrology and Earth System Sciences |
| title | Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas |
| title_full | Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas |
| title_fullStr | Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas |
| title_full_unstemmed | Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas |
| title_short | Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas |
| title_sort | monitoring small reservoirs storage with satellite remote sensing in inaccessible areas |
| url | https://www.hydrol-earth-syst-sci.net/21/6445/2017/hess-21-6445-2017.pdf |
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