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Monitoring Recent Fluctuations of the Southern Pool of Lake Chad Using Multiple Remote Sensing Data: Implications for Water Balance Analysis
- Source :
- Remote Sensing, Vol 9, Iss 10, p 1032 (2017)
- Publication Year :
- 2017
- Publisher :
- MDPI AG, 2017.
-
Abstract
- The drought episodes in the second half of the 20th century have profoundly modified the state of Lake Chad and investigation of its variations is necessary under the new circumstances. Multiple remote sensing observations were used in this paper to study its variation in the recent 25 years. Unlike previous studies, only the southern pool of Lake Chad (SPLC) was selected as our study area, because it is the only permanent open water area after the serious lake recession in 1973–1975. Four satellite altimetry products were used for water level retrieval and 904 Landsat TM/ETM+ images were used for lake surface area extraction. Based on the water level (L) and surface area (A) retrieved (with coinciding dates), linear regression method was used to retrieve the SPLC’s L-A curve, which was then integrated to estimate water volume variations ( Δ V ). The results show that the SPLC has been in a relatively stable phase, with a slight increasing trend from 1992 to 2016. On annual average scale, the increase rate of water level, surface area and water volume is 0.5 cm year−1, 0.14 km2 year−1 and 0.007 km3 year−1, respectively. As for the intra-annual variations of the SPLC, the seasonal variation amplitude of water level, lake area and water volume is 1.38 m, 38.08 km2 and 2.00 km3, respectively. The scatterplots between precipitation and Δ V indicate that there is a time lag of about one to two months in the response of water volume variations to precipitation, which makes it possible for us to predict Δ V . The water balance of the SPLC is significantly different from that of the entire Lake Chad. While evaporation accounts for 96% of the lake’s total water losses, only 16% of the SPLC’s losses are consumed by evaporation, with the other 84% offset by outflow.
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 9
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.17e403900c9046c6a9c02153fbe061dc
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs9101032