Publications

Tong, XH; Pan, HY; Xie, H; Xu, X; Li, FT; Chen, L; Luo, X; Liu, SJ; Chen, P; Jin, YM (2016). Estimating water volume variations in Lake Victoria over the past 22 years using multi-mission altimetry and remotely sensed images. REMOTE SENSING OF ENVIRONMENT, 187, 400-413.

Abstract
Lake Victoria is the largest freshwater lake in Africa and the second largest in the world. In order to investigate the change of Lake Victoria over the past decades, this paper presents an approach for the long time series analysis of water volume by using a combination of multi-mission altimetry and remotely sensed images. The proposed approach consists of three main components. (i) Estimation of the lake surface area variations from 2000 to 2012 by the use of support vector machine (SVM) for remotely sensed imagery. (ii) Calculation of the lake surface height from 1991 to 2012 by the use of multi-mission altimetry data through an elimination of the bias between different satellite missions. (iii) Development of the relationship between the area-water level above lowest level (WLALL) and water volume above lowest level (WVALL) by the use of regression and integration analysis to estimate the volume variations over the past 22 years. Several new findings discovered through the experimental results: (i) Lake surface area, height, and volume have experienced significant fluctuations over the past 22 years as follows: (a) the relatively stable period from 1991 to 1997; (b) the significant increase period from 1998 to 1999; (c) the sharp drop period from 2000 to 2006; and (d) the gradual increase period from 2007 to 2012. (ii) The intra-annual analysis indicates that lake surface area, height, and volume show obvious seasonal patterns. (iii) The significant changes of Lake Victoria, which are detected from remotely sensed imagery and satellite altimetry data, coincide with the events responsible for these variations, which are excessive outflow, weather conditions, rapid population growth and land-cover changes. (C) 2016 Elsevier Inc. All rights reserved.

DOI:
10.1016/j.rse.2016.10.012

ISSN:
0034-4257