their time series variations with an ENSO index. The Multivariate ENSO Index (MEI) is chosen because this index integrates multiple climate variables that make it suitable for climate-land-atmosphere interaction studies [Wolter and Timlin, 1998]. MEI has a long monthly record back to 1950, and it is updated monthly.
MEI data are developed byWolter and Timlin[1993,1998], and are provided on a National Oceanic & Atmospheric Administration’s (NOAA) webpage:https:
//www.esrl.noaa.gov/psd/enso/mei/.
4.3 Evaluations of the MODIS-derived surface water extent
As already mentioned previously, variation of the surface water volume is calcu-lated as the product of the surface water extent and height. The accuracy of the two components need to be checked to guarantee good quality of the surface wa-ter volume variation. For validation of the first component, the MODIS-derived surface water extent is evaluated with the SAR-derived surface water extent (the output of Chapter3), precipitation data, and in situ water level data before be-ing used to calculate surface water volume variation in the lower Mekong basin.
The MODIS-derived surface water extent is also compared to the ENSO index to understand the relationship between them.
4.3.1 Comparison with SAR-derived surface water extent
Time series of surface water extent derived from optical MODIS observations and SAR Sentinel-1 observations over a common area in the Mekong basin (latitude:
8.5°- 13.5°N; longitude: 103°- 107°E) for two years (2015-2016) are shown in Figure 4.2. Similar to findings in Chapter3 (see Figure3.12), there is an amplitude gap between MODIS- and SAR-derived surface water extent, but the two products share the same dynamics with a high linear temporal correlation (94%) over the common period. The two surface water extent time series confirm the wetland seasonality and its variation in the lower Mekong basin. However, it is impossible to conclude which dataset is better because no reference dataset for comparison is available. SAR-derived products are expected to be more reliable and closer to the reality than MODIS-derived ones because of its cloud penetration ability, as well as its higher spatial resolution (30 m compared to 500 m of MODIS imagery).
Inundation frequency maps in the studied area, calculated from different op-tical Landsat, MODIS and SAR Sentinel-1 satellite observations are shown in Fig-ure 4.3. Landsat inundation frequency map is calculated from the global water occurence product by Pekel et al. [2016], based on ∼3 million optical Landsat satellite images during 32 years (from March 1984 to October 2015). This product gives the frequency of global water occurrence at 30 m spatial resolution. MODIS inundation frequency map is calculated based on 16-year optical MODIS observa-tions (2001-2016, as presented in Chapter2), and Sentinel-1 inundation frequency map is calculated based on 2-year SAR observations (2015-2016, as presented in
Jan15 Apr15 Jul15 Oct15 Jan16 Apr16 Jul16 Oct16 0.5
1 1.5
2 104
MODIS water extent Sentinel water extent
FIGURE 4.2: Surface water extent time series derived from optical MODIS and SAR Sentinel-1 observations in the Mekong Delta and Cambodia, over the
com-mon period (2015-2016).
(a) (b) (c)
FIGURE4.3: Inundation frequency derived from 32-year optical Landsat obser-vations (a) [Pekel et al.,2016], 16-year optical MODIS observations (b), and 2-year
SAR Sentinel-1 obsrvations (c), over the Mekong Delta and Cambodia.
Chapter 3). Although the total number of Landsat, MODIS, and Sentinel-1 ob-servations used to produce the three inundation frequency maps are different, spatial distributions of wetlands, rivers, lakes and water bodies are very similar in these maps. Lakes and rivers appear clearly in all the three maps, with high inundation frequency. The wetland distribution for the area over the Cambodia-Vietnam border (latitude: 10°–11.5°N, longitude: 104.5°–106°E) is similar in the three maps, especially between the two maps derived from optical data. It is less extended in the SAR map because the map was created based on limited SAR observations in just 2 years. In addition, the southern part of the Mekong Delta (latitude: 8.5°–9.5°N, longitude: 105°–106°E) appears similarly in the three maps, with high inundation frequency. There are water fields in this area where local farmers raise aquatic animals all along the year. Despite the similarity, there are differences among the three maps. Inundation frequency of the Tonle Sap Lake derived from the Landsat map (Figure4.3a) is lower than that from the MODIS and SAR maps (Figure 4.3b,c). It may due to the lack of free-cloud images ob-served by the optical Landsat sensors. For a region located to the east of the Mekong delta (latitude: 10°–11°N, longitude: 106°–107°E), it is dryer in MODIS and SAR inundation frequency maps than in Landsat map. The land use change due to urban development in this area could be the reason to explain the differ-ence in the three maps.
4.3.2 Comparison with precipitation data
Time series of the MODIS-derived surface water extent are compared to satellite-based TMPA precipitation data. Relationships between surface water extent and local precipitation (over the Mekong basin lower than latitude 15°N) are pre-sented in Figure4.4, while Figure4.5shows comparisons with precipitation over the higher Mekong basin (higher than latitude 15°N). Local precipitation partly contributes to the variation of surface water extent. For example, less local rainfall than mean values during the wet season in 2010 contributed to a lower peak of surface water extent at the same time. The year after, local rainfall increased mak-ing an increase to the maximum of surface water extent. Peaks of local precipi-tation normally occur in Septembers, 2-3 weeks before the peaks of surface wa-ter extent. Their anomalies show some good agreements during wet years (2002, 2003, 2005, 2006 and 2011), as well as during dry years (2002, 2004, 2007, 2010, and 2012). Rainfall over the higher Mekong basin affects less the variation of sur-face water extent over the Mekong Delta than the local rainfall. Over the higher Mekong basin, precipitation reaches their maximum 1-month earlier, normally in Augusts, compared to the maximum of surface water extent in the Mekong Delta.
2002 2004 2006 2008 2010 2012
0
2002 2004 2006 2008 2010 2012
-200
FIGURE4.4:(a)Time series,(b)Monthly-mean annual cycle, and(c)Anomaly of MODIS-derived surface water extent over the Mekong Delta and Cambodia, and satellite-based precipitation over the Mekong basin located lower than latitude
15°N, over the 2001-2012 period.
2002 2004 2006 2008 2010 2012
2002 2004 2006 2008 2010 2012
-200
FIGURE4.5: Similar to Figure4.4, but satellite-based precipitation data cover the Mekong basin located higher than latitude 15°N.
There is no strong relationships between their anomalies, except for some strong events like the drought in 2012.
4.3.3 Comparison with in situ water level data
20080 2009 2010 2011 2012 2013 2014 2015 2016 2017 1
R = 93% MODIS water extent
In situ water level
FIGURE 4.6: Left: Time series of MODIS-derived surface water extent over the Mekong Delta and Cambodia, and in situ water level at the Tonle Sap Lake gauge station, over the common period (2008-2016). Right: Monthly-mean annual cycle
from the two time series.
Time series of the MODIS-derived surface water are compared to in situ water level data at the Tonle Sap gauge station, over the 2008-2016 period (Figure4.6).
Similar dynamics between surface water extent and in situ water level can be
observed for the common period, with a high linear temporal correlation (93%).
Monthly-mean annual cycles extracted from the two time series are shown in Figure4.6-right.
4.3.4 Comparison with the Multivariate ENSO Index
Figure4.7shows comparisons between time series and anomalies of the MODIS-derived surface water extent, TMPA precipitation and GIEMS-MODIS-derived surface water extent in the lower Mekong basin, and the Multivariate ENSO index (MEI) over their common periods. Details of the Global Inundation Extent from Multi-Satellites (GIEMS) will be presented in Chapter5. Relationships between the vari-ation of MODIS-derived surface water extent in the lower Mekong basin and the MEI over the 2001-2016 period, are shown in Figure4.7a,b. A linear correlation of 62% is found between MODIS-derived surface water extent anomaly and the MEI during a 5-year period (from May 2001 to June 2016). The effects of the strong 2014-2016 El Niño event on the lack of surface water extent in the lower Mekong basin is clearly observed. The link between surface water extent and the MEI
2005 2010 2015
MODIS water extent ENSO Index (d)
2002 2004 2006 2008 2010 2012 0
2002 2004 2006 2008 2010 2012 -200
1994 1996 1998 2000 2002 2004 2006 2008 0
1994 1996 1998 2000 2002 2004 2006 2008 -4
GIEMS water extent ENSO Index (f)
FIGURE 4.7: Comparisons between time series (left) and anomalies (right) of MODIS-derived surface water extent (a & d), precipitation (b & e) and GIEMS-derived surface water extent (c & f) over the lower Mekong basin, and the
Mul-tivariate ENSO Index, over their common periods.
is not obvious in other years when the ENSO is in its "Neutral" phase, as ex-pected. Similar conclusion can be made between variation of local precipitation in the Mekong Delta and the MEI over the 2002-2012 period (Figure4.7b,e). Up-dated TMPA precipitation data for recent years are not available to evaluate the effects of the 2014-2016 El Niño event on the variation of local precipitation in the Mekong Delta. Surface water extent in the Mekong basin, derived from the GIEMS dataset over the 1993-2007 period [Prigent et al., 2007, 2012], is also ac-cessed to study the relationships between surface water extent and the ENSO in previous years. Similar to what have been observed during the 2014-2016 El Niño event, there was a decrease of GIEMS-derived surface water extent in the lower Mekong basin during the 1997-1998 El Niño event (Figure4.7c,f).