SRTM digital elevation model

The SRTM DEM was created from phase-difference measurements of interferometric synthetic aperture radar (InSAR) collected in February 2000 and was the first near-global topography product for the Earth acquired in a consistent way13. The SRTM was designed to create a DEM with an absolute vertical accuracy of 16 m and this goal was met as 90% of the absolute elevation errors is <9 m49. The SRTM DEM is a digital surface model, describing the elevation of the Earth’s surface including objects at the surface, like buildings and vegetation. Therefore, the SRTM DEM has a tendency to overestimate actual ground surface elevation. There are different versions of the SRTM DEM available and efforts have been made to optimize the SRTM DEM, for example through vegetation removal50,51. Previously published SLR impact assessments for the Mekong delta used basic versions of the SRTM DEM, readily available through online portals, and no post-processing steps were performed to optimize the SRTM DEM for the studied area28,29,38. As this paper aims to assess the effect of using a basic version of the SRTM DEM for SLR assessments, we also selected a readily downloadable and widely-used version of the SRTM DEM without performing post-processing corrections. We used the SRTM Plus (or void-filled) DEM version 3.0 with an one-arc second grid, approximately ~30 × 30 m and a vertical resolution of 1 m (DEM available through: lpdaac.usgs.gov/data_access/data_pool).

MERIT digital elevation model

The high-accuracy global MERIT DEM37 was developed by removing major error components, i.e. absolute bias, stripe noise, speckle noise, and tree height bias from existing DEMs. For the Mekong delta region, the MERIT DEM uses the SRTM DEM as baseline, and unobserved areas were filled with the Viewfinder Panoramas DEM. The authors report an improvement of vertical accuracy compared to the original DEMs (from 39 to 58% of the land areas mapped with an accuracy of ±2 m or better)37. To portray the improvements of the MERIT DEM, and especially the improved landscape representation for flat regions, the Mekong delta was used as example on the data portal website (http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/). We acquired the MERIT DEM for the Mekong delta from the data portal.

Both the SRTM and the MERIT DEMs contain an obvious elevation error in the southwest corner of the delta where the elevation is <−1 m below MSL (Supplementary Fig. 12 and Supplementary Discussion 1). This part of the SRTM and MERIT DEM was therefore omitted in the DEM quality assessments in this study.

Topographical elevation points

We acquired a dataset with almost 20,000 elevation points located in the Vietnamese Mekong delta from the Division of Water Resources Planning and Investigation of the South of Vietnam derived from the national topographical map of 2014 (scale 1:200,000) made by the Department of Survey and Mapping of Vietnam, part of Vietnam’s Ministry of Natural Resources and Environment (Supplementary Fig. 1). The dataset has an average point density of 0.51 points per km2. The precision of the elevation indicated on the maps is 0.1 m for elevation points up to +2 m. Between +2 m and +3 m the elevations are given at 0.5 m intervals, elevations higher than +3 m are documented with intervals of 1 m. The data is projected in the VN-2000 coordinate reference system and vertically referenced to the Vietnam’s geodetic Hon Dau datum, which has its elevation origin at mean sea level (MSL) of the tide gauge at Hon Dau, an island offshore of Hai Phong in North Vietnam. The applied measurement technique of the elevation points present in the topographical map is not documented but likely derived from geodetic survey and photogrammetric data, as is common practice in Vietnam. A potential offset between mean sea level at the Hon Dau tide gauge (defining its zero datum level) and mean sea level in the Mekong delta cannot be excluded and may introduce additional uncertainty in elevation relative to local sea level along the Mekong. Still, this topographical dataset is presently the only and best available elevation data for the Mekong delta, apart from the global DEMs.

Interpolation of the topographical elevation model

We interpolated the elevation points to create a smooth, delta-wide, topographical (Topo) DEM. Based on the optimal points per grid cell52 and the point density of the dataset (0.51 points km−2), a grid cell size of 500 × 500 m is appropriate. A larger cell size would result in an increased RMSE, while a smaller cell size would result in an unfounded higher resolution. We tested several interpolation methods available in the 3D analyst and geostatistical analyst toolbox of ArcMap v.10.3.1., i.e. Inverse distance weighting, ordinary kriging, empirical Bayesian kriging, nearest neighbor, spline and ANUDEM. We compared the resulting DEMs based on a statistical analysis using 120 randomly distributed control points (a subset from the elevation points excluded from the interpolation, see SI, Supplementary Methods 1, Supplementary Fig. 13) and inspection of interpolation correctness in areas with large elevation differences (e.g. spline interpolation created erroneous negative elevations around higher elevated bed rock outcrops). The DEM interpolated using empirical Bayesian kriging employing empirical data transformation and an exponential model produced the lowest mean absolute deviation of all control points (0.22 m) and interpolated realistically between points with larger elevation differences (Supplementary Table 6, Supplementary Fig. 13). Consequently, this method was selected to interpolate the topographical elevation points and create the Topo DEM (see Supplementary Fig. 14 for interpolation settings).

Before interpolation, all elevation points exceeding individual elevations of +10 m were removed from the dataset. These points are located on highly elevated limestone outcrops towering above the otherwise flat delta plain and including them in the interpolation would inevitably introduce errors to the elevation of the flat delta plain in the immediate surroundings. After interpolation, these areas with elevated limestone bedrock outcrops were excluded from further analyses using a shapefile delineating them based on Google Earth imagery. Furthermore, the large Mekong river branches were removed from the Topo DEM, which is also the case for the SRTM DEM. The Topo DEM resulting from the interpolation has an average root mean square error (RMSE) of 0.16 m that spatially increases with decreasing elevation point density and increasing local elevation variation (Supplementary Fig. 15).

Validation of absolute elevation

We evaluated the absolute elevation of the SRTM, MERIT, and Topo DEMs relative to Vietnam’s geodetic datum using an independent dataset of 69 national benchmark elevation measurements throughout the delta managed by the Department of Survey and Mapping of Vietnam (see SI, Supplementary Table 2 and Supplementary Fig. 4). The dataset provides coordinates (VN-2000) and vertical elevation at mm precision referenced to Vietnam 2000 geodetic Hon Dau datum (origin at MSL at Hon Dau tide gauge)53. The geodetic network of national benchmarks in South Vietnam was built by radio-positioning and traverse measurement techniques connected to stable points with known elevation at bedrock outcrops at the edge of the delta plain53. Vertical elevation accuracy of the measurements is not documented. Benchmarks are reportedly located ~30 cm below terrain surface for protection (Supplementary Fig. 5), however it is uncertain whether this is the case for all benchmarks in the dataset. As we compare the elevation of point locations to the average elevation of an entire grid cell (30 m × 30 m for the STRM DEM, 94 m × 94 m for the MERIT DEM and 500 m × 500 m for the Topo DEM), we do expect differences between individual elevation points and the elevation models cells. If the overall elevation of the DEM is in agreement with the overall benchmark elevation, the residuals are expected to show a narrow, non-skewed normal distribution centered at zero.

Validation of relative elevation

We assessed the correctness of the spatial distribution of relative elevation of the DEMs by using two datasets that function as proxy for relative elevation: (i) a geomorphological map39 and (ii) a flood occurrence map15. The geomorphological map of the Vietnamese Mekong delta39 was mapped using aerial photographs and satellite images combined with field surveys, cored sediment samples and paleoenvironmental assessment using microfossils (Supplementary Fig. 7). It shows the presence and distribution of different geomorphological regions and features throughout the delta. In a natural setting, each geomorphological unit is characterized by a certain elevation relative to other geomorphological units because on differences in depositional environment (Supplementary Fig. 6). For example, natural levees and beach ridges are higher elevated than adjacent flood basins and coastal plains. Therefore, the geomorphological map can serve as proxy for spatial relative elevation distribution. A correct DEM should provide a similar logical elevation pattern, correctly reflecting the relative elevation of the different geomorphological units. We digitized the geomorphological map into a polygon shapefile in ArcMap and extracted the DEMs statistics per geomorphological unit.

We grouped the geomorphological units in three categories that characterize depositional environments with a typical elevation distribution. The first category consists of the Pleistocene geomorphological units, which are mainly found in the N and NW of the Vietnamese Mekong delta. We expect all Pleistocene deposits to be higher elevated than the younger Holocene deposits, because, otherwise, they would have been buried by Holocene onlap deposits. Within the Holocene deposits, we distinguish between the higher elevated, alluvial landscape in the Upper delta plain and the lower elevated coastal plain in the Lower delta plain54 (Supplementary Fig. 7).

Within each category, we estimated the expected elevation of a geomorphological unit relative to the other units based on typical landscape geomorphology (Table 2; Supplementary Fig. 6A). For the alluvial landscape of the Upper delta plain, we based our expected relative elevation on typical channel belt—floodplain morphology in lowlands55. Natural levees are the highest elevated units, followed by channel bars and abandoned channel belts, which are in turn elevated higher than flood basins (partly as a result of post-depositional subsidence of soft flood basin soils). Swamps—requiring frequent flooded and waterlogged conditions—are located in the lowest parts of the landscape. For the coastal environments, we based the expected relative elevation on typical coastal morphology, with mangroves and relict sandy beach ridges separating the tidal flats from the back barrier salt marshes and coastal plain with fresh water marshes in the hinterland (Table 2; Supplementary Fig. 6B). The elevation of tidal flats at the coastline are expected to match high tide levels. Sand spits and especially relict beach ridges are generally elevated higher than the tidal flats. The near-coastal mangrove and salt marshes are expected to have a similar elevation as the tidal flats as they trap sediments during high tide. The back barrier coastal plain is expected to have a lower elevation, as a result of the combination of ongoing compaction of the Holocene strata25 and reduced sediment supply with progradation of the coastline. Inland marshes within the coastal plain are expected to have the lowest relative elevation, as they are located furthest away from the coastline and active tidal channels, which reduces sediment delivery even further. At delta scale, the coastal plain in the western part of the delta is expected to be lower elevated than the coastal plain in the east, as the nearby Gulf of Thailand only has a tidal range of 40 cm40 and no direct sediment delivery by rivers.

The second method to validate the spatial distribution of the relative elevation is based on the assumption that lower areas in the flat coastal zone are more often inundated than higher areas, either naturally-induced by flooding or human-induced for agri- and aquaculture purposes Kuenzer et al.15 created 128 maps of the extent of floods in the Mekong delta from 2007 to 2011 based on Envisat ASAR-WSM (Advanced Synthetic Aperture Radar Wide Swath Mode) satellite images. Combing these maps resulted in a cumulative inundation map showing the number in which an area was inundated during this four year period with a grid cell size of 150 m (Supplementary Fig. 9). The authors distinguished four influencing factors for inundation in the Mekong delta: (1) natural floods of the Mekong river and overland flow, (2) artificial floodwater distributed by canals and controlled by dykes and sluice gates, (3) extreme local precipitation events, and (4) floods related to high tides15,56. Inundations resulting from the first three factors do not solely correlate to lowly elevated areas, as they also occur in elevated areas. For example, river floodwater and overland flow happens mostly in the higher, upstream areas as dikes and canals block and retain the floodwater, preventing it to reach the lowest, more distal parts of the delta plain. Extreme precipitation events can occur anywhere in the delta, as the flat topography of the region does not cause orographic lift which would induce increased precipitation at a certain location. However, inundations following tidal flooding are expected to negatively correlate to elevation in terms of extent and duration, as tidal floodwater inundates the lowest topographical areas first and longest. In general, inundation in the northern and middle part of the Mekong delta is predominantly caused by river-induced floods, overland flow and human floodwater control and retention, whereas in the southwestern part of the delta, flooding is induced by both high tides and human action (Supplementary Fig. 9).

We compared the spatial pattern of tide-dominated flood occurrences (which is related to the elevation relative to sea level) to the relative elevation of the DEMs. We only considered those areas where floods are determined by sea water level and tides, which include the provinces of Ca Mau, Bac Lieu, Soc Trang and the southern part of Kien Giang (Supplementary Fig. 9). Part of the area in the southwestern tip of the Mekong delta experience very long, up to year-round, inundation to accommodate aquaculture, mainly shrimp farms57. Although inundation of such aquaculture areas is human controlled, e.g. by opening/closing of sluices58, they are located in the lowest parts in the landscape, to facilitate water circulation and management. Therefore, the presence of aquaculture does not obstruct the correlation between inundated area and elevation.

The analysis was performed by sampling the elevation of the DEMs at the center of each inundation-map raster cell and calculating the elevation statistics per inundation occurrence. Less than one percent of the total area is inundated more than 25 out of 128 times. As the areas per inundation occurrence >25 became too small to derive a representative mean elevation from the DEMs, they were excluded from the analysis.

Sea-level rise impact assessments

To evaluate the effect of using the SRTM, the MERIT or the Topo DEM for relative SLR (hereafter: SLR) impact assessments, we estimated the area below sea level after future SLR for each DEM. Both the SRTM and the MERIT DEM are referenced to WGS84 and EGM96. Zero vertical elevation in these DEMs represents zero elevation to the global earth gravitational model (EGM) and this likely differs from the local tidal datum, and thus sea level. Nonetheless, numerous previous studies directly used the SRTM DEMs elevation for SLR impact assessments, erroneously assuming 0-m elevation (to EGM96 datum) to equal local mean sea level28,29,38. To evaluate to what extent such assumption would lead to errors in SLR impact assessments, for sake of discussion, we purposely assumed 0-m elevation in both STRM and MERIT DEMs to represent mean sea level, thereby mimicking previous studies. Although actual MSL in the Mekong delta possibly also differs from the Hon Dau tidal datum, in the absence of additional data, we assumed the zero elevation in Hon Dau datum to represent current MSL in the Mekong delta. For the purpose of analysis of comparing the performance of the Topo and the MERIT DEMs in SLR impact assessments, we attempted to account for the difference in vertical datum by vertically shifting the MERIT DEM to match the Topo DEM’s mean elevation of the Mekong Delta. This was done by subtraction of the absolute difference in mean elevation of the two DEMs, in this case 2.5 m.

The vertical resolution of both the MERIT and the Topo DEMs allowed detailed quantification of the area affected by rising sea level. We quantified the areas falling below sea level for SLR scenarios of 20, 50, 80, and 100 cm. In case of the SRTM DEM with a vertical resolution of 1 meter, we determined the area falling below sea level for a SLR of 1 meter, similar to analyses done in previous studies28,29,38. We also estimated the number of people living in the area below sea level for each scenario by using provincial population statistics of 2016 (people per km2; Supplementary Table 7). As spatial data on the population distribution within provinces was not available, we assumed an even distribution excluding rivers and steep bedrock outcrops. Additionally, a detailed analysis of delta surface and people impacted for each province individually was done for the Topo DEM.