2. Delta Elevation

forces in a given morphological setting, influenced by a large number of drivers. Therefore, salinity intrusion is not only influenced by climate change — as reflected in discharge variation, global sea level rise, evaporation, and precipitation etc. — but also by anthropogenic drivers that modify river discharge and water levels, or the bathymetry and geometry of river and estuarine channels [ Eslami et al., 2019b ]. The most recent scientific findings on salt intrusion in the delta show that anthropogenic riverbed incision, driven by sediment starvation due to upstream impoundments and downstream sand mining, currently outpaces climate change effects by orders of magnitude [ Eslami et al., 2019b, 2021a, 2021b ]. Riverbed-level changes simplify salinity intrusion in the deeper estuarine channels and amplify the tidal range that increases ocean forces in salt intrusion. As well as impacting salinity, tidal amplification exacerbates city flooding in subsiding cities of the VMD and creates a feedback loop that contributes to riverbed/bank erosion. While the VMD is already impacted by climate change, it is the combined and cumulative impact of climate change and “local drivers of exposure

2.1 A key parameter for the delta’s future

The elevation of the land surface relative to mean sea level is an important factor that determines the impact of climatic and environmental changes on life in a delta. Low elevation relative to sea level means increased and vulnerability” [ Oppenheimer et al., 2019 ] that determine the environmental pathways of the delta over the next decades.

This chapter aims to provide a holistic view of the past, present and future dynamics of change in the VMD regarding relative sealevel rise and saline water intrusions, by disentangling the effects of various environmental (sea level rise, natural subsidence, and river discharge anomalies) and anthropogenic (human-induced subsidence and sediment starvation) systems stressors. We exhibit the environmental pathways in the coming decades as they relate to elevation as well as saline water intrusion. For the latter, we show how climate change — through sea level rise and upstream discharge anomalies, extraction-induced land subsidence, and riverbed erosion — influences salinity in delta, developing a range of possibilities for the next 3 decades. Figure 9.2 demonstrates a range of salt intrusion scenarios until 2040. The outcome offers crucial input for effective climate adaptation and anthropogenic mitigation strategies in the VMD.

exposure of the delta, its inhabitants and its economic activities to flooding, salinization, and erosion. Lower elevation decreases resilience of the delta to changes in the environment and exponentially increases the costs of livelihood [ Nicholls et al., 2021 ].

2.2 Accurate elevation data crucial for risk assessment

It is imperative to have good estimates of present elevation and the relevant processes

[ Figure 9.2 ] Elevation, sand mining and saline water intrusions

Digital elevation map of the Mekong Delta [ Minderhoud et al., 2019 ], including the salinity increase rates at multiple stations [ Eslami et al., 2019b ], the estimated sand mining volumes (scaled with surface area of the circles) [ Eslami et al., 2019b ]; The sand mining figures upstream of the VMD are extracted from previous publications [ Bravard et al., 2013 ], but updated within the VMD; the contour lines show present and projected peak salt intrusion (2 PPT contour lines) under moderate and extreme scenarios of climate change (SLR and discharge variation under RCP scenarios), groundwater extraction-induced subsidence [ Minderhoud et al., 2020 ] and riverbed level incision due to sediment starvation [ Eslami et al., 2019b, 2021b ], assuming the coastline remains unchanged (coord. system WGS84-UTM 48 N).

driving elevation change to create accurate future projections and reliable impact assessments, e.g. for sea level rise.

In the past, many assessments of exposure to sea level rise in the VMD have been based on globally available, satellite-derived elevation data. The problems with these public data are: 1 ] the relatively high vertical error, which is especially problematic for flat deltaic regions and 2 ] the fact that the data are referenced to a global approximate sea level (the so-called geoid), which can differ by several dm/m from the local sea level height [ Box 9.1 ]. Almost all previous sea level rise impact assessments using satellite-derived data have omitted the required conversion from global to local sea level, thereby creating a structural height bias that overestimated the elevation of the VMD [ Carew-reid, 2008; Kondolf et al., 2018; Schmitt et al., 2017; Warner et al., 2010 ] (see Box 9.1).

An exception to the above is the assessment by Climate Central using the Coastal DEM, an automated-error-removed DEM based on SRTM data [ Kulp and Straus, 2019 ] and properly-converted vertical datum to local mean sea level. However, instead of overestimating elevation in the VMD, the automatic-generated Coastal DEM underestimates the elevation. According to the Coastal DEM, the average elevation of the VMD at present is already -0.5 m below mean sea level, which is not the

[ Box 9.1 ] Elevation models of the VMD

Digital Elevation Models (DEMs) are fundamental inputs for inundation or sea level rise risk assessments. Projections of sea level rise are in the order of cm to dm at decadal timescales; hence ideally the DEM should provide a similar accuracy and precision. This holds true for DEMs created using high-accuracy elevation observation methods such as airborne-based laser altimetry data ( LiDAR) or ground elevation measurements from geodetic surveys (e.g. spirit levelling campaigns). These high-level elevation data are available to Vietnamese ministries and used for internal sea level rise impact assessments but are not publicly accessible. As a result, many international studies have had to rely on globally available satellite-based DEMs instead, and predominantly NASA’s SRTM DEM [ Farr et al., 2007 ]. Data quality issues and improper use have resulted in unreliable risk assessments for the VMD for the following two reasons: 1 ] The vertical absolute error of SRTM data is ~6.2 m in Eurasia [ Rodriguez et al., 2005 ] and the original SRTM data are binned to 1 m steps, which is up to two orders of magnitude larger than decadal rates of sea- level rise. The height errors result from canopy cover or buildings but also from data artefacts such as the obvious NE-SW-oriented striping pattern present over the VMD [ Figure 9.3 ]. As a result, sea level rise risk assessments in the VMD using SRTM data predominantly show elevation inaccuracies rather than the actual sea level rise impact. 2 ] The vast majority of the assessments do not convert the vertical datum to local Mean Sea Level (MSL). Global satellite-derived DEMs are referenced to a global elevation datum, the so-called geoid, which is a model of global mean sea level based on gravity and Earth rotation, excluding local effects of winds and tides. The standard reference of the SRTM DEM is the Earth Gravitational Model of 1996 (EGM96). For the Mekong delta, local MSL differs + 1.01 m from EGM96 elevation at the tide gauge located at Ha Tien (average MSL from October 1992 to December 2010 based on AVISO altimetry data). As a result, risk assessments using the SRTM DEM that do correct for this, include a height bias (overestimation) of 1 m to local MSL, greatly underestimating the true risk.

[ Figure 9.3 ] Topography of the delta

SRTM DEM and TopoDEM of the VMD. The SRTM is purposefully referenced to EGM96, to show the large difference with the many previous sea level rise assessments that did not convert vertical datum to local MSL, which is about +1 meter higher. Average elevation is calculated for the delta plain excluding bedrock outcrops (Modified after Minderhoud et al., 2019).

case; this would mean that large areas would be permanently inundated (P. Minderhoud, personal communication). The sea level rise impact assessment for the VMD, besides not accounting for vertical land motion, is thus dominated by this initial underestimate of elevation, and should be discarded.

Since 2012 at least, the Vietnamese government has produced its own internal sea level rise impact assessments for the VMD, based on high-accuracy data, which are superior to the publicly available satellite-based DEMs. However, until now, these sea level rise impact assessments only considered the climate change-driven global sea level rise, and did not include vertical land movement (i.e., subsidence). The significant errors in previous sea level rise impact assessments for the Mekong delta that resulted from (mis)using inaccurate satellite-based DEMs became clear for the international community in a recent publication [ Minderhoud et al., 2019 ]. The authors created the TopoDEM, based on data digitized by interpolating elevation points from a topographical map. The mean delta elevation of the delta according to TopoDEM is ~0.8 m above local mean sea level [ Figure 9.3 ]. Although the TopoDEM enables far more accurate sea level rise assessments compared with the satellite-based DEMs, it has very low spatial resolution (0.5 km), an estimated vertical elevation error of 20–30 cm, and unknown source and acquisition data. The TopoDEM falls short in accuracy compared to the Viet-

namese government’s LIDAR-based elevation model. However, at present the TopoDEM is the best publicly available estimate of Mekong delta elevation and enables reasonable, spatiotemporal assessment of relative sealevel rise and its impact on flood risk and salinization, for example.

2.3 A sinking delta

It is common knowledge that sea level is not stable, but neither is the elevation of the land of a delta. While elevation in a delta is built by sediment deposition, it diminishes over time due to land subsidence. We define land subsidence here as gradual lowering of the land surface due to natural and human-induced processes that cause compaction and volume reduction of sediment in the subsurface (see Box 9.2). Hence, land subsidence does not include other, unrelated processes, like riverbank or riverbed erosion, slumps and landslides, or other sudden large changes in surface level. As the Vietnamese term for these phenomena does not differentiate between them, this often leads to confusion in media articles or in discussions. The total subsidence rate is defined as surface lowering over time resulting from the sum of all subsidence processes together. Final elevation change is the combined effect of elevation loss following subsidence and elevation gain by, for example, sedimentation. Following this definition, reduced sedimentation is not a cause of delta subsidence but rather a reduction of the natural compensation mechanism [ Hoang et al., 2016 ]. Over the previous decades, intensification of agricultural practices and on-going urbanisation have triggered and increased the impact of the anthropogenic subsidence drivers [ Minderhoud et al., 2018 ]. At present, the VMD is experiencing subsidence rates in the order of several cm/year, a magnitude larger than current rates of global sea level rise. As sedimentation rates are too low to compensate for these high rates of relative sea level rise, the delta is losing elevation, predominantly as a result of land subsidence. In this section we discuss the causes of deltaic subsidence and highlight recent monitoring and modelling efforts in the VMD.

Measuring subsidence

Accurately monitoring subsidence in a delta as large as the VMD is a challenge: not just because of its scale, but also because of spatial and temporal variability of deltaic subsidence. The latter holds true especially for human-induced, accelerating subsidence [ Minderhoud et al., 2018 ]. Moreover, compaction of unconsolidated sediments can happen at different depths in the subsurface of the delta, from the top few centimetres down to hundreds of metres in depth. Subsidence rates in the VMD have been determined in various ways: 1 ] ground-based measurements and 2 ] space-borne observations using satellite-based interferometric synthetic aperture radar [ InSAR). No single measuring technique can resolve every subsidence process at all relevant temporal and spatial scales, and each method has its advantages and disadvantages. Therefore, the combined use of different measurement techniques is important, since they complement each other and together can provide a full overview.

Ground-based measurements of subsidence Ground measurements generally have high vertical accuracies and can measure subsidence at millimetre scale. As the measured object is known, the measurement can be interpreted directly in relation to depth, e.g. a foundation-less monument at the delta sur-

[ Box 9.2 ] Drivers and processes of subsidence in deltas

Subsidence in a delta is the cumulative result of a range of different drivers and processes. Figure 9.4 gives an overview of processes and drivers that can cause and/or enhance land subsidence in deltas and coastal plains. Processes ( in blue) are initiated by a driver (in black/green/red). Multiple drivers and processes can play a role at the same time and add to the total subsidence. Total subsidence depends on local conditions and can be highly variable spatially within a delta. Also, subsidence processes can accelerate and decelerate over time, and even vary throughout the year between wet and dry seasons and variations in anthropogenic drivers. In general, subsidence due to anthropogenic drivers can be reduced or even stopped, while natural subsidence is unavoidable. Natural drivers (green in Figure 9.4) include compaction (or consolidation) of soft, unconsolidated sediments over time and with increased natural loading (e.g. new sediments or seasonal flooding), and effects resulting from solid earth movements such as tectonic activity or isostatic adjustment. Other natural processes causing subsidence are oxidation of organic material in the soil and ripening of clay soils. Anthropogenic drivers stem from human activities that alter the natural situation in the delta both at the surface and in the subsurface (red in Figure 9.4). They can enhance natural subsidence processes or trigger new subsidence, for example by adding weight to the surface through buildings or infrastructure, lowering the surface water table or over-extracting groundwater. When water pumping reduces water pressure in the subsurface, sediments experience increased stress, driving pore space reduction and compaction. In sandy deposits a large part of this compression is reversible (i.e. elastic) and can be recovered when water levels increase again, but for silts and clays the process is largely irreversible (i.e. plastic). Groundwater extraction is notorious for creating the highest subsidence rates in deltas, up to several cm/year, and world-wide there are numerous examples of land subsidence caused by groundwater extraction, for example cumulative subsidence in Bangkok (2.1 m), Jakarta (4.1 m, Tokyo (4.3 m) and Shanghai ( 2.6 m) [ Gambolati and Teatini, 2015 ].

Figure 9.4 An overview of natural and anthropogenic drivers and processes of subsidence in a delta system (modified after Minderhoud et al., 2015).

face, or a benchmark or extensometer fixed at a certain depth. Except for several monitoring stations that measure displacement continuously, the temporal resolution of observations is rather low (sometimes only a single measurement in several years). While this enables computation of longer-term average movements, it does not capture seasonality or temporal trends. Also, as the measurements are point measurements, they do not provide a spatial pattern and should not be interpolated over large areas, as this would ignore the spatial heterogeneity of subsidence and put too much weight on single point measurements and potential outliers.

Official MoNRE (Viet Nam Ministry of Natural Resources and Environment) measurements of subsidence are created based on 287 geodetic benchmarks at the delta surface throughout the delta. The benchmarks were measured in 2005, 2014, 2015 and 2017. The average subsidence rates between 2005 and 2017 attained peaks of 57 mm/year, with an average rate of 9.6 mm/year. Cumulatively, the benchmarks subsided on average 10.6 cm, with cumulative subsidence up to 62.6 cm. Although the interpolated map based on the point measurements should be viewed with strong reservations (see reasons above), these data show clear evidence of widespread downward vertical land motion throughout the delta between 2005 and 2017.

Other ground-based measurements of subsidence in the VMD include rod surfaceelevation tables (RSETs), installed since 2010 at several locations in the Mekong Delta, especially in mangrove forests in the coastal zone. In combination with a surface marker horizon, the RSETs provide measurements of subsidence of the shallow, Holocene deposits. Reported subsidence rates for this shallow depth interval range between 13.4 and 46.2 mm/year (measured between 2010 and 2014, Lovelock et al., 2015). The Viet Nam Institute of Geosciences and Mineral Resources (VIGMR) and the Norwegian Geotechnical Institute (NGI) installed three subsidence monitoring stations in Ca Mau province in 2017. These stations measure subsidence in the upper 100 m of the subsurface [ Karlsrud et al., 2017, 2019; Karlsrud & Vangelsten, 2017 ]. Two of the three stations provide reliable data, and measured 24 and 31 mm/year of subsidence (2017–2019). However, the sparse measurement times and short measurement intervals make these measurements unreliable, and insufficient to support the study’s conclusion on fast (neo) tectonic movements in the VMD. Alongside direct measurements of subsidence, several studies have estimated subsidence indirectly, inferred from time series from river stage across the VMD [ Fujihara et al., 2015 ] and in the city of Can Tho [ Takagi et al., 2016 ]. On average, the river stage monitoring stations recorded an estimated subsidence of 17.1 mm/year between 1993 and 2014.

Space-borne subsidence observations Space-borne observations, using satellite-based interferometric synthetic aperture radar (InSAR), have the advantage of providing an unprecedented spatial resolution of vertical land movement. However, the uncertainty of the rates is relatively large, due to relatively high atmospheric distortion in the region and limited availability of stable points to convert relative movements into absolute movement. InSAR renders the movement of surface reflectors, i.e. hard surfaces such as roads and rooftops that reflect the radar signal well. Therefore, it does not directly provide delta surface movements but should be interpreted through the movement of respective reflectors, which can be quite different: for example,

[ Figure 9.5 ] Subsidence rates estimated from satellite imagery (InSAR) over the period 2006–2010 (a) and 2014–2019 (b)

InSAR data source: a) Erban, et al., (2014) and b) EU Copernicus EMSN062 after Minderhoud et al. (2020b).

roads without foundations versus buildings with deep foundations [ de Wit et al., 2021 ]. The first InSAR analysis for the Mekong Delta was performed by [ Erban et al., 2013, 2014 ]. The studies showed that large parts of the delta experienced subsidence rates varying from 0–40 mm/year over the period 2006–2010, with a structural measurement error of 5–10 mm/year [ Erban et al., 2013 ], and an additional uncertainty (up to 10 mm) related to the selection of stable (zero-movement) reference points of the different satellite image tiles. Apart from these relatively high uncertainties, the studies revealed the widespread occurrence of subsidence in the delta.

In 2019 new satellite-based subsidence quantifications became available for the cities of Ca Mau, Rach Gia and Long Xuyen and their direct surroundings for the period November 2014 to January 2019. Land subsidence rates were derived following the persistent scattered interferometry (PSI) technique, using Sentinel-1 sensor data as part of a Copernicus project (project code: EMSN057). In a second Copernicus EMS project (EMSN-062), almost the entire Mekong Delta was analysed. The datasets show subsidence rates up to 60 mm/year, which are significantly higher than the INSARestimates [ Erban et al., 2014 ] from a decade earlier (2006–2010) [ Figure 9.5a ]. This may point to acceleration over time. Another important difference is that whereas in the 2006–2010 analysis cities and densely populated areas were clearly the locations experiencing the highest rates of subsidence, the 2014–2019 data reveals new subsidence hotspots located in agricultural areas [ Figure 9.5b ]. These datasets show that high subsidence rates are now occurring in areas away from dense urbanisation, which is a new phenomenon compared to a decade earlier.

[ Figure 9.6 ] Simulated rates of natural compaction

Estimated maximum natural compaction of Holocene clays in the VMD (Modified after Minderhoud, 2019).

Modelling subsidence in the Mekong delta

The use of computer models is a way to increase understanding and create physics-based interpolation and predictions of observed subsidence. Models enable the quantification of subsidence beyond the spatial and temporal scale of observations. When properly calibrated and validated against observations, they can be used to create process-based interpolations, i.e., maps. These maps can be superior to the mathematical interpolation of point measurements since they incorporate physical processes and spatial variability. No single computer model is capable of modelling all the relevant processes at different depths in a delta. Therefore, unlike measurements of total subsidence, a model is built to simulate specific processes and drivers, thus addressing only a part of the total subsidence in the delta. For the VMD, two numerical models have been created, targeting two distinct subsidence processes: 1 ] shallow, natural compaction of Holocene sediments [ Zoccarato et al., 2018 ] and 2 ] aquifer-system compaction following groundwater extraction, and consequent changes in the hydrogeological situation in the delta. Both models were built using large sets of field data and were calibrated and validated using observations of subsidence.

Using a novel computer code, the shallow natural compaction of Holocene sediments was modelled for a 2D transect in the Ca Mau peninsula, following the progradation of the delta in the last 4000 years [ Zoccarato et al., 2018 ]. This novel approach revealed that the combination of high progradation rates and high compressibility of clay deposits can be responsible for unprecedentedly high rates of natural compaction in the youngest parts of the VMD. The model confirmed that the high shallow compaction rates measured in these areas by RSETs (13.4–46.2 mm/year) could be of natural origin. Recently, the first delta-wide map of maximum potential natu-

[ Figure 9.7 ] Simulated rates of extraction-induced subsidence

Simulated extraction-induced subsidence showing the gradual acceleration following increased groundwater extractions in the VMD [ Minderhoud et al., 2017 ].

ral compaction was created, by interpolating the 2D-modelled compaction using the spatial distribution of clays in the shallow Holocene delta deposits [ Figure 9.6 ].

Groundwater extraction is a well-known driver of anthropogenic-induced subsidence in deltaic areas. In the VMD the volume of extracted groundwater has seen a steady increase over the last decades [ Chapter 7 ]. The water is extracted from different aquifers (i.e., sand bodies) in the subsurface, which in some places reach depths over 500 m. The water pressure ( i.e., hydraulic head) in the aquifers has been monitored since 1990, when the groundwater situation was still fairly undisturbed in many places. Since then, following the steady increase of extractions, water pressure in the different aquifers has shown decreasing trends throughout the delta [ Chapter 7 ]. Following the drop in pressure, water has been drained from fine-grained deposits (i.e., aquitards, low permeable layers separating the different aquifers), causing compaction of the entire aquifer-system.

The impact of groundwater extraction on subsidence in the VMD was studied using a delta-wide 3D hydro-geological model that simulated groundwater extractions, groundwater flow and pressure change, and consequent compaction of subsurface layers [ Minderhoud et al., 2017 ]. The modelling results revealed the accelerating trend of aquifer-system compaction in the VMD following the increase in groundwater exploitation [ Min-

[ Box 9.3 ] Environmental drivers of salt intrusion

Salt intrusion within the deltaic surface water systems is mainly driven through the estuarine channels. Estuarine salinity is determined by the competition between 1 ] upstream (dispersive] salt transport by density gradient and ocean forces (e.g. tides) against the 2 ] downstream (Eulerian) salt transport, e.g. by river discharge within 3 ] a given morphology [ Geyer and MacCready, 2013; Pritchard, 1952; Savenije, 1993, 2005 ]. Therefore, alterations in any of the three main determinants of salt intrusion translate into changes in estuarine salinity and its extent of intrusion.

Global rising temperatures [ IPCC, 2014 ] modify precipitation/evaporation patterns that both directly, and through upstream discharge anomalies [ Winsemius et al., 2016 ], influence fresh-saline water dynamics. Oceanic thermal expansion and melting of the ice sheets and glaciers increase ocean water levels [ Bamber et al., 2019; IPCC, 2014 ] and impact oceanic tidal patterns [ Pickering et al., 2017 ] that affect estuarine salinity. Estuarine bathymetry (the 3rd determinant) itself responds to the rising seas and changing tides [ Leuven et al., 2019 ]. Along with climatic changes, ever-growing agri-/aqua-cultural developments are sources of stress on fluvial freshwater resources. Upstream impoundments have reduced fluvial sediment supply, leading to morphological changes such as bed/bank/coastal erosion [ Anthony et al., 2015; Dunn et al., 2019; Syvitski and Milliman, 2007; Syvitski and Saito, 2007 ]. Rapid urbanization and demand for freshwater have generated increased groundwater extraction, leading to subsidence in rates and orders of magnitude that exceed current sea level rise [ Erban et al., 2014; Minderhoud et al., 2017; Syvitski et al., 2009 ]. The combination of all the above-mentioned drivers [ Figure 9.8 ] influences change in estuarine salinity.

Figure 9.8 A cross-profile of a delta through its estuarine system, and the primary anthropogenic (black) and climatic (grey) drivers of change (red)