Land Uplift Model Research Articles

Deferring Flood Damage in Coastal Lowlands: Assessing Surface Uplift by Geo-Engineered CO2-Sequestration with Easy-to-Use Land-Uplift Model

Deferring Flood Damage in Coastal Lowlands: Assessing Surface Uplift by Geo-Engineered CO2-Sequestration with Easy-to-Use Land-Uplift Model

Sea Level Rise and Future Projections in the Baltic Sea

This article aimed to provide an overview of relative and absolute sea level rise in the Baltic Sea based on different studies, where researchers have used data from tide gauges, satellite altimetry, sea level rise, and land uplift models. These results provide an opportunity to get an overview of the sea level rise in the Baltic Sea. However, to better understand the impact of sea level rise on the coastal area of the Baltic Sea, and especially in Estonia, two post-glacial land uplift models, the latest land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) and Estonian land uplift model EST2020VEL, were used. These models enabled to eliminate post-glacial land uplift from absolute sea level rise. To determine the relative sea level rise in the coastal area of the Baltic Sea, the rates from land uplift models were compared to ESA’s BalticSEAL absolute sea level rise model. It was found that the relative sea level rise between 1995–2019 was −5 to 4.5 mm/yr (based on NKG2016LU) in the Baltic Sea. In addition, the southern area is more affected by relative sea level rise than the northern part. During the research, it was also found that the IPCC AR5 sea level projections predict a maximum relative sea level rise in the Baltic Sea by the year 2100 of between 0.3 to 0.7 m. As coastal areas in the southern part of the Baltic Sea are predominantly flat, the sea level may reach the real estate properties by the end of the 21st century. In the coastal area of Estonia, the relative sea level rise in the period 1995–2019 was −1.1 to 3.1 mm/yr (based on NKG2016LU) and −0.3 to 3.4 mm/yr (based on EST2020VEL), the difference between the land uplift models is −0.9 to 0.1 mm/y. In Estonia, the west and southwest area are most threatened by sea level rise, where the coast is quite flat. One of the largest cities in Estonia, Pärnu, is also located there. Using the ESA’s sea level and EST2020VEL land uplift models, it was found that the relative sea level rise will be 0.28 m by the year 2100. Based on the large spatial resolution IPCC AR5 sea level projections, the relative sea level rise will be on the same scale: 0.2–0.4 m.

Mantle Viscosity Derived From Geoid and Different Land Uplift Data in Greenland

AbstractThe Earth's mass redistribution due to deglaciation and recent ice sheet melting causes changes in the Earth's gravity field and vertical land motion in Greenland. The changes are because of ongoing mass redistribution and related elastic (on a short time scale) and viscoelastic (on time scales of a few thousands of years) responses. These signatures can be used to determine the mantle viscosity. In this study, we infer the mantle viscosity associated with the glacial isostatic adjustment (GIA) and long‐wavelength geoid beneath the Greenland lithosphere. The viscosity is determined based on a spatio‐spectral analysis of the Earth's gravity field and the land uplift rate in order to find the GIA‐related gravity field. We used different land uplift data, that is, the vertical land motions obtained by the Greenland Global Positioning System (GPS) Network (GNET), gravity recovery and climate experiment (GRACE) and glacial isostatic adjustment (GIA) data, and also combined them using the Kalman filtering technique. Using different land uplift rates, one can obtain different GIA‐related gravity fields. As shown in this study, the mantle viscosities of 1.9 × 1022 Pa s and 7.8 × 1021 Pa s for a depth of 200–700 km are obtained using ICE‐6G (VM5a) model and the combined land uplift model, respectively, and the GIA‐related gravity potential signal.

Forty-three years of absolute gravity observations of the Fennoscandian postglacial rebound in Finland

Postglacial rebound in Fennoscandia causes striking trends in gravity measurements of the area. We present time series of absolute gravity data collected between 1976 and 2019 on 12 stations in Finland with different types of instruments. First, we determine the trends at each station and analyse the effect of the instrument types. We estimate, for example, an offset of 6.8 μgal for the JILAg-5 instrument with respect to the FG5-type instruments. Applying the offsets in the trend analysis strengthens the trends being in good agreement with the NKG2016LU_gdot model of gravity change. Trends of seven stations were found robust and were used to analyse the stabilization of the trends in time and to determine the relationship between gravity change rates and land uplift rates as measured with global navigation satellite systems (GNSS) as well as from the NKG2016LU_abs land uplift model. Trends calculated from combined and offset-corrected measurements of JILAg-5- and FG5-type instruments stabilized in 15 to 20 years and at some stations even faster. The trends of FG5-type instrument data alone stabilized generally within 10 years. The ratio between gravity change rates and vertical rates from different data sets yields values between − 0.206 ± 0.017 and − 0.227 ± 0.024 µGal/mm and axis intercept values between 0.248 ± 0.089 and 0.335 ± 0.136 µGal/yr. These values are larger than previous estimates for Fennoscandia.

Lake and mire isolation data set for the estimation of post-glacial land uplift in Fennoscandia

Abstract. Postglacial land uplift is a complex process related to the continental ice retreat that took place about 10 000 years ago and thus started the viscoelastic response of the Earth's crust to rebound back to its equilibrium state. To empirically model the land uplift process based on past behaviour of shoreline displacement, data points of known spatial location, elevation and dating are needed. Such data can be obtained by studying the isolation of lakes and mires from the sea. Archaeological data on human settlements (i.e. human remains, fireplaces etc.) are also very useful as the settlements were indeed situated on dry land and were often located close to the coast. This information can be used to validate and update the postglacial land uplift model. In this paper, a collection of data underlying empirical land uplift modelling in Fennoscandia is presented. The data set is available at https://doi.org/10.1594/PANGAEA.905352 (Pohjola et al., 2019).

NKG2016LU: a new land uplift model for Fennoscandia and the Baltic Region

We present the official land uplift model NKG2016LU of the Nordic Commission of Geodesy (NKG) for northern Europe. The model was released in 2016 and covers an area from 49° to 75° latitude and 0° to 50° longitude. It shows a maximum absolute uplift of 10.3 mm/a near the city of Umeå in northern Sweden and a zero-line that follows the shores of Germany and Poland. The model replaces the NKG2005LU model from 2005. Since then, we have collected more data in the core areas of NKG2005LU, specifically in Norway, Sweden, Denmark and Finland, and included observations from the Baltic countries as well. Additionally, we have derived an underlying geophysical glacial isostatic adjustment (GIA) model within NKG as an integrated part of the NKG2016LU project. A major challenge is to estimate a realistic uncertainty grid for the model. We show how the errors in the observations and the underlying GIA model propagate through the calculations to the final uplift model. We find a standard error better than 0.25 mm/a for most of the area covered by precise levelling or uplift rates from Continuously Operating Reference Stations and up to 0.7 mm/a outside this area. As a check, we show that two different methods give approximately the same uncertainty estimates. We also estimate changes in the geoid and derive an alternative uplift model referring to this rising geoid. Using this latter model, the maximum uplift in Umeå reduces from 10.3 to 9.6 mm/a and with a similar reduction ratio elsewhere. When we compare this new NKG2016LU with the former NKG2005LU, we find the largest differences where the GIA model has the strongest influence, i.e. outside the area of geodetic observation. Here, the new model gives from − 3 to 4 mm/a larger values. Within the observation area, similar differences reach − 1.5 mm/a at the northernmost part of Norway and − 1.0 mm/a at the north-western coast of Denmark, but generally within the range of − 0.5 to 0.5 mm/a.

An Attempt to Observe Vertical Land Motion along the Norwegian Coast by CryoSat-2 and Tide Gauges

Present-day climate-change-related ice-melting induces elastic glacial isostatic adjustment (GIA) effects, while paleo-GIA effects describe the ongoing viscous response to the melting of late-Pleistocene ice sheets. The unloading initiated an uplift of the crust close to the centers of former ice sheets. Today, vertical land motion (VLM) rates in Fennoscandia reach values up to around 10 mm/year and are dominated by GIA. Uplift signals from GIA can be computed by solving the sea-level equation (SLE), 
 
 
 
 S
 ˙
 
 
 
 = 
 
 
 
 N
 ˙
 
 
 
 − 
 
 
 
 U
 ˙
 
 
 
 . All three quantities can also be determined from geodetic observations: relative sea-level variations (
 
 
 
 S
 ˙
 
 
 
 ) are observed by means of tide gauges, while rates of absolute sea-level change (
 
 
 
 N
 ˙
 
 
 
 ) can be observed by satellite altimetry; rates of VLM (
 
 
 
 U
 ˙
 
 
 
 ) can be determined by GPS (Global Positioning System). Based on the SLE, 
 
 
 
 U
 ˙
 
 
 
 can be derived by combining sea-surface measurements from satellite altimetry and relative sea-level records from tide gauges. In the present study, we have combined 7.5 years of CryoSat-2 satellite altimetry and tide-gauge data to estimate linear VLM rates at 20 tide gauges along the Norwegian coast. Thereby, we made use of monthly averaged tide-gauge data from PSMSL (Permanent Service for Mean Sea Level) and a high-frequency tide-gauge data set with 10-min sampling rate from NMA (Norwegian Mapping Authority). To validate our VLM estimates, we have compared them with the independent semi-empirical land-uplift model NKG2016LU_abs for the Nordic-Baltic region, which is based on GPS, levelling, and geodynamical modeling. Estimated VLM rates from 1 Hz CryoSat-2 and high-frequency tide-gauge data reflect well the amplitude of coastal VLM as provided by NKG2016LU_abs. We find a coastal average of 2.4 mm/year (average over all tide gauges), while NKG2016LU_abs suggests 2.8 mm/year; the spatial correlation is 0.58.

Decomposition of Relative Sea Level Variations at Tide Gauges Using Results From Four Estonian Precise Levelings and Uplift Models

Variations in Estonian sea level records (1842–2016) are interpreted using harmonic and sliding window trend analysis together with the latest findings on the crustal movements in the region of the Baltic Sea. Considering the most recent relative-to-geoid land uplift (LU) rates from the semiempirical LU model NKG2016LU_lev, it was possible, probably for the first time, to properly interpret the climate-related sea level variation components in the Estonian tide gauges. The LU relative to geoid in Estonia (0.3–3.4 mm/yr) partly compensates for the global sea level rise (GSLR). Trends in Estonian relative sea level vary site dependently between –1.05 and 1.14 mm/yr (in 1954–2016) or between –0.17 and 1.14 mm/yr (in 1900–2010), yielding a “local sea level rise” (approximately 2.2 to 2.8 mm/yr in 1900–2010), which is faster by ∼0.8 mm/yr than the GSLR over similar period. This gap mainly originates from local land subsidence and variations in water exchange processes between the Baltic Sea and the World Ocean. Moreover, due to high intra- and inter-annual variability (standard deviations in detrended monthly data series from 20 to 22 cm), the sea level trend estimates are not stable enough and the usability of Estonian time series is relatively low for contributing to GSLR estimations.

Using the Nordic Geodetic Observing System for land uplift studies

Abstract. Geodetic observing systems have been planned and developed during the last decade. An ideal observing system consists of a network of geodetic observing stations with several techniques at the same site, publicly accessible databases, and as a product delivers data time series, combination of techniques or some other results obtained from the data sets. Globally, there is the International Association of Geodesy (IAG) Global Geodetic Observing System (GGOS), and there are ongoing attempts to create also regional observing systems. In this paper we introduce one regional system, the Nordic Geodetic Observing System (NGOS) hosted by the Nordic Geodetic Commission (NKG). Data availability and accessibility are one of the major issues today. We discuss in general data-related topics, and introduce a pilot database project of NGOS. As a demonstration of the use of such a database, we apply it for postglacial rebound studies in the Fennoscandian area. We compare land uplift values from three techniques, GNSS, tide gauges and absolute gravity, with the Nordic Geodetic Commission NKG2005LU land uplift model for Fennoscandia. The purpose is to evaluate the data obtained from different techniques and different sources and get the most reliable values for the uplift using publicly available data. The primary aim of observing systems will be to produce data and other products needed by multidisciplinary projects, such as Upper Mantle Dynamics and Quaternary Climate in Cratonic Areas (DynaQlim) or the European Plate Observing System (EPOS), but their needs may currently exceed the scope of an existing observing system. We discuss what requirements the projects pose to observing systems and their development. To make comparisons between different studies possible and reliable, the researcher should document what they have in detail, either in appendixes, supplementary material or some other available format.

Postglacial land uplift in Estonia based on four precise levelings

Abstract The vertical velocities of the fundamental benchmarks of Estonian 1st order leveling network were estimated, based on the four precise leveling campaigns from 1933 to 2010. The kinematic least squares adjustment of the network was used, where heights and velocities were introduced as unknown parameters. For detection of outliers, Baarda's data snooping method was applied. Estimation of variance components by the Helmert's and the IAUE methods provided realistic weights in the network adjustment and revealed also that the observation errors of the first three levelings are up to 3 times larger than was assumed a priori. To obtain apparent uplift rates and fix velocity in kinematic adjustment, the velocity value + 2.1 mm/yr of the Ristna tide gauge on island Hiiumaa was transferred to the nearest stable benchmark by using precise levelings from tide gauge to the national height network. Average standard deviation of velocities at benchmarks was estimated to be ± 0.5 mm/yr. Based on apparent vertical velocities of the benchmarks, an interpolated land uplift surface was created using “kriging” and “minimum curvature” gridding methods. Although the two methods gave similar surfaces (RMS of differences was below ± 0.1 mm/yr), the kriging solution was used in comparison with the results of the earlier studies. The uncertainty of new velocity surface was estimated to be ± 0.5 to ± 0.7 mm/yr. The new land uplift model fits well with the Fennoscandian land uplift model NKG2005LU. The RMS of the differences was ± 0.2 mm/yr. Good agreement was also confirmed with the earlier land uplift maps of Estonia (RMS of differences ± 0.6 mm/yr). However, clear disagreement was noticed when tide gauge observations from several studies were used in comparison (RMS of differences up to ± 1.0 mm/yr). Apparently, different velocity solutions of Estonian tide gauges are systematically biased; the reasons for these biases need further investigation.

Landscape development modeling based on statistical framework

Future biosphere modeling has an essential role in assessing the safety of a proposed nuclear fuel repository. In Finland the basic inputs needed for future biosphere modeling are the digital elevation model and the land uplift model because the surface of the ground is still rising due to the download stress caused by the last ice age. The future site-scale land uplift is extrapolated by fitting mathematical expressions to known data from past shoreline positions. In this paper, the parameters of this fitting have been refined based on information about lake and mire basin isolation and archaeological findings. Also, an alternative eustatic model is used in parameter refinement. Both datasets involve uncertainties so Monte Carlo simulation is used to acquire several realizations of the model parameters. The two statistical models, the digital elevation model and the refined land uplift model, were used as inputs to a GIS-based toolbox where the characteristics of lake projections for the future Olkiluoto nuclear fuel repository site were estimated. The focus of the study was on surface water bodies since they are the major transport channels for radionuclides in containment failure scenarios. The results of the study show that the different land uplift modeling schemes relying on alternative eustatic models, Moho map versions and function fitting techniques yield largely similar landscape development tracks. However, the results also point out some more improbable realizations, which deviate significantly from the main development tracks.

A land uplift model in Fennoscandia combining GRACE and absolute gravimetry data

Since 2002 the GRACE satellite mission provides monthly solutions of the Earth’s gravity field reflecting mass variations on various spatial and temporal scales. The glacial isostatic adjustment (GIA)-induced trend signal in Fennoscandia can be obtained with a spatial resolution of about 300–400km. Moreover, since 2003 the Institut für Erdmessung has carried out absolute gravity (AG) measurements in Fennoscandia in close cooperation with the Scandinavian partners. From the AG data, point-wise mass variations at the AG sites have been determined including the GIA-induced trend signal. For direct comparison of those point values with regional results from GRACE, vertical movements of the sites have been considered using rates determined from permanent GPS measurements. The various results for GIA-related effects agree well near the uplift center, although the different raw data contain different signal contributions. In a final step, we combine the AG trend values (including GPS rates) and the GRACE results to obtain a data-based solution of the present-day secular mass variation in Fennoscandia.Here, we present results of the individual techniques as well as the combined solution, where we also discuss possible errors sources.